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All Classes All Packages

A

AArffLoader - Class in weka.core.converters

Safe version of the ArffLoader, always retaining string values.

AArffLoader() - Constructor for class weka.core.converters.AArffLoader

AArffLoader.AArffReader - Class in weka.core.converters

AArffReader(Reader) - Constructor for class weka.core.converters.AArffLoader.AArffReader

Reads the data completely from the reader.

AArffReader(Reader, int) - Constructor for class weka.core.converters.AArffLoader.AArffReader

AArffReader(Reader, int, boolean) - Constructor for class weka.core.converters.AArffLoader.AArffReader

Reads only the header and reserves the specified space for instances.

AArffReader(Reader, Instances, int) - Constructor for class weka.core.converters.AArffLoader.AArffReader

Reads the data without header according to the specified template.

AArffReader(Reader, Instances, int, int) - Constructor for class weka.core.converters.AArffLoader.AArffReader

Initializes the reader without reading the header according to the specified template.

AArffReader(Reader, Instances, int, int, boolean) - Constructor for class weka.core.converters.AArffLoader.AArffReader

Initializes the reader without reading the header according to the specified template.

abortExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner

Aborts the experiment.

abortExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Aborts the experiment.

abortExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.runner.RemoteWekaExperimentRunner

Aborts the experiment.

ABOVE - weka.classifiers.meta.ClassifierCascade.ThresholdCheck

absDev(int, Instances) - Static method in class weka.classifiers.trees.m5.Rule2

Returns the absolute deviation value of the supplied attribute index.

absErrTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Returns the tip text for this property

absErrTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Returns the tip text for this property

ABSOLUTE - adams.flow.transformer.WekaBootstrapping.ErrorCalculation

AbsolutePredictionErrorComparator - Class in adams.flow.transformer.wekaevaluationpostprocessor

Comparator for predictions using the (absolute) prediction error (sorting increasingly).

AbsolutePredictionErrorComparator() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.AbsolutePredictionErrorComparator

absoluteTipText() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Returns the tip text for this property.

AbstainAttributePercentile - Class in weka.classifiers.meta

Only predict if attribute value within percentile range.

AbstainAttributePercentile() - Constructor for class weka.classifiers.meta.AbstainAttributePercentile

AbstainAverage - Class in weka.classifiers.meta

Average base classifiers, abstain if difference outside thresholds

Valid options are:

AbstainAverage() - Constructor for class weka.classifiers.meta.AbstainAverage

AbstainAverageWithClassifierWeights - Class in weka.classifiers.meta

Average base classifiers, abstain if difference outside thresholds

Valid options are:

AbstainAverageWithClassifierWeights() - Constructor for class weka.classifiers.meta.AbstainAverageWithClassifierWeights

AbstainingCascade - Class in weka.classifiers.meta

The specified classifiers represent a cascade: if the first one abstains, the second is used (and so on), otherwise the prediction is returned.
If all classifiers prior to the last one abstained then the prediction of the last one is returned.

AbstainingCascade() - Constructor for class weka.classifiers.meta.AbstainingCascade

AbstainingClassifier - Interface in weka.classifiers

Interface for classifiers that may support abstaining.

AbstainingClassifierWrapper - Class in weka.classifiers.meta

Wraps an abstaining classifier and allows turning on/of abstaining.

AbstainingClassifierWrapper() - Constructor for class weka.classifiers.meta.AbstainingClassifierWrapper

Initializes the classifier.

AbstainingLWL - Class in weka.classifiers.lazy

LWL variant that supports abstaining if the base classifier is able to.

AbstainingLWL() - Constructor for class weka.classifiers.lazy.AbstainingLWL

AbstainLeastMedianSq - Class in weka.classifiers.meta

Finds the base classifier with the best least median squared error.

AbstainLeastMedianSq() - Constructor for class weka.classifiers.meta.AbstainLeastMedianSq

AbstainMinimumProbability - Class in weka.classifiers.meta

Abstains if the probability of the chosen class label is below the specified threshold.

AbstainMinimumProbability() - Constructor for class weka.classifiers.meta.AbstainMinimumProbability

AbstainVote - Class in weka.classifiers.meta

Finds the base classifier with the best least median squared error.

AbstainVote() - Constructor for class weka.classifiers.meta.AbstainVote

AbstractAdamsExperimentIO<T extends AbstractExperiment> - Class in adams.gui.tools.wekamultiexperimenter.io

Ancestor for classes that handle loading/saving of experiments.

AbstractAdamsExperimentIO() - Constructor for class adams.gui.tools.wekamultiexperimenter.io.AbstractAdamsExperimentIO

AbstractAdamsExperimentReader - Class in adams.data.io.input

Ancestor for readers for ADAMS Experiments.

AbstractAdamsExperimentReader() - Constructor for class adams.data.io.input.AbstractAdamsExperimentReader

AbstractAdamsExperimentRunner<T extends AbstractExperiment> - Class in adams.gui.tools.wekamultiexperimenter.runner

Ancestor for classes that handle running a copy of the experiment in a separate thread.

AbstractAdamsExperimentRunner(ExperimenterPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner

Initializes the thread.

AbstractAdamsExperimentWriter - Class in adams.data.io.output

Ancestor for ADAMS Experiment writers.

AbstractAdamsExperimentWriter() - Constructor for class adams.data.io.output.AbstractAdamsExperimentWriter

AbstractAdamsSetupPanel - Class in adams.gui.tools.wekamultiexperimenter.setup

Ancestor for setup panels for ADAMS experiments.

AbstractAdamsSetupPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractAdamsSetupPanel

AbstractAdditionalExplorerPanel - Class in weka.gui.explorer.panels

Wrapper class for additional panels to be displayed in the Explorer.

AbstractAdditionalExplorerPanel() - Constructor for class weka.gui.explorer.panels.AbstractAdditionalExplorerPanel

AbstractAnalysisPanel - Class in adams.gui.tools.wekamultiexperimenter.analysis

Ancestor for panels that analysis experimental results.

AbstractAnalysisPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

AbstractAssociatorEvaluation - Class in adams.gui.tools.wekainvestigator.tab.associatetab.evaluation

Ancestor for associator evaluation setups.

AbstractAssociatorEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation

AbstractAttributeCapabilities - Class in adams.flow.condition.bool

Ancestor for capabilities-based conditions.

AbstractAttributeCapabilities() - Constructor for class adams.flow.condition.bool.AbstractAttributeCapabilities

AbstractAttributeSelectionEvaluation - Class in adams.gui.tools.wekainvestigator.tab.attseltab.evaluation

Ancestor for attribute selection evaluation setups.

AbstractAttributeSelectionEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation

AbstractCallableWekaClassifierEvaluator - Class in adams.flow.transformer

Ancestor for classifier evaluators that make use of a callable classifier.

AbstractCallableWekaClassifierEvaluator() - Constructor for class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

AbstractCallableWekaClustererEvaluator - Class in adams.flow.transformer

Ancestor for clusterer evaluators that make use of a callable clusterer.

AbstractCallableWekaClustererEvaluator() - Constructor for class adams.flow.transformer.AbstractCallableWekaClustererEvaluator

AbstractClassAttributeHeuristic - Class in adams.data.weka.classattribute

Ancestor for heuristics that determine the class attribute for a dataset.

AbstractClassAttributeHeuristic() - Constructor for class adams.data.weka.classattribute.AbstractClassAttributeHeuristic

AbstractClassifierBasedGeneticAlgorithm - Class in adams.opt.genetic

Ancestor for genetic algorithms that evaluate classifiers.

AbstractClassifierBasedGeneticAlgorithm() - Constructor for class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob<T extends AbstractClassifierBasedGeneticAlgorithm> - Class in adams.opt.genetic

Job class for algorithms with datasets.

AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation - Class in adams.opt.genetic

Ancestor for genetic algorithms that offer a second evaluation using a different seed value.

AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation() - Constructor for class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob<T extends AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation> - Class in adams.opt.genetic

Job class for algorithms with datasets.

AbstractClassifierBasedGeneticAlgorithmWizard - Class in adams.gui.menu

Ancestor for optimizing datasets (attribute selection) using a genetic algorithm.

AbstractClassifierBasedGeneticAlgorithmWizard() - Constructor for class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

Initializes the menu item with no owner.

AbstractClassifierBasedGeneticAlgorithmWizard(AbstractApplicationFrame) - Constructor for class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

Initializes the menu item.

AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot - Class in adams.gui.menu

For plotting the performance of the genetic algorithm.

AbstractClassifierEvaluation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation

Ancestor for classifier evaluation setups.

AbstractClassifierEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation

AbstractClassifierSetupProcessor - Class in adams.flow.transformer.wekaclassifiersetupprocessor

Ancestor for schemes that preprocess classifier arrays.

AbstractClassifierSetupProcessor() - Constructor for class adams.flow.transformer.wekaclassifiersetupprocessor.AbstractClassifierSetupProcessor

AbstractClustererEvaluation - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation

Ancestor for clusterer evaluation setups.

AbstractClustererEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation

AbstractClustererPostProcessor - Class in adams.flow.transformer.wekaclusterer

Ancestor for post-processors for output that the WekaClusterer transformer produces.

AbstractClustererPostProcessor() - Constructor for class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor

AbstractClusterMembershipPostProcessor - Class in adams.flow.transformer.wekaclusterer

Ancestor for post-processors that require a built clusterer and the dataset that was used to build the clusterer to be present in the model container.

AbstractClusterMembershipPostProcessor() - Constructor for class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor

AbstractColumnFinder - Class in adams.data.weka.columnfinder

Ancestor for classes that find columns of interest in datasets.

AbstractColumnFinder() - Constructor for class adams.data.weka.columnfinder.AbstractColumnFinder

AbstractColumnFinderApplier - Class in weka.filters.unsupervised.attribute

Ancestor for filters that apply ColumnFinder schemes to the data.

AbstractColumnFinderApplier() - Constructor for class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

AbstractColumnFinderWithCapabilities - Class in adams.data.weka.columnfinder

Ancestor for classes that find columns of interest in datasets.

AbstractColumnFinderWithCapabilities() - Constructor for class adams.data.weka.columnfinder.AbstractColumnFinderWithCapabilities

AbstractCommunicationProcessor - Class in adams.data.wekapyroproxy

Ancestor for classes processing the communication to/fro Pyro proxy models.

AbstractCommunicationProcessor() - Constructor for class adams.data.wekapyroproxy.AbstractCommunicationProcessor

AbstractCrossvalidatedInstanceEvaluator<T extends AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer> - Class in adams.data.weka.evaluator

Ancestor for evalutors that use cross-validation for initialization.

AbstractCrossvalidatedInstanceEvaluator() - Constructor for class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer - Class in adams.data.weka.evaluator

Container for storing the evaluation results.

AbstractDataContainer - Class in adams.gui.tools.wekainvestigator.data

Ancestor for data containers.

AbstractDataContainer() - Constructor for class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Initializes the container with no data.

AbstractDataContainer(Instances) - Constructor for class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Initializes the container with just the data.

AbstractDataPreparation - Class in weka.classifiers.meta.socketfacade

Ancestor for classes that prepare data for the SocketFacade classifier.

AbstractDataPreparation() - Constructor for class weka.classifiers.meta.socketfacade.AbstractDataPreparation

AbstractDatasetInstanceEvaluator - Class in adams.data.weka.evaluator

Ancestor for evaluators that need a data set for initialization.

AbstractDatasetInstanceEvaluator() - Constructor for class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

AbstractDetrend - Class in weka.filters.unsupervised.attribute.detrend

Ancestor for schemes that perform detrend.

AbstractDetrend() - Constructor for class weka.filters.unsupervised.attribute.detrend.AbstractDetrend

AbstractEditableDataTableAction - Class in adams.gui.tools.wekainvestigator.datatable.action

Ancestor for actions on the data displayed on a tab using a AbstractInvestigatorTabWithEditableDataTable.

AbstractEditableDataTableAction() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

AbstractErrorScaler - Class in adams.data.weka.predictions

Ancestor for classes that scale predictions.

AbstractErrorScaler() - Constructor for class adams.data.weka.predictions.AbstractErrorScaler

AbstractEvaluation<T extends AbstractInvestigatorTab,R extends AbstractResultItem> - Class in adams.gui.tools.wekainvestigator.evaluation

Ancestor for evaluation setups.

AbstractEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Constructor.

AbstractExperiment - Class in adams.gui.tools.wekamultiexperimenter.experiment

Ancestor for simple experiments.

AbstractExperiment() - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

AbstractExperiment.AbstractExperimentJob<T extends AbstractExperiment> - Class in adams.gui.tools.wekamultiexperimenter.experiment

For evaluating a single classifier/dataset combination.

AbstractExperimenterPanel - Class in adams.gui.tools.wekamultiexperimenter

Ancestor for panels in the experimenter.

AbstractExperimenterPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel

AbstractExperimentIO<T> - Class in adams.gui.tools.wekamultiexperimenter.io

Ancestor for classes that handle loading/saving of experiments.

AbstractExperimentIO() - Constructor for class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO

AbstractExperimentJob(T, int, Classifier, Instances) - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

Initializes the run.

AbstractExperimentRunner<T> - Class in adams.gui.tools.wekamultiexperimenter.runner

Ancestor for classes that handle running a copy of the experiment in a separate thread.

AbstractExperimentRunner(ExperimenterPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Initializes the thread.

AbstractExperimentSetup - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.setup

Ancestor for experiment setups.

AbstractExperimentSetup() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup

AbstractExplorerPanelHandler - Class in weka.gui.explorer

Ancestor for handlers for specific Explorer panels.

AbstractExplorerPanelHandler() - Constructor for class weka.gui.explorer.AbstractExplorerPanelHandler

AbstractFilteredColumnFinder - Class in adams.data.weka.columnfinder

Ancestor for column finders that pre-filter the columns.

AbstractFilteredColumnFinder() - Constructor for class adams.data.weka.columnfinder.AbstractFilteredColumnFinder

AbstractFilteredRowFinder - Class in adams.data.weka.rowfinder

Ancestor for row finders that pre-filter the rows.

AbstractFilteredRowFinder() - Constructor for class adams.data.weka.rowfinder.AbstractFilteredRowFinder

AbstractFinalModelGenerator - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel

.

AbstractFinalModelGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.AbstractFinalModelGenerator

AbstractGeneticAlgorithm - Class in adams.opt.optimise.genetic

Base class for genetic algorithms.

AbstractGeneticAlgorithm() - Constructor for class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

AbstractGeneticDoubleMatrixDiscoveryHandler - Class in adams.core.discovery.genetic

Ancestor for genetic discovery handlers that handle matrix properties.

AbstractGeneticDoubleMatrixDiscoveryHandler() - Constructor for class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

AbstractHashableInstance - Class in weka.core

Ancestor for instance classes that wraps around any WEKA Instance and allow them to be used in data structures that make use of on object's hash, like maps or hashtables.

AbstractHashableInstance(Instance) - Constructor for class weka.core.AbstractHashableInstance

Initializes the wrapper.

AbstractHistoryPopupMenuItem<H extends adams.gui.core.AbstractNamedHistoryPanel,T extends AbstractInvestigatorTab> - Class in adams.gui.tools.wekainvestigator.history

Ancestor for classes that add menu items to the history popup menu.

AbstractHistoryPopupMenuItem - Class in adams.gui.tools.wekainvestigator.tab.associatetab.history

Ancestor for classes that add menu items to the history popup menu.

AbstractHistoryPopupMenuItem - Class in adams.gui.tools.wekainvestigator.tab.attseltab.history

Ancestor for classes that add menu items to the history popup menu.

AbstractHistoryPopupMenuItem - Class in adams.gui.tools.wekainvestigator.tab.classifytab.history

Ancestor for classes that add menu items to the history popup menu.

AbstractHistoryPopupMenuItem - Class in adams.gui.tools.wekainvestigator.tab.clustertab.history

Ancestor for classes that add menu items to the history popup menu.

AbstractHistoryPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem

AbstractHistoryPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.history.AbstractHistoryPopupMenuItem

AbstractHistoryPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.history.AbstractHistoryPopupMenuItem

AbstractHistoryPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.history.AbstractHistoryPopupMenuItem

AbstractHistoryPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.history.AbstractHistoryPopupMenuItem

AbstractInstanceEvaluator - Class in adams.data.weka.evaluator

Ancestor for evaluators that evaluate weka.core.Instance objects.

AbstractInstanceEvaluator() - Constructor for class adams.data.weka.evaluator.AbstractInstanceEvaluator

AbstractInstanceGenerator<T extends adams.data.container.DataContainer & adams.data.report.ReportHandler> - Class in adams.data.instances

Abstract base class for schemes that turn temperature profiles into weka.core.Instance objects.

AbstractInstanceGenerator<T extends adams.data.container.DataContainer> - Class in adams.flow.transformer

Ancestor for transformers that turn data containers into WEKA Instance objects.

AbstractInstanceGenerator() - Constructor for class adams.data.instances.AbstractInstanceGenerator

AbstractInstanceGenerator() - Constructor for class adams.flow.transformer.AbstractInstanceGenerator

AbstractInstanceInfoFrame - Class in adams.gui.visualization.weka

Ancestor for frames for displaying information on the displayed data, with some more domain-specific functionality.

AbstractInstanceInfoFrame() - Constructor for class adams.gui.visualization.weka.AbstractInstanceInfoFrame

AbstractInstancePaintlet - Class in adams.gui.visualization.instance

Ancestor for Instance paintlets.

AbstractInstancePaintlet() - Constructor for class adams.gui.visualization.instance.AbstractInstancePaintlet

AbstractInstancePanelUpdater - Class in adams.gui.visualization.instance

Ancestor for classes that determine when to update the instance panel, i.e., repaint all of it.

AbstractInstancePanelUpdater() - Constructor for class adams.gui.visualization.instance.AbstractInstancePanelUpdater

AbstractInstancesAnalysis - Class in adams.data.instancesanalysis

Ancestor for data analysis classes.

AbstractInstancesAnalysis() - Constructor for class adams.data.instancesanalysis.AbstractInstancesAnalysis

AbstractInstancesIndexedSplitsRunsGenerator - Class in adams.flow.transformer.indexedsplitsrunsgenerator

Ancestor for generators that process Instances objects.

AbstractInstancesIndexedSplitsRunsGenerator() - Constructor for class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

AbstractInvestigatorTab - Class in adams.gui.tools.wekainvestigator.tab

Ancestor for tabs in the Investigator.

AbstractInvestigatorTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

AbstractInvestigatorTab.SerializationOption - Enum in adams.gui.tools.wekainvestigator.tab

options for serialization.

AbstractInvestigatorTabWithDataTable - Class in adams.gui.tools.wekainvestigator.tab

Ancestor for tabs that have the data table on top.

AbstractInvestigatorTabWithDataTable() - Constructor for class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

AbstractInvestigatorTabWithEditableDataTable - Class in adams.gui.tools.wekainvestigator.tab

Ancestor for tabs with modifiable data table.

AbstractInvestigatorTabWithEditableDataTable() - Constructor for class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

AbstractLinearRegressionBased<T extends adams.data.container.DataContainer> - Class in adams.data.baseline

Abstract ancestor for linear regression based baseline correction schemes.

AbstractLinearRegressionBased() - Constructor for class adams.data.baseline.AbstractLinearRegressionBased

AbstractMatchWekaInstanceAgainstHeader - Class in adams.data.conversion

Ancestor for classes that match Instance objects against Instances headers.

AbstractMatchWekaInstanceAgainstHeader() - Constructor for class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader

AbstractMerge - Class in adams.flow.transformer.wekadatasetsmerge

AbstractMerge() - Constructor for class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

AbstractMerge.SourceAttribute - Class in adams.flow.transformer.wekadatasetsmerge

Helper class for determining the mapping from input attributes in the source datasets to output attributes in the merged dataset.

AbstractMultiClassPLS - Class in adams.data.instancesanalysis.pls

Ancestor for schemes that predict multiple classes.

AbstractMultiClassPLS() - Constructor for class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

AbstractMultiplicativeScatterCorrection - Class in weka.filters.unsupervised.attribute.multiplicativescattercorrection

Ancestor for correction schemes.

AbstractMultiplicativeScatterCorrection() - Constructor for class weka.filters.unsupervised.attribute.multiplicativescattercorrection.AbstractMultiplicativeScatterCorrection

AbstractMultiRowProcessorPlugin - Class in weka.filters.unsupervised.instance.multirowprocessor

Ancestor for MultiRowProcessor plugins.

AbstractMultiRowProcessorPlugin() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

AbstractNestableResultItem - Class in adams.gui.tools.wekainvestigator.output

Container for a data to be stored in result history that can also store nested result items.

AbstractNestableResultItem(Instances) - Constructor for class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem

Initializes the item.

AbstractNumericClassPostProcessor - Class in adams.flow.transformer.wekaevaluationpostprocessor

Ancestor for numeric class post-processors.

AbstractNumericClassPostProcessor() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.AbstractNumericClassPostProcessor

AbstractOutputGenerator<T extends AbstractResultItem> - Class in adams.gui.tools.wekainvestigator.output

Ancestor for output generators.

AbstractOutputGenerator - Class in adams.gui.tools.wekainvestigator.tab.associatetab.output

Ancestor for output generators using t.

AbstractOutputGenerator - Class in adams.gui.tools.wekainvestigator.tab.attseltab.output

Ancestor for output generators using t.

AbstractOutputGenerator - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Ancestor for output generators using the data from the per-fold pane.

AbstractOutputGenerator - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output

Ancestor for output generators using t.

AbstractOutputGenerator - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.output

Ancestor for output generators using the data from the per-fold pane.

AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator

AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.output.AbstractOutputGenerator

AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.output.AbstractOutputGenerator

AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.AbstractOutputGenerator

AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.AbstractOutputGenerator

AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.output.AbstractOutputGenerator

AbstractOutputGeneratorWithSeparateFoldsSupport<T extends JComponent> - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Ancestor for output generators that can generate output for separate folds just using the Evaluation objects.

AbstractOutputGeneratorWithSeparateFoldsSupport() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.AbstractOutputGeneratorWithSeparateFoldsSupport

AbstractOutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka

Ancestor for panels that allow the user to configure ResultListeners.

AbstractOutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel

AbstractOutputPanelWithPopupMenu<T extends adams.gui.chooser.BaseFileChooser> - Class in adams.gui.tools.wekainvestigator.output

Ancestor for output panels that can save the displayed output to a file.

AbstractOutputPanelWithPopupMenu() - Constructor for class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu

AbstractPanelWithFile<T extends adams.gui.chooser.AbstractChooserPanel> - Class in adams.gui.tools.weka

Ancestor for panels that allow the user to select a file.

AbstractPanelWithFile() - Constructor for class adams.gui.tools.weka.AbstractPanelWithFile

AbstractParameterHandlingWekaMenuItemDefinition - Class in adams.gui.menu

Abstract menu item definition for Weka elements that also handle additional parameters.

AbstractParameterHandlingWekaMenuItemDefinition() - Constructor for class adams.gui.menu.AbstractParameterHandlingWekaMenuItemDefinition

Initializes the menu item with no owner.

AbstractParameterHandlingWekaMenuItemDefinition(AbstractApplicationFrame) - Constructor for class adams.gui.menu.AbstractParameterHandlingWekaMenuItemDefinition

Initializes the menu item.

AbstractPerFoldPopupMenuItem - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold

Ancestor for classes that add menu items to the per-fold popup menu.

AbstractPerFoldPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem

AbstractPlotColumn - Class in adams.gui.visualization.instances.instancestable

Ancestor for plugins that plot a column.

AbstractPlotColumn() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractPlotColumn

AbstractPlotRow - Class in adams.gui.visualization.instances.instancestable

Ancestor for plugins that plot a row.

AbstractPlotRow() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractPlotRow

AbstractPlotSelectedRows - Class in adams.gui.visualization.instances.instancestable

Ancestor for plugins that plot rows.

AbstractPlotSelectedRows() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

AbstractPLS - Class in adams.data.instancesanalysis.pls

Ancestor for PLS implementations.

AbstractPLS() - Constructor for class adams.data.instancesanalysis.pls.AbstractPLS

AbstractPLSAttributeEval - Class in weka.attributeSelection

Ancestor for PLS attribute evaluators

AbstractPLSAttributeEval() - Constructor for class weka.attributeSelection.AbstractPLSAttributeEval

AbstractPLSAttributeEval.LoadingsCalculations - Enum in weka.attributeSelection

AbstractProcessCell - Class in adams.gui.visualization.instances.instancestable

Ancestor for plugins that process a cell.

AbstractProcessCell() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractProcessCell

AbstractProcessColumn - Class in adams.gui.visualization.instances.instancestable

Ancestor for plugins that process a column.

AbstractProcessColumn() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractProcessColumn

AbstractProcessRow - Class in adams.gui.visualization.instances.instancestable

Ancestor for plugins that process a row.

AbstractProcessRow() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractProcessRow

AbstractProcessSelectedRows - Class in adams.gui.visualization.instances.instancestable

Ancestor for plugins that process a row.

AbstractProcessSelectedRows() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

AbstractProcessWekaInstanceWithModel<T> - Class in adams.flow.transformer

Ancestor for transformers that user models for processing Instance objects, e.g., classifiers making predictions.

AbstractProcessWekaInstanceWithModel() - Constructor for class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

AbstractRangeBasedSelectionProcessor - Class in weka.filters.unsupervised.instance.multirowprocessor.processor

Ancestor for processors that work on a range of attributes.

AbstractRangeBasedSelectionProcessor() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor

AbstractRelationNameHeuristic - Class in adams.data.weka.relationname

Ancestor for heuristics that determine the relation name for a dataset.

AbstractRelationNameHeuristic() - Constructor for class adams.data.weka.relationname.AbstractRelationNameHeuristic

AbstractResultItem - Class in adams.gui.tools.wekainvestigator.output

Container for a data to be stored in result history.

AbstractResultItem(Instances) - Constructor for class adams.gui.tools.wekainvestigator.output.AbstractResultItem

Initializes the item.

AbstractResultsHandler - Class in adams.gui.tools.wekamultiexperimenter.experiment

Ancestor for classes that store the results from an experiment run.

AbstractResultsHandler() - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.AbstractResultsHandler

AbstractResultsPanel - Class in adams.gui.tools.wekamultiexperimenter.analysis

Ancestor for displaying the results of an analysis.

AbstractResultsPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel

AbstractRowFinder - Class in adams.data.weka.rowfinder

Ancestor for classes that find rows of interest in datasets.

AbstractRowFinder() - Constructor for class adams.data.weka.rowfinder.AbstractRowFinder

AbstractRowFinderApplier - Class in weka.filters.unsupervised.instance

Ancestor for filters that apply RowFinder schemes to the data.

AbstractRowFinderApplier() - Constructor for class weka.filters.unsupervised.instance.AbstractRowFinderApplier

AbstractRowFinderWithCapabilities - Class in adams.data.weka.rowfinder

Ancestor for classes that find rows of interest in datasets.

AbstractRowFinderWithCapabilities() - Constructor for class adams.data.weka.rowfinder.AbstractRowFinderWithCapabilities

AbstractRowSelection - Class in weka.filters.unsupervised.instance.multirowprocessor.selection

Ancestor for row selection schemes.

AbstractRowSelection() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.selection.AbstractRowSelection

AbstractSelectedAttributesAction - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction

Ancestor for actions on ther checked attributes in the PreprocessTab.

AbstractSelectedAttributesAction() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

AbstractSelectionProcessor - Class in weka.filters.unsupervised.instance.multirowprocessor.processor

Ancestor for row selection processors.

AbstractSelectionProcessor() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractSelectionProcessor

AbstractSetupOptionPanel - Class in adams.gui.tools.wekamultiexperimenter.setup

Ancestor for panels that get added to a AbstractSetupPanel.

AbstractSetupOptionPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

AbstractSetupPanel<T> - Class in adams.gui.tools.wekamultiexperimenter.setup

Ancestor for setup panels.

AbstractSetupPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

AbstractSetupPanel.ModificationActionListener - Class in adams.gui.tools.wekamultiexperimenter.setup

Action listener that just sets the modified flag.

AbstractSetupPanel.ModificationChangeListener - Class in adams.gui.tools.wekamultiexperimenter.setup

Change listener that just sets the modified flag.

AbstractSetupPanel.ModificationDocumentListener - Class in adams.gui.tools.wekamultiexperimenter.setup

Document listener that just sets the modified flag.

AbstractSimpleClassifier - Class in weka.classifiers.simple

Ancestor for classifiers using ADAMS option handling.

AbstractSimpleClassifier() - Constructor for class weka.classifiers.simple.AbstractSimpleClassifier

AbstractSimpleOptionHandler - Class in weka.core

Ancestor for Weka classes that use the ADAMS option handling framework.

AbstractSimpleOptionHandler() - Constructor for class weka.core.AbstractSimpleOptionHandler

AbstractSimpleRegressionMeasure - Class in weka.classifiers.evaluation

Computes the mean error.

AbstractSimpleRegressionMeasure() - Constructor for class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure

AbstractSingleClassPLS - Class in adams.data.instancesanalysis.pls

Ancestor for schemes that predict a single class.

AbstractSingleClassPLS() - Constructor for class adams.data.instancesanalysis.pls.AbstractSingleClassPLS

AbstractSource - Class in adams.gui.tools.wekainvestigator.source

Ancestor for additional "source" actions in the main menu.

AbstractSource() - Constructor for class adams.gui.tools.wekainvestigator.source.AbstractSource

AbstractSplitGenerator - Class in weka.classifiers

Ancestor for helper classes that generates dataset splits.

AbstractSplitGenerator() - Constructor for class weka.classifiers.AbstractSplitGenerator

Initializes the generator.

AbstractSplitter - Class in adams.data.weka.datasetsplitter

Parent class for different methods of splitting a dataset into smaller datasets.

AbstractSplitter() - Constructor for class adams.data.weka.datasetsplitter.AbstractSplitter

AbstractTokenCleaner - Class in weka.core.tokenizers.cleaners

Ancestor for cleaning tokens.

AbstractTokenCleaner() - Constructor for class weka.core.tokenizers.cleaners.AbstractTokenCleaner

AbstractTrainableColumnFinder - Class in adams.data.weka.columnfinder

Ancestor for ColumnFinder algorithms that can be trained.

AbstractTrainableColumnFinder() - Constructor for class adams.data.weka.columnfinder.AbstractTrainableColumnFinder

AbstractTrainableRowFinder - Class in adams.data.weka.rowfinder

Ancestor for RowFinder algorithms that can be trained.

AbstractTrainableRowFinder() - Constructor for class adams.data.weka.rowfinder.AbstractTrainableRowFinder

AbstractWekaClassifierEvaluator - Class in adams.flow.transformer

Ancestor for transformers that evaluate classifiers.

AbstractWekaClassifierEvaluator() - Constructor for class adams.flow.transformer.AbstractWekaClassifierEvaluator

AbstractWekaEnsembleGenerator - Class in adams.flow.transformer.wekaensemblegenerator

Ancestor for schemes that generate ensembles.

AbstractWekaEnsembleGenerator() - Constructor for class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator

AbstractWekaEvaluationPostProcessor - Class in adams.flow.transformer.wekaevaluationpostprocessor

Ancestor for classes that post-process Evaluation objects.

AbstractWekaEvaluationPostProcessor() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor

AbstractWekaExperimentIO<T extends weka.experiment.Experiment> - Class in adams.gui.tools.wekamultiexperimenter.io

Ancestor for classes that handle loading/saving of experiments.

AbstractWekaExperimentIO() - Constructor for class adams.gui.tools.wekamultiexperimenter.io.AbstractWekaExperimentIO

AbstractWekaExperimentRunner<T extends weka.experiment.Experiment> - Class in adams.gui.tools.wekamultiexperimenter.runner

Ancestor for classes that handle running a copy of the experiment in a separate thread.

AbstractWekaExperimentRunner(ExperimenterPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.runner.AbstractWekaExperimentRunner

Initializes the thread.

AbstractWEKAFitnessFunction - Class in adams.opt.optimise.genetic.fitnessfunctions

Perform attribute selection using WEKA classification.

AbstractWEKAFitnessFunction() - Constructor for class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

AbstractWEKAFitnessFunction.Measure - Enum in adams.opt.optimise.genetic.fitnessfunctions

The measure to use for evaluating.

AbstractWekaMenuItemDefinition - Class in adams.gui.menu

Abstract menu item menu item definitions for Weka elements.

AbstractWekaMenuItemDefinition() - Constructor for class adams.gui.menu.AbstractWekaMenuItemDefinition

Initializes the menu item with no owner.

AbstractWekaMenuItemDefinition(AbstractApplicationFrame) - Constructor for class adams.gui.menu.AbstractWekaMenuItemDefinition

Initializes the menu item.

AbstractWekaModelReader - Class in adams.flow.transformer

Ancestor for actors that deserialize models.

AbstractWekaModelReader() - Constructor for class adams.flow.transformer.AbstractWekaModelReader

AbstractWekaModelWriter - Class in adams.flow.sink

Ancestor for actors that serialize models.

AbstractWekaModelWriter() - Constructor for class adams.flow.sink.AbstractWekaModelWriter

AbstractWekaPackageManagerAction - Class in adams.flow.source.wekapackagemanageraction

Ancestor for package manager actions.

AbstractWekaPackageManagerAction - Class in adams.flow.standalone.wekapackagemanageraction

Ancestor for package manager actions.

AbstractWekaPackageManagerAction - Class in adams.flow.transformer.wekapackagemanageraction

Ancestor for package manager actions.

AbstractWekaPackageManagerAction() - Constructor for class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction

AbstractWekaPackageManagerAction() - Constructor for class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction

AbstractWekaPackageManagerAction() - Constructor for class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction

AbstractWekaPredictionsTransformer - Class in adams.flow.transformer

Ancestor for transformers that convert the predictions stored in an Evaluation object into a different format.

AbstractWekaPredictionsTransformer() - Constructor for class adams.flow.transformer.AbstractWekaPredictionsTransformer

AbstractWekaRepeatedCrossValidationOutput<T> - Class in adams.flow.transformer.wekarepeatedcrossvalidationoutput

Ancestor for classes that generate output from repeated cross-validations.

AbstractWekaRepeatedCrossValidationOutput() - Constructor for class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput

AbstractWekaSetupGenerator<T> - Class in adams.flow.source

Abstract ancestor for setup generator sources.

AbstractWekaSetupGenerator() - Constructor for class adams.flow.source.AbstractWekaSetupGenerator

AbstractWekaSetupPanel - Class in adams.gui.tools.wekamultiexperimenter.setup

Ancestor for setup panels for Weka experiments.

AbstractWekaSetupPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractWekaSetupPanel

AbstractWekaSpreadSheetReader - Class in adams.data.io.input

Ancestor for WEKA file format readers.

AbstractWekaSpreadSheetReader() - Constructor for class adams.data.io.input.AbstractWekaSpreadSheetReader

AbstractWekaSpreadSheetWriter - Class in adams.data.io.output

Ancestor for WEKA file format readers.

AbstractWekaSpreadSheetWriter() - Constructor for class adams.data.io.output.AbstractWekaSpreadSheetWriter

ACC - adams.flow.transformer.WekaClassifierRanker.Measure

evaluation via: Accuracy.

ACC - adams.opt.genetic.Measure

Accuracy.

ACC - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure

evaluation via: Accuracy.

accepts() - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.AdamsInstanceToWekaInstance

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.MapToWekaInstance

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.ReportToWekaInstance

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.SpreadSheetToWekaInstances

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.WekaCapabilitiesToInstances

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.WekaCapabilitiesToSpreadSheet

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.WekaDrawableToString

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.WekaEvaluationToCostCurve

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.WekaEvaluationToMarginCurve

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.WekaInstanceToAdamsInstance

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.WekaInstanceToMap

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.WekaPackageToMap

Returns the class that is accepted as input.

accepts() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the class that is accepted as input.

accepts() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.condition.bool.AdamsInstanceCapabilities

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.condition.bool.WekaCapabilities

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.condition.bool.WekaClassification

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.AbstractWekaModelWriter

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaAttributeSummary

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaClassifierErrors

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaCostCurve

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaExperimentFileWriter

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaFileWriter

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaGraphVisualizer

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaInstancesDisplay

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaInstancesPlot

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaMarginCurve

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaThresholdCurve

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.sink.WekaTreeVisualizer

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.AbstractInstanceGenerator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.AbstractWekaModelReader

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

The accepted classes.

accepts() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

Returns the type of classes that are accepted as input.

accepts() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

The accepted classes.

accepts() - Method in class adams.flow.transformer.WekaAccumulatedError

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaAggregateEvaluations

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaAttributeIterator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaAttributeSelectionSummary

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaChooseAttributes

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaClassifierInfo

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaClassifierOptimizer

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaClassSelector

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaClusterAssignments

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaClustererInfo

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaClustererPostProcessor

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaDatasetsMerge

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaDatasetSplit

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator

Returns the input data the generator processes.

accepts() - Method in class adams.flow.transformer.WekaEnsembleGenerator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels

Returns the input data the generator processes.

accepts() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels

Returns the input data the generator processes.

accepts() - Method in class adams.flow.transformer.WekaEvaluationInfo

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaEvaluationValues

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaExperiment

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaExperimentExecution

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaExperimentFileReader

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaExtractArray

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaExtractPLSMatrix

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaFileReader

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaFilter

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaGetCapabilities

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaGetInstancesValue

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaGetInstanceValue

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaInstancesAppend

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaInstancesInfo

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaInstancesStatistic

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaNewInstance

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction

The types of data the action accepts.

accepts() - Method in class adams.flow.transformer.WekaPackageManagerAction

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromFile

The types of data the action accepts.

accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromURL

The types of data the action accepts.

accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

The types of data the action accepts.

accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallPackage

The types of data the action accepts.

accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall

The types of data the action accepts.

accepts() - Method in class adams.flow.transformer.WekaPrincipalComponents

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaRandomSplit

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaRegexToRange

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaRelationName

Deprecated.

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaRenameRelation

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaSetInstancesValue

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaSetInstanceValue

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaSplitGenerator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaStoreInstance

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaStreamEvaluator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaStreamFilter

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaSubsets

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaTextDirectoryReader

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaTrainAssociator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaTrainClassifier

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaTrainClusterer

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

Returns the class that the consumer accepts.

accepts() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator

Returns the class that the consumer accepts.

acceptSelection() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Generates the indices.

AccessibleGenericObjectEditor() - Constructor for class adams.gui.goe.WekaEditorsRegistration.AccessibleGenericObjectEditor

AccessiblePluginManager() - Constructor for class adams.gui.goe.WekaEditorsRegistration.AccessiblePluginManager

AccumulatedLWLWeights - Class in weka.filters.unsupervised.instance

Generates an LWL-like dataset for each instance of the data from the first batch and accumulate these weights.

AccumulatedLWLWeights() - Constructor for class weka.filters.unsupervised.instance.AccumulatedLWLWeights

actCol - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState

the actual column.

actionPerformed(ActionEvent) - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

Gets called when the one of the buttons in the GOE panel gets pressed.

actionPerformed(ActionEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationActionListener

actionTipText() - Method in class adams.flow.source.WekaPackageManagerAction

Returns the tip text for this property.

actionTipText() - Method in class adams.flow.standalone.WekaPackageManagerAction

Returns the tip text for this property.

actionTipText() - Method in class adams.flow.transformer.WekaPackageManagerAction

Returns the tip text for this property.

activate() - Method in class adams.gui.application.WekaExperimenterPreferencesPanel

Activates the settings.

activate() - Method in class adams.gui.application.WekaExplorerPreferencesPanel

Activates the settings.

activate() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel

Activates the settings.

activate(int) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Activates the selected dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Activates the specified dataset.

activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Activates the specified dataset.

actRow - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState

the actual row.

actRows - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState

the actual rows.

ACTUAL_MINUS_PREDICTED - adams.flow.transformer.WekaBootstrapping.ErrorCalculation

actualMaxTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

actualMinTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

actualTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the tip text for this property.

actualTipText() - Method in class weka.classifiers.functions.FromPredictions

Returns the tip text for this property.

ADAMS_FILE_EXTENSION - Static variable in class adams.gui.menu.MakeCompatibleDatasets

ADAMS_READER - Static variable in class adams.gui.menu.MakeCompatibleDatasets

adams.core.base - package adams.core.base

adams.core.classmanager - package adams.core.classmanager

adams.core.discovery.genetic - package adams.core.discovery.genetic

adams.core.management - package adams.core.management

adams.core.option - package adams.core.option

adams.core.option.parsing - package adams.core.option.parsing

adams.data - package adams.data

adams.data.baseline - package adams.data.baseline

adams.data.binning - package adams.data.binning

adams.data.conversion - package adams.data.conversion

adams.data.featureconverter - package adams.data.featureconverter

adams.data.indexedsplits - package adams.data.indexedsplits

adams.data.instance - package adams.data.instance

adams.data.instances - package adams.data.instances

adams.data.instancesanalysis - package adams.data.instancesanalysis

adams.data.instancesanalysis.pls - package adams.data.instancesanalysis.pls

adams.data.io.input - package adams.data.io.input

adams.data.io.output - package adams.data.io.output

adams.data.spreadsheet.filter - package adams.data.spreadsheet.filter

adams.data.weka - package adams.data.weka

adams.data.weka.classattribute - package adams.data.weka.classattribute

adams.data.weka.columnfinder - package adams.data.weka.columnfinder

adams.data.weka.datasetsplitter - package adams.data.weka.datasetsplitter

adams.data.weka.evaluator - package adams.data.weka.evaluator

adams.data.weka.predictions - package adams.data.weka.predictions

adams.data.weka.relationname - package adams.data.weka.relationname

adams.data.weka.rowfinder - package adams.data.weka.rowfinder

adams.data.wekapyroproxy - package adams.data.wekapyroproxy

adams.env - package adams.env

adams.flow.condition.bool - package adams.flow.condition.bool

adams.flow.container - package adams.flow.container

adams.flow.core - package adams.flow.core

adams.flow.sink - package adams.flow.sink

adams.flow.source - package adams.flow.source

adams.flow.source.valuedefinition - package adams.flow.source.valuedefinition

adams.flow.source.wekapackagemanageraction - package adams.flow.source.wekapackagemanageraction

adams.flow.standalone - package adams.flow.standalone

adams.flow.standalone.wekapackagemanageraction - package adams.flow.standalone.wekapackagemanageraction

adams.flow.template - package adams.flow.template

adams.flow.transformer - package adams.flow.transformer

adams.flow.transformer.indexedsplitsrunsevaluation - package adams.flow.transformer.indexedsplitsrunsevaluation

adams.flow.transformer.indexedsplitsrunsgenerator - package adams.flow.transformer.indexedsplitsrunsgenerator

adams.flow.transformer.indexedsplitsrunspredictions - package adams.flow.transformer.indexedsplitsrunspredictions

adams.flow.transformer.wekaclassifiersetupprocessor - package adams.flow.transformer.wekaclassifiersetupprocessor

adams.flow.transformer.wekaclusterer - package adams.flow.transformer.wekaclusterer

adams.flow.transformer.wekadatasetsmerge - package adams.flow.transformer.wekadatasetsmerge

adams.flow.transformer.wekaensemblegenerator - package adams.flow.transformer.wekaensemblegenerator

adams.flow.transformer.wekaevaluationpostprocessor - package adams.flow.transformer.wekaevaluationpostprocessor

adams.flow.transformer.wekapackagemanageraction - package adams.flow.transformer.wekapackagemanageraction

adams.flow.transformer.wekarepeatedcrossvalidationoutput - package adams.flow.transformer.wekarepeatedcrossvalidationoutput

adams.gui - package adams.gui

adams.gui.application - package adams.gui.application

adams.gui.chooser - package adams.gui.chooser

adams.gui.event - package adams.gui.event

adams.gui.flow.tree.quickaction - package adams.gui.flow.tree.quickaction

adams.gui.goe - package adams.gui.goe

adams.gui.goe.popupmenu - package adams.gui.goe.popupmenu

adams.gui.help - package adams.gui.help

adams.gui.menu - package adams.gui.menu

adams.gui.tools - package adams.gui.tools

adams.gui.tools.previewbrowser - package adams.gui.tools.previewbrowser

adams.gui.tools.weka - package adams.gui.tools.weka

adams.gui.tools.wekainvestigator - package adams.gui.tools.wekainvestigator

adams.gui.tools.wekainvestigator.data - package adams.gui.tools.wekainvestigator.data

adams.gui.tools.wekainvestigator.datatable - package adams.gui.tools.wekainvestigator.datatable

adams.gui.tools.wekainvestigator.datatable.action - package adams.gui.tools.wekainvestigator.datatable.action

adams.gui.tools.wekainvestigator.evaluation - package adams.gui.tools.wekainvestigator.evaluation

adams.gui.tools.wekainvestigator.history - package adams.gui.tools.wekainvestigator.history

adams.gui.tools.wekainvestigator.job - package adams.gui.tools.wekainvestigator.job

adams.gui.tools.wekainvestigator.output - package adams.gui.tools.wekainvestigator.output

adams.gui.tools.wekainvestigator.source - package adams.gui.tools.wekainvestigator.source

adams.gui.tools.wekainvestigator.tab - package adams.gui.tools.wekainvestigator.tab

adams.gui.tools.wekainvestigator.tab.associatetab - package adams.gui.tools.wekainvestigator.tab.associatetab

adams.gui.tools.wekainvestigator.tab.associatetab.evaluation - package adams.gui.tools.wekainvestigator.tab.associatetab.evaluation

adams.gui.tools.wekainvestigator.tab.associatetab.history - package adams.gui.tools.wekainvestigator.tab.associatetab.history

adams.gui.tools.wekainvestigator.tab.associatetab.output - package adams.gui.tools.wekainvestigator.tab.associatetab.output

adams.gui.tools.wekainvestigator.tab.attseltab - package adams.gui.tools.wekainvestigator.tab.attseltab

adams.gui.tools.wekainvestigator.tab.attseltab.evaluation - package adams.gui.tools.wekainvestigator.tab.attseltab.evaluation

adams.gui.tools.wekainvestigator.tab.attseltab.history - package adams.gui.tools.wekainvestigator.tab.attseltab.history

adams.gui.tools.wekainvestigator.tab.attseltab.output - package adams.gui.tools.wekainvestigator.tab.attseltab.output

adams.gui.tools.wekainvestigator.tab.classifytab - package adams.gui.tools.wekainvestigator.tab.classifytab

adams.gui.tools.wekainvestigator.tab.classifytab.evaluation - package adams.gui.tools.wekainvestigator.tab.classifytab.evaluation

adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel - package adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel

adams.gui.tools.wekainvestigator.tab.classifytab.history - package adams.gui.tools.wekainvestigator.tab.classifytab.history

adams.gui.tools.wekainvestigator.tab.classifytab.output - package adams.gui.tools.wekainvestigator.tab.classifytab.output

adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold - package adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold

adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated - package adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated

adams.gui.tools.wekainvestigator.tab.clustertab - package adams.gui.tools.wekainvestigator.tab.clustertab

adams.gui.tools.wekainvestigator.tab.clustertab.evaluation - package adams.gui.tools.wekainvestigator.tab.clustertab.evaluation

adams.gui.tools.wekainvestigator.tab.clustertab.history - package adams.gui.tools.wekainvestigator.tab.clustertab.history

adams.gui.tools.wekainvestigator.tab.clustertab.output - package adams.gui.tools.wekainvestigator.tab.clustertab.output

adams.gui.tools.wekainvestigator.tab.experimenttab - package adams.gui.tools.wekainvestigator.tab.experimenttab

adams.gui.tools.wekainvestigator.tab.experimenttab.output - package adams.gui.tools.wekainvestigator.tab.experimenttab.output

adams.gui.tools.wekainvestigator.tab.experimenttab.setup - package adams.gui.tools.wekainvestigator.tab.experimenttab.setup

adams.gui.tools.wekainvestigator.tab.preprocesstab - package adams.gui.tools.wekainvestigator.tab.preprocesstab

adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction - package adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction

adams.gui.tools.wekamultiexperimenter - package adams.gui.tools.wekamultiexperimenter

adams.gui.tools.wekamultiexperimenter.analysis - package adams.gui.tools.wekamultiexperimenter.analysis

adams.gui.tools.wekamultiexperimenter.experiment - package adams.gui.tools.wekamultiexperimenter.experiment

adams.gui.tools.wekamultiexperimenter.io - package adams.gui.tools.wekamultiexperimenter.io

adams.gui.tools.wekamultiexperimenter.runner - package adams.gui.tools.wekamultiexperimenter.runner

adams.gui.tools.wekamultiexperimenter.setup - package adams.gui.tools.wekamultiexperimenter.setup

adams.gui.tools.wekamultiexperimenter.setup.weka - package adams.gui.tools.wekamultiexperimenter.setup.weka

adams.gui.visualization.debug.inspectionhandler - package adams.gui.visualization.debug.inspectionhandler

adams.gui.visualization.debug.objectexport - package adams.gui.visualization.debug.objectexport

adams.gui.visualization.debug.objectrenderer - package adams.gui.visualization.debug.objectrenderer

adams.gui.visualization.instance - package adams.gui.visualization.instance

adams.gui.visualization.instance.containerlistpopup - package adams.gui.visualization.instance.containerlistpopup

adams.gui.visualization.instance.plotpopup - package adams.gui.visualization.instance.plotpopup

adams.gui.visualization.instances - package adams.gui.visualization.instances

adams.gui.visualization.instances.instancestable - package adams.gui.visualization.instances.instancestable

adams.gui.visualization.weka - package adams.gui.visualization.weka

adams.gui.wizard - package adams.gui.wizard

adams.ml.data - package adams.ml.data

adams.ml.model.classification - package adams.ml.model.classification

adams.ml.model.clustering - package adams.ml.model.clustering

adams.ml.model.regression - package adams.ml.model.regression

adams.multiprocess - package adams.multiprocess

adams.opt.genetic - package adams.opt.genetic

adams.opt.genetic.initialsetups - package adams.opt.genetic.initialsetups

adams.opt.optimise - package adams.opt.optimise

adams.opt.optimise.genetic - package adams.opt.optimise.genetic

adams.opt.optimise.genetic.fitnessfunctions - package adams.opt.optimise.genetic.fitnessfunctions

adams.tools - package adams.tools

AdamsExperimentFileChooser - Class in adams.gui.chooser

A specialized JFileChooser that lists all available file Readers and Writers for ADAMS Experiments.

AdamsExperimentFileChooser() - Constructor for class adams.gui.chooser.AdamsExperimentFileChooser

Constructs a FileChooser pointing to the user's default directory.

AdamsExperimentFileChooser(File) - Constructor for class adams.gui.chooser.AdamsExperimentFileChooser

Constructs a FileChooser using the given File as the path.

AdamsExperimentFileChooser(String) - Constructor for class adams.gui.chooser.AdamsExperimentFileChooser

Constructs a FileChooser using the given path.

AdamsExperimentRunner<T extends AbstractExperiment> - Class in adams.gui.tools.wekamultiexperimenter.runner

Ancestor for classes that handle running a copy of the experiment in a separate thread.

AdamsExperimentRunner(ExperimenterPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.runner.AdamsExperimentRunner

Initializes the thread.

AdamsHelper - Class in weka.gui

Helper class to make Weka GUI more ADAMS-like.

AdamsHelper() - Constructor for class weka.gui.AdamsHelper

AdamsInstanceCapabilities - Class in adams.flow.condition.bool

Filters adams.data.instance.Instance based on defined capabilities.

AdamsInstanceCapabilities() - Constructor for class adams.flow.condition.bool.AdamsInstanceCapabilities

AdamsInstanceToWekaInstance - Class in adams.data.conversion

Converts adams.data.instance.Instance objects into weka.core.Instance ones.

AdamsInstanceToWekaInstance() - Constructor for class adams.data.conversion.AdamsInstanceToWekaInstance

add(int, Instance) - Method in class weka.core.InstancesView

Adds one instance at the given position in the list.

add(SpreadSheet, int, int, int, int[], boolean) - Method in class weka.classifiers.AggregateEvaluations

Adds the data from the spreadsheet as predictions.

add(ArrayHistogram, Instance) - Method in class adams.gui.visualization.instance.HistogramFactory.Dialog

Adds a plot of the given instance.

add(ArrayHistogram, Instance) - Method in class adams.gui.visualization.instance.HistogramFactory.Panel

Adds a plot of the given instance.

add(ArrayHistogram, Instance, String) - Method in class adams.gui.visualization.instance.HistogramFactory.Dialog

Adds a plot of the given instance.

add(ArrayHistogram, Instance, String) - Method in class adams.gui.visualization.instance.HistogramFactory.Panel

Adds a plot of the given instance.

add(DataContainer) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

Adds the data container and sets the undo enabled flag accordingly.

add(InstanceContainer) - Method in class adams.gui.visualization.instance.InstanceContainerManager

Adds the given container to the list.

add(String, int, double, double) - Method in class adams.opt.optimise.genetic.PackDataDef

add(List<String>, char, boolean) - Static method in class weka.core.WekaOptionUtils

Adds the boolean flag (if true) to the options.

add(List<String>, char, double) - Static method in class weka.core.WekaOptionUtils

Adds the double value to the options.

add(List<String>, char, float) - Static method in class weka.core.WekaOptionUtils

Adds the float value to the options.

add(List<String>, char, int) - Static method in class weka.core.WekaOptionUtils

Adds the int value to the options.

add(List<String>, char, long) - Static method in class weka.core.WekaOptionUtils

Adds the long value to the options.

add(List<String>, char, BaseObject) - Static method in class weka.core.WekaOptionUtils

Adds the BaseObject to the options.

add(List<String>, char, BaseObject[]) - Static method in class weka.core.WekaOptionUtils

Adds the BaseObject to the options.

add(List<String>, char, Index) - Static method in class weka.core.WekaOptionUtils

Adds the Index to the options.

add(List<String>, char, Index[]) - Static method in class weka.core.WekaOptionUtils

Adds the Index to the options.

add(List<String>, char, OptionHandler) - Static method in class weka.core.WekaOptionUtils

Adds the adams.core.option.OptionHandler to the options.

add(List<String>, char, Range) - Static method in class weka.core.WekaOptionUtils

Adds the adams.core.Range to the options.

add(List<String>, char, Range[]) - Static method in class weka.core.WekaOptionUtils

Adds the adams.core.Range to the options.

add(List<String>, char, File) - Static method in class weka.core.WekaOptionUtils

Adds the File value to the options.

add(List<String>, char, Enum) - Static method in class weka.core.WekaOptionUtils

Adds the enum value to the options.

add(List<String>, char, Object) - Static method in class weka.core.WekaOptionUtils

Adds the array to the options.

add(List<String>, char, String) - Static method in class weka.core.WekaOptionUtils

Adds the String value to the options.

add(List<String>, char, OptionHandler) - Static method in class weka.core.WekaOptionUtils

Adds the OptionHandler to the options.

add(List<String>, String[]) - Static method in class weka.core.WekaOptionUtils

Adds the "super" options to the current list.

add(List<String>, String, boolean) - Static method in class weka.core.WekaOptionUtils

Adds the boolean flag (if true) to the options.

add(List<String>, String, double) - Static method in class weka.core.WekaOptionUtils

Adds the double value to the options.

add(List<String>, String, float) - Static method in class weka.core.WekaOptionUtils

Adds the float value to the options.

add(List<String>, String, int) - Static method in class weka.core.WekaOptionUtils

Adds the int value to the options.

add(List<String>, String, long) - Static method in class weka.core.WekaOptionUtils

Adds the long value to the options.

add(List<String>, String, BaseObject) - Static method in class weka.core.WekaOptionUtils

Adds the BaseObject to the options.

add(List<String>, String, BaseObject[]) - Static method in class weka.core.WekaOptionUtils

Adds the BaseObject to the options.

add(List<String>, String, Index) - Static method in class weka.core.WekaOptionUtils

Adds the Index to the options.

add(List<String>, String, Index[]) - Static method in class weka.core.WekaOptionUtils

Adds the Index to the options.

add(List<String>, String, OptionHandler) - Static method in class weka.core.WekaOptionUtils

Adds the adams.core.option.OptionHandler to the options.

add(List<String>, String, Range) - Static method in class weka.core.WekaOptionUtils

Adds the adams.core.Range to the options.

add(List<String>, String, Range[]) - Static method in class weka.core.WekaOptionUtils

Adds the adams.core.Range to the options.

add(List<String>, String, File) - Static method in class weka.core.WekaOptionUtils

Adds the File value to the options.

add(List<String>, String, Enum) - Static method in class weka.core.WekaOptionUtils

Adds the enum value to the options.

add(List<String>, String, Object) - Static method in class weka.core.WekaOptionUtils

Adds the array to the options.

add(List<String>, String, String) - Static method in class weka.core.WekaOptionUtils

Adds the String value to the options.

add(List<String>, String, OptionHandler) - Static method in class weka.core.WekaOptionUtils

Adds the OptionHandler to the options.

add(Vector, Enumeration) - Static method in class weka.core.WekaOptionUtils

Adds the option description of the super class.

add(Evaluation) - Method in class weka.classifiers.AggregateEvaluations

Adds the predictions of the given Evaluation object.

add(Prediction) - Method in class weka.classifiers.AggregateEvaluations

Adds the prediction.

add(Instance) - Method in class weka.core.InstancesView

Adds one instance to the end of the set.

ADD - adams.gui.event.InstancesSortSetupEvent.EventType

a definition was added.

addAction(InstancesTablePopupMenuItemHelper.TableState, boolean, JMenuItem, InstancesTablePopupMenuItem) - Static method in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper

Adds the appropriate action to the menuitem.

addAdditionalAttributes(SpreadSheet, Instances, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Adds the additional columns from the Instances to the spreadsheet.

addAdditionalAttributes(SpreadSheet, Instances, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Adds the additional columns from the Instances to the spreadsheet.

addAdditionalAttributes(SpreadSheet, Instances, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Adds the additional columns from the Instances to the spreadsheet.

addAll(Collection<? extends DataContainer>) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

Adds all the data containers and sets their undo enabled flag accordingly.

addAttributeInformationTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

Returns the tip text for this property.

addCapabilities(String, Capabilities) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator

generates a string from the capapbilities, suitable to add to the help text.

addCell(int) - Method in class adams.ml.data.InstancesHeaderRow

Adds a cell with the key of the cell in the header at the specified location.

addCell(int) - Method in class adams.ml.data.InstanceView

Adds a cell with the key of the cell in the header at the specified location.

addCell(String) - Method in class adams.ml.data.InstancesHeaderRow

Adds a cell with the given key to the list and returns the created object.

addCell(String) - Method in class adams.ml.data.InstanceView

Adds a cell with the given key to the list and returns the created object.

addChangeListener(ChangeListener) - Method in class adams.gui.goe.WekaGenericObjectEditorPopupMenu

Adds the listener to the internal list of listeners that get notified when the user changes the setup.

addChangeListener(ChangeListener) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Adds the change listener to the internal list.

addChangeListener(ChangeListener) - Method in class adams.gui.visualization.instances.InstancesTable

Adds the listener to the pool of listeners that get notified when the data changes.

addClassificationLabelTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the tip text for this property.

addClassificationTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the tip text for this property.

addClassifier(Classifier) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Adds a classifier.

AddCluster - Class in adams.flow.transformer.wekaclusterer

Just adds the predicted cluster (or distribution) to the original dataset.
Stored in container under: Clustered dataset

AddCluster() - Constructor for class adams.flow.transformer.wekaclusterer.AddCluster

addComment(String) - Method in class adams.ml.data.InstancesView

Adds the comment to the internal list of comments.

addComment(List<String>) - Method in class adams.ml.data.InstancesView

Ignored.

addData(DataContainer) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource

Adds the data.

addDatabaseIDTipText() - Method in class adams.data.instances.AbstractInstanceGenerator

Returns the tip text for this property.

addDataset(PlaceholderFile) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Adds a dataset.

addDatasetInfo(JsonObject, Instances) - Method in class weka.classifiers.meta.socketfacade.Simple

Information about the dataset to the JSON object.

addDatasetInformationTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

Returns the tip text for this property.

addDefaultTabs() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Adds the default tabs.

addDefinition() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Adds a new definition.

addDistributionTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the tip text for this property.

addFlag(Vector, String, char) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addFlag(Vector, String, String) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addIndexTipText() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the tip text for this property.

addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.FilteredSearch

Adds the given instance info.

addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.NewNNSearch

Adds the given instance info.

addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.PCANNSearch

Adds the given instance info.

addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.PLSNNSearch

Adds the given instance info.

addInstancesSortSetupListener(InstancesSortSetupListener) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Adds the specified listener.

addIQR(Integer, TDoubleArrayList) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Calculates and adds the IQR stats for this key.

AdditionalExplorerPanel - Interface in weka.gui.explorer.panels

Interface for classes that supply additional Explorer panels.

additionalFieldsTipText() - Method in interface adams.data.instances.InstanceGeneratorWithAdditionalFields

Returns the tip text for this property.

additionalTipText() - Method in class weka.classifiers.functions.FromPredictions

Returns the tip text for this property.

addLabelIndexTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the tip text for this property.

addLabelIndexTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Returns the tip text for this property.

addLastSetup(Class, boolean, boolean, Object) - Method in class adams.gui.visualization.instances.InstancesTable

Stores this last setup.

addMetaLevelPrediction(Instance, int, double) - Method in class weka.classifiers.meta.ClassifierCascade

Adds the class distribution of the specified classifier to the meta-level instance.

addMetaLevelPrediction(Instance, int, double[]) - Method in class weka.classifiers.meta.ClassifierCascade

Adds the class distribution of the specified classifier to the meta-level instance.

addMetric(SpreadSheet, String, Object) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

Adds the metric to the results, automatically expands spreadsheet.

addMetrics(SpreadSheet, int, Classifier, Instances, Evaluation) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

Adds the metrics from the Evaluation object to the results.

addNestedItem(String, AbstractNestableResultItem) - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem

Adds the nested item.

addObjectSize(MetaData, String, Object) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Adds the object size to the meta-data.

addOneTipText() - Method in class weka.filters.unsupervised.attribute.LogTransform

Returns the tip text for this property.

addOption(Vector, String, Index, char) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addOption(Vector, String, Index, String) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addOption(Vector, String, Range, char) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addOption(Vector, String, Range, String) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addOption(Vector, String, String, char) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addOption(Vector, String, String, String) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addOption(Vector, String, OptionHandler, char) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addOption(Vector, String, OptionHandler, String) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addOption(Vector, String, Range, char) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addOption(Vector, String, Range, String) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addOption(Vector, String, SingleIndex, char) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addOption(Vector, String, SingleIndex, String) - Static method in class weka.core.WekaOptionUtils

Adds an Option for a flag to the list of options.

addPage(MultiPagePane, String, JComponent, int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.AbstractOutputGenerator

Adds a page for the confusion matrix.

addPage(String, Component, int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane

Adds the page at the end.

addPanel(ExplorerExt, String) - Method in class weka.gui.explorer.MultiExplorer

Adds the given explorer panel.

addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.SqlPanel

Adds a PropertyChangeListener who will be notified of value changes.

addRecentFile(File, AbstractFileLoader) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Adds the specified file/loader combination to the recent files list.

addResult(String, Double) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Adds a result to the cache.

addResult(String, Double) - Method in class adams.opt.optimise.GeneticAlgorithm

Adds a result to the cache.

addRow() - Method in class adams.ml.data.InstancesView

Appends a row to the spreadsheet.

addRow(String) - Method in class adams.ml.data.InstancesView

Adds a row with the given key to the list and returns the created object.

addSecondResult(String, Double) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Adds a result to the cache (second evaluation).

addSelectionListener(ListSelectionListener) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Add a listener to the list that's notified each time a change to the selection occurs.

addStatistic(SpreadSheet, String, Object) - Method in class adams.flow.transformer.WekaInstancesInfo

Adds a statistic to the dataset.

addStatistic(Evaluation, SpreadSheet, EvaluationStatistic, int, boolean) - Method in class adams.flow.transformer.WekaEvaluationValues

Adds the specified statistic to the spreadsheet.

addSubRangeInfo(MetaData, double[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation

Adds the range information to a clone of the provided meta-data info and returns it.

addSubRangeInfo(MetaData, double[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation

Adds the range information to a clone of the provided meta-data info and returns it.

addTab(AbstractInvestigatorTab) - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane

Adds the tab.

addTab(AbstractInvestigatorTab, boolean) - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane

Adds the tab.

addTab(T, JComponent) - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator

Adds the component as tab to the result item.

addTableModelListener(TableModelListener) - Method in class adams.gui.visualization.instances.InstancesTableModel

adds a listener to the list that is notified each time a change to data model occurs

addToHistory(AbstractNamedHistoryPanel<R>, R) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Adds the item to the history and selects it.

addToPopupMenu(InstancesTablePopupMenuItemHelper.TableState, boolean, JPopupMenu, List<InstancesTablePopupMenuItem>, Set<Class>) - Static method in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper

Adds the available menu items to the menu.

addToPopupMenu(InstancesTablePopupMenuItemHelper.TableState, JPopupMenu, boolean) - Static method in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper

Adds the available menu items to the menu.

addUndoPoint() - Method in class adams.gui.visualization.instances.InstancesTable

adds an undo point to the undo history, if the undo support is enabled

addUndoPoint() - Method in class adams.gui.visualization.instances.InstancesTableModel

adds an undo point to the undo history, if the undo support is enabled

addUndoPoint(String) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Adds an undo point with the given comment.

adjust(double) - Method in enum adams.opt.genetic.Measure

Adjusts the measure value for sorting: either multiplies it with -1 or 1.

adjust(double) - Method in enum adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure

Adjusts the measure value for sorting: either multiplies it with -1 or 1.

Adjust - Class in adams.gui.visualization.instance.plotpopup

Whether to adjust the plot to the loaded or visible data.

Adjust() - Constructor for class adams.gui.visualization.instance.plotpopup.Adjust

afterTableLayoutChanged() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTable

Can be called after the layout changed.

afterTableLayoutChanged() - Method in class adams.gui.visualization.instances.InstancesTable

Can be called after the layout changed.

aggregated() - Method in class weka.classifiers.AggregateEvaluations

Returns the aggregated evaluation.

AggregateEvaluations - Class in weka.classifiers

Allows the aggregation of Evaluation objects.

AggregateEvaluations() - Constructor for class weka.classifiers.AggregateEvaluations

Initializes the object.

ALGORITHM_CDF2_4 - Static variable in class weka.filters.unsupervised.attribute.FastWavelet

the type of algorithm: CDF2 4.

ALGORITHM_DAUBECHIES2 - Static variable in class weka.filters.unsupervised.attribute.FastWavelet

the type of algorithm: Daubechies2.

ALGORITHM_HAAR - Static variable in class weka.filters.unsupervised.attribute.FastWavelet

the type of algorithm: Haar.

ALGORITHM_SYMMLET8 - Static variable in class weka.filters.unsupervised.attribute.FastWavelet

the type of algorithm: Symmlet8.

algorithmsTipText() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

algorithmTipText() - Method in class adams.data.instancesanalysis.PLS

Returns the tip text for this property.

algorithmTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns the tip text for this property.

algorithmTipText() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

algorithmTipText() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

algorithmTipText() - Method in class weka.classifiers.functions.GeneticAlgorithm

Returns the tip text for this property.

algorithmTipText() - Method in class weka.classifiers.functions.PLSWeighted

Returns the tip text for this property

algorithmTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

algorithmTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

algorithmTipText() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the tip text for this property

algorithmTipText() - Method in class weka.filters.supervised.attribute.PLS

Returns the tip text for this property

algorithmTipText() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Returns the tip text for this property.

AlignDataset - Class in weka.filters.unsupervised.instance

Aligns the dataset(s) passing through to the reference dataset.
Makes use of the following other filters internally:
- weka.filters.unsupervised.attribute.AnyToString
- weka.filters.unsupervised.instance.RemoveWithLabels

Valid options are:

AlignDataset() - Constructor for class weka.filters.unsupervised.instance.AlignDataset

alignIndices(int[]) - Static method in class weka.classifiers.CrossValidationHelper

Reorders the indices to align with the original data.

alignPredictions(ArrayList<Prediction>, int[]) - Static method in class weka.classifiers.CrossValidationHelper

Reorders the predictions to align with the original data.

ALL - adams.data.instancesanalysis.pls.PredictionType

predict all Ys.

ALL - adams.flow.source.wekapackagemanageraction.ListPackages.ListType

ALL - adams.opt.genetic.OutputType

setup and data.

AllFinder - Class in adams.data.weka.columnfinder

Dummy finder, finds all columns.

AllFinder - Class in adams.data.weka.rowfinder

Dummy finder, finds all rows.

AllFinder() - Constructor for class adams.data.weka.columnfinder.AllFinder

AllFinder() - Constructor for class adams.data.weka.rowfinder.AllFinder

allowAccessToFullInputFormat() - Method in class weka.filters.FilteredFilter

Returns whether to allow the determineOutputFormat(Instances) method access to the full dataset rather than just the header.

allowAccessToFullInputFormat() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Returns whether to allow the determineOutputFormat(Instances) method access to the full dataset rather than just the header.

allowAccessToFullInputFormat() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Returns whether to allow the determineOutputFormat(Instances) method access to the full dataset rather than just the header.

alphaTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the alpha option.

alphaTipText() - Method in class weka.filters.supervised.attribute.YGradientEPO

Returns the tip text for this property

alphaTipText() - Method in class weka.filters.supervised.attribute.YGradientGLSW

Returns the tip text for this property

alwaysShowMarkersTipText() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Returns the tip text for this property.

alwaysUseContainerTipText() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Returns the tip text for this property.

amountTipText() - Method in class weka.filters.unsupervised.instance.LatestRecords

Returns the tip text for this property.

AnalysisPanel - Class in adams.gui.tools.wekamultiexperimenter

The analysis panel.

AnalysisPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

analyze() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Performs the analysis.

AndrewsCurves - Class in weka.filters.unsupervised.attribute

Generates Andrews Curves from array data.
César Ignacio García Osorio, Colin Fyfe (2003).

AndrewsCurves() - Constructor for class weka.filters.unsupervised.attribute.AndrewsCurves

antiAliasingEnabledTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

antiAliasingEnabledTipText() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Returns the tip text for this property.

antiAliasingEnabledTipText() - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet

Returns the tip text for this property.

AnyToString - Class in weka.filters.unsupervised.attribute

Turns the selected range of attributes into string ones.

AnyToString() - Constructor for class weka.filters.unsupervised.attribute.AnyToString

append(String) - Method in class adams.gui.tools.wekainvestigator.tab.LogTab

Appends the message to the log.

append(String) - Method in class adams.gui.tools.wekamultiexperimenter.LogPanel

Appends the log message.

Append - Class in adams.gui.tools.wekainvestigator.datatable.action

Appends the selected datasets into single dataset (one-after-the-other).

Append() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Append

Instantiates the action.

AppendDatasets - Class in adams.gui.menu

For appending datasets into single dataset.

AppendDatasets() - Constructor for class adams.gui.menu.AppendDatasets

Initializes the menu item with no owner.

AppendDatasets(AbstractApplicationFrame) - Constructor for class adams.gui.menu.AppendDatasets

Initializes the menu item.

AppendDatasetsPanel - Class in adams.gui.tools.weka

Wizard panel that allows appending datasets (one after the other).

AppendDatasetsPanel(boolean) - Constructor for class adams.gui.tools.weka.AppendDatasetsPanel

Initializes the panel.

appendResults(SpreadSheet) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Adds the results to the existing ones.

appliesToNominalClass() - Method in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure

Return true if this evaluation metric can be computed when the class is nominal

appliesToNominalClass() - Method in class weka.classifiers.evaluation.Dice

Return true if this evaluation metric can be computed when the class is nominal

appliesToNumericClass() - Method in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure

Return true if this evaluation metric can be computed when the class is numeric

appliesToNumericClass() - Method in class weka.classifiers.evaluation.Dice

Return true if this evaluation metric can be computed when the class is numeric

apply(Instances, int[]) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Applies the indices to the data.

apply(Instances, int[]) - Method in class weka.filters.unsupervised.attribute.DatasetCleaner

Applies the indices to the data.

apply(Instances, int[]) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Applies the indices to the data.

apply(Instances, int[]) - Method in class weka.filters.unsupervised.instance.DatasetCleaner

Applies the indices to the data.

apply(Instances, int[]) - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Applies the indices to the data.

applyCombination(double[]) - Method in class weka.classifiers.meta.ClassifierCascade

Applies the selected combination to the array.

applyIndexedSplit(IndexedSplit, Instances) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Applies the splits defined in the indexed split and returns the generated subsets.

applyIndexedSplit(IndexedSplit, Instances) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Applies the splits defined in the indexed split and returns the generated subsets.

applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Restores the data from the undo point.

applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer

Restores the data from the undo point.

applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer

Restores the data from the undo point.

applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.FileContainer

Restores the data from the undo point.

applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer

Restores the data from the undo point.

applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer

Restores the data from the undo point.

APPROVE_OPTION - Static variable in class adams.gui.goe.WekaGenericArrayEditorDialog

constant for dialog approval.

APPROVE_OPTION - Static variable in class adams.gui.goe.WekaGenericObjectEditorDialog

constant for dialog approval.

APPROX - weka.classifiers.trees.XGBoost.TreeMethod

AREA_UNDER_PRC - adams.flow.core.EvaluationStatistic

AREA_UNDER_PRC - adams.flow.core.ExperimentStatistic

AREA_UNDER_PRC - adams.opt.genetic.Measure

area under precision recall curve.

AREA_UNDER_ROC - adams.flow.core.EvaluationStatistic

AREA_UNDER_ROC - adams.flow.core.ExperimentStatistic

AREA_UNDER_ROC - adams.opt.genetic.Measure

area under receiver operator curve.

ARFF - adams.flow.sink.WekaExperimentGenerator.ResultFormat

ARFF.

ARFF - adams.flow.transformer.WekaInstanceDumper.OutputFormat

ARFF.

ArffOutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka

Stores the results in an ARFF file.

ArffOutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel

ArffSpreadSheetReader - Class in adams.data.io.input

Reads WEKA datasets in ARFF format and turns them into spreadsheets.

ArffSpreadSheetReader() - Constructor for class adams.data.io.input.ArffSpreadSheetReader

ArffSpreadSheetWriter - Class in adams.data.io.output

Writes a spreadsheet in ARFF file format.

ArffSpreadSheetWriter() - Constructor for class adams.data.io.output.ArffSpreadSheetWriter

ArffUtils - Class in adams.data.weka

A helper class for ARFF related stuff.

ArffUtils() - Constructor for class adams.data.weka.ArffUtils

ArffViewer - Class in adams.gui.menu

Opens the ARFF viewer.

ArffViewer() - Constructor for class adams.gui.menu.ArffViewer

Initializes the menu item with no owner.

ArffViewer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.ArffViewer

Initializes the menu item.

ArrayStatistic - Class in adams.gui.visualization.instances.instancestable

Allows the calculation of row statistics.

ArrayStatistic() - Constructor for class adams.gui.visualization.instances.instancestable.ArrayStatistic

arrayToHashSet(int[]) - Static method in class adams.data.weka.columnfinder.AbstractColumnFinder

Turns the array into a hashset.

arrayToHashSet(int[]) - Static method in class adams.data.weka.rowfinder.AbstractRowFinder

Turns the array into a hashset.

AS_IS - weka.classifiers.meta.MinMaxLimits.LimitHandling

no special handling, just as-is.

ASCENDING - adams.data.conversion.WekaPredictionContainerToSpreadSheet.Sorting

ascending.

assembleSetup(double, Classifier, int, int[]) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Assembles the data for the textual setup output.

assembleSetup(double, Classifier, int, int[]) - Method in class adams.opt.genetic.DarkLord.DarkLordJob

Assembles the data for the textual setup output.

assembleSetup(double, Classifier, int, int[]) - Method in class adams.opt.genetic.Hermione.HermioneJob

Assembles the data for the textual setup output.

assign(DataContainer<InstancePoint>) - Method in class adams.data.instance.Instance

Obtains the stored variables from the other data point, but not the actual data points.

assign(DataPoint) - Method in class adams.data.instance.InstancePoint

Obtains the stored variables from the other data point.

assign(Cell) - Method in class adams.ml.data.DataCellView

Obtains the content/type of the other cell, but not the owner.

assign(Row) - Method in class adams.ml.data.InstancesHeaderRow

Obtains copies of the cells from the other row, but not the owner.

assign(Row) - Method in class adams.ml.data.InstanceView

Obtains copies of the cells from the other row, but not the owner.

assign(SpreadSheet) - Method in class adams.ml.data.InstancesView

Clears this spreadsheet and copies all the data from the given one.

assign(InstanceContainer) - Method in class adams.gui.visualization.instance.InstanceContainer

Updates itself with the values from given container (the manager is excluded!).

assign(AbstractHashableInstance) - Method in class weka.core.AbstractHashableInstance

Assigns all the data, apart from wrapped instance, that the provided hashable instance provides.

assign(Experiment) - Method in class weka.experiment.ExtExperiment

Assigns the values from the other experiment.

assignIDs(int) - Method in class weka.classifiers.trees.m5.RuleNode2

Assigns a unique identifier to each node in the tree

AssociateTab - Class in adams.gui.tools.wekainvestigator.tab

Tab for associators.

AssociateTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.AssociateTab

AssociateTab.HistoryPanel - Class in adams.gui.tools.wekainvestigator.tab

Customized history panel.

AssociationsHandler - Class in weka.gui.explorer

Manages the AssociationsPanel.

AssociationsHandler() - Constructor for class weka.gui.explorer.AssociationsHandler

associatorTipText() - Method in class adams.flow.source.WekaAssociatorSetup

Returns the tip text for this property.

associatorTipText() - Method in class adams.flow.transformer.WekaTrainAssociator

Returns the tip text for this property.

ATT_CONSTANT - Static variable in class weka.classifiers.meta.LogTargetRegressor

Constant to add to attributes before logarithm is taken.

ATT_DATE - Static variable in class adams.core.base.AttributeTypeList

the type string for date attributes.

ATT_NOMINAL - Static variable in class adams.core.base.AttributeTypeList

the type string for nominal attributes.

ATT_NUMERIC - Static variable in class adams.core.base.AttributeTypeList

the type string for numeric attributes.

ATT_RANGE - Static variable in class weka.filters.unsupervised.instance.KennardStone

ATT_REGEXP - Static variable in class weka.filters.unsupervised.attribute.Detrend

ATT_REGEXP - Static variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

ATT_STRING - Static variable in class adams.core.base.AttributeTypeList

the type string for string attributes.

attRangeTipText() - Method in class weka.filters.unsupervised.instance.KennardStone

Returns the tip text for this property.

attRegExpTipText() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns the tip text for this property.

attRegExpTipText() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns the tip text for this property.

attribute(int) - Method in class weka.core.AbstractHashableInstance

Returns the attribute with the given index.

ATTRIBUTE_NAME - adams.flow.transformer.WekaInstancesInfo.InfoType

the name of the attribute (at specified index).

ATTRIBUTE_NAME - Static variable in class adams.flow.transformer.WekaInstanceEvaluator

the default name of the attribute with the evaluation value.

ATTRIBUTE_NAMES - adams.flow.transformer.WekaInstancesInfo.InfoType

the names of all attributes.

ATTRIBUTE_NAMES_SORTED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent

sort attribute names.

ATTRIBUTE_PREFIX - Static variable in class adams.flow.source.WekaNewInstances

the prefix for attributes (if nto specified explicitly).

ATTRIBUTE_PREFIX - Static variable in class weka.classifiers.meta.ClassifierCascade

the prefix for the additional cascade attributes.

ATTRIBUTE_RANGE - Static variable in class weka.filters.unsupervised.attribute.SimpleDetrend

ATTRIBUTE_SELECTION - Static variable in class weka.filters.unsupervised.attribute.EquiDistance

the option for the attribute selection.

ATTRIBUTE_TYPE - adams.flow.transformer.WekaInstancesInfo.InfoType

the attribute type (selected attribute).

attributeAsClassAt(int) - Method in class adams.gui.visualization.instances.InstancesTableModel

sets the attribute at the given col index as the new class attribute, i.e.

attributeIndex - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute

The index of the source attribute in the source dataset.

AttributeIndex - Class in adams.data.weka.classattribute

Uses the supplied attribute index to select the class attribute.

AttributeIndex - Class in adams.data.weka.relationname

Uses the name of the specified attribute as relation name.

AttributeIndex() - Constructor for class adams.data.weka.classattribute.AttributeIndex

AttributeIndex() - Constructor for class adams.data.weka.relationname.AttributeIndex

attributeIndexTipText() - Method in class adams.data.weka.rowfinder.ByLabel

Returns the tip text for this property.

attributeIndexTipText() - Method in class adams.data.weka.rowfinder.ByNumericRange

Returns the tip text for this property.

attributeIndexTipText() - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns the tip text for this property.

attributeIndexTipText() - Method in class adams.flow.transformer.WekaInstancesInfo

Returns the tip text for this property.

attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.SpellChecker

Returns the tip text for this property.

attributeIndexTipText() - Method in class weka.filters.unsupervised.instance.SortOnAttribute

Returns the tip text for this property.

AttributeInfoPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel

Initializes the widget.

attributeName - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute

The name of the source attribute in the source dataset.

attributeNamesTipText() - Method in class adams.flow.source.WekaNewInstances

Returns the tip text for this property.

attributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Returns the tip text for this property.

attributeNameTipText() - Method in class adams.flow.transformer.WekaGetInstanceValue

Returns the tip text for this property.

attributeNameTipText() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Returns the tip text for this property.

attributeNameTipText() - Method in class weka.filters.unsupervised.instance.LatestRecords

Returns the tip text for this property.

attributePrefixTipText() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Returns the tip text for this property.

attributeRangeTipText() - Method in class adams.data.instancesanalysis.FastICA

Returns the tip text for this property.

attributeRangeTipText() - Method in class adams.data.instancesanalysis.PCA

Returns the tip text for this property.

attributeRangeTipText() - Method in class adams.data.instancesanalysis.PLS

Returns the tip text for this property.

attributeRangeTipText() - Method in class adams.data.weka.rowfinder.FilteredIQR

Returns the tip text for this property.

attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Returns the tip text for this property.

attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Returns the tip text for this property.

attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Returns the tip text for this property.

attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.LogTransform

Returns the tip text for this property.

attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.SetMissingValue

Returns the tip text for this property.

attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Returns the tip text for this property.

attributeRenamesExpTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the tip-text for the attribute-renaming regexs option.

attributeRenamesFormatTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the tip-text for the attribute renaming format strings option.

ATTRIBUTES_NAMES_UNSORTED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent

don't sort attribute names.

AttributeSelection - Class in adams.opt.optimise.genetic.fitnessfunctions

Perform attribute selection using WEKA classification.

AttributeSelection() - Constructor for class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection

AttributeSelectionHandler - Class in weka.gui.explorer

Manages the AttributeSelectionPanel.

AttributeSelectionHandler() - Constructor for class weka.gui.explorer.AttributeSelectionHandler

attributeSelectionMethodTipText() - Method in class weka.classifiers.functions.LinearRegressionJ

Returns the tip text for this property

AttributeSelectionPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab

Creates a panel that displays the attributes contained in a set of instances, letting the user toggle whether each attribute is selected or not (eg: so that unselected attributes can be removed before classification).

AttributeSelectionPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

AttributeSelectionPanel.AttributeTableModel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab

A table model that looks at the names of attributes and maintains a list of attributes that have been "selected".

AttributeSelectionTab - Class in adams.gui.tools.wekainvestigator.tab

Tab for attribute selection.

AttributeSelectionTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

AttributeSelectionTab.HistoryPanel - Class in adams.gui.tools.wekainvestigator.tab

Customized history panel.

attributeSelectionTipText() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the tip text for this property.

attributeSparse(int) - Method in class weka.core.AbstractHashableInstance

Returns the attribute with the given index in the sparse representation.

AttributeStatistics - Class in adams.gui.visualization.instances.instancestable

Displays statistics for the selected attribute.

AttributeStatistics() - Constructor for class adams.gui.visualization.instances.instancestable.AttributeStatistics

attributeStats(int) - Method in class weka.core.InstancesView

Calculates summary statistics on the values that appear in this set of instances for a specified attribute.

attributesTipText() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Returns the tip text for this property.

AttributeSummaryPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab

This panel displays summary statistics about an attribute: name, type number/% of missing/unique values, number of distinct values.

AttributeSummaryPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

Creates the instances panel with no initial instances.

AttributeSummaryPanel.AttributeInfoPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab

Panel with labels displaying some basic info.

AttributeSummaryPanel.StatisticsTable - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab

Displays other stats in a table.

AttributeSummaryTransferFilter - Class in weka.filters.unsupervised.attribute

Filter which trains another filter to summarise a sub-set of the data's attributes.

AttributeSummaryTransferFilter() - Constructor for class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

AttributeTableModel(Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel

Creates the tablemodel with the given set of instances.

attributeTipText() - Method in class weka.classifiers.meta.AbstainAttributePercentile

AttributeTypeList - Class in adams.core.base

Wrapper for a comma-separated list of attribute types.

AttributeTypeList() - Constructor for class adams.core.base.AttributeTypeList

Initializes the list with length 0.

AttributeTypeList(String) - Constructor for class adams.core.base.AttributeTypeList

Initializes the object with the string to parse.

attributeTypesTipText() - Method in class adams.flow.source.WekaNewInstances

Returns the tip text for this property.

AttributeValueCellRenderer - Class in adams.gui.visualization.instances

Handles the background colors for missing values differently than the DefaultTableCellRenderer.

AttributeValueCellRenderer() - Constructor for class adams.gui.visualization.instances.AttributeValueCellRenderer

initializes the Renderer with a standard color

AttributeValueCellRenderer(Color, Color) - Constructor for class adams.gui.visualization.instances.AttributeValueCellRenderer

initializes the Renderer with the given colors

AttributeVisualizationPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab

Creates a panel that shows a visualization of an attribute in a dataset.

AttributeVisualizationPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Constructor - If used then the class will not show the class selection combo box.

AttributeVisualizationPanel(boolean) - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Constructor.

AttributeVisualizationPanel.BarCalc - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab

Internal class that calculates the barplot to display, in a separate thread.

AttributeVisualizationPanel.HistCalc - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab

Internal class that calculates the histogram to display, in a separate thread.

attributeXTipText() - Method in class adams.flow.sink.WekaInstancesPlot

Returns the tip text for this property.

attributeXTipText() - Method in class adams.flow.sink.WekaThresholdCurve

Returns the tip text for this property.

attributeXTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Returns the tip text for this property.

attributeYTipText() - Method in class adams.flow.sink.WekaInstancesPlot

Returns the tip text for this property.

attributeYTipText() - Method in class adams.flow.sink.WekaThresholdCurve

Returns the tip text for this property.

attributeYTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Returns the tip text for this property.

AUTO - weka.classifiers.trees.XGBoost.TreeMethod

autoKeyGenerationTipText() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the tip text for this property.

automaticOrderInfo() - Method in class adams.flow.core.WekaFilterModelLoader

Returns information how the model is loaded in case of AbstractModelLoader.ModelLoadingType.AUTO.

AutoScaler - Class in adams.data.weka.predictions

Applies the specified numeric scaler to the data in case of a numeric class attribute, otherwise just passes on the data.

AutoScaler() - Constructor for class adams.data.weka.predictions.AutoScaler

AVAILABLE - adams.flow.source.wekapackagemanageraction.ListPackages.ListType

Average - Class in weka.filters.unsupervised.instance.multirowprocessor.processor

Computes the average of the numeric attributes defined in the range.

Average() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.processor.Average

AVERAGE - weka.classifiers.meta.ClassifierCascade.Combination

average the probabilities/classifications.

AVERAGE_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType

AVERAGE_RULE - Static variable in class weka.classifiers.meta.AbstainVote

combination rule: Average of Probabilities

AverageSilhouetteCoefficient - Class in adams.flow.transformer.wekaclusterer

Computes the average Silhouette coefficient for the clusters.

AverageSilhouetteCoefficient() - Constructor for class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient

axisXTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the tip text for this property.

axisYTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the tip text for this property.

B

BACKUP_ACCUMULATEDERROR - Static variable in class adams.flow.transformer.WekaAccumulatedError

the key for storing the current accumulated error in the backup.

BACKUP_ATTRIBUTESTOPROCESS - Static variable in class adams.flow.transformer.WekaMultiLabelSplitter

the key for storing the current attributes to process in the backup.

BACKUP_BUFFER - Static variable in class adams.flow.transformer.WekaInstanceBuffer

the key for storing the current buffer in the backup.

BACKUP_BUFFER - Static variable in class adams.flow.transformer.WekaInstanceDumper

the key for storing the buffer in the backup.

BACKUP_CALLABLEACTOR - Static variable in class adams.flow.transformer.WekaGeneticAlgorithm

the key for backing up the callable actor.

BACKUP_CLASSATTRIBUTES - Static variable in class adams.flow.transformer.WekaMultiLabelSplitter

the key for storing the current class attributes in the backup.

BACKUP_CLaSSIFIER - Static variable in class adams.flow.transformer.WekaStreamEvaluator

the backup key for the classifier.

BACKUP_CONFIGURED - Static variable in class adams.flow.transformer.WekaGeneticAlgorithm

the key for backing up the configured state.

BACKUP_COUNTER - Static variable in class adams.flow.transformer.WekaInstanceDumper

the key for storing the counter in the backup.

BACKUP_CURRENT - Static variable in class adams.flow.transformer.WekaStreamEvaluator

the backup key for the current counter.

BACKUP_EVALUATION - Static variable in class adams.flow.transformer.WekaAggregateEvaluations

the key for storing the current accumulated error in the backup.

BACKUP_EVALUATION - Static variable in class adams.flow.transformer.WekaStreamEvaluator

the backup key for the evaluation.

BACKUP_GENERATOR - Static variable in class adams.flow.transformer.WekaCrossValidationSplit

the key for storing the current fold in the backup.

BACKUP_HEADER - Static variable in class adams.flow.transformer.WekaInstanceDumper

the key for storing the header in the backup.

BACKUP_HEADER - Static variable in class adams.flow.transformer.WekaStreamEvaluator

the backup key for the current header.

BACKUP_INCREMENTALCLASSIFIER - Static variable in class adams.flow.transformer.WekaTrainClassifier

the key for storing the current incremental classifier in the backup.

BACKUP_INCREMENTALCLUSTERER - Static variable in class adams.flow.transformer.WekaTrainClusterer

the key for storing the current incremental clusterer in the backup.

BACKUP_INITIALIZED - Static variable in class adams.flow.transformer.WekaFilter

the key for storing the current initialized state in the backup.

BACKUP_INITIALIZED - Static variable in class adams.flow.transformer.WekaStreamFilter

the key for storing the current initialized state in the backup.

BACKUP_ITERATOR - Static variable in class adams.flow.transformer.WekaInstanceBuffer

the key for storing the current iterator in the backup.

BACKUP_MODEL - Static variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

the key for storing the current model in the backup.

BACKUP_NUMPREDICTIONS - Static variable in class adams.flow.transformer.WekaAccumulatedError

the key for storing the current number of predictions in the backup.

BACKUP_PREDICTIONS - Static variable in class adams.flow.transformer.WekaAccumulatedError

the key for storing the current predictions in the backup.

BACKUP_REFERENCE - Static variable in class adams.flow.transformer.WekaReorderAttributesToReference

the key for storing the reference dataset in the backup.

BACKUP_REORDER - Static variable in class adams.flow.transformer.WekaReorderAttributesToReference

the key for storing the reorder filter in the backup.

BACKUP_SAVER - Static variable in class adams.flow.sink.WekaDatabaseWriter

the key for storing the current incremental clusterer in the backup.

BACKUP_SEARCH - Static variable in class adams.flow.transformer.WekaNearestNeighborSearch

the key for storing the current initialized state in the backup.

BACKUP_SOURCE - Static variable in class adams.flow.transformer.WekaFileReader

the key for storing the current source in the backup.

BACKUP_STRUCTURE - Static variable in class adams.flow.transformer.WekaFileReader

the key for storing the current structure in the backup.

backupSelection() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Returns the data containers that are currently selected.

backupState() - Method in class adams.flow.sink.WekaDatabaseWriter

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaAccumulatedError

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaAggregateEvaluations

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaFileReader

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaFilter

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaInstanceBuffer

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaInstanceDumper

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaStreamEvaluator

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaStreamFilter

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaTrainClassifier

Backs up the current state of the actor before update the variables.

backupState() - Method in class adams.flow.transformer.WekaTrainClusterer

Backs up the current state of the actor before update the variables.

BarCalc(int, int) - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel.BarCalc

baseScoreTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the baseScore option.

baseTipText() - Method in class adams.data.instancesanalysis.pls.OPLS

Returns the tip text for this property

baseTipText() - Method in class weka.classifiers.meta.Fallback

Returns the tip text for this property.

BasicAdamsSetupPanel - Class in adams.gui.tools.wekamultiexperimenter.setup

Basic interface for setting up an ADAMS experiment.

BasicAdamsSetupPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

BasicWekaSetupPanel - Class in adams.gui.tools.wekamultiexperimenter.setup

Basic interface for setting up a Weka experiment.

BasicWekaSetupPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

batchFilter(String[], Filter, String, boolean, File) - Method in class adams.gui.tools.weka.BatchFilterDatasetsPanel

Performs the batch filtering.

BatchFilterDatasets - Class in adams.gui.menu

For batch filtering datasets using a single filter setup (files get output into a different directory).

BatchFilterDatasets() - Constructor for class adams.gui.menu.BatchFilterDatasets

Initializes the menu item with no owner.

BatchFilterDatasets(AbstractApplicationFrame) - Constructor for class adams.gui.menu.BatchFilterDatasets

Initializes the menu item.

BatchFilterDatasetsPanel - Class in adams.gui.tools.weka

Wizard panel that allows appending datasets (one after the other).

BatchFilterDatasetsPanel(boolean) - Constructor for class adams.gui.tools.weka.BatchFilterDatasetsPanel

Initializes the panel.

BatchFilterJob(Filter, Instances) - Constructor for class adams.flow.transformer.WekaFilter.BatchFilterJob

Initializes the job.

batchFinished() - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive

Signify that this batch of input to the filter is finished.

batchFinished() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Signify that this batch of input to the filter is finished.

batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Signify that this batch of input to the filter is finished.

batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Signify that this batch of input to the filter is finished.

batchSizeTipText() - Method in class weka.classifiers.functions.PyroProxy

Returns the tip text for this property.

BatchTrainJob(Classifier, Instances) - Constructor for class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob

Initializes the job.

BatchTrainJob(Clusterer, Instances, AbstractClustererPostProcessor) - Constructor for class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob

Initializes the job.

BayesNetEditor - Class in adams.gui.menu

Opens the BayesNet Editor.

BayesNetEditor() - Constructor for class adams.gui.menu.BayesNetEditor

Initializes the menu item with no owner.

BayesNetEditor(AbstractApplicationFrame) - Constructor for class adams.gui.menu.BayesNetEditor

Initializes the menu item.

beforeShow() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog

Hook method just before the dialog is made visible.

beforeShow() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

Hook method just before the dialog is made visible.

beforeShow() - Method in class adams.gui.InstanceCompare

Hook method just before the dialog is made visible.

beforeShow() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Hook method just before the dialog is made visible.

BELOW - weka.classifiers.meta.ClassifierCascade.ThresholdCheck

BestBinnedNumericClassRandomSplitGenerator - Class in weka.classifiers

Picks the best binning algorithm from the provided ones.

BestBinnedNumericClassRandomSplitGenerator() - Constructor for class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

bestRangeTipText() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the tip text for this property.

Bias - Class in weka.classifiers.evaluation

Computes the bias (mean error) for regression models.

Bias() - Constructor for class weka.classifiers.evaluation.Bias

BIAS - adams.flow.core.EvaluationStatistic

BIAS - adams.flow.core.ExperimentStatistic

biasTipText() - Method in class weka.classifiers.meta.VotedImbalance

Returns the tip text for this property.

BINARY_ATTRIBUTES - adams.flow.core.Capability

can handle binary attributes.

BINARY_CLASS - adams.flow.core.Capability

can handle binary classes.

binCalculationTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the tip text for this property.

BinnableInstances - Class in adams.data.binning

Helper class for binning instances.

BinnableInstances() - Constructor for class adams.data.binning.BinnableInstances

BinnableInstances.ClassValueBinValueExtractor - Class in adams.data.binning

Uses the class value as bin value.

BinnableInstances.GroupedClassValueBinValueExtractor - Class in adams.data.binning

Uses the class value of the first instance in the group as bin value.

BinnableInstances.NumericClassGroupExtractor - Class in adams.data.binning

Group extractor for numeric class attributes (using string representation of values).

BinnableInstances.StringAttributeGroupExtractor - Class in adams.data.binning

Group extractor for string attributes.

BinnedNumericClassCrossValidationFoldGenerator - Class in weka.classifiers

Helper class for generating cross-validation folds.

BinnedNumericClassCrossValidationFoldGenerator() - Constructor for class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Initializes the generator.

BinnedNumericClassCrossValidationFoldGenerator(Instances, int, long, boolean) - Constructor for class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Initializes the generator.

BinnedNumericClassCrossValidationFoldGenerator(Instances, int, long, boolean, boolean, String) - Constructor for class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Initializes the generator.

BinnedNumericClassRandomSplitGenerator - Class in weka.classifiers

Generates random splits of datasets with numeric classes using a binning algorithm.

BinnedNumericClassRandomSplitGenerator() - Constructor for class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Initializes the generator.

BinnedNumericClassRandomSplitGenerator(Instances, double) - Constructor for class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Initializes the generator.

BinnedNumericClassRandomSplitGenerator(Instances, long, double) - Constructor for class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Initializes the generator.

BinnedNumericClassRandomSplitGenerator(Instances, long, double, boolean) - Constructor for class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Initializes the generator.

Binning - Class in adams.gui.visualization.instances.instancestable

Allows to perform binning of the values from a column or row.

Binning() - Constructor for class adams.gui.visualization.instances.instancestable.Binning

binsPointTipText() - Method in class weka.core.SAXDistance

Returns the tip text for this property.

binsPointTipText() - Method in class weka.filters.unsupervised.attribute.SAX

Returns the tip text for this property.

binWidthTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the tip text for this property.

bitsPerGeneTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

bitsTipText() - Method in class adams.opt.optimise.GeneticAlgorithm

Returns the tip text for this property.

bitsToMatrix(String, double, double, int, int, int, int) - Static method in class adams.core.discovery.genetic.WekaGeneticHelper

Convert bit string into weka Matrix

BITSTRING - Static variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

bitstringTipText() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

boosterTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the booster option.

borderTipText() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the tip text for this property.

BOTH - adams.flow.transformer.WekaBootstrapping.ErrorCalculation

BoundaryVisualizer - Class in adams.gui.menu

Displays data in the boundary visualizer.

BoundaryVisualizer() - Constructor for class adams.gui.menu.BoundaryVisualizer

Initializes the menu item with no owner.

BoundaryVisualizer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.BoundaryVisualizer

Initializes the menu item.

BOX - adams.gui.visualization.instance.InstanceLinePaintlet.MarkerShape

a square box.

BoxPlotTab - Class in adams.gui.tools.wekainvestigator.tab

Visualizes the selected dataset as box plot.

BoxPlotTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.BoxPlotTab

bufferSizeTipText() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns the tip text for this property.

build(Instance) - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Constructs the weighted dataset.

build(Instance) - Method in class weka.classifiers.lazy.LWLSynchro

Builds the classifier.

build(Instance) - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

Builds the classifier.

build(Instance) - Method in class weka.classifiers.lazy.LWLSynchroSplit

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.functions.ClassificationViaPLS

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.functions.FakeClassifier

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.functions.FromPredictions

Just loads the predictions.

buildClassifier(Instances) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

buildClassifier(Instances) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Method for building the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Method for building the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.functions.GeneticAlgorithm

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.functions.GPD

Method for building the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.functions.LinearRegressionJ

Builds a regression model for the given data.

buildClassifier(Instances) - Method in class weka.classifiers.functions.MathExpressionClassifier

Builds the classifier on the training data.

buildClassifier(Instances) - Method in class weka.classifiers.functions.PLSClassifierWeighted

builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.functions.PLSWeighted

builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.functions.PyroProxy

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Builds a simple linear regression model given the supplied training data.

buildClassifier(Instances) - Method in class weka.classifiers.lazy.AbstainingLWL

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.lazy.LWLSynchro

buildClassifier(Instances) - Method in class weka.classifiers.lazy.LWLSynchroSplit

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.AbstainAttributePercentile

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.AbstainAverage

Buildclassifier builds all sub-classifiers

buildClassifier(Instances) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Buildclassifier builds all sub-classifiers

buildClassifier(Instances) - Method in class weka.classifiers.meta.AbstainingCascade

Builds the ensemble.

buildClassifier(Instances) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.AbstainMinimumProbability

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.AbstainVote

Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.

buildClassifier(Instances) - Method in class weka.classifiers.meta.ClassificationViaRegressionD

Builds the classifiers.

buildClassifier(Instances) - Method in class weka.classifiers.meta.ClassifierCascade

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.Consensus

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.ConsensusOrVote

Builds the ensemble.

buildClassifier(Instances) - Method in class weka.classifiers.meta.Corr

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.Fallback

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.FilteredClassifierExt

Build the classifier on the filtered data.

buildClassifier(Instances) - Method in class weka.classifiers.meta.HighLowSplit

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.LeastMedianSq

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.LogClassRegressor

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.LogTargetRegressor

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.MinMaxLimits

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.PartitionedStacking

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.PeakTransformed

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.RangeCheck

Build the classifier on the filtered data.

buildClassifier(Instances) - Method in class weka.classifiers.meta.SocketFacade

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.SubsetEnsemble

Stump method for building the classifiers

buildClassifier(Instances) - Method in class weka.classifiers.meta.SumTransformed

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.SuppressModelOutput

Builds the base classifier using the provided data.

buildClassifier(Instances) - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Builds the classifier with the training data.

buildClassifier(Instances) - Method in class weka.classifiers.meta.Veto

Builds the ensemble.

buildClassifier(Instances) - Method in class weka.classifiers.meta.VotedImbalance

Stump method for building the classifiers

buildClassifier(Instances) - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper

Generates a classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.M5Base2

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.Rule2

Generates a single rule or m5 model tree.

buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.RuleNode2

Build this node (find an attribute and split point)

buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomModelTrees

buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomRegressionForest

builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.trees.XGBoost

Trains the XGBoost classifier on the incoming dataset.

buildClassifier2(Instances) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Method for building the classifier.

buildClassifiers() - Method in class weka.classifiers.meta.SubsetEnsemble

Does the actual construction of the ensemble.

buildClassifiers() - Method in class weka.classifiers.meta.VotedImbalance

Does the actual construction of the ensemble.

buildClassifiers(Instances) - Method in class weka.classifiers.meta.PartitionedStacking

Does the actual construction of the base-classifiers.

buildClusterer(Instances) - Method in class weka.clusterers.SAXKMeans

Generates a clusterer.

buildEvaluator(Instances) - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Generates a attribute evaluator.

buildEvaluator(Instances) - Method in class weka.attributeSelection.LinearRegressionAttributeEval

Generates a attribute evaluator.

buildFilter(double, int) - Method in class weka.core.neighboursearch.PCANNSearch

buildFilter(int) - Method in class weka.core.neighboursearch.PLSNNSearch

BuildModel - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation

Builds a model and serializes it to a file.

BuildModel - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation

Builds a model and serializes it to a file.

BuildModel() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

BuildModel() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

buildRegressionTreeTipText() - Method in class weka.classifiers.trees.m5.M5Base2

Returns the tip text for this property

buildWaitTipText() - Method in class weka.classifiers.functions.FakeClassifier

Returns the tip text for this property.

ByExactName - Class in adams.data.weka.classattribute

Returns indices of columns which names match the exact name.

ByExactName - Class in adams.data.weka.columnfinder

Returns indices of columns which names match the exact name.

ByExactName() - Constructor for class adams.data.weka.classattribute.ByExactName

ByExactName() - Constructor for class adams.data.weka.columnfinder.ByExactName

ByLabel - Class in adams.data.weka.rowfinder

Returns the indices of rows which attributes labels match the provided regular expression.

ByLabel() - Constructor for class adams.data.weka.rowfinder.ByLabel

ByName - Class in adams.data.weka.classattribute

The first attribute name that matches the regular expression is used as class attribute.

ByName - Class in adams.data.weka.columnfinder

Returns indices of attributes which names match the regular expression.

ByName() - Constructor for class adams.data.weka.classattribute.ByName

ByName() - Constructor for class adams.data.weka.columnfinder.ByName

ByNumericRange - Class in adams.data.weka.rowfinder

Returns indices of rows which numeric value match the min/max.

ByNumericRange() - Constructor for class adams.data.weka.rowfinder.ByNumericRange

ByNumericValue - Class in adams.data.weka.rowfinder

Returns indices of rows which numeric value match the min/max.

ByNumericValue() - Constructor for class adams.data.weka.rowfinder.ByNumericValue

C

calcAverageWidth(double[][]) - Static method in class adams.data.weka.evaluator.IntervalEstimatorBased

Calculates the average width of the intervals.

calcDistribution(List<Binnable<Instance>>, double) - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Calculates the class distribution.

calcFitness() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Calculates the fitness of the population.

calcFitness() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Override the following function in sub-classes.

calcFitness() - Method in class adams.opt.optimise.GeneticAlgorithm

Calculates the fitness of the population.

calcGraph(int, int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Recalculates the barplot or histogram to display, required usually when the attribute is changed or the component is resized.

calcNewFitness() - Method in class adams.opt.genetic.DarkLord.DarkLordJob

Calculates the new fitness.

calcNewFitness() - Method in class adams.opt.genetic.Hermione.HermioneJob

Calculates the new fitness.

calcNewFitness(FitnessFunction, int[]) - Method in class adams.opt.optimise.GeneticAlgorithm

Calculates the new fitness.

calcNumBits() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Calculates the number of bits to use.

calcNumBits() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

Calculates the number of bits to use.

calcStats(WekaEvaluationContainer[], SpreadSheet, MessageCollection, CenterStatistic, LowerStatistic, UpperStatistic, int, Logger, TIntList, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.PredictionUtils

Generates a spreadsheet with the statistics.

calcStats(ResultItem, MessageCollection, CenterStatistic, LowerStatistic, UpperStatistic, int, Logger, TIntList) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.PredictionUtils

Generates a spreadsheet with the statistics.

calcStats(ResultItem, MessageCollection, CenterStatistic, LowerStatistic, UpperStatistic, int, Logger, TIntList, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.PredictionUtils

Generates a spreadsheet with the statistics.

calculate() - Method in class adams.ml.data.DataCellView

Does nothing.

calculate() - Method in class adams.ml.data.InstancesView

Triggers all formula cells to recalculate their values.

calculateCenters(Instances, Clusterer, Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters

Calculates the centers.

calculateDistance(Instance, Instance) - Method in class weka.filters.unsupervised.instance.KennardStone

Calculate the distance between any two instances.

calculateModelSize() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns whether model sizes should get calculated.

calculateSE(boolean[], double[]) - Method in class weka.classifiers.functions.LinearRegressionJ

Calculate the squared error of a regression model on the training data

calculateStatistics(Instances, Clusterer, Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterStatistics

Calculates the statistics.

calcWidth(double[]) - Static method in class adams.data.weka.evaluator.IntervalEstimatorBased

Calculates the width of the interval.

callableNameTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns the tip text for this property.

canAbstain() - Method in interface weka.classifiers.AbstainingClassifier

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.lazy.AbstainingLWL

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.AbstainAttributePercentile

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.AbstainAverage

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.AbstainMinimumProbability

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.AbstainVote

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.Consensus

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.ConsensusOrVote

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.FilteredClassifierExt

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.MinMaxLimits

Whether abstaining is possible, e.g., used in meta-classifiers.

canAbstain() - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper

Whether abstaining is possible, e.g., used in meta-classifiers.

CANCEL_OPTION - Static variable in class adams.gui.goe.WekaGenericArrayEditorDialog

constant for dialog cancellation.

CANCEL_OPTION - Static variable in class adams.gui.goe.WekaGenericObjectEditorDialog

constant for dialog cancellation.

canCopyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu

Returns whether copying to the clipboard is supported.

canCopyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel

Returns whether copying to the clipboard is supported.

canCopyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel

Returns whether copying to the clipboard is supported.

canCopyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel

Returns whether copying to the clipboard is supported.

canEdit() - Method in class weka.gui.explorer.ExplorerExt

Checks whether editing the data is possible.

canEvaluate(Associator) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation

Tests whether the associator can be evaluated.

canEvaluate(Associator) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

Tests whether the associator can be evaluated.

canEvaluate(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation

Tests whether attribute selection can be performed.

canEvaluate(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

Tests whether attribute selection can be performed.

canEvaluate(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

Tests whether attribute selection can be performed.

canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation

Tests whether the classifier can be evaluated.

canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Tests whether the classifier can be evaluated.

canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Tests whether the classifier can be evaluated.

canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Tests whether the classifier can be evaluated.

canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

Tests whether the classifier can be evaluated.

canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Tests whether the classifier can be evaluated.

canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Tests whether the classifier can be evaluated.

canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Tests whether the classifier can be evaluated.

canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Tests whether the classifier can be evaluated.

canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Tests whether the classifier can be evaluated.

canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation

Tests whether the clusterer can be evaluated.

canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

Tests whether the clusterer can be evaluated.

canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Tests whether the clusterer can be evaluated.

canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

Tests whether the clusterer can be evaluated.

canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Tests whether the clusterer can be evaluated.

canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

Tests whether the clusterer can be evaluated.

canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

Tests whether the clusterer can be evaluated.

canExecute(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup

Tests whether the experiment setup can be executed for the classifier.

canExecute(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Tests whether the experiment setup can be executed for the classifier.

canExecute(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Tests whether the experiment setup can be executed for the classifier.

canFilter() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Checks whether data can be filtered.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.ModelOutput

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.Rules

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.RunInformation

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.ReducedData

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.RunInformation

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.GraphSource

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyClassifierErrors

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyGraphVisualizer

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyMarginCurve

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyTreeVisualizer

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ModelOutput

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsFitted

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsPredictor

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.RunInformation

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeVisualizer

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ClusterAssignments

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.GraphSource

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.LegacyTreeVisualizer

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ModelOutput

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.RunInformation

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.RunInformation

Checks whether output can be generated from this item.

canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Checks whether output can be generated from this item.

canGenerateOutput(T) - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator

Checks whether output can be generated from this item.

canNotify(InstancePanel, InstanceContainer) - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater

Checks whether all conditions are met to notify the listeners for changes in the plot.

CANOPY - Static variable in class weka.clusterers.SAXKMeans

canopyInit(Instances) - Method in class weka.clusterers.SAXKMeans

Initialize with the canopy centers of the Canopy clustering method

canopyMaxNumCanopiesToHoldInMemoryTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

canopyMinimumCanopyDensityTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

canopyPeriodicPruningRateTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

canopyT1TipText() - Method in class weka.clusterers.SAXKMeans

Tip text for this property

canopyT2TipText() - Method in class weka.clusterers.SAXKMeans

Tip text for this property

canPaint(Graphics) - Method in class adams.gui.visualization.instance.InstancePanel

Returns true if the paintlets can be executed.

canRandomize() - Method in class weka.classifiers.AbstractSplitGenerator

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.DefaultRandomSplitGenerator

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Returns whether randomization is enabled.

canRandomize() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns whether randomization is enabled.

canReload() - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer

Whether it is possible to reload this item.

canReload() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer

Whether it is possible to reload this item.

canReload() - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer

Whether it is possible to reload this item.

canReload() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer

Whether it is possible to reload this item.

canReload() - Method in class adams.gui.tools.wekainvestigator.data.MemoryContainer

Whether it is possible to reload this item.

canReload() - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer

Whether it is possible to reload this item.

canReload() - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer

Whether it is possible to reload this item.

canRenderCached(Object, JPanel) - Method in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer

Checks whether the renderer can use a cached setup to render an object.

canReset() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel

Returns whether the panel supports resetting the options.

canRevert() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Revert

Checks whether any selected container can be reverted.

canStartExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Returns whether a new job can be executed.

canSwap(PropertyPath.Path, PropertyDescriptor, Object, Object) - Method in class adams.data.conversion.SwapPLS

Checks whether a swap can be made.

canUndo() - Method in class adams.gui.visualization.instances.InstancesTable

returns whether an undo is possible, i.e.

canUndo() - Method in class adams.gui.visualization.instances.InstancesTableModel

returns whether an undo is possible, i.e.

canUndo() - Method in class weka.gui.explorer.ExplorerExt

Checks whether undo is possible.

canVisualize() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Returns whether data can be visualized.

canVisualize() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Returns whether data can be visualized.

canVisualize() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Returns whether data can be visualized.

canVisualize() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Returns whether data can be visualized.

capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.ExperimentPanel

method gets called in case of a change event.

capabilitiesTipText() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Returns the tip text for this property.

Capability - Enum in adams.flow.core

Enumeration of all capabilities.

CC - adams.flow.transformer.WekaClassifierRanker.Measure

evaluation via: Correlation coefficient.

CC - adams.opt.genetic.Measure

Correlation coefficient.

CC - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure

evaluation via: Correlation coefficient.

cellKeys() - Method in class adams.ml.data.InstancesHeaderRow

Returns a collection of all stored cell keys.

cellKeys() - Method in class adams.ml.data.InstanceView

Returns a collection of all stored cell keys.

cellKeyToIndex(String) - Method in class adams.ml.data.InstancesHeaderRow

Turns the cellKey into a column index.

cellKeyToIndex(String) - Method in class adams.ml.data.InstancesView

Turns the cellKey into a column index.

cellKeyToIndex(String) - Method in class adams.ml.data.InstanceView

Turns the cellKey into a column index.

cellPaddingTipText() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the tip text for this property.

cellRenderingCustomizerTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Returns the tip text for this property.

cells() - Method in class adams.ml.data.InstancesHeaderRow

Returns all cells.

cells() - Method in class adams.ml.data.InstanceView

Returns all cells.

cellSpacingTipText() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the tip text for this property.

CENTER - adams.data.instancesanalysis.pls.PreprocessingType

centerClass(Instances) - Method in class weka.classifiers.trees.RandomRegressionForest

Centers the class value in the data.

centerDataTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Returns the tip text for this property

CenterStatistic - Enum in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated

Enumeration of available center statistics.

ChangeAttributeWeight - Class in adams.gui.visualization.instances.instancestable

Allows the user to change the weight of the selected attribute.

ChangeAttributeWeight() - Constructor for class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight

changeColorProvider() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Lets the user choose another color provider.

changedUpdate(DocumentEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationDocumentListener

ChangeInstanceWeights - Class in adams.gui.visualization.instances.instancestable

Allows the user to change the weight of the selected attribute.

ChangeInstanceWeights() - Constructor for class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights

charSetTipText() - Method in class adams.flow.transformer.WekaTextDirectoryReader

Returns the tip text for this property.

check() - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction

Hook method for performing checks.

check() - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction

Hook method for performing checks.

check(PlaceholderFile) - Method in class adams.data.io.input.AbstractAdamsExperimentReader

Performs checks.

check(WekaEvaluationContainer) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor

Checks the container whether it can be processed.

check(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor

Checks the model container.

check(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor

Checks the model container.

check(AbstractExperiment) - Method in class adams.data.io.output.AbstractAdamsExperimentWriter

Performs checks.

check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotColumn

Hook method for checks before attempting the plot.

check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotRow

Hook method for checks before attempting the plot.

check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

Hook method for checks before attempting processing.

check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell

Hook method for checks before attempting processing.

check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn

Hook method for checks before attempting processing.

check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow

Hook method for checks before attempting processing.

check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

Hook method for checks before attempting processing.

check(Object) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Checks whether the data can be processed.

check(Object) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Checks whether the data can be processed.

check(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator

Check method before generating the ensemble.

check(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels

Check method before generating the ensemble.

check(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels

Check method before generating the ensemble.

check(Object) - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction

Hook method for performing checks.

check(List<Instance>) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractSelectionProcessor

Hook method for performing checks.

check(Classifier[]) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.AbstractClassifierSetupProcessor

Hook method for performing checks on the classifiers.

check(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractNumericClassPostProcessor

Checks the container whether it can be processed.

check(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor

Checks the evaluation whether it can be processed.

check(Instance) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Peforms checks on the instance that is about to be evaluated.

check(Instances) - Method in class adams.data.instancesanalysis.FastICA

Hook method for checks.

check(Instances) - Method in class adams.data.instancesanalysis.PCA

Hook method for checks.

check(Instances) - Method in class adams.data.instancesanalysis.PLS

Hook method for checks.

check(Instances) - Method in class adams.data.weka.columnfinder.AbstractColumnFinder

Checks the data.

check(Instances) - Method in class adams.data.weka.columnfinder.AbstractColumnFinderWithCapabilities

Checks the data.

check(Instances) - Method in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder

Checks the data.

check(Instances) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter

Checks that the input data is correctly formatted for our purposes.

check(Instances) - Method in class adams.data.weka.datasetsplitter.RowSplitter

Checks that the input data is correctly formatted for our purposes.

check(Instances) - Method in class adams.data.weka.rowfinder.AbstractRowFinder

Checks the data.

check(Instances) - Method in class adams.data.weka.rowfinder.AbstractRowFinderWithCapabilities

Checks the data.

check(Instances) - Method in class adams.data.weka.rowfinder.AbstractTrainableRowFinder

Checks the data.

check(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.AbstractRowSelection

Hook method for performing checks.

check(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Hook method for performing checks before attempting the merge.

check(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Hook method for performing checks before attempting the merge.

check(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.Simple

Hook method for performing checks before attempting the merge.

check(Instances, IndexedSplitsRuns) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

For checking the data.

checkAllDatasetsHaveIDAttribute(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Checks that each of the given datasets has the unique ID attribute.

checkAttributeMapping(Map<String, List<AbstractMerge.SourceAttribute>>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Makes sure the source data for each mapped attribute is the same type.

checkAttributeMapping(Map<String, List<AbstractMerge.SourceAttribute>>) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Makes sure the source data for each mapped attribute is the same type.

checkBest(Double, OptData, FitnessFunction, int) - Method in class adams.opt.optimise.GeneticAlgorithm

checkCompatibility(Instances, Instances) - Method in class weka.filters.unsupervised.instance.AlignDataset

Checks the compatibility between reference dataset and the one to be aligned with it.

checkDataset(Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Hook method for performing checks before converting a dataset.

checkDimensions() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

checks whether the dimensions of filters and ranges fit together.

checkDimensions() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

checks whether the dimensions of filters and ranges fit together.

checkHeader(T) - Method in class adams.data.instances.AbstractInstanceGenerator

Checks whether the number of waves are the same.

checkHeaderTipText() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns the tip text for this property.

checkHeaderTipText() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns the tip text for this property.

checkInitialize(Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Hook method for performing checks before initializing.

checkInput(T) - Method in class adams.data.instances.AbstractInstanceGenerator

Checks the input profile.

checkInstance(Instance) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Hook method for performing checks before converting the Instance.

checkNext() - Method in class weka.classifiers.AbstractSplitGenerator

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.DefaultRandomSplitGenerator

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Returns true if the iteration has more elements.

checkNext() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns true if the iteration has more elements.

checkOK(double, double) - Method in class weka.classifiers.meta.AbstainAverage

Check prediction difference against thresholds

checkOK(double, double) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Check prediction difference against thresholds

checkOK(double, double) - Method in class weka.classifiers.meta.AbstainVote

checkPrediction(Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Hook method for performing checks before parsing the prediction.

checkPredictions(Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Hook method for performing checks before parsing the predictions.

checkRangeForInstance(Instance) - Method in class weka.classifiers.meta.RangeCheck

Checks the range for the instance.

checkRangeForInstance(Instance) - Method in interface weka.classifiers.RangeCheckClassifier

Checks the range for the instance.

checkSetup() - Method in class adams.data.instances.AbstractInstanceGenerator

Checks whether the setup is consistent.

choleskyDecomposition(double[][]) - Method in class weka.classifiers.functions.GPD

Cholesky decomposition.

chooseClassAttributeHeuristic() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Lets the user choose the class attribute heuristic.

chooseColor(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, List<InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Viewport

Allows the user to choose the color for all the instances.

chooseRelationNameHeuristic() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Lets the user choose the relation name heuristic.

CIRCLE - adams.gui.visualization.instance.InstanceLinePaintlet.MarkerShape

a circle.

Class - Class in adams.data.weka.columnfinder

Column finder which finds the class column (if one is set).

Class() - Constructor for class adams.data.weka.columnfinder.Class

CLASS_ATTRIBUTE_NAME - adams.flow.transformer.WekaEvaluationInfo.InfoType

CLASS_ATTRIBUTE_NAME - adams.flow.transformer.WekaInstancesInfo.InfoType

the name of the class attribute.

CLASS_CONSTANT - Static variable in class weka.classifiers.meta.LogClassRegressor

Constant to add to class before logarithm is taken.

CLASS_CONSTANT - Static variable in class weka.classifiers.meta.LogTargetRegressor

Constant to add to class before logarithm is taken.

CLASS_INDEX - Static variable in class weka.classifiers.meta.ClassifierCascade

CLASS_LABEL_COUNT - adams.flow.transformer.WekaInstancesInfo.InfoType

the number of instances with the specified class label (only nominal).

CLASS_LABEL_COUNTS - adams.flow.transformer.WekaInstancesInfo.InfoType

the counts per class label (only nominal).

CLASS_LABEL_DISTRIBUTION - adams.flow.transformer.WekaInstancesInfo.InfoType

the distribution (percentages, 0-1) per class label (only nominal).

CLASS_LABELS - adams.flow.transformer.WekaInstancesInfo.InfoType

the class labels (only nominal class attribute).

CLASS_RANGE - weka.classifiers.meta.MinMaxLimits.LimitHandling

determined based on class attribute range.

CLASS_TYPE - adams.flow.transformer.WekaInstancesInfo.InfoType

the class attribute type.

classAttribute() - Method in class weka.core.AbstractHashableInstance

Returns class attribute.

ClassAttribute - Class in adams.data.weka.relationname

Uses the class attribute name.

ClassAttribute() - Constructor for class adams.data.weka.relationname.ClassAttribute

classAttributesTipText() - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

Returns the tip text for this property

classAttributeTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the tip text for this property.

classDetailsTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the tip text for this property.

classDetailsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Returns the tip text for this property.

classDistributionTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the tip text for this property.

classDistributionTipText() - Method in class weka.classifiers.functions.FromPredictions

Returns the tip text for this property.

ClassesToClusters - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation

Tries to map the clusters of the built clusterer to the class labels in the dataset.

ClassesToClusters() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

classFinderTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the tip-text for the classFinder option.

CLASSIFICATION - adams.flow.sink.WekaExperimentGenerator.ExperimentType

classification.

classificationEntryTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the tip text for this property.

classificationLabelEntryTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the tip text for this property.

classificationNumericAverage(Instance) - Method in class weka.classifiers.meta.AbstainVote

classificationNumericAverage(Instance, boolean) - Method in class weka.classifiers.meta.AbstainAverage

Do the classification.

classificationNumericAverage(Instance, boolean) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Do the classification.

classificationNumericMedian(Instance) - Method in class weka.classifiers.meta.AbstainVote

ClassificationViaPLS - Class in weka.classifiers.functions

Performs ClassificationViaRegression using PLSClassifierWeightedWithLoadings as base classifier, allowing access to the PLS matrices.

ClassificationViaPLS() - Constructor for class weka.classifiers.functions.ClassificationViaPLS

Initializes the classifier.

ClassificationViaRegressionD - Class in weka.classifiers.meta

Class for doing classification using regression methods.

ClassificationViaRegressionD() - Constructor for class weka.classifiers.meta.ClassificationViaRegressionD

Default constructor.

CLASSIFIER - Static variable in class weka.filters.supervised.instance.RemoveOutliers

ClassifierBasedGeneticAlgorithmJob(T, int, int[], Instances, Instances) - Constructor for class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Initializes the job.

ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob(T, int, int[], Instances, Instances) - Constructor for class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob

Initializes the job.

ClassifierCascade - Class in weka.classifiers.meta

Generates a classifier cascade, with each deeper level of classifiers being built on the input data and either the class distributions (nominal class) or classification (numeric class) of the classifiers of the previous level in the cascade.
The build process is stopped when either the maximum number of levels is reached, the termination criterion is satisfied or no further improvement is achieved.
In case of a level performing worse than the prior one, the build process is terminated immediately and the current level discarded.

ClassifierCascade() - Constructor for class weka.classifiers.meta.ClassifierCascade

ClassifierCascade.Combination - Enum in weka.classifiers.meta

Defines how to combine the predictions of the final layer and turn it into actual predictions.

ClassifierCascade.ThresholdCheck - Enum in weka.classifiers.meta

Defines how to check the threshold.

ClassifierErrors - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Generates classifier errors plot.

ClassifierErrors() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

ClassifierHandler - Class in weka.gui.explorer

Manages the ClassifierPanel.

ClassifierHandler() - Constructor for class weka.gui.explorer.ClassifierHandler

ClassifierPanel - Class in adams.gui.tools.wekamultiexperimenter.setup

Panel for listing datasets.

ClassifierPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

classifiersTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the tip text for this property.

classifierTipText() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Returns the tip text for this property.

classifierTipText() - Method in class adams.flow.source.WekaClassifierSetup

Returns the tip text for this property.

classifierTipText() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

Returns the tip text for this property.

classifierTipText() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns the tip text for this property.

classifierTipText() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Returns the tip text for this property.

classifierTipText() - Method in class adams.flow.transformer.WekaClassifierOptimizer

Returns the tip text for this property.

classifierTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the tip text for this property.

classifierTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the tip text for this property.

classifierTipText() - Method in class adams.flow.transformer.WekaStreamEvaluator

Returns the tip text for this property.

classifierTipText() - Method in class adams.flow.transformer.WekaTrainClassifier

Returns the tip text for this property.

classifierTipText() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator

Returns the tip text for this property.

classifierTipText() - Method in class adams.ml.model.classification.WekaClassifier

Returns the tip text for this property.

classifierTipText() - Method in class adams.ml.model.regression.WekaRegressor

Returns the tip text for this property.

classifierTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

classifierTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the tip text for this property.

classifierTipText() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the tip text for this property.

classifierTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Returns the tip text for this property

classifierTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Returns the tip text for this property

classifierWeightsTipText() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Returns the tip text for this property

classify(Row) - Method in class adams.ml.model.classification.WekaClassificationModel

Returns the class label for the given row.

classify(Row) - Method in class adams.ml.model.regression.WekaRegressionModel

Returns the regression for the given row.

classifyInstance(Instance) - Method in class weka.classifiers.functions.ClassificationViaPLS

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.functions.FakeClassifier

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.functions.FromPredictions

Always returns 0.

classifyInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Classifies a given instance.

classifyInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Classifies a given instance.

classifyInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Classifies a given instance.

classifyInstance(Instance) - Method in class weka.classifiers.functions.GeneticAlgorithm

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.functions.GPD

Classifies a given instance.

classifyInstance(Instance) - Method in class weka.classifiers.functions.LinearRegressionJ

Classifies the given instance using the linear regression function.

classifyInstance(Instance) - Method in class weka.classifiers.functions.MathExpressionClassifier

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.functions.PLSClassifierWeighted

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.functions.PLSWeighted

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Generate a prediction for the supplied instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainAttributePercentile

Returns the prediction.

classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainAverage

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainingCascade

Predicts the class label index for the given instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Synchronized call of super method for making classification.

classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Returns the prediction.

classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainVote

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.ClassifierCascade

Returns the classification for the instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.Consensus

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.ConsensusOrVote

Predicts the class label index for the given instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.Corr

Returns the prediction.

classifyInstance(Instance) - Method in class weka.classifiers.meta.Fallback

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.FilteredClassifierExt

Simply synchronized call of inherited method.

classifyInstance(Instance) - Method in class weka.classifiers.meta.HighLowSplit

Returns the prediction.

classifyInstance(Instance) - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

Returns the prediction.

classifyInstance(Instance) - Method in class weka.classifiers.meta.LeastMedianSq

Returns the prediction.

classifyInstance(Instance) - Method in class weka.classifiers.meta.LogClassRegressor

Returns the prediction.

classifyInstance(Instance) - Method in class weka.classifiers.meta.LogTargetRegressor

Returns the prediction.

classifyInstance(Instance) - Method in class weka.classifiers.meta.MinMaxLimits

Returns the prediction.

classifyInstance(Instance) - Method in class weka.classifiers.meta.PartitionedStacking

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.PeakTransformed

Returns the prediction.

classifyInstance(Instance) - Method in class weka.classifiers.meta.SocketFacade

Generates a classification for the instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.SubsetEnsemble

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.SumTransformed

Returns the prediction.

classifyInstance(Instance) - Method in class weka.classifiers.meta.SuppressModelOutput

Classifies the given instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper

Synchronized method for classifying data.

classifyInstance(Instance) - Method in class weka.classifiers.meta.Veto

Predicts the class label index for the given instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.VotedImbalance

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.simple.AbstractSimpleClassifier

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.M5Base2

Calculates a prediction for an instance using a set of rules or an M5 model tree

classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.Rule2

Calculates a prediction for an instance using this rule or M5 model tree

classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.RuleNode2

Classify an instance using this node.

classifyInstance(Instance) - Method in class weka.classifiers.trees.RandomModelTrees

Calculates the class membership probabilities for the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.trees.RandomRegressionForest

Calculates the class membership probabilities for the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.trees.RandomRegressionForest.Node

classifies the given instance

classifyInstance(Instance) - Method in class weka.classifiers.trees.XGBoost

Classifies the given test instance.

classifyInstanceMedian(Instance) - Method in class weka.classifiers.meta.AbstainVote

Classifies the given test instance, returning the median from all classifiers.

ClassifyTab - Class in adams.gui.tools.wekainvestigator.tab

Tab for classification.

ClassifyTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.ClassifyTab

ClassifyTab.HistoryPanel - Class in adams.gui.tools.wekainvestigator.tab

Customized history panel.

classIndex() - Method in class weka.core.AbstractHashableInstance

Returns the class attribute's index.

classIndex(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Returns the index of the selected class attribute in the provided dataset.

classIndexTipText() - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Returns the tip text for this property.

classIndexTipText() - Method in class adams.flow.source.WekaNewInstances

Returns the tip text for this property.

classIndexTipText() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the tip text for this property.

classIndexTipText() - Method in class adams.flow.transformer.WekaClassSelector

Returns the tip text for this property.

classIndexTipText() - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Returns the tip text for this property.

classIndexTipText() - Method in class adams.flow.transformer.WekaEvaluationValues

Returns the tip text for this property.

classIndexTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Returns the tip text for this property.

classIndexTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis

Returns the tip text for this property.

classIndexTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Returns the tip text for this property.

classIndexTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

classIndexTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the tip text for this property.

classIndexTipText() - Method in class weka.classifiers.meta.ClassifierCascade

Returns the tip text for this property.

classIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Returns the tip text for this property

classIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Returns the tip text for this property

classIsMissing() - Method in class weka.core.AbstractHashableInstance

Tests if an instance's class is missing.

classLabelIndexTipText() - Method in class adams.data.conversion.WekaEvaluationToCostCurve

Returns the tip text for this property.

classLabelIndexTipText() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve

Returns the tip text for this property.

classLabelIndexTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the tip text for this property.

classLabelIndexTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

classLabelRangeTipText() - Method in class adams.flow.sink.WekaCostCurve

Returns the tip text for this property.

classLabelRangeTipText() - Method in class adams.flow.sink.WekaThresholdCurve

Returns the tip text for this property.

classLabelRangeTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve

Returns the tip text for this property.

classLabelRangeTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Returns the tip text for this property.

classLabelTipText() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the tip text for this property.

classnameTipText() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the tip text for this property.

classnameTipText() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the tip text for this property.

classnameTipText() - Method in class adams.core.discovery.genetic.GenericInteger

Returns the tip text for this property.

classnameTipText() - Method in class adams.core.discovery.genetic.GenericString

Returns the tip text for this property.

classnameTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode

Returns the tip text for this property.

classNameTipText() - Method in class adams.flow.source.WekaNewInstances

Returns the tip text for this property.

classNameTipText() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the tip-text for the class-name option.

classNoiseTipText() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Returns the tip text for this property.

ClassRangeBasedClassifierErrors - Class in weka.gui.visualize.plugins

Displays the classifier errors using Weka panels, but with a sizes adjusted to the class range.

ClassRangeBasedClassifierErrors() - Constructor for class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors

classValue() - Method in class weka.core.AbstractHashableInstance

Returns an instance's class value as a floating-point number.

ClassValueBinValueExtractor() - Constructor for class adams.data.binning.BinnableInstances.ClassValueBinValueExtractor

clean(String) - Method in class weka.core.tokenizers.cleaners.AbstractTokenCleaner

Determines whether a token is clean or not.

clean(String) - Method in class weka.core.tokenizers.cleaners.MultiCleaner

Determines whether a token is clean or not.

clean(String) - Method in class weka.core.tokenizers.cleaners.NormalizeDuplicateChars

Determines whether a token is clean or not.

clean(String) - Method in class weka.core.tokenizers.cleaners.PassThrough

Passes tokens through.

clean(String) - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

Determines whether a token is clean or not.

clean(String) - Method in interface weka.core.tokenizers.cleaners.TokenCleaner

Determines whether a token is clean or not.

CLEANER - Static variable in class weka.core.tokenizers.cleaners.MultiCleaner

CLEANER - Static variable in class weka.core.tokenizers.PreCleanedTokenizer

cleanersTipText() - Method in class weka.core.tokenizers.cleaners.MultiCleaner

Returns the tip text for this property.

cleanerTipText() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns the tip text for this property.

cleanOutputBuffer() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Cleans up the output buffer.

cleanUp() - Method in class adams.data.instances.AbstractInstanceGenerator

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.flow.transformer.WekaClassifierRanker

Frees up memory in a "destructive" non-reversible way.

cleanUp() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.flow.transformer.WekaTrainAssociator.TrainJob

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment.CrossValidationExperimentJob

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.visualization.instance.InstanceExplorer

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.visualization.instance.InstancePanel

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.gui.visualization.instance.InstancePointHitDetector

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.multiprocess.WekaCrossValidationExecution

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.multiprocess.WekaCrossValidationJob

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.opt.optimise.GeneticAlgorithm

Cleans up data structures, frees up memory.

cleanUp() - Method in class adams.tools.CompareDatasets

Cleans up data structures, frees up memory.

cleanUpGUI() - Method in class adams.flow.sink.WekaClassifierErrors

Removes all graphical components.

cleanUpGUI() - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Removes all graphical components.

cleanUpGUI() - Method in class adams.flow.sink.WekaCostCurve

Removes all graphical components.

cleanUpGUI() - Method in class adams.flow.sink.WekaInstancesDisplay

Removes all graphical components.

cleanUpGUI() - Method in class adams.flow.sink.WekaInstancesPlot

Removes all graphical components.

cleanUpGUI() - Method in class adams.flow.sink.WekaInstanceViewer

Removes all graphical components.

cleanUpGUI() - Method in class adams.flow.sink.WekaMarginCurve

Removes all graphical components.

cleanUpGUI() - Method in class adams.flow.sink.WekaThresholdCurve

Removes all graphical components.

clear() - Method in class adams.data.instance.Instance

Removes all the points and report and nulls the header reference.

clear() - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

clear() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Removes all currently loaded datasets.

clear() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Removes all entries and payloads.

clear() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Removes all entries and payloads.

clear() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Removes all entries and payloads.

clear() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Removes all entries and payloads.

clear() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Clears the content.

clear() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Saves the result as a new dataset.

clear() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Removes all entries and payloads.

clear() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel

Clears the display.

clear() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.StatisticsTable

Clears the table.

clear() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

Clears the display.

clear() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

Clears the display.

clear() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel.HistoryPanel

Removes all entries and payloads.

clear() - Method in class adams.gui.tools.wekamultiexperimenter.LogPanel

Clears the content.

clear() - Method in class adams.gui.visualization.instance.InstanceContainerManager

Clears the container list.

clear() - Method in class adams.ml.data.InstancesHeaderRow

Removes all cells.

clear() - Method in class adams.ml.data.InstancesView

Removes all cells, but leaves comments.

clear() - Method in class adams.ml.data.InstanceView

Removes all cells.

clear() - Method in class weka.experiment.ResultMatrixAdamsCSV

removes the stored data but retains the dimensions of the matrix.

clear() - Method in class weka.gui.explorer.MultiExplorer

Removes all panels.

clearBufferTipText() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns the tip text for this property.

clearData() - Method in class adams.gui.visualization.instance.InstanceExplorer

Removes all the data.

clearLog() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Empties the log.

clearLog() - Method in class adams.gui.tools.wekainvestigator.tab.LogTab

Clears the log.

clearPanel() - Method in class adams.flow.sink.WekaAttributeSummary

Clears the content of the panel.

clearPanel() - Method in class adams.flow.sink.WekaClassifierErrors

Clears the content of the panel.

clearPanel() - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Clears the content of the panel.

clearPanel() - Method in class adams.flow.sink.WekaCostCurve

Clears the content of the panel.

clearPanel() - Method in class adams.flow.sink.WekaGraphVisualizer

Clears the content of the panel.

clearPanel() - Method in class adams.flow.sink.WekaInstancesDisplay

Clears the content of the panel.

clearPanel() - Method in class adams.flow.sink.WekaInstancesPlot

Clears the content of the panel.

clearPanel() - Method in class adams.flow.sink.WekaInstanceViewer

Clears the content of the panel.

clearPanel() - Method in class adams.flow.sink.WekaMarginCurve

Clears the content of the panel.

clearPanel() - Method in class adams.flow.sink.WekaThresholdCurve

Clears the content of the panel.

clearPanel() - Method in class adams.flow.sink.WekaTreeVisualizer

Clears the content of the panel.

clearProgress() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Clears the progress of the experiment.

clearRemainder() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

clearResults() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Clears all currently stored results.

clearResults() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Clears all currently stored results.

clearResults() - Method in class adams.opt.optimise.GeneticAlgorithm

Clears all currently stored results.

clearUndo() - Method in class adams.gui.visualization.instances.InstancesTable

removes the undo history

clearUndo() - Method in class adams.gui.visualization.instances.InstancesTableModel

removes the undo history

clip(double) - Method in class weka.classifiers.evaluation.MSLE

Limits the value to MSLE.EPSILON or larger.

Clipboard - Class in adams.gui.tools.wekainvestigator.source

Parses content on the clipboard.

Clipboard() - Constructor for class adams.gui.tools.wekainvestigator.source.Clipboard

Instantiates the action.

cloneContent() - Method in class adams.data.instance.WekaInstanceContainer

Returns a clone of the content.

close() - Method in class adams.gui.tools.DatasetCompatibilityPanel

Closes the dialog.

close() - Method in class adams.gui.visualization.instance.InstanceComparePanel

closes the dialog/frame.

close() - Method in class adams.gui.visualization.instance.InstanceExplorer

closes the dialog/frame.

close() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Closes the dialog.

close() - Method in class weka.gui.explorer.ExplorerExt

Closes the dialog.

closeServer() - Method in class weka.classifiers.meta.SocketFacade

Closes the server socket if necessary.

cluster(Row) - Method in class adams.ml.model.clustering.WekaClusteringModel

Returns the cluster for the given row.

ClusterAssignments - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output

Displays the cluster assignments.

ClusterAssignments() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.ClusterAssignments

ClusterCenters - Class in adams.flow.transformer.wekaclusterer

Computes the cluster centers for the provided dataset.

ClusterCenters() - Constructor for class adams.flow.transformer.wekaclusterer.ClusterCenters

ClusterCounts - Class in adams.flow.transformer.wekaclusterer

Creates an overview of how many instances get clustered into each cluster.
Stored in container under: Clustered dataset

ClusterCounts() - Constructor for class adams.flow.transformer.wekaclusterer.ClusterCounts

ClustererHandler - Class in weka.gui.explorer

Manages the ClustererPanel.

ClustererHandler() - Constructor for class weka.gui.explorer.ClustererHandler

clustererTipText() - Method in class adams.flow.source.WekaClustererSetup

Returns the tip text for this property.

clustererTipText() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator

Returns the tip text for this property.

clustererTipText() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Returns the tip text for this property.

clustererTipText() - Method in class adams.flow.transformer.WekaTrainClusterer

Returns the tip text for this property.

clustererTipText() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

Returns the tip text for this property.

clustererTipText() - Method in class adams.ml.model.clustering.WekaClusterer

Returns the tip text for this property.

clusterInstance(Instance) - Method in class weka.clusterers.SAXKMeans

Classifies a given instance.

ClusterStatistics - Class in adams.flow.transformer.wekaclusterer

Computes cluster statistics (min/max/mean/stdev) for the provided dataset.

ClusterStatistics() - Constructor for class adams.flow.transformer.wekaclusterer.ClusterStatistics

ClusterTab - Class in adams.gui.tools.wekainvestigator.tab

Tab for clustering.

ClusterTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.ClusterTab

ClusterTab.HistoryPanel - Class in adams.gui.tools.wekainvestigator.tab

Customized history panel.

coefficients() - Method in class weka.classifiers.functions.LinearRegressionJ

Returns the coefficients for this linear model.

collapse(Instances) - Method in class weka.core.InstanceGrouping

Collapses the data into a fake dataset with only the the group and the class attribute.

collapsedHeader() - Method in class weka.core.InstanceGrouping

Creates the header for the collapsed data.

colNameTipText() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

Returns the tip text for this property.

colNameTipText() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall

Returns the tip text for this property.

colorFieldTipText() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Returns the tip text for this property.

colorProviderTipText() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the tip text for this property.

colorProviderTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Returns the tip text for this property.

COLUMN - adams.flow.transformer.WekaExtractArray.ExtractionType

column.

COLUMN_BY_INDEX - adams.flow.transformer.WekaInstancesStatisticDataType

obtains columns (by index).

COLUMN_BY_REGEXP - adams.flow.transformer.WekaInstancesStatisticDataType

obtains columns (by reg exp).

COLUMN_NAME - Static variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

the name column in the spreadsheet.

COLUMN_VALUE - Static variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

the value column in the spreadsheet.

columnAsVector(Matrix, int) - Static method in class weka.core.matrix.MatrixHelper

returns the given column as a vector (actually a n x 1 matrix)

ColumnContainer(String, int) - Constructor for class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer

Initializes the container.

ColumnFinder - Interface in adams.data.weka.columnfinder

Interface for classes that "find" columns of interest in datasets.

columnFinderTipText() - Method in class adams.data.weka.columnfinder.AbstractFilteredColumnFinder

Returns the tip text for this property.

columnFinderTipText() - Method in class adams.data.weka.datasetsplitter.ColumnSplitter

Gets the tip-text for the columnFinder option.

columnFinderTipText() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Returns the tip text for this property.

columnFinderTipText() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the tip-text for the column-finder option.

columnFinderTipText() - Method in class weka.filters.unsupervised.attribute.DatasetCleaner

Returns the tip text for this property.

COLUMNS - Static variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

columnSampleByLevelTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the columnSampleByLevel option.

columnSampleByNodeTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the columnSampleByNode option.

columnSampleByTreeTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the columnSampleByTree option.

ColumnSplitter - Class in adams.data.weka.datasetsplitter

Splits a dataset in two based on the columns selected by a column-finder.

ColumnSplitter() - Constructor for class adams.data.weka.datasetsplitter.ColumnSplitter

ColumnStatistic - Class in adams.gui.visualization.instances.instancestable

Allows the calculation of column statistics.

ColumnStatistic() - Constructor for class adams.gui.visualization.instances.instancestable.ColumnStatistic

columnsTipText() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the tip text for this property.

columnsTipText() - Method in class adams.data.weka.columnfinder.Constant

Gets the tip-text for the columns option.

columnsTipText() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

columnTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the tip text for this property.

columnTipText() - Method in class adams.flow.transformer.WekaGetInstancesValue

Returns the tip text for this property.

columnTipText() - Method in class adams.flow.transformer.WekaSetInstancesValue

Returns the tip text for this property.

columnTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the tip text for this property.

colVersionTipText() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

Returns the tip text for this property.

COMBINATION - Static variable in class weka.classifiers.meta.ClassifierCascade

combinationRuleTipText() - Method in class weka.classifiers.meta.AbstainVote

Returns the tip text for this property

combinationRuleTipText() - Method in class weka.classifiers.meta.SubsetEnsemble

Returns the tip text for this property.

combinationRuleTipText() - Method in class weka.classifiers.meta.VotedImbalance

Returns the tip text for this property.

combinationTipText() - Method in class adams.data.weka.columnfinder.MultiColumnFinder

Returns the tip text for this property.

combinationTipText() - Method in class adams.data.weka.rowfinder.MultiRowFinder

Returns the tip text for this property.

combinationTipText() - Method in class weka.classifiers.meta.ClassifierCascade

Returns the tip text for this property.

COMBINE_COMPONENTS - weka.attributeSelection.AbstractPLSAttributeEval.LoadingsCalculations

COMBINED - adams.flow.transformer.WekaClassifierRanker.Measure

evaluation via: Combined = ("", Performance.1-CC) + RRSE + RAE.

commandlineToObject(String) - Method in class adams.flow.source.WekaSelectObjects

Turns a commandline into an object.

commentTipText() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary

Returns the tip text for this property.

commentTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the tip text for this property.

commonSubsequence(String, String, boolean) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Determines the common subsequence of the two strings.

commonSubsequence(String, String, boolean) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Determines the common subsequence of the two strings.

communicationTipText() - Method in class weka.classifiers.functions.PyroProxy

Returns the tip text for this property.

communicationTipText() - Method in interface weka.core.PyroProxyObject

Returns the tip text for this property.

compactify() - Method in class weka.core.InstancesView

Does nothing.

comparatorTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the tip text for this property.

compare(DataPoint, DataPoint) - Method in class adams.data.instance.InstancePointComparator

Compares its two arguments for order.

compare(AbstractHistoryPopupMenuItem, AbstractHistoryPopupMenuItem) - Method in class adams.gui.tools.wekainvestigator.history.MenuItemComparator

Compares the menu items based on category and title.

compare(AbstractPerFoldPopupMenuItem, AbstractPerFoldPopupMenuItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.MenuItemComparator

Compares the menu items based on category and title.

compare(File[], Instances[]) - Method in class adams.gui.tools.DatasetCompatibilityPanel

Performs the actual comparison.

compare(List<AbstractMerge.SourceAttribute>, List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Compares two lists of source attributes to determine the order in which their mapped attributes should appear in the merged dataset.

compare(List<AbstractMerge.SourceAttribute>, List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Compares two lists of source attributes to determine the order in which their mapped attributes should appear in the merged dataset.

compare(Prediction, Prediction) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbsolutePredictionErrorComparator

Compares the error of the predictions.

compare(Instance, Instance) - Method in class adams.data.instances.InstanceComparator

Compares its two arguments for order.

compareData() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Compares the data

CompareDatasets - Class in adams.tools

Compares two datasets, either row-by-row or using a row attribute listing a unique ID for matching the rows, outputting the correlation coefficient of the numeric attributes found in the ranges defined by the user.
In order to trim down the number of generated rows, a threshold can be specified.

CompareDatasets() - Constructor for class adams.tools.CompareDatasets

compareIDs() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Compares the IDs.

compareInstances() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Performs the comparison between the rows from the two datasets.

CompareModels - Class in adams.gui.tools.wekainvestigator.tab.classifytab.history

Compares the predictions of two models.

CompareModels() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.history.CompareModels

compareNumeric(String, ResultItem, String, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.CompareModels

Compares the two evaluations (numeric class).

compareOutput(AbstractOutputGenerator, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and then displays the generated outputs side by side.

compareOutput(AbstractOutputGenerator, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and then displays the generated outputs side by side.

compareOutput(AbstractOutputGenerator, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and then displays the generated outputs side by side.

compareOutput(AbstractOutputGenerator, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and then displays the generated outputs side by side.

compareStructure() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Compares the structure.

CompareTab - Class in adams.gui.tools.wekainvestigator.tab

For comparing datasets.

CompareTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.CompareTab

compareTo(WekaPredictionContainerToSpreadSheet.SortContainer) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer

Compares this object with the specified object for order.

compareTo(AbstractMerge.SourceAttribute) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute

compareTo(DataContainer) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Compares this container with the specified one.

compareTo(InstancesColumnComboBox.ColumnContainer) - Method in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer

Compares itself to the other container.

compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotColumn

For sorting the menu items.

compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotRow

For sorting the menu items.

compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

For sorting the menu items.

compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell

For sorting the menu items.

compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn

For sorting the menu items.

compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow

For sorting the menu items.

compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

For sorting the menu items.

compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.Binning

For sorting the menu items.

compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.Histogram

For sorting the menu items.

compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

For sorting the menu items.

compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

For sorting the menu items.

compareTo(Object) - Method in class adams.data.instance.InstancePoint

Compares this object with the specified object for order.

compareTo(Object) - Method in class adams.data.instances.AbstractInstanceGenerator

Compares this object with the specified object for order.

compareTo(Object) - Method in class adams.data.weka.columnfinder.AbstractColumnFinder

Compares this object with the specified object for order.

compareTo(Object) - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer

Compares this object with the specified object for order.

compareTo(Object) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Compares this object with the specified object for order.

compareTo(Object) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval

Compares this object with the specified object for order.

compareTo(Object) - Method in class adams.data.weka.predictions.AbstractErrorScaler

Compares this object with the specified object for order.

compareTo(Object) - Method in class adams.data.weka.rowfinder.AbstractRowFinder

Compares this object with the specified object for order.

compareTo(Object) - Method in class adams.flow.transformer.WekaAccumulatedError.SortablePrediction

Compares this object with the specified object for order.

compareTo(Object) - Method in class weka.core.neighboursearch.NewNNSearch.InstanceNode

comparisonFieldTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the tip text for this property.

comparisonFieldTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the tip text for this property.

Compatibility - Class in adams.gui.tools.wekainvestigator.datatable.action

Checks the compatibility of the selected datasets.

Compatibility() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Compatibility

Instantiates the action.

completedClassifier(int, boolean) - Method in class weka.classifiers.meta.SubsetEnsemble

Records the completion of the training of a single classifier.

completedClassifier(int, boolean) - Method in class weka.classifiers.meta.VotedImbalance

Records the completion of the training of a single classifier.

completeRowsOnlyTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Gets the tip-text for the complete-rows-only option.

complexityStatisticsTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the tip text for this property.

complexityStatisticsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Returns the tip text for this property.

ComponentContentPanel - Class in adams.gui.tools.wekainvestigator.output

Panel for exporting the graphical component as image.

ComponentContentPanel(JComponent, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.ComponentContentPanel

Initializes the panel with the specified component.

componentRangeTipText() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Returns the tip text for this property

computeHashCode() - Method in class weka.core.AbstractHashableInstance

Computes the hashcode.

computeHashCode() - Method in class weka.core.HashableInstanceUsingString

Computes the hashcode.

computeHashCode() - Method in class weka.core.HashableInstanceUsingSum

Computes the hashcode.

computePercentage(double, double, double) - Static method in class weka.classifiers.RangeCheckHelper

Calculates the percentage of how much the value is outside the range.

computeStdDev(Instance, Matrix) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Computes standard deviation for given instance, without transforming target back into original space.

computeThresholds(Instances) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

computes the thresholds for outliers and extreme values

confidenceLevelTipText() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Returns the tip text for this property.

configureOutput(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and returns it if accepted.

configureOutput(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and returns it if accepted.

configureOutput(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and returns it if accepted.

configureOutput(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and returns it if accepted.

configureOutput(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and returns it if accepted.

configureRowFinder(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Configures the row finder that determines whether the classifier/dataset combination is still required.

ConfusionMatrix - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Displays the confusion matrix.

ConfusionMatrix() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

confusionMatrixTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the tip text for this property.

confusionMatrixTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Returns the tip text for this property.

consensus(Instance) - Method in class weka.classifiers.meta.Consensus

Checks whether there is consensus between the classifiers.

Consensus - Class in weka.classifiers.meta

Outputs predictions only if the ensemble agrees.

Consensus() - Constructor for class weka.classifiers.meta.Consensus

ConsensusOrVote - Class in weka.classifiers.meta

If the required minimum number of classifiers of the ensemble agree on a label, then this label is predicted.

ConsensusOrVote() - Constructor for class weka.classifiers.meta.ConsensusOrVote

Constant - Class in adams.data.weka.columnfinder

Column finder that finds a constant set of columns.

Constant - Class in adams.data.weka.rowfinder

Row finder that finds a constant set of rows.

Constant() - Constructor for class adams.data.weka.columnfinder.Constant

Constant() - Constructor for class adams.data.weka.rowfinder.Constant

constructEnsemble() - Method in class weka.classifiers.meta.VotedImbalance

Constructs the ensemble.

constructEnsemble(Instance) - Method in class weka.classifiers.meta.SubsetEnsemble

Constructs the ensemble.

containersInViewport(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Viewport

Locates the visible instances that are on display in the current viewport.

conversionTipText() - Method in class weka.core.converters.SpreadSheetLoader

The tip text for this property.

convert() - Method in class adams.gui.tools.WekaOptionsConversionPanel

Performs the conversion.

convert(Class, String) - Method in class adams.flow.core.WekaPropertyValueConverter

Converts the variable value into the appropriate object, if possible.

convertCapabilities(Capabilities) - Static method in class adams.ml.data.WekaConverter

Converts Weka capabilities into ADAMS ones.

convertDataset(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Performs the dataset conversion.

converterTipText() - Method in class adams.data.conversion.WekaCommandToCode

Returns the tip text for this property.

convertInstance(PyroProxy, Instance) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Converts the instance into a different format.

convertInstance(Instance) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Transform an instance in original (unormalized) format.

ConvertToDate - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction

Converts the selected string attributes to date ones.

ConvertToDate() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToDate

Instantiates the action.

ConvertToNominal - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction

Converts the selected attributes to nominal ones.

ConvertToNominal() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToNominal

Instantiates the action.

ConvertToString - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction

Converts the selected attributes to string ones.

ConvertToString() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToString

Instantiates the action.

COORD_DESCENT - weka.classifiers.trees.XGBoost.Updater

copy() - Method in class weka.core.AbstractHashableInstance

This method produces a shallow copy of an object.

copy(double[]) - Method in class weka.core.AbstractHashableInstance

Copies the instance but fills up its values based on the given array of doubles.

copy(Instances) - Method in class adams.gui.visualization.instances.InstancesTableModel

Returns a new model with the same setup.

copy(ExplorerExt, boolean) - Static method in class weka.gui.explorer.WorkspaceHelper

Copies an explorer instance.

Copy - Class in adams.gui.tools.wekainvestigator.datatable.action

Copies the selected dataset.

Copy() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Copy

Instantiates the action.

copyGene(int, int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Copies the values of one gene to another.

copySelectedTab() - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane

Creates a copy of the current tab.

CopySetup - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold

Simply copies the classifier setup to the clipboard.

CopySetup() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.CopySetup

copyTabAt(int) - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane

Creates a copy of the specified tab.

copyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu

Copies the content to the clipboard.

copyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel

Copies the content to the clipboard.

copyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel

Copies the content to the clipboard.

copyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel

Copies the content to the clipboard.

copyWorkspace() - Method in class adams.gui.tools.wekainvestigator.InvestigatorManagerPanel

Copies a workspace.

Corr - Class in weka.classifiers.meta

Assume NO MISSING VALUES, all attributes must be NUMERIC (or 0/1 maybe ...).

Corr() - Constructor for class weka.classifiers.meta.Corr

correct(double[], double[]) - Method in class weka.filters.unsupervised.attribute.detrend.AbstractDetrend

Corrects the spectrum.

correct(double[], double[]) - Method in class weka.filters.unsupervised.attribute.detrend.Mean

Corrects the spectrum.

correct(double[], double[]) - Method in class weka.filters.unsupervised.attribute.detrend.RangeBased

Corrects the spectrum.

correct(double[], double[], double[]) - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.AbstractMultiplicativeScatterCorrection

Corrects the spectrum.

correct(double[], double[], double[]) - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased

Corrects the spectrum.

correctData(T, double[]) - Method in class adams.data.baseline.AbstractLinearRegressionBased

Corrects the data with the given coefficients.

CORRECTION - Static variable in class weka.filters.unsupervised.attribute.Detrend

CORRECTION - Static variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

CORRECTION - Static variable in class weka.filters.unsupervised.attribute.SimpleDetrend

correctionTipText() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns the tip text for this property.

correctionTipText() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns the tip text for this property.

correctionTipText() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Returns the tip text for this property.

correctTipText() - Method in class weka.filters.unsupervised.attribute.SpellChecker

Returns the tip text for this property.

CORRELATION_COEFFICIENT - adams.flow.core.EvaluationStatistic

CORRELATION_COEFFICIENT - adams.flow.core.ExperimentStatistic

CORRELATION_COEFFICIENT - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

CorrelationMatrix - Class in weka.filters.unsupervised.attribute

Computes a matrix with the correlation coefficients between attributes.

CorrelationMatrix() - Constructor for class weka.filters.unsupervised.attribute.CorrelationMatrix

CostCurve - Class in adams.gui.menu

Displays Cost curve data.

CostCurve() - Constructor for class adams.gui.menu.CostCurve

Initializes the menu item with no owner.

CostCurve(AbstractApplicationFrame) - Constructor for class adams.gui.menu.CostCurve

Initializes the menu item.

CostCurvePanel - Class in adams.gui.tools.weka

Displays cost curve data.

CostCurvePanel() - Constructor for class adams.gui.tools.weka.CostCurvePanel

count() - Method in class weka.gui.explorer.MultiExplorer

Returns the number of explorer panels.

countVisible() - Method in class adams.gui.visualization.instance.InstanceContainerManager

Returns the number of visible containers.

COX_REGRESSION - weka.classifiers.trees.XGBoost.Objective

CPU - weka.classifiers.trees.XGBoost.Predictor

create() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO

Creates a new experiment.

create() - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultAdamsExperimentIO

Creates a new experiment.

create() - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultWekaExperimentIO

Creates a new experiment.

create() - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO

Creates a new experiment.

createAttribute(String) - Method in class weka.core.converters.SimpleArffLoader

Creates an attribute from the specification line.

createAttributeMapping() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Creates a mapping from the attributes in each input dataset to the corresponding attribute in the merged dataset.

createCellPopup(MouseEvent) - Method in class adams.gui.visualization.instances.InstancesTable

Creates a popup menu for the cells.

createChooserPanel() - Method in class adams.gui.tools.weka.AbstractPanelWithFile

Generates the panel to use.

createChooserPanel() - Method in class adams.gui.tools.weka.CostCurvePanel

Generates the panel to use.

createComponent() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableWithButtons

Creates the component to use in the panel.

createContainerList() - Method in class adams.gui.visualization.instance.InstancePanel

Returns the container list.

createCustomEditor() - Method in class adams.gui.goe.WekaExperimentFileEditor

Gets the custom editor component.

createDataset(Evaluation) - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator

Generates a dataset, containing the predicted vs actual values.

createDefaultDataModel() - Method in class adams.gui.visualization.instance.InstanceTable

Creates an empty default model.

createDialog() - Method in class adams.gui.tools.wekainvestigator.source.Clipboard

Creates a new dialog.

createDialog(Container) - Static method in class adams.gui.goe.WekaGenericArrayEditorDialog

Creates a modal dialog for the parent.

createDialog(Container) - Static method in class adams.gui.goe.WekaGenericObjectEditorDialog

Creates a modal dialog for the parent.

createDialog(Container, PropertyEditor) - Static method in class adams.gui.goe.WekaGenericObjectEditorDialog

Creates a modal dialog for the parent with the provided editor.

createDialog(Container, PropertyEditor, Object) - Static method in class adams.gui.goe.WekaGenericObjectEditorDialog

Creates a modal dialog for the parent with the provided editor and initial value.

createDialog(Container, Object) - Static method in class adams.gui.goe.WekaGenericArrayEditorDialog

Creates a modal dialog for the parent with the provided editor and initial value.

createDisplayPanel(Token) - Method in class adams.flow.sink.WekaAttributeSummary

Creates a new display panel for the token.

createDisplayPanel(Token) - Method in class adams.flow.sink.WekaClassifierErrors

Creates a new panel for the token.

createDisplayPanel(Token) - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Creates a new panel for the token.

createDisplayPanel(Token) - Method in class adams.flow.sink.WekaCostCurve

Creates a new panel for the token.

createDisplayPanel(Token) - Method in class adams.flow.sink.WekaGraphVisualizer

Creates a new display panel for the token.

createDisplayPanel(Token) - Method in class adams.flow.sink.WekaInstancesDisplay

Creates a new panel for the token.

createDisplayPanel(Token) - Method in class adams.flow.sink.WekaInstancesPlot

Creates a new panel for the token.

createDisplayPanel(Token) - Method in class adams.flow.sink.WekaInstanceViewer

Creates a new panel for the token.

createDisplayPanel(Token) - Method in class adams.flow.sink.WekaMarginCurve

Creates a new panel for the token.

createDisplayPanel(Token) - Method in class adams.flow.sink.WekaThresholdCurve

Creates a new panel for the token.

createDisplayPanel(Token) - Method in class adams.flow.sink.WekaTreeVisualizer

Creates a new display panel for the token.

createDummy() - Static method in class adams.ml.data.InstancesView

Returns a dummy dataset.

createEmptyResultantDataset(Map<String, List<AbstractMerge.SourceAttribute>>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Creates the resultant dataset, ready to be filled with data.

createExperimentIO() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

Creates the handler for the IO, i.e., loading/saving of experiments.

createExperimentIO() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

Creates the handler for the IO, i.e., loading/saving of experiments.

createExperimentIO() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

Creates the handler for the IO, i.e., loading/saving of experiments.

createFakeModel() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Creates the fake model.

createFileChooser() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu

Creates the filechooser to use.

createFileChooser() - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel

Creates the filechooser to use.

createFileChooser() - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel

Creates the filechooser to use.

createFileChooser() - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel

Creates the filechooser to use.

createFileChooser() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractAdamsExperimentIO

Creates and returns a file chooser for loading/saving experiments.

createFileChooser() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO

Creates and returns a file chooser for loading/saving experiments.

createFileChooser() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractWekaExperimentIO

Creates and returns a file chooser for loading/saving experiments.

createFilename(Instances) - Method in class adams.flow.transformer.WekaInstanceDumper

Generates the filename for the output.

createFileName(double, Instances, String) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Generates a file name for the fitness.

createFlow(PlaceholderFile[], AbstractFileLoader, SpreadSheetReader, String, PlaceholderDirectory) - Method in class adams.gui.menu.MakeCompatibleDatasets

Creates the flow.

createGraphVisualizer(Token) - Method in class adams.flow.sink.WekaGraphVisualizer

Creates a tree visualizer from the token.

createHeader(Instances) - Method in class adams.flow.transformer.WekaInstanceDumper

Turns the dataset header into the appropriate format.

createHeaderPopup(MouseEvent) - Method in class adams.gui.visualization.instances.InstancesTable

Shows a popup menu for the header.

createHistoryEntryToolTip(AbstractNamedHistoryPanel<ResultItem>, int) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Gets called when a tooltip needs to get generated.

createHistoryEntryToolTip(AbstractNamedHistoryPanel<ResultItem>, int) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Gets called when a tooltip needs to get generated.

createHistoryEntryToolTip(AbstractNamedHistoryPanel<ResultItem>, int) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Gets called when a tooltip needs to get generated.

createHistoryEntryToolTip(AbstractNamedHistoryPanel<ResultItem>, int) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Gets called when a tooltip needs to get generated.

createHistoryEntryToolTip(AbstractNamedHistoryPanel<ResultItem>, int) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Gets called when a tooltip needs to get generated.

createIDInfoPanel(BaseTextArea) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Generates an info panel for an ID text area.

createLastSetupKey(Class, boolean, boolean) - Method in class adams.gui.visualization.instances.InstancesTable

Generates a key for the HashMap used for the last setups.

createMappedAttribute(String, List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Creates the attribute for the output merged dataset for the given attribute mapping.

createMenuItem(ClassifyTab.HistoryPanel, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.CompareModels

Creates the menu item to add to the history's popup menu.

createMenuItem(ClassifyTab.HistoryPanel, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation

Creates the menu item to add to the history's popup menu.

createMenuItem(PerFoldMultiPagePane, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem

Creates the menu item to add to the pane's popup menu.

createMenuItem(PerFoldMultiPagePane, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.CopySetup

Creates the menu item to add to the pane's popup menu.

createMenuItem(PerFoldMultiPagePane, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation

Creates the menu item to add to the pane's popup menu.

createMenuItem(H, int[]) - Method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem

Creates the menu item to add to the history's popup menu.

createMetaLevelHeader(Instances) - Method in class weka.classifiers.meta.ClassifierCascade

Generates the dataset structure for the meta-levels.

createMetaLevelInstance(Instances, Instance) - Method in class weka.classifiers.meta.ClassifierCascade

Generates an instance for the meta-level using the original data.

createModel(InstanceContainerManager) - Method in class adams.gui.visualization.instance.InstanceContainerList

Creates a new model.

createName() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

Creates the name from the members.

createName() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

Creates the name from the members.

createName() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Creates the name from the members.

createName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Creates the name from the members.

createName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Creates the name from the members.

createName() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

Creates the name from the members.

createNext() - Method in class weka.classifiers.AbstractSplitGenerator

Creates the next result.

createNext() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Creates the next result.

createNext() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns the next element in the iteration.

createNext() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Creates the next result.

createNext() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns the next element in the iteration.

createNext() - Method in class weka.classifiers.DefaultRandomSplitGenerator

Creates the next result.

createNext() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the next element in the iteration.

createNext() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Creates the next result.

createNext() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the next element in the iteration.

createNext() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns the next element in the iteration.

createNext() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Creates the next result.

createNext() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Returns the next element in the iteration.

createNext() - Method in class weka.classifiers.MultiLevelSplitGenerator

Creates the next result.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.ModelOutput

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.Rules

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.RunInformation

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.ReducedData

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.RunInformation

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.AbstractOutputGeneratorWithSeparateFoldsSupport

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.GraphSource

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyGraphVisualizer

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyTreeVisualizer

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ModelOutput

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.RunInformation

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeVisualizer

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ClusterAssignments

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.GraphSource

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.LegacyTreeVisualizer

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ModelOutput

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.RunInformation

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.RunInformation

Generates output from the item.

createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Generates output from the item.

createOutput(T, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator

Generates output from the item.

createOutput(Evaluation, int[], SpreadSheet, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Generates a plot actor from the evaluation.

createOutput(Evaluation, int[], SpreadSheet, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Generates the output from the evaluation.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.AbstractOutputGeneratorWithSeparateFoldsSupport

Generates the table with the confusion matrix.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Generates the table with the confusion matrix.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Creates the 4-in-1 plot for the evaluation.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyClassifierErrors

Generates output from the evaluation.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis

Generates output from the evaluation.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve

Generates output from the evaluation.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyMarginCurve

Generates output from the evaluation.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Generates output from the evaluation.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Generates the output from the evaluation.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Generates the output for the evaluation.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsFitted

Generates output from the evaluation.

createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsPredictor

Generates the output from the evaluation.

createOutput(Evaluation, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Generates a panel from the results of the evaluation.

createOutputFormat(Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters

Generates the output format (additional attribute for cluster index).

createOutputFormat(Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterCounts

Generates the output format (additional attribute for cluster index).

createOutputFormat(Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterStatistics

Generates the output format (additional attribute for cluster index).

createParamsFromOptions() - Method in class weka.classifiers.trees.XGBoost

Converts the options into a parameter map as expected by XGBoost.

createPlot(InstancesTablePopupMenuItemHelper.TableState, boolean, TDoubleArrayList, String) - Method in class adams.gui.visualization.instances.instancestable.Binning

Generates the plot.

createPlot(InstancesTable, boolean, SpreadSheet, String, int[]) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Plots the data.

createPlot(InstancesTable, boolean, List<Double>[], String, String[]) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Generates the plot.

createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Generates the right-click menu for the JList.

createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Generates the right-click menu for the JList.

createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Generates the right-click menu for the JList.

createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane

Generates the right-click menu for the JList.

createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Generates the right-click menu for the JList.

createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Generates the right-click menu for the JList.

createPopupMenu() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu

Creates and returns the popup menu.

createPopupMenu() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Creates and returns the popup menu.

createPrefix(Instances, int) - Method in class adams.flow.transformer.WekaInstancesMerge

Generates the prefix for the dataset/index.

createPreview(File) - Method in class adams.gui.tools.previewbrowser.InstanceExplorerHandler

Creates the actual view.

createPreview(File) - Method in class adams.gui.tools.previewbrowser.WekaDatasetHandler

Creates the actual view.

createPreview(Object) - Method in class adams.gui.tools.previewbrowser.GraphSource

Creates the actual preview.

createPreview(Object) - Method in class adams.gui.tools.previewbrowser.GraphVisualizer

Creates the actual preview.

createPreview(Object) - Method in class adams.gui.tools.previewbrowser.InterQuartileRangeViewer

Creates the actual preview.

createPreview(Object) - Method in class adams.gui.tools.previewbrowser.TreeVisualizer

Creates the actual preview.

createRelationName(String, String, int, boolean) - Static method in class weka.classifiers.CrossValidationHelper

Generates a relation name for the current fold.

createRelationName(String, String, String, boolean) - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Generates a relation name for the current value.

createRow(int, String, Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterStatistics

Creates a new stats row.

createRow(Instance) - Method in class adams.flow.transformer.WekaInstanceDumper

Turns the row into the appropriate format.

createRunner(ExperimenterPanel) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO

Creates an experiment runner thread object.

createRunner(ExperimenterPanel) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultAdamsExperimentIO

Creates an experiment runner thread object.

createRunner(ExperimenterPanel) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultWekaExperimentIO

Creates an experiment runner thread object.

createRunner(ExperimenterPanel) - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO

Creates an experiment runner thread object.

createSubEvaluation(ClassifyTab.HistoryPanel, ResultItem, double[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation

Creates the sub-range evaluation and adds it to the history.

createSubEvaluation(PerFoldMultiPagePane, ResultItem, Evaluation, int, double[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation

Creates the sub-range evaluation and adds it to the pane.

createSubEvaluations(PerFoldMultiPagePane, ResultItem, Evaluation[], int[], double[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation

Creates the sub-range evaluation and adds it to the pane.

createToken(Object, Object) - Method in class adams.flow.transformer.WekaFilter

Creates a token with the data.

createTreeVisualizer(Token) - Method in class adams.flow.sink.WekaTreeVisualizer

Creates a tree visualizer from the token.

createViewTipText() - Method in interface adams.data.weka.InstancesViewCreator

Returns the tip text for this property.

createViewTipText() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the tip text for this property.

createViewTipText() - Method in class adams.flow.transformer.WekaRandomSplit

Returns the tip text for this property.

CROSS_VALIDATION - adams.flow.sink.WekaExperimentGenerator.EvaluationType

cross-validation.

crossValidate(Instances, int) - Method in class weka.filters.supervised.instance.RemoveOutliers

Cross-validates the classifier on the given data.

crossValidateModel(Classifier, Instances, int, Random, Object...) - Method in class weka.classifiers.evaluation.StoppableEvaluation

Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.

CrossValidation - Class in adams.gui.tools.wekainvestigator.tab.attseltab.evaluation

Performs cross-validation.

CrossValidation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation

Performs cross-validation.

CrossValidation - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation

Performs cross-validation.

CrossValidation() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

CrossValidation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

CrossValidation() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

CrossValidationExperiment - Class in adams.gui.tools.wekamultiexperimenter.experiment

Performs cross-validation.

CrossValidationExperiment() - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

CrossValidationExperiment.CrossValidationExperimentJob - Class in adams.gui.tools.wekamultiexperimenter.experiment

Performs cross-validation on the classifier/data combination.

CrossValidationExperimentJob(CrossValidationExperiment, int, Classifier, Instances) - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment.CrossValidationExperimentJob

Initializes the run.

CrossValidationFoldGenerator - Interface in weka.classifiers

Interface for generating cross-validation folds.

CrossValidationHelper - Class in weka.classifiers

Helper class for cross-validation.

CrossValidationHelper() - Constructor for class weka.classifiers.CrossValidationHelper

crossValidationIndices() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns the cross-validation indices.

crossValidationIndices() - Method in interface weka.classifiers.CrossValidationFoldGenerator

Returns the cross-validation indices.

crossValidationIndices() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns the cross-validation indices.

crossValidationIndices() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the cross-validation indices.

crossValidationIndices() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the cross-validation indices.

crossValidationIndices() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns the cross-validation indices.

crossValidationIndices(Instances, int, Random) - Static method in class weka.classifiers.CrossValidationHelper

Returns the indices from the original dataset for tracing the predictions back to the original dataset (stratified).

crossValidationIndices(Instances, int, Random, boolean) - Static method in class weka.classifiers.CrossValidationHelper

Returns the indices from the original dataset for tracing the predictions back to the original dataset.

crossValidationSeedTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

crossValidationSeedTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the tip text for this property.

CrossValidationSetup - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.setup

Setup for a cross-validation experiment.

CrossValidationSetup() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

CSV - adams.flow.sink.WekaExperimentGenerator.ResultFormat

CSV.

CSV - adams.flow.transformer.WekaInstanceDumper.OutputFormat

comma-separated.

CsvOutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka

Stores the results in a CSV file.

CsvOutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel

cTipText() - Method in class adams.data.instancesanalysis.pls.PRM

Returns the tip text for this property

CUSTOM_ADAMS_READER - Static variable in class adams.gui.menu.MakeCompatibleDatasets

CUSTOM_WEKA_FILE_LOADER - Static variable in class adams.gui.menu.MakeCompatibleDatasets

customize(AbstractContainerListPopupCustomizer.Context<Instance, InstanceContainerManager, InstanceContainer>, JPopupMenu) - Method in class adams.gui.visualization.instance.containerlistpopup.SaveAs

Returns a popup menu for the table of the container list.

customize(AbstractContainerListPopupCustomizer.Context<Instance, InstanceContainerManager, InstanceContainer>, JPopupMenu) - Method in class adams.gui.visualization.instance.containerlistpopup.ViewAsTable

Returns a popup menu for the table of the container list.

customize(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, MouseEvent, JPopupMenu) - Method in class adams.gui.visualization.instance.plotpopup.Adjust

Returns a popup menu for the table of the container list.

customize(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, MouseEvent, JPopupMenu) - Method in class adams.gui.visualization.instance.plotpopup.Histogram

Returns a popup menu for the table of the container list.

customize(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, MouseEvent, JPopupMenu) - Method in class adams.gui.visualization.instance.plotpopup.SaveVisible

Returns a popup menu for the table of the container list.

customize(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, MouseEvent, JPopupMenu) - Method in class adams.gui.visualization.instance.plotpopup.Viewport

Returns a popup menu for the table of the container list.

customLoaderTipText() - Method in class adams.flow.transformer.WekaFileReader

Returns the tip text for this property.

customLoaderTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the tip text for this property.

customLoaderTipText() - Method in class weka.filters.unsupervised.instance.AlignDataset

Returns the tip text for this property.

customLoaderTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the tip text for this property.

CustomOutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka

Allows the user to configure any ResultListener.

CustomOutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel

customPaintletTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

CustomPropertySheetPanel() - Constructor for class adams.gui.wizard.WekaPropertySheetPanelPage.CustomPropertySheetPanel

customPropsFileTipText() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the tip text for this property.

customPropsFileTipText() - Method in class adams.flow.source.WekaDatabaseReader

Returns the tip text for this property.

customSaverTipText() - Method in class adams.flow.sink.WekaFileWriter

Returns the tip text for this property.

customStopMessageTipText() - Method in class adams.flow.source.WekaSelectDataset

Returns the tip text for this property.

CYCLIC - weka.classifiers.trees.XGBoost.FeatureSelector

D

DarkLord - Class in adams.gui.menu

For optimizing datasets (attribute selection) using genetic algorithm.

DarkLord - Class in adams.opt.genetic

DarkLord() - Constructor for class adams.gui.menu.DarkLord

Initializes the menu item with no owner.

DarkLord() - Constructor for class adams.opt.genetic.DarkLord

DarkLord(AbstractApplicationFrame) - Constructor for class adams.gui.menu.DarkLord

Initializes the menu item.

DarkLord.DarkLordJob - Class in adams.opt.genetic

A job class specific to The Dark Lord.

DarkLordJob(DarkLord, int, int[], Instances, Instances) - Constructor for class adams.opt.genetic.DarkLord.DarkLordJob

Initializes the job.

DART - weka.classifiers.trees.XGBoost.BoosterType

DATA - adams.opt.genetic.OutputType

only the data.

Database - Class in adams.gui.tools.wekainvestigator.source

For loading data from a database.

Database() - Constructor for class adams.gui.tools.wekainvestigator.source.Database

Instantiates the action.

DatabaseContainer - Class in adams.gui.tools.wekainvestigator.data

Dataset loaded from database.

DatabaseContainer(String, String, String, String) - Constructor for class adams.gui.tools.wekainvestigator.data.DatabaseContainer

Loads the data using the specified url/query.

DataCellView - Class in adams.ml.data

Wrapper for single cell values in a Instance object.

DataCellView(InstanceView, int) - Constructor for class adams.ml.data.DataCellView

Initializes the cell.

dataChanged(DataChangeEvent) - Method in class adams.gui.visualization.instance.InstanceExplorer

Gets called if the data of the instance panel has changed.

dataChanged(WekaInvestigatorDataEvent) - Method in interface adams.gui.event.WekaInvestigatorDataListener

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.DataTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.LogTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Notifies the tab that the data changed.

dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

Notifies the tab that the data changed.

DataContainer - Interface in adams.gui.tools.wekainvestigator.data

Interface for data containers.

DataContainerList - Class in adams.gui.tools.wekainvestigator.data

For managing the data containers.

DataContainerList() - Constructor for class adams.gui.tools.wekainvestigator.data.DataContainerList

DataGenerator - Class in adams.gui.tools.wekainvestigator.source

For generating data using a data generator.

DataGenerator() - Constructor for class adams.gui.tools.wekainvestigator.source.DataGenerator

Instantiates the action.

DataGenerator(Evaluation, AbstractErrorScaler) - Constructor for class adams.flow.sink.WekaClassifierErrors.DataGenerator

Initializes the generator.

DataGeneratorContainer - Class in adams.gui.tools.wekainvestigator.data

Dataset generated by datagenerator.

DataGeneratorContainer(DataGenerator) - Constructor for class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer

Loads the data using the specified loader.

dataGeneratorTipText() - Method in class adams.flow.source.WekaDataGenerator

Returns the tip text for this property.

DataInfo(String, int, double, double) - Constructor for class adams.opt.optimise.genetic.PackDataDef.DataInfo

DataQueryTab - Class in adams.gui.tools.wekainvestigator.tab

Allows the execution of an SQL-like query to manipulate datasets.

DataQueryTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.DataQueryTab

dataRowTypeTipText() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet

Returns the tip text for this property.

dataset - Variable in class weka.classifiers.lazy.LWLDatasetBuilder.LWLContainer

the weighted dataset.

dataset() - Method in class weka.core.AbstractHashableInstance

Returns the dataset this instance has access to.

DATASET - adams.flow.transformer.WekaFileReader.OutputType

the complete dataset.

DATASET_KEYWORD - Static variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

The keyword to replace with the dataset name in attribute renaming.

DATASET_NAME - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator

DATASET_NUMATTRIBUTES - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator

DATASET_NUMINSTANCES - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator

dataset1TipText() - Method in class adams.tools.CompareDatasets

Returns the tip text for this property.

dataset2TipText() - Method in class adams.tools.CompareDatasets

Returns the tip text for this property.

DatasetCleaner - Class in weka.filters.unsupervised.attribute

Removes all columns from the data data that have been indentified.

DatasetCleaner - Class in weka.filters.unsupervised.instance

Removes all rows from the data data that have been indentified.

DatasetCleaner() - Constructor for class weka.filters.unsupervised.attribute.DatasetCleaner

DatasetCleaner() - Constructor for class weka.filters.unsupervised.instance.DatasetCleaner

DatasetCompatibility - Class in adams.gui.menu

For checking compatibility of datasets.

DatasetCompatibility() - Constructor for class adams.gui.menu.DatasetCompatibility

Initializes the menu item with no owner.

DatasetCompatibility(AbstractApplicationFrame) - Constructor for class adams.gui.menu.DatasetCompatibility

Initializes the menu item.

DatasetCompatibilityPanel - Class in adams.gui.tools

Compares the headers of a number of datasets and outputs the results.

DatasetCompatibilityPanel() - Constructor for class adams.gui.tools.DatasetCompatibilityPanel

DatasetFileChooserPanel - Class in adams.gui.chooser

A panel that contains a text field with the current file and a button for bringing up a ConverterFileChooser.

DatasetFileChooserPanel() - Constructor for class adams.gui.chooser.DatasetFileChooserPanel

Initializes the panel with no file.

DatasetFileChooserPanel(File) - Constructor for class adams.gui.chooser.DatasetFileChooserPanel

Initializes the panel with the given filename/directory.

DatasetFileChooserPanel(String) - Constructor for class adams.gui.chooser.DatasetFileChooserPanel

Initializes the panel with the given filename/directory.

datasetForSingleInstance(Instance) - Method in class adams.flow.transformer.WekaDatasetsMerge

Creates an Instances dataset, containing a copy of the single instance provided.

DatasetHelper - Class in adams.gui.tools.wekainvestigator.evaluation

Helper class for dealing with datasets.

DatasetHelper() - Constructor for class adams.gui.tools.wekainvestigator.evaluation.DatasetHelper

datasetIndex - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute

The index of the source dataset.

DatasetIndexer() - Constructor for class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Initializes the indexer.

DatasetLabeler - Class in weka.filters.unsupervised.instance

Adds an additional attribute to the dataset containing a label whether it was a match or not, i.e., whether the row finder selected a particular row or not.

DatasetLabeler() - Constructor for class weka.filters.unsupervised.instance.DatasetLabeler

datasetNamesTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the tip-text for the dataset names option.

DatasetPanel - Class in adams.gui.tools.wekamultiexperimenter.setup

Panel for listing datasets.

DatasetPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

DatasetPanel(String, String) - Constructor for class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Initializes the panel.

DATASETS - adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption

datasetsTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the tip text for this property.

datasetTipText() - Method in class adams.flow.transformer.WekaStoreInstance

Returns the tip text for this property.

datasetTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the tip text for this property.

DataSort - Class in adams.gui.visualization.instances.instancestable

Allows sorting the data using multiple columns.

DataSort() - Constructor for class adams.gui.visualization.instances.instancestable.DataSort

DataTab - Class in adams.gui.tools.wekainvestigator.tab

Lists the currently loaded datasets.

DataTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.DataTab

DataTable - Class in adams.gui.tools.wekainvestigator.datatable

Specialized table with custom cell editors for the class.

DataTable(DataTableModel) - Constructor for class adams.gui.tools.wekainvestigator.datatable.DataTable

Constructs a DataTable that is initialized with dm as the data model, a default column model, and a default selection model.

DataTableModel - Class in adams.gui.tools.wekainvestigator.datatable

Model for displaying the loaded data.

DataTableModel(List<DataContainer>, boolean) - Constructor for class adams.gui.tools.wekainvestigator.datatable.DataTableModel

Initializes the model.

dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Gets called when the user changes the selection.

dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

Gets called when the user changes the selection.

dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab

Gets called when the user changes the selection.

dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Gets called when the user changes the selection.

dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.DataTab

Gets called when the user changes the selection.

dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab

Gets called when the user changes the selection.

dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Gets called when the user changes the selection.

dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

Gets called when the user changes the selection.

DataTableWithButtons - Class in adams.gui.tools.wekainvestigator.datatable

Specialized table with buttons.

DataTableWithButtons(DataTableModel) - Constructor for class adams.gui.tools.wekainvestigator.datatable.DataTableWithButtons

Constructs a DataTableWithButtons that is initialized with dm as the data model, a default column model, and a default selection model.

dataTypeTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the tip text for this property.

dataTypeTipText() - Method in class adams.flow.transformer.WekaInstancesStatistic

Returns the tip text for this property.

DATE_ATTRIBUTES - adams.flow.core.Capability

can handle date attributes.

DATE_CLASS - adams.flow.core.Capability

can handle date classes.

DEBUG - weka.classifiers.trees.XGBoost.Verbosity

DEBUG - Static variable in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

debugMsg(String) - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

Outputs a debugging message on stderr.

debugMsg(String) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Outputs a debugging message on stderr.

debugTipText() - Method in class weka.core.converters.SpreadSheetLoader

the tip text for this property

debugTipText() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

Returns the tip text for this property.

deepCopy(Object, boolean) - Method in class adams.core.classmanager.WekaClassManager

Creates a deep copy of the given object (must be serializable!).

DEFAULT - weka.classifiers.trees.XGBoost.Predictor

DEFAULT - weka.classifiers.trees.XGBoost.ProcessType

DEFAULT_AMOUNT - Static variable in class weka.filters.unsupervised.instance.LatestRecords

the default number of records to keep.

DEFAULT_ATT_RANGE - Static variable in class weka.filters.unsupervised.instance.KennardStone

DEFAULT_ATTNAME - Static variable in class weka.filters.unsupervised.instance.LatestRecords

the default attribute name.

DEFAULT_CLASS - Static variable in class adams.flow.source.WekaNewInstances

the class attribute name (if not specified explicitly).

DEFAULT_CLASS_INDEX - Static variable in class weka.classifiers.meta.ClassifierCascade

DEFAULT_COMBINATION - Static variable in class weka.classifiers.meta.ClassifierCascade

DEFAULT_DATE_FORMAT - Static variable in class adams.flow.source.WekaNewInstances

the default date format.

DEFAULT_FORMAT - Static variable in class weka.filters.unsupervised.attribute.StringToDate

DEFAULT_GROUP - Static variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

DEFAULT_HOLDOUT_PERCENTAGE - Static variable in class weka.classifiers.meta.ClassifierCascade

DEFAULT_MAX_CLASS_RANGE_PERCENTAGE - Static variable in class weka.classifiers.meta.MinMaxLimits

the default class range percentage for the lower limit.

DEFAULT_MAX_DECIMAL_PLACES - Static variable in class weka.core.converters.SimpleArffSaver

the default number of decimal places.

DEFAULT_MAX_HANDLING - Static variable in class weka.classifiers.meta.MinMaxLimits

the default handling of the lower limit.

DEFAULT_MAX_LEVELS - Static variable in class weka.classifiers.meta.ClassifierCascade

DEFAULT_MAX_MANUAL - Static variable in class weka.classifiers.meta.MinMaxLimits

the default manual limit of the lower limit.

DEFAULT_MIN_CLASS_RANGE_PERCENTAGE - Static variable in class weka.classifiers.meta.MinMaxLimits

the default class range percentage for the lower limit.

DEFAULT_MIN_HANDLING - Static variable in class weka.classifiers.meta.MinMaxLimits

the default handling of the lower limit.

DEFAULT_MIN_IMPROVEMENT - Static variable in class weka.classifiers.meta.ClassifierCascade

DEFAULT_MIN_MANUAL - Static variable in class weka.classifiers.meta.MinMaxLimits

the default manual limit of the lower limit.

DEFAULT_NAME - Static variable in class weka.filters.unsupervised.instance.DatasetLabeler

the default name of the attribute.

DEFAULT_NAME - Static variable in class weka.gui.explorer.MultiExplorer

the default name for new panels.

DEFAULT_NAME_FIRST - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

the default first attribute name.

DEFAULT_NAME_SECOND - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

the default second attribute name.

DEFAULT_NUM_FOLDS - Static variable in class weka.classifiers.meta.ClassifierCascade

DEFAULT_NUM_THREADS - Static variable in class weka.classifiers.meta.ClassifierCascade

DEFAULT_NUMBER_IN_SUBSET - Static variable in class weka.filters.unsupervised.instance.KennardStone

DEFAULT_PRE_FILTER - Static variable in class weka.filters.unsupervised.instance.KennardStone

DEFAULT_PREFIX - Static variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis

DEFAULT_REGEXP - Static variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis

DEFAULT_REMOVE_CHARS - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

characters to remove from start/end of the merged name.

DEFAULT_REMOVE_CHARS - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

characters to remove from start/end of the merged name.

DEFAULT_STATISTIC - Static variable in class weka.classifiers.meta.ClassifierCascade

DEFAULT_THRESHOLD - Static variable in class weka.classifiers.meta.ClassifierCascade

DEFAULT_THRESHOLD_CHECK - Static variable in class weka.classifiers.meta.ClassifierCascade

DefaultAdamsExperimentIO - Class in adams.gui.tools.wekamultiexperimenter.io

Default IO handler for experiments.

DefaultAdamsExperimentIO() - Constructor for class adams.gui.tools.wekamultiexperimenter.io.DefaultAdamsExperimentIO

DefaultAnalysisPanel - Class in adams.gui.tools.wekamultiexperimenter.analysis

Default panel for analyzing results from experiments.

DefaultAnalysisPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

DefaultAnalysisPanel.HistoryPanel - Class in adams.gui.tools.wekamultiexperimenter.analysis

Customized history panel.

defaultClassifierOptions() - Method in class weka.classifiers.meta.HighLowSplit

String describing options for default classifier.

defaultClassifierOptions() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

String describing options for default classifier.

defaultClassifierString() - Method in class weka.classifiers.lazy.LWLSynchro

Default classifier classname.

defaultClassifierString() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

Default classifier classname.

defaultClassifierString() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Default classifier classname.

defaultClassifierString() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

String describing default classifier.

defaultClassifierString() - Method in class weka.classifiers.meta.ClassificationViaRegressionD

String describing default classifier.

defaultClassifierString() - Method in class weka.classifiers.meta.Corr

String describing default classifier.

defaultClassifierString() - Method in class weka.classifiers.meta.HighLowSplit

String describing default classifier.

defaultClassifierString() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

String describing default classifier.

defaultColorTipText() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Returns the tip text for this property.

DefaultCrossValidationFoldGenerator - Class in weka.classifiers

Helper class for generating cross-validation folds.

DefaultCrossValidationFoldGenerator() - Constructor for class weka.classifiers.DefaultCrossValidationFoldGenerator

Initializes the generator.

DefaultCrossValidationFoldGenerator(Instances, int, long, boolean) - Constructor for class weka.classifiers.DefaultCrossValidationFoldGenerator

Initializes the generator.

DefaultCrossValidationFoldGenerator(Instances, int, long, boolean, boolean, String) - Constructor for class weka.classifiers.DefaultCrossValidationFoldGenerator

Initializes the generator.

DefaultHandler - Class in weka.gui.explorer

Dummy handler, in case no other handler was located for an explorer panel.

DefaultHandler() - Constructor for class weka.gui.explorer.DefaultHandler

DefaultRandomSplitGenerator - Class in weka.classifiers

Generates random splits of datasets.

DefaultRandomSplitGenerator() - Constructor for class weka.classifiers.DefaultRandomSplitGenerator

Initializes the generator.

DefaultRandomSplitGenerator(Instances, double) - Constructor for class weka.classifiers.DefaultRandomSplitGenerator

Initializes the generator.

DefaultRandomSplitGenerator(Instances, long, double) - Constructor for class weka.classifiers.DefaultRandomSplitGenerator

Initializes the generator.

DefaultRandomSplitGenerator(Instances, long, double, boolean) - Constructor for class weka.classifiers.DefaultRandomSplitGenerator

Initializes the generator.

DefaultWekaExperimentIO - Class in adams.gui.tools.wekamultiexperimenter.io

Default IO handler for experiments.

DefaultWekaExperimentIO() - Constructor for class adams.gui.tools.wekamultiexperimenter.io.DefaultWekaExperimentIO

DefaultWekaExperimentRunner - Class in adams.gui.tools.wekamultiexperimenter.runner

A class that handles running a copy of the experiment in a separate thread.

DefaultWekaExperimentRunner(ExperimenterPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.runner.DefaultWekaExperimentRunner

Initializes the thread.

defineOptions() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Adds options to the internal list of options.

defineOptions() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Adds options to the internal list of options.

defineOptions() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Adds options to the internal list of options.

defineOptions() - Method in class adams.core.discovery.genetic.GenericInteger

Adds options to the internal list of options.

defineOptions() - Method in class adams.core.discovery.genetic.GenericString

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.baseline.AbstractLinearRegressionBased

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.MapToWekaInstance

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.ReportToWekaInstance

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.SpreadSheetToWekaInstances

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.SwapPLS

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.WekaCapabilitiesToInstances

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.WekaCommandToCode

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.WekaEvaluationToCostCurve

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instances.AbstractInstanceGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.FastICA

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.PCA

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.PLS

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.pls.DIPLS

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.pls.NIPALS

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.pls.OPLS

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.pls.PRM

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.pls.SIMPLS

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.instancesanalysis.pls.VCPLS

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.io.input.NestedAdamsExperimentReader

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.spreadsheet.filter.WekaFilter

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.classattribute.AttributeIndex

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.classattribute.ByExactName

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.classattribute.ByName

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.columnfinder.AbstractFilteredColumnFinder

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.columnfinder.ByExactName

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.columnfinder.ByName

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.columnfinder.Constant

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.columnfinder.MultiColumnFinder

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.datasetsplitter.ColumnSplitter

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.datasetsplitter.RowSplitter

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.predictions.AutoScaler

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.predictions.FixedSizeErrorScaler

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.relationname.AttributeIndex

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.rowfinder.AbstractFilteredRowFinder

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.rowfinder.ByLabel

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.rowfinder.ByNumericRange

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.rowfinder.ByNumericValue

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.rowfinder.Constant

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.rowfinder.FilteredIQR

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.weka.rowfinder.MultiRowFinder

Adds options to the internal list of options.

defineOptions() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.condition.bool.WekaClassification

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.sink.WekaAttributeSummary

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.sink.WekaClassifierErrors

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.sink.WekaCostCurve

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.sink.WekaDatabaseWriter

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.sink.WekaExperimentFileWriter

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.sink.WekaExperimentGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.sink.WekaFileWriter

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.sink.WekaInstancesPlot

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.sink.WekaInstanceViewer

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.sink.WekaThresholdCurve

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.source.WekaAssociatorSetup

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.source.WekaClassifierSetup

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.source.WekaClustererSetup

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.source.WekaDatabaseReader

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.source.WekaDataGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.source.WekaNewExperiment

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.source.WekaNewInstances

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.source.WekaPackageManagerAction

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.source.WekaSelectDataset

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.standalone.WekaPackageManagerAction

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.template.InstanceDumperVariable

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.AbstractInstanceGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.AbstractWekaModelReader

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaAccumulatedError

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaAttributeIterator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaAttributeSelection

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaBootstrapping

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaChooseAttributes

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaClassifierInfo

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaClassifierOptimizer

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaClassifierRanker

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaClassifying

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaClassSelector

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaclusterer.AddCluster

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaClustererInfo

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaClustererPostProcessor

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaDatasetsMerge

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaDatasetSplit

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaEnsembleGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaEvaluationInfo

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaEvaluationSummary

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaEvaluationValues

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaExperiment

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaExperimentExecution

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaExperimentFileReader

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaExtractArray

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaExtractPLSMatrix

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaFileReader

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaFilter

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaGetInstancesValue

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaGetInstanceValue

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaInstanceBuffer

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaInstanceDumper

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaInstancesInfo

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaInstancesMerge

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaInstancesStatistic

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaModelReader

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaNewInstance

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaPackageManagerAction

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaPrincipalComponents

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaRandomSplit

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaRegexToRange

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaRenameRelation

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaSetInstancesValue

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaSetInstanceValue

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaSplitGenerator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaStoreInstance

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaStreamEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaStreamFilter

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaSubsets

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaTextDirectoryReader

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaTrainAssociator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaTrainClassifier

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaTrainClusterer

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.InstanceCompare

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

Adds options to the internal list of options.

defineOptions() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

Adds options to the internal list of options.

defineOptions() - Method in class adams.ml.model.classification.WekaClassifier

Adds options to the internal list of options.

defineOptions() - Method in class adams.ml.model.clustering.WekaClusterer

Adds options to the internal list of options.

defineOptions() - Method in class adams.ml.model.regression.WekaRegressor

Adds options to the internal list of options.

defineOptions() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Adds options to the internal list of options.

defineOptions() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Adds options to the internal list of options.

defineOptions() - Method in class adams.opt.genetic.Hermione

Adds options to the internal list of options.

defineOptions() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Adds options to the internal list of options.

defineOptions() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Adds options to the internal list of options.

defineOptions() - Method in class adams.opt.optimise.GeneticAlgorithm

Adds options to the internal list of options.

defineOptions() - Method in class adams.tools.CompareDatasets

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.AbstractSplitGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.DefaultRandomSplitGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.functions.FromPredictions

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.functions.PyroProxy

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.MultiLevelSplitGenerator

Adds options to the internal list of options.

defineOptions() - Method in class weka.classifiers.trees.XGBoost

Adds options to the internal list of options.

defineOptions() - Method in class weka.filters.unsupervised.attribute.detrend.RangeBased

Adds options to the internal list of options.

defineOptions() - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased

Adds options to the internal list of options.

deflationModeTipText() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns the tip text for this property

delete() - Method in class weka.core.InstancesView

Removes all instances from the set.

delete(int) - Method in class weka.core.InstancesView

Removes an instance at the given position from the set.

deleteAttributeAt(int) - Method in class adams.gui.visualization.instances.InstancesTableModel

deletes the attribute at the given col index.

deleteAttributeAt(int) - Method in class weka.core.AbstractHashableInstance

Deletes an attribute at the given position (0 to numAttributes() - 1).

deleteAttributeAt(int) - Method in class weka.core.InstancesView

Deletes an attribute at the given position (0 to numAttributes() - 1).

deleteAttributeAt(int, boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel

deletes the attribute at the given col index

deleteAttributes(int[]) - Method in class adams.gui.visualization.instances.InstancesTableModel

deletes the attributes at the given indices

deleteAttributeType(int) - Method in class weka.core.InstancesView

Deletes all attributes of the given type in the dataset.

deleteInstanceAt(int) - Method in class adams.gui.visualization.instances.InstancesTableModel

deletes the instance at the given index

deleteInstanceAt(int, boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel

deletes the instance at the given index

deleteInstances(int[]) - Method in class adams.gui.visualization.instances.InstancesTableModel

deletes the instances at the given positions

deleteWithMissing(int) - Method in class weka.core.InstancesView

Removes all instances with missing values for a particular attribute from the dataset.

DEPTHWISE - weka.classifiers.trees.XGBoost.GrowPolicy

derivativeOrderTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns the tip text for this property.

derivativeOrderTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns the tip text for this property.

DESCENDING - adams.data.conversion.WekaPredictionContainerToSpreadSheet.Sorting

descending.

deselectColinearAttributes(boolean[], double[]) - Method in class weka.classifiers.functions.LinearRegressionJ

Removes the attribute with the highest standardised coefficient greater than 1.5 from the selected attributes.

deserialize(InvestigatorPanel, Object, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper

Deserializes the data and configures the panel.

deserialize(ObjectInputStream) - Static method in class weka.gui.explorer.WorkspaceHelper

Deserializes an explorer instance from the input stream.

deserialize(Object, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Deserializes the data and configures the tab.

deserialize(Object, GenericObjectEditor) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Deserializes the data and configures the GenericObjectEditor with it.

deserialize(Object, ResultHistoryPanel) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Deserializes the data and configures the ResultHistoryPanel with it.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Restores the objects.

deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Restores the objects.

deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Deserializes the data and configures the panel.

deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.AssociationsHandler

Deserializes the data and configures the panel.

deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.AttributeSelectionHandler

Deserializes the data and configures the panel.

deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.ClassifierHandler

Deserializes the data and configures the panel.

deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.ClustererHandler

Deserializes the data and configures the panel.

deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.DefaultHandler

Deserializes the data and configures the panel.

deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.ExperimentHandler

Deserializes the data and configures the panel.

deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.PreprocessHandler

Deserializes the data and configures the panel.

DESERIALIZED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent

the data got deserialized.

deserializeFile(MessageCollection) - Method in class adams.flow.core.WekaClassifierModelLoader

Deserializes the model file.

deserializeFile(MessageCollection) - Method in class adams.flow.core.WekaClustererModelLoader

Deserializes the model file.

destroy() - Method in class adams.data.instances.AbstractInstanceGenerator

Frees up memory in a "destructive" non-reversible way.

destroy() - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Frees up memory in a "destructive" non-reversible way.

DETECTOR - Static variable in class weka.filters.supervised.instance.RemoveOutliers

detectorTipText() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the tip text for this property.

determineAttributeName(Instances) - Method in class adams.flow.transformer.WekaInstanceEvaluator

Determines the name of the evaluation attribute.

determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.AbstractClassAttributeHeuristic

Determines the class attribute index for the given dataset.

determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.AttributeIndex

Determines the class attribute index for the given dataset.

determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.ByExactName

Determines the class attribute index for the given dataset.

determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.ByName

Determines the class attribute index for the given dataset.

determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.LastAttribute

Determines the class attribute index for the given dataset.

determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.NoClassAttribute

Determines the class attribute index for the given dataset.

determineColumnNames(BaseString[], String) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns a vector with column names of the dataset, listed in "list".

determineOutputFormat(Instances) - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class adams.data.instancesanalysis.pls.OPLS

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.FilteredFilter

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.FlowFilter

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.SerializedFilter

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.supervised.attribute.MultiPLS

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.supervised.attribute.PLS

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.supervised.attribute.PLSFilterExtended

Override original, in order to put more than one class attribute to the output format.

determineOutputFormat(Instances) - Method in class weka.filters.supervised.attribute.YGradientEPO

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.supervised.attribute.YGradientGLSW

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.supervised.instance.RemoveOutliers

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AnyToString

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.DatasetCleaner

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Detrend

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.DownSample

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.EquiDistance

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.FastWavelet

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.FFT

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.InputSmearing

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.LogTransform

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PAA

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Determines the output format based only on the full input dataset and returns this otherwise null is returned.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RowSum

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SAX

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SetMissingValue

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SpellChecker

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.StringToDate

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.AlignDataset

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.DatasetCleaner

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.KeepRange

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.KennardStone

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.LatestRecords

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RowNorm

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.Scale

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.Sort

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.SortOnAttribute

Determines the output format based on the input format and returns this.

determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Determines the output format based on the input format and returns this.

determineRelationName(File, Instances) - Method in class adams.data.weka.relationname.AbstractRelationNameHeuristic

Determines the relation name for the given file/dataset pair.

determineRelationName(File, Instances) - Method in class adams.data.weka.relationname.AttributeIndex

Determines the relation name for the given file/dataset pair.

determineRelationName(File, Instances) - Method in class adams.data.weka.relationname.ClassAttribute

Determines the relation name for the given file/dataset pair.

determineRelationName(File, Instances) - Method in class adams.data.weka.relationname.FileName

Determines the relation name for the given file/dataset pair.

determineRelationName(File, Instances) - Method in class adams.data.weka.relationname.NoChange

Determines the relation name for the given file/dataset pair.

determineUnusedIndices(Instances) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

determines the indices of unused attributes (ones that are not covered by any of the range).

Detrend - Class in weka.filters.unsupervised.attribute

Performs Detrend, using the specified correction scheme.

Detrend() - Constructor for class weka.filters.unsupervised.attribute.Detrend

devTipText() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Returns the tip text for this property.

Dialog(Dialog, Dialog.ModalityType) - Constructor for class adams.gui.visualization.instance.HistogramFactory.Dialog

Initializes the dialog.

Dialog(Frame, boolean) - Constructor for class adams.gui.visualization.instance.HistogramFactory.Dialog

Initializes the dialog.

diameterTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

Dice - Class in weka.classifiers.evaluation

Sørensen–Dice coefficient: https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient

Dice() - Constructor for class weka.classifiers.evaluation.Dice

difference(int, double, double) - Method in class weka.core.SAXDistance

Computes the difference between two given attribute values.

difference(int, double, double) - Method in class weka.core.WeightedEuclideanDistance

Computes the difference between two given attribute values.

difference(int, double, double) - Method in class weka.core.WeightedEuclideanDistanceRidge

Computes the difference between two given attribute values.

differTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Returns the tip text for this property.

differTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Returns the tip text for this property.

diffToString() - Method in class weka.classifiers.meta.AbstainAverage

Convert thresholds from array to string

diffToString() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Convert thresholds from array to string

diffToString() - Method in class weka.classifiers.meta.AbstainVote

DIPLS - Class in adams.data.instancesanalysis.pls

DIPLS() - Constructor for class adams.data.instancesanalysis.pls.DIPLS

disableButtons(Container) - Method in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog

Disables the buttons in the SimpleSetupPanel.

disambiguateTitle(String) - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane

Disambiguates the title, appending " (X)" to it.

discardPredictions(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Discards the predictions in the results to save memory.

discardPredictionsTipText() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

Returns the tip text for this property.

discardPredictionsTipText() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns the tip text for this property.

discardPredictionsTipText() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Returns the tip text for this property.

display() - Method in class adams.gui.tools.weka.CostCurvePanel

Loads/displays the data.

display(Token) - Method in class adams.flow.sink.WekaAttributeSummary

Displays the token (the panel and dialog have already been created at this stage).

display(Token) - Method in class adams.flow.sink.WekaClassifierErrors

ClassifierErrorss the token (the panel and dialog have already been created at this stage).

display(Token) - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Plots the token (the panel and dialog have already been created at this stage).

display(Token) - Method in class adams.flow.sink.WekaCostCurve

Plots the token (the panel and dialog have already been created at this stage).

display(Token) - Method in class adams.flow.sink.WekaGraphVisualizer

Displays the token (the panel and dialog have already been created at this stage).

display(Token) - Method in class adams.flow.sink.WekaInstancesDisplay

Displays the token (the panel and dialog have already been created at this stage).

display(Token) - Method in class adams.flow.sink.WekaInstancesPlot

Plots the token (the panel and dialog have already been created at this stage).

display(Token) - Method in class adams.flow.sink.WekaInstanceViewer

Displays the token (the panel and dialog have already been created at this stage).

display(Token) - Method in class adams.flow.sink.WekaMarginCurve

Plots the token (the panel and dialog have already been created at this stage).

display(Token) - Method in class adams.flow.sink.WekaThresholdCurve

Plots the token (the panel and dialog have already been created at this stage).

display(Token) - Method in class adams.flow.sink.WekaTreeVisualizer

Displays the token (the panel and dialog have already been created at this stage).

display(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, List<InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Viewport

Displays the IDs etc of the instances.

display(ResultMatrix) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel

Displays the results.

displayData() - Method in class adams.gui.tools.wekainvestigator.tab.DataTab

Displays the data.

displayData() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Displays the data.

displayData() - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

Displays the data.

displayDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Displays the dataset in a separate window.

displayPanelRequiresScrollPane() - Method in class adams.flow.sink.WekaAttributeSummary

Returns whether the created display panel requires a scroll pane or not.

displayPanelRequiresScrollPane() - Method in class adams.flow.sink.WekaClassifierErrors

Returns whether the created display panel requires a scroll pane or not.

displayPanelRequiresScrollPane() - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Returns whether the created display panel requires a scroll pane or not.

displayPanelRequiresScrollPane() - Method in class adams.flow.sink.WekaCostCurve

Returns whether the created display panel requires a scroll pane or not.

displayPanelRequiresScrollPane() - Method in class adams.flow.sink.WekaGraphVisualizer

Returns whether the created display panel requires a scroll pane or not.

displayPanelRequiresScrollPane() - Method in class adams.flow.sink.WekaInstancesDisplay

Returns whether the created display panel requires a scroll pane or not.

displayPanelRequiresScrollPane() - Method in class adams.flow.sink.WekaInstancesPlot

Returns whether the created display panel requires a scroll pane or not.

displayPanelRequiresScrollPane() - Method in class adams.flow.sink.WekaInstanceViewer

Returns whether the created display panel requires a scroll pane or not.

displayPanelRequiresScrollPane() - Method in class adams.flow.sink.WekaMarginCurve

Returns whether the created display panel requires a scroll pane or not.

displayPanelRequiresScrollPane() - Method in class adams.flow.sink.WekaThresholdCurve

Returns whether the created display panel requires a scroll pane or not.

displayPanelRequiresScrollPane() - Method in class adams.flow.sink.WekaTreeVisualizer

Returns whether the created display panel requires a scroll pane or not.

displayStdDevsTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

distance(Instance, Instance) - Method in class weka.core.SAXDistance

Calculates the distance between two instances.

distance(Instance, Instance) - Method in class weka.core.WeightedEuclideanDistance

Calculates the distance between two instances.

distance(Instance, Instance) - Method in class weka.core.WeightedEuclideanDistanceRidge

Calculates the distance between two instances.

distance(Instance, Instance, double, PerformanceStats) - Method in class weka.core.WeightedEuclideanDistance

distance(Instance, Instance, double, PerformanceStats) - Method in class weka.core.WeightedEuclideanDistanceRidge

distance(Instance, Instance, PerformanceStats) - Method in class weka.core.SAXDistance

Calculates the distance (or similarity) between two instances.

distance(Instance, Instance, PerformanceStats) - Method in class weka.core.WeightedEuclideanDistance

Calculates the distance (or similarity) between two instances.

distance(Instance, Instance, PerformanceStats) - Method in class weka.core.WeightedEuclideanDistanceRidge

Calculates the distance (or similarity) between two instances.

distanceFunctionTipText() - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient

Returns the tip text for this property.

distanceFunctionTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

distances - Variable in class weka.classifiers.lazy.LWLDatasetBuilder.LWLContainer

the distances.

distribution(Row) - Method in class adams.ml.model.classification.WekaClassificationModel

Returns the class distribution for the given row.

distribution(Row) - Method in class adams.ml.model.clustering.WekaClusteringModel

Returns the cluster distribution for the given row.

distributionForInstance(Instance) - Method in class weka.classifiers.functions.ClassificationViaPLS

Predicts the class memberships for a given instance.

distributionForInstance(Instance) - Method in class weka.classifiers.functions.GeneticAlgorithm

Predicts the class memberships for a given instance.

distributionForInstance(Instance) - Method in class weka.classifiers.functions.PyroProxy

Classifies the given test instance.

distributionForInstance(Instance) - Method in class weka.classifiers.lazy.LWLSynchro

Calculates the class membership probabilities for the given test instance.

distributionForInstance(Instance) - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

Calculates the class membership probabilities for the given test instance.

distributionForInstance(Instance) - Method in class weka.classifiers.lazy.LWLSynchroSplit

Calculates the class membership probabilities for the given test instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.AbstainingCascade

Predicts the class memberships for a given instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Returns the class distribution for an instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.AbstainMinimumProbability

Returns the class distribution for an instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.AbstainVote

Classifies a given instance using the selected combination rule.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.ClassificationViaRegressionD

Returns the distribution for an instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.ClassifierCascade

Returns the distribution for the instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.Consensus

Predicts the class memberships for a given instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.ConsensusOrVote

Predicts the class memberships for a given instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.Fallback

Predicts the class memberships for a given instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.FilteredClassifierExt

Classifies a given instance after filtering.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.RangeCheck

Classifies a given instance after filtering.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.SocketFacade

Generates a class distribution for the instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.SubsetEnsemble

Predicts the class memberships for a given instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.SuppressModelOutput

Returns the class distribution for the given instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper

Returns the class distribution for an instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns the class distribution for the instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.VotedImbalance

Predicts the class memberships for a given instance.

distributionForInstance(Instance) - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper

Predicts the class memberships for a given instance.

distributionForInstance(Instance) - Method in class weka.classifiers.simple.AbstractSimpleClassifier

Predicts the class memberships for a given instance.

distributionForInstanceAverage(Instance) - Method in class weka.classifiers.meta.AbstainVote

Classifies a given instance using the Average of Probabilities combination rule.

distributionForInstanceMajorityVoting(Instance) - Method in class weka.classifiers.meta.AbstainVote

Classifies a given instance using the Majority Voting combination rule.

distributionForInstanceMax(Instance) - Method in class weka.classifiers.meta.AbstainVote

Classifies a given instance using the Maximum Probability combination rule.

distributionForInstanceMin(Instance) - Method in class weka.classifiers.meta.AbstainVote

Classifies a given instance using the Minimum Probability combination rule.

distributionForInstanceProduct(Instance) - Method in class weka.classifiers.meta.AbstainVote

Classifies a given instance using the Product of Probabilities combination rule.

distributionFormatTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the tip text for this property.

distributionsForInstances(Instances) - Method in class weka.classifiers.functions.PyroProxy

Batch scoring method

distributionsForInstances(Instances) - Method in class weka.classifiers.meta.FilteredClassifierExt

Batch scoring method.

distributionSortingTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the tip text for this property.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.Append

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.Compatibility

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.Copy

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.Merge

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.Randomize

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.RemoveTestSet

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.Rename

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.Revert

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.Save

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.Split

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.source.Clipboard

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.source.Database

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.source.DataGenerator

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.source.SpreadSheet

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.source.TextDirectory

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToDate

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToNominal

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToString

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.Remove

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.Rename

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ReorderAttributes

Invoked when an action occurs.

doActionPerformed(ActionEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.UseAsClass

Invoked when an action occurs.

doAggregate() - Method in class weka.classifiers.AggregateEvaluations

Performs the aggregation.

doAnalyze(Instances) - Method in class adams.data.instancesanalysis.FastICA

Performs the actual analysis.

doAnalyze(Instances) - Method in class adams.data.instancesanalysis.PCA

Performs the actual analysis.

doAnalyze(Instances) - Method in class adams.data.instancesanalysis.PLS

Performs the actual analysis.

doAppend(File[], File) - Method in class adams.gui.tools.weka.AppendDatasetsPanel

Performs the append.

doBuildModel(Dataset) - Method in class adams.ml.model.classification.WekaClassifier

Builds a model from the data.

doBuildModel(Dataset) - Method in class adams.ml.model.clustering.WekaClusterer

Builds a model from the data.

doBuildModel(Dataset) - Method in class adams.ml.model.regression.WekaRegressor

Builds a model from the data.

doChoose() - Method in class adams.gui.chooser.DatasetFileChooserPanel

Performs the actual choosing of an object.

doChoose() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Performs the actual choosing of an object.

doChoose() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel

Performs the actual choosing of an object.

doConvert() - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.AdamsInstanceToWekaInstance

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.MapToWekaInstance

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.ReportToWekaInstance

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.SpreadSheetToWekaInstances

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaCapabilitiesToInstances

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaCapabilitiesToSpreadSheet

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaCommandToCode

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaDrawableToString

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaEvaluationToCostCurve

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaEvaluationToMarginCurve

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaInstanceToAdamsInstance

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaInstanceToMap

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaPackageToMap

Performs the actual conversion.

doConvert() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Performs the actual conversion.

doConvertDataset(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Performs the dataset conversion.

doConvertDataset(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Performs the initialization.

doConvertDataset(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor

Performs the initialization.

doConvertDataset(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor

Performs the initialization.

doConvertInstance(PyroProxy, Instance) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Converts the instance into a different format.

doConvertInstance(PyroProxy, Instance) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Converts the instance into a different format.

doConvertInstance(PyroProxy, Instance) - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor

Converts the instance into a different format.

doConvertInstance(PyroProxy, Instance) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor

Converts the instance into a different format.

doCrossovers() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Performs cross-over.

doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.EncloseClassifier

Customizes the GOE popup menu.

doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.EncloseClusterer

Customizes the GOE popup menu.

doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.InvertInstancesColumnFinder

Customizes the GOE popup menu.

doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.InvertInstancesRowFinder

Customizes the GOE popup menu.

doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpClassifier

Customizes the GOE popup menu.

doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpClusterer

Customizes the GOE popup menu.

doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpInstancesColumnFinder

Customizes the GOE popup menu.

doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpInstancesRowFinder

Customizes the GOE popup menu.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.LogTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Restores the objects.

doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Restores the objects.

doDisplay() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel

Displays the results.

doDisplay() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel

Displays the results.

doDisplay() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

Displays the results.

doEvaluate(Actor, Token) - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Performs the actual evaluation.

doEvaluate(Actor, Token) - Method in class adams.flow.condition.bool.AdamsInstanceCapabilities

Performs the actual evaluation.

doEvaluate(Actor, Token) - Method in class adams.flow.condition.bool.WekaCapabilities

Performs the actual evaluation.

doEvaluate(Actor, Token) - Method in class adams.flow.condition.bool.WekaClassification

Performs the actual evaluation.

doEvaluate(Associator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation

Evaluates the associator and updates the result item.

doEvaluate(Associator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

Evaluates the associator and updates the result item.

doEvaluate(ASEvaluation, ASSearch, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation

Performs attribute selections and updates the result item.

doEvaluate(ASEvaluation, ASSearch, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

Performs attribute selections and updates the result item.

doEvaluate(ASEvaluation, ASSearch, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

Performs attribute selections and updates the result item.

doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation

Evaluates the classifier and updates the result item.

doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Evaluates the classifier and updates the result item.

doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Evaluates the classifier and updates the result item.

doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Evaluates the classifier and updates the result item.

doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

Evaluates the classifier and updates the result item.

doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Evaluates the classifier and updates the result item.

doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Evaluates the classifier and updates the result item.

doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Evaluates the classifier and updates the result item.

doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Evaluates the classifier and updates the result item.

doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Evaluates the classifier and updates the result item.

doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation

Evaluates the clusterer and updates the result item.

doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

Evaluates the clusterer and updates the result item.

doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Evaluates the clusterer and updates the result item.

doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

Evaluates the clusterer and updates the result item.

doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Evaluates the clusterer and updates the result item.

doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

Evaluates the clusterer and updates the result item.

doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

Evaluates the clusterer and updates the result item.

doEvaluate(Instance) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Performs the actual evaluation.

doEvaluate(Instance) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Performs the actual evaluation.

doEvaluate(Instance) - Method in class adams.data.weka.evaluator.PassThrough

Performs no real evaluation, just returns 1.0.

doEvaluate(Instances, IndexedSplitsRuns, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Performs an evaluation by applying the indexed splits runs to the data.

doExecute() - Method in class adams.flow.sink.AbstractWekaModelWriter

Executes the flow item.

doExecute() - Method in class adams.flow.sink.WekaDatabaseWriter

Executes the flow item.

doExecute() - Method in class adams.flow.sink.WekaExperimentFileWriter

Executes the flow item.

doExecute() - Method in class adams.flow.sink.WekaExperimentGenerator

Executes the flow item.

doExecute() - Method in class adams.flow.sink.WekaFileWriter

Executes the flow item.

doExecute() - Method in class adams.flow.sink.WekaInstancesDisplay

Executes the flow item.

doExecute() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Executes the flow item.

doExecute() - Method in class adams.flow.source.WekaAssociatorSetup

Executes the flow item.

doExecute() - Method in class adams.flow.source.WekaClassifierSetup

Executes the flow item.

doExecute() - Method in class adams.flow.source.WekaClustererSetup

Executes the flow item.

doExecute() - Method in class adams.flow.source.WekaDatabaseReader

Executes the flow item.

doExecute() - Method in class adams.flow.source.WekaDataGenerator

Executes the flow item.

doExecute() - Method in class adams.flow.source.WekaNewExperiment

Executes the flow item.

doExecute() - Method in class adams.flow.source.WekaNewInstances

Executes the flow item.

doExecute() - Method in class adams.flow.source.WekaPackageManagerAction

Executes the flow item.

doExecute() - Method in class adams.flow.source.WekaSelectDataset

Executes the flow item.

doExecute() - Method in class adams.flow.standalone.WekaPackageManagerAction

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.AbstractInstanceGenerator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.AbstractWekaModelReader

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaAccumulatedError

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaAggregateEvaluations

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaAttributeIterator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaAttributeSelection

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaAttributeSelectionSummary

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaBootstrapping

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaChooseAttributes

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaClassifierInfo

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaClassifierOptimizer

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaClassifierRanker

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaClassSelector

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaClusterAssignments

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaClustererInfo

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaClustererPostProcessor

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaDatasetsMerge

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaDatasetSplit

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaEnsembleGenerator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaEvaluationInfo

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaEvaluationSummary

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaEvaluationValues

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaExperiment

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaExperimentExecution

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaExperimentFileReader

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaExtractArray

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaExtractPLSMatrix

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaFileReader

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaFilter

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaGetCapabilities

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaGetInstancesValue

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaGetInstanceValue

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaInstanceBuffer

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaInstanceDumper

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaInstancesAppend

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaInstancesInfo

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaInstancesMerge

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaInstancesStatistic

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaModelReader

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaNewInstance

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaPackageManagerAction

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaPredictionsToInstances

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaPredictionsToSpreadSheet

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaPrincipalComponents

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaRandomSplit

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaRegexToRange

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaRelationName

Deprecated.

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaRenameRelation

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaSetInstancesValue

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaSetInstanceValue

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaSplitGenerator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaStoreInstance

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaStreamEvaluator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaStreamFilter

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaSubsets

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaTextDirectoryReader

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaTrainAssociator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaTrainClassifier

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaTrainClusterer

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

Executes the flow item.

doExecute() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator

Executes the flow item.

doExecute() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Runs the actual experiment.

doExecute(MessageCollection) - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction

Executes the action.

doExecute(MessageCollection) - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

Executes the action.

doExecute(MessageCollection) - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction

Executes the action.

doExecute(MessageCollection) - Method in class adams.flow.standalone.wekapackagemanageraction.RefreshCache

Executes the action.

doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction

Executes the action.

doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromFile

Executes the action.

doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromURL

Executes the action.

doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

Executes the action.

doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallPackage

Executes the action.

doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall

Executes the action.

doExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup

Executes the experiment setup for the classifier and updates the result item.

doExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Executes the experiment setup for the classifier and updates the result item.

doExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Executes the experiment setup for the classifier and updates the result item.

doExport(Object, File) - Method in class adams.gui.visualization.debug.objectexport.WekaInstancesExporter

Performs the actual export.

doFilter(SpreadSheet) - Method in class adams.data.spreadsheet.filter.WekaFilter

Performs the actual filtering of the spreadsheet.

doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.AbstractColumnFinder

Returns the columns of interest in the dataset.

doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.AllFinder

Returns the columns of interest in the dataset.

doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.ByExactName

Returns the columns of interest in the dataset.

doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.ByName

Returns the columns of interest in the dataset.

doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.Class

Returns the columns of interest in the dataset.

doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.Constant

Returns the columns of interest in the dataset.

doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.Invert

Returns the columns of interest in the dataset.

doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.MultiColumnFinder

Returns the columns of interest in the dataset.

doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.NullFinder

Returns the columns of interest in the dataset.

doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder

Returns the columns of interest in the dataset.

doFindRows(Instances) - Method in class adams.data.weka.rowfinder.AbstractRowFinder

Returns the rows of interest in the dataset.

doFindRows(Instances) - Method in class adams.data.weka.rowfinder.AllFinder

Returns the rows of interest in the dataset.

doFindRows(Instances) - Method in class adams.data.weka.rowfinder.ByLabel

Returns the rows of interest in the dataset.

doFindRows(Instances) - Method in class adams.data.weka.rowfinder.ByNumericRange

Returns the rows of interest in the spreadsheet.

doFindRows(Instances) - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns the rows of interest in the spreadsheet.

doFindRows(Instances) - Method in class adams.data.weka.rowfinder.Constant

Returns the rows of interest in the dataset.

doFindRows(Instances) - Method in class adams.data.weka.rowfinder.FilteredIQR

Returns the rows of interest in the dataset.

doFindRows(Instances) - Method in class adams.data.weka.rowfinder.Invert

Returns the rows of interest in the dataset.

doFindRows(Instances) - Method in class adams.data.weka.rowfinder.MultiRowFinder

Returns the rows of interest in the dataset.

doFindRows(Instances) - Method in class adams.data.weka.rowfinder.NullFinder

Returns the rows of interest in the dataset.

doGenerate() - Method in class adams.flow.template.InstanceDumperVariable

Generates the actor.

doGenerate(ChildFrame, Properties) - Method in class adams.gui.menu.MakeCompatibleDatasets

Performs the data generation.

doGenerate(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator

Generates the ensemble from the input.

doGenerate(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels

Generates the ensemble from the input.

doGenerate(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels

Generates the ensemble from the input.

doGenerate(Object, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Generates the indexed splits.

doGenerate(Object, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Generates the indexed splits.

doGenerate(Object, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Generates the indexed splits.

doGenerate(Object, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Generates the indexed splits.

doGenerate(Instances, IndexedSplitsRuns, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Generates predictions by applying the indexed splits runs to the data.

doGenerateHeader(HeaderDefinition) - Method in class adams.data.featureconverter.Weka

Performs the actual generation of a row from the raw data.

doGenerateOutput(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput

Generates the data.

doGenerateOutput(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Generates the data.

doGenerateOutput(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Generates the data.

doGenerateOutput(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Generates the data.

doGenerateRow(List<Object>) - Method in class adams.data.featureconverter.Weka

Performs the actual generation of a row from the raw data.

doInitialize() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner

Initializes the experiment.

doInitialize() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Initializes the experiment.

doInitialize() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractWekaExperimentRunner

Initializes the experiment.

doInitialize(AbstractApplicationFrame) - Method in class adams.gui.application.WekaPluginManagerExtensions

Performs the initialization.

doInitialize(AbstractApplicationFrame) - Method in class adams.gui.application.WekaSystemProperties

Performs the initialization.

doInitialize(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Performs the initialization.

doInitialize(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Performs the initialization.

doInitialize(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor

Performs the initialization.

doInitialize(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor

Performs the initialization.

doInitializeFilters() - Method in class adams.gui.chooser.AdamsExperimentFileChooser

Performs the actual initialization of the filters.

doInitializeFilters() - Method in class adams.gui.chooser.WekaFileChooser

Performs the actual initialization of the filters.

doInitializeIterator() - Method in class weka.classifiers.AbstractSplitGenerator

Initializes the iterator, randomizes the data if required.

doInitializeIterator() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Initializes the iterator.

doInitializeIterator() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Initializes the iterator, randomizes the data if required.

doInitializeIterator() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Initializes the iterator.

doInitializeIterator() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Initializes the iterator, randomizes the data if required.

doInitializeIterator() - Method in class weka.classifiers.DefaultRandomSplitGenerator

Initializes the iterator, randomizes the data if required.

doInitializeIterator() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Initializes the iterator, randomizes the data if required.

doInitializeIterator() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Initializes the iterator.

doInitializeIterator() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Initializes the iterator, randomizes the data if required.

doInitializeIterator() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Initializes the iterator, randomizes the data if required.

doInitializeIterator() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Initializes the iterator, randomizes the data if required.

doInitializeIterator() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Initializes the iterator, randomizes the data if required.

doInitializeIterator() - Method in class weka.classifiers.MultiLevelSplitGenerator

Initializes the iterator.

doInteract() - Method in class adams.flow.source.WekaSelectDataset

Performs the interaction with the user.

doInteract() - Method in class adams.flow.transformer.WekaChooseAttributes

Performs the interaction with the user.

doInteractHeadless() - Method in class adams.flow.source.WekaSelectDataset

Performs the interaction with the user in a headless environment.

doMerge(ChildFrame, File[], WekaMergeInstancesActor, File) - Method in class adams.gui.menu.MergeDatasets

Performs the merge.

doMutations() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Performs mutations.

doMutations2() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Performs mutations.

dontReplaceMissingValuesTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

doOptimize(ChildFrame, AbstractClassifierBasedGeneticAlgorithm, String[]) - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

Performs the optimization.

doPack(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the packed bits for the genetic algorithm.

doParsePrediction(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Parses the prediction.

doParsePrediction(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Parses the prediction.

doParsePrediction(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor

Parses the prediction.

doParsePrediction(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor

Parses the prediction.

doParsePredictions(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Parses the predictions.

doParsePredictions(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Parses the predictions.

doParsePredictions(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor

Parses the predictions.

doParsePredictions(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor

Parses the predictions.

doPerformPaint(Graphics, PaintEvent.PaintMoment) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

The paint routine of the paintlet.

doPerformPaint(Graphics, PaintEvent.PaintMoment) - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet

The paint routine of the paintlet.

doPlotColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotColumn

Plots the specified column.

doPlotRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotRow

Plots the specified row.

doPlotSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

Plots the specified rows.

doPostProcess(WekaEvaluationContainer) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor

Post-processes the evaluation container.

doPostProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor

Performs the actual post-processing.

doPostProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor

Performs the actual post-processing.

doPostProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient

Performs the actual post-processing.

doPostProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor

Performs the actual post-processing.

doPostProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.PassThrough

Simply returns the container, no post-processing done.

doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor

Post-processes the evaluation.

doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor

Post-processes the Evaluation.

doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.PassThrough

Post-processes the evaluation.

doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst

Post-processes the evaluation.

doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev

Post-processes the evaluation.

doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Post-processes the evaluation.

doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange

Post-processes the evaluation.

doProcess(Classifier[]) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.AbstractClassifierSetupProcessor

Processes the classifier array.

doProcess(Classifier[]) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.PassThrough

Processes the classifier array.

doProcess(Classifier[]) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs

Processes the classifier array.

doProcessCell(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell

Processes the specified cell.

doProcessCell(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ViewCell

Processes the specified cell.

doProcessColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn

Processes the specified column.

doProcessColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AttributeStatistics

Processes the specified column.

doProcessColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight

Processes the specified column.

doProcessColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ColumnStatistic

Processes the specified column.

doProcessColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.DataSort

Processes the specified column.

doProcessRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow

Processes the specified row.

doProcessRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.RowStatistic

Processes the specified row.

doProcessRows(List<Instance>) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractSelectionProcessor

Returns the list of row indices generated from the data.

doProcessRows(List<Instance>) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.Average

Returns the list of row indices generated from the data.

doProcessRows(List<Instance>) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.PassThrough

Returns the list of row indices generated from the data.

doProcessSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

Processes the specified rows.

doProcessSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic

Processes the specified row.

doProcessSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights

Processes the specified rows.

doProcessSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset

Processes the specified rows.

doRead(PlaceholderFile) - Method in class adams.data.io.input.AbstractAdamsExperimentReader

Performs the actual reading of the experiment file.

doRead(PlaceholderFile) - Method in class adams.data.io.input.JsonAdamsExperimentReader

Performs the actual reading of the experiment file.

doRead(PlaceholderFile) - Method in class adams.data.io.input.NestedAdamsExperimentReader

Performs the actual reading of the experiment file.

doRead(PlaceholderFile) - Method in class adams.data.io.input.SerializedAdamsExperimentReader

Performs the actual reading of the experiment file.

doRead(File) - Method in class adams.data.io.input.AbstractWekaSpreadSheetReader

Performs the actual reading.

doRegister() - Method in class adams.gui.goe.WekaEditorsRegistration

Performs the registration of the editors.

doRegression(boolean[]) - Method in class weka.classifiers.functions.LinearRegressionJ

Calculate a linear regression using the selected attributes

doReload() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Reloads the data.

doReload() - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer

Reloads the data.

doReload() - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer

Reloads the data.

doReload() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer

Reloads the data.

doReload() - Method in class adams.gui.tools.wekainvestigator.data.MemoryContainer

Reloads the data.

doReload() - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer

Reloads the data.

doReload() - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer

Reloads the data.

doRender(Object, JPanel, Integer) - Method in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer

Performs the actual rendering.

doRenderCached(Object, JPanel, Integer) - Method in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer

Performs the actual rendering.

doRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob

Performs the actual execution.

doRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob

Performs the actual execution.

doRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabRunnableJob

Performs the actual execution.

doRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner

Performs the actual running of the experiment.

doRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Performs the actual running of the experiment.

doRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.DefaultWekaExperimentRunner

Performs the actual running of the experiment.

doRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.RemoteWekaExperimentRunner

Performs the actual running of the experiment.

doRun() - Method in class adams.tools.CompareDatasets

Performs the comparison.

doSelectRows(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.AbstractRowSelection

Returns the list of row indices generated from the data.

doSelectRows(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Returns the list of row indices generated from the data.

doSelectRows(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.IndividualRows

Returns the list of row indices generated from the data.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.LogTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Returns the objects for serialization.

doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Returns the objects for serialization.

doTrain(SpreadSheet) - Method in class adams.data.spreadsheet.filter.WekaFilter

Performs the actual retraining on the spreadsheet.

doTrainColumnFinder(Instances) - Method in class adams.data.weka.columnfinder.AbstractFilteredColumnFinder

Performs the actual training of the column finder with the specified dataset.

doTrainColumnFinder(Instances) - Method in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder

Performs the actual training of the column finder with the specified dataset.

doTrainColumnFinder(Instances) - Method in class adams.data.weka.columnfinder.MultiColumnFinder

Performs the actual training of the column finder with the specified dataset.

doTrainColumnFinder(Instances) - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder

Performs the actual training of the column finder with the specified dataset.

doTrainRowFinder(Instances) - Method in class adams.data.weka.rowfinder.AbstractFilteredRowFinder

Performs the actual training of the row finder with the specified dataset.

doTrainRowFinder(Instances) - Method in class adams.data.weka.rowfinder.AbstractTrainableRowFinder

Performs the actual training of the row finder with the specified dataset.

doTrainRowFinder(Instances) - Method in class adams.data.weka.rowfinder.FilteredIQR

Performs the actual training of the row finder with the specified dataset.

doTrainRowFinder(Instances) - Method in class adams.data.weka.rowfinder.MultiRowFinder

Performs the actual training of the row finder with the specified dataset.

doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Transforms the data, initializes if necessary.

doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.DIPLS

Transforms the data, initializes if necessary.

doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.KernelPLS

Transforms the data, initializes if necessary.

doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.NIPALS

Transforms the data, initializes if necessary.

doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.OPLS

Transforms the data, initializes if necessary.

doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.PLS1

Transforms the data, initializes if necessary.

doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.PRM

Transforms the data, initializes if necessary.

doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.SIMPLS

Transforms the data, initializes if necessary.

doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.SparsePLS

Transforms the data, initializes if necessary.

doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.VCPLS

Transforms the data, initializes if necessary.

doUnpack(PropertyPath.PropertyContainer, String) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Unpacks and applies the bits from the genetic algorithm.

DownSample - Class in weka.filters.unsupervised.attribute

A simple filter that retains only every nth attribute.

DownSample() - Constructor for class weka.filters.unsupervised.attribute.DownSample

doWrite(PlaceholderFile, AbstractExperiment) - Method in class adams.data.io.output.AbstractAdamsExperimentWriter

Performs the actual writing of the experiment file.

doWrite(PlaceholderFile, AbstractExperiment) - Method in class adams.data.io.output.JsonAdamsExperimentWriter

Performs the actual writing of the experiment file.

doWrite(PlaceholderFile, AbstractExperiment) - Method in class adams.data.io.output.NestedAdamsExperimentWriter

Performs the actual writing of the experiment file.

doWrite(PlaceholderFile, AbstractExperiment) - Method in class adams.data.io.output.SerializedAdamsExperimentWriter

Performs the actual writing of the experiment file.

doWrite(SpreadSheet, OutputStream) - Method in class adams.data.io.output.AbstractWekaSpreadSheetWriter

Performs the actual writing.

drawData(Graphics, Instance, Color) - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet

Draws the data with the given color.

drawData(Graphics, Instance, Color, InstanceLinePaintlet.MarkerShape) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Draws the data with the given color.

dropAboveTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Returns the tip text for this property.

dropAtMostTipText() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns the tip text for this property.

dropBelowTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Returns the tip text for this property.

dropBelowTipText() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns the tip text for this property.

dropNonClassYsTipText() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the tip text for this property

E

edit() - Method in class weka.gui.explorer.ExplorerExt

Performs an undo.

editOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Allows the user to modify the output generators.

editOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Allows the user to modify the output generators.

editOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Allows the user to modify the output generators.

editOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Allows the user to modify the output generators.

editOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Allows the user to modify the output generators.

EditWekaASEvaluator - Class in adams.gui.flow.tree.quickaction

Lets the user edit the Weka attribute selection evaluator.

EditWekaASEvaluator() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaASEvaluator

EditWekaASSearch - Class in adams.gui.flow.tree.quickaction

Lets the user edit the Weka attribute selection search.

EditWekaASSearch() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaASSearch

EditWekaClassifier - Class in adams.gui.flow.tree.quickaction

Lets the user edit the Weka classifier.

EditWekaClassifier() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaClassifier

EditWekaClusterer - Class in adams.gui.flow.tree.quickaction

Lets the user edit the Weka clusterer.

EditWekaClusterer() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaClusterer

EditWekaDataGenerator - Class in adams.gui.flow.tree.quickaction

Lets the user edit the Weka data generator.

EditWekaDataGenerator() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaDataGenerator

EditWekaFilter - Class in adams.gui.flow.tree.quickaction

Lets the user edit the Weka filter.

EditWekaFilter() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaFilter

EditWekaStreamableFilter - Class in adams.gui.flow.tree.quickaction

Lets the user edit the Weka filter.

EditWekaStreamableFilter() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaStreamableFilter

ELAPSED_TIME_TESTING - adams.flow.core.ExperimentStatistic

ELAPSED_TIME_TRAINING - adams.flow.core.ExperimentStatistic

eliminateColinearAttributesTipText() - Method in class weka.classifiers.functions.LinearRegressionJ

Returns the tip text for this property

EMPTY_NOMINAL_ATTRIBUTES - adams.flow.core.Capability

can handle empty nominal attributes.

EMPTY_NOMINAL_CLASS - adams.flow.core.Capability

can handle empty nominal classes.

EncloseClassifier - Class in adams.gui.goe.popupmenu

For enclosing classifiers in SingleClassifierEnhancer wrappers.

EncloseClassifier() - Constructor for class adams.gui.goe.popupmenu.EncloseClassifier

EncloseClusterer - Class in adams.gui.goe.popupmenu

For enclosing clusterers in SingleClustererEnhancer wrappers.

EncloseClusterer() - Constructor for class adams.gui.goe.popupmenu.EncloseClusterer

encodingTipText() - Method in class adams.data.io.input.NestedAdamsExperimentReader

Returns the tip text for this property.

encodingTipText() - Method in class weka.core.converters.SimpleArffLoader

Returns the tip text for this property.

encodingTipText() - Method in class weka.core.converters.SimpleArffSaver

Returns the tip text for this property.

ensureEqualValuesTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the tip-text for the ensure-equal-values option.

enumerateAttributes() - Method in class weka.core.AbstractHashableInstance

Returns an enumeration of all the attributes.

enumerateInstances() - Method in class weka.core.InstancesView

Returns an enumeration of all instances in the dataset.

enumerateMeasures() - Method in class weka.classifiers.trees.m5.M5Base2

Returns an enumeration of the additional measure names

ENV_VAR - Static variable in class adams.core.management.WekaHomeEnvironmentModifier

the WEKA_HOME environment variable.

EPSILON - Static variable in class weka.classifiers.evaluation.MSLE

equal(Matrix, Matrix) - Static method in class weka.core.matrix.MatrixHelper

Compares the two matrices.

equal(Matrix, Matrix, double) - Static method in class weka.core.matrix.MatrixHelper

Compares the two matrices.

equalHeaders(Instance) - Method in class weka.core.AbstractHashableInstance

Tests if the headers of two instances are equivalent.

equalHeadersMsg(Instance) - Method in class weka.core.AbstractHashableInstance

Checks if the headers of two instances are equivalent.

equals(Object) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer

Indicates whether some other object is "equal to" this one.

equals(Object) - Method in class adams.data.instances.AbstractInstanceGenerator

Returns whether the two objects are the same.

equals(Object) - Method in class adams.data.weka.columnfinder.AbstractColumnFinder

Returns whether the two objects are the same.

equals(Object) - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer

Returns whether the two objects are the same.

equals(Object) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Returns whether the two objects are the same.

equals(Object) - Method in class adams.data.weka.predictions.AbstractErrorScaler

Returns whether the two objects are the same.

equals(Object) - Method in class adams.data.weka.rowfinder.AbstractRowFinder

Returns whether the two objects are the same.

equals(Object) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Checks whether the specified object is the same.

equals(Object) - Method in class weka.core.AbstractHashableInstance

Returns only true if the same class and the same hashcode.

equalsHeader(SpreadSheet) - Method in class adams.ml.data.InstancesView

Compares the header of this spreadsheet with the other one.

EquiDistance - Class in weka.filters.unsupervised.attribute

A filter for interpolating the numeric attributes.Using the same number of points as are currently present in the input will have no effect.

EquiDistance() - Constructor for class weka.filters.unsupervised.attribute.EquiDistance

EquiDistance.AttributeSelection - Enum in weka.filters.unsupervised.attribute

Defines how the attributes are selected.

errorCalculationTipText() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the tip text for this property.

errorScalerTipText() - Method in class adams.flow.sink.WekaClassifierErrors

Returns the tip text for this property.

errorTipText() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

errorTipText() - Method in class weka.classifiers.meta.LeastMedianSq

etaTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the eta option.

evaluate() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

Performs the evaluation.

evaluate() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment.CrossValidationExperimentJob

Performs the cross-validation.

evaluate() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment.TrainTestSplitExperimentJob

Performs the evaluation.

evaluate(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Creates a runnabel to evaluate the classifier on the dataset.

evaluate(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

Evaluates the classifier on the dataset.

evaluate(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Evaluates the classifier on the dataset.

evaluate(OptData) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection

evaluate(Associator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation

Evaluates the associator and updates the result item.

evaluate(ASEvaluation, ASSearch, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation

Performs attribute selections and updates the result item.

evaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation

Evaluates the classifier and updates the result item.

evaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation

Evaluates the clusterer and updates the result item.

evaluate(Instance) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Evaluates the given instance.

evaluate(Instances, Instances) - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

Performs an evaluation on the given train and test set.

evaluate(Instances, Instances) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Performs an evaluation on the given train and test set.

evaluateAttribute(int) - Method in class weka.attributeSelection.AbstractPLSAttributeEval

evaluates an individual attribute

evaluateAttribute(int) - Method in class weka.attributeSelection.LinearRegressionAttributeEval

evaluates an individual attribute

evaluateClassifier(Classifier, Instances, int, int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Evaluates the classifier on the dataset and returns the metric.

evaluateClassifier(Classifier, Instances, Instances) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Evaluates the classifier on the dataset and returns the metric.

evaluateExperiment(Instances) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Evaluates the experiment data.

EvaluateJob(Classifier, Instances, Instances, StoppableEvaluation, AbstractOutput) - Constructor for class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

Initializes the job.

EvaluateJob(StoppableEvaluation, Classifier, Instances, AbstractOutput) - Constructor for class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob

Initializes the job.

evaluateModel(Classifier, Instances, Object...) - Method in class weka.classifiers.evaluation.StoppableEvaluation

Evaluates the classifier on a given set of instances.

evaluateModel(Classifier, Instances, Evaluation, int, TestingHelper.TestingUpdateListener) - Static method in class weka.classifiers.TestingHelper

Evaluates the model on the test data and sends updates to the listener (if available).

evaluateModel(Classifier, Instances, Evaluation, int, TestingHelper.TestingUpdateListener, StoppableWithFeedback) - Static method in class weka.classifiers.TestingHelper

Evaluates the model on the test data and sends updates to the listener (if available).

EvaluationContainer(Instance) - Constructor for class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer

Initializes the container.

EvaluationHelper - Class in adams.flow.core

A helper class for Evaluation related things.

EvaluationHelper() - Constructor for class adams.flow.core.EvaluationHelper

evaluationPostProcessorTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

EvaluationStatistic - Enum in adams.flow.core

The enumeration for the comparison field.

evaluationToSpreadSheet(Evaluation) - Method in class weka.filters.supervised.instance.RemoveOutliers

Turns the predictions of the evaluation object into a spreadsheet.

evaluationTypeTipText() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the tip text for this property.

evaluatorTipText() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns the tip text for this property.

evaluatorTipText() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Returns the tip text for this property.

EXACT - weka.classifiers.trees.XGBoost.TreeMethod

exactMatchTipText() - Method in class adams.data.conversion.SwapPLS

Returns the tip text for this property.

EXCEPT_CLASS - adams.data.instancesanalysis.pls.PredictionType

predict all Ys except class attribute.

excludeAttributes(Instances) - Method in class adams.flow.transformer.WekaInstancesMerge

Excludes attributes from the data.

excludedAttributesTipText() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the tip text for this property.

execute() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Executes the experiment.

execute() - Method in class adams.multiprocess.WekaCrossValidationExecution

Executes the flow item.

execute(MessageCollection) - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction

Executes the action.

execute(MessageCollection) - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction

Executes the action.

execute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction

Executes the action.

execute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup

Executes the experiment setup for the classifier and updates the result item.

executeQuery() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Applies the query to the dataset.

executionFinished() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Gets called when a job finishes.

executionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Gets called when a job finishes.

expand(Instances, boolean) - Method in class weka.core.InstanceGrouping

Expands the fake data into the original dataset space.

expand(Instances, TIntList) - Method in class weka.core.InstanceGrouping

Expands the fake data into the original dataset space.

expandCheck(Instances) - Method in class weka.core.InstanceGrouping

Ensures that the data to expand is in the right format.

Experimenter - Class in adams.gui.menu

Opens the WEKA Experimenter.

Experimenter() - Constructor for class adams.gui.menu.Experimenter

Initializes the menu item with no owner.

Experimenter(AbstractApplicationFrame) - Constructor for class adams.gui.menu.Experimenter

Initializes the menu item.

ExperimenterEntryPanel - Class in adams.gui.tools.wekamultiexperimenter

Allows the display of multiple Experimenter panels.

ExperimenterEntryPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.ExperimenterEntryPanel

ExperimenterPanel - Class in adams.gui.tools.wekamultiexperimenter

The Experimenter panel.

ExperimenterPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

experimentFileTipText() - Method in class adams.flow.transformer.WekaExperiment

Returns the tip text for this property.

ExperimentHandler - Class in weka.gui.explorer

Manages the ExperimentPanel.

ExperimentHandler() - Constructor for class weka.gui.explorer.ExperimentHandler

ExperimentPanel - Class in weka.gui.explorer

This panel allows the user to select and configure a classifier, set the attribute of the current dataset to be used as the class, and perform an Experiment (like in the Experimenter) with this Classifier/Dataset combination.

ExperimentPanel() - Constructor for class weka.gui.explorer.ExperimentPanel

Creates the Experiment panel.

ExperimentStatistic - Enum in adams.flow.core

The enumeration for the comparison field.

ExperimentTab - Class in adams.gui.tools.wekainvestigator.tab

Tab for running experiment on selected dataset/classifier.

ExperimentTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.ExperimentTab

ExperimentTab.HistoryPanel - Class in adams.gui.tools.wekainvestigator.tab

Customized history panel.

experimentTipText() - Method in class adams.flow.source.WekaNewExperiment

Returns the tip text for this property.

experimentTypeTipText() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the tip text for this property.

ExperimentWithCustomizableRelationNames - Interface in adams.gui.tools.wekamultiexperimenter.experiment

Interface for experiments that allow customizing the relation names of the datasets.

Explorer - Class in adams.gui.menu

Opens the WEKA Explorer.

Explorer() - Constructor for class adams.gui.menu.Explorer

Initializes the menu item with no owner.

Explorer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.Explorer

Initializes the menu item.

ExplorerEntryPanel - Class in weka.gui.explorer

Allows the display of multiple Explorer panels.

ExplorerEntryPanel() - Constructor for class weka.gui.explorer.ExplorerEntryPanel

ExplorerExt - Class in weka.gui.explorer

An extended Explorer interface using menus instead of buttons, as well as remembering recent files.

ExplorerExt() - Constructor for class weka.gui.explorer.ExplorerExt

Default constructor.

export() - Method in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane

Exports the components using a AbstractMultiObjectExport scheme.

expressionTipText() - Method in class weka.classifiers.functions.MathExpressionClassifier

Returns the tip text for this property.

ExtExperiment - Class in weka.experiment

Extended version of the Weka Experiment class.

ExtExperiment() - Constructor for class weka.experiment.ExtExperiment

Default constructor.

ExtExperiment(Experiment) - Constructor for class weka.experiment.ExtExperiment

Assigns the values from the given experiment.

extract(Evaluation, boolean, int) - Method in enum adams.opt.genetic.Measure

Extracts the measure from the Evaluation object.

extractBinValue(BinnableGroup<Instance>) - Method in class adams.data.binning.BinnableInstances.GroupedClassValueBinValueExtractor

Extracts the numeric value to use for binning from the object.

extractBinValue(Instance) - Method in class adams.data.binning.BinnableInstances.ClassValueBinValueExtractor

Extracts the numeric value to use for binning from the object.

extractDatabaseID(String) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Extracts the database ID from a string in the comboxbox.

extractGroup(Binnable<Instance>) - Method in class adams.data.binning.BinnableInstances.NumericClassGroupExtractor

Extracts the group from the binnable object.

extractGroup(Binnable<Instance>) - Method in class adams.data.binning.BinnableInstances.StringAttributeGroupExtractor

Extracts the group from the binnable object.

extractLoadings(Instances, ArrayList<ArrayList<Double>>) - Method in class adams.data.instancesanalysis.PCA

Create a spreadsheet to output from the coefficients 2D array

extractPLSKey(String) - Method in class weka.filters.supervised.attribute.MultiPLS

Extracts key in the PLS map from the combined matrix name.

F

F_MEASURE - adams.flow.core.EvaluationStatistic

F_MEASURE - adams.flow.core.ExperimentStatistic

F_MEASURE - adams.opt.genetic.Measure

F measure.

FakeClassifier - Class in weka.classifiers.functions

Fake classifier that requires no dataset for training and just outputs random values within the specified bounds.
Fake build and prediction times can be set as well.

FakeClassifier() - Constructor for class weka.classifiers.functions.FakeClassifier

Fallback - Class in weka.classifiers.meta

In case the base classifier fails to make predictions, uses fallback one.

Fallback() - Constructor for class weka.classifiers.meta.Fallback

fallbackTipText() - Method in class weka.classifiers.meta.Fallback

Returns the tip text for this property.

FALLOUT - adams.flow.sink.WekaThresholdCurve.AttributeName

FALSE_NEG - adams.flow.sink.WekaThresholdCurve.AttributeName

FALSE_NEG_RATE - adams.opt.genetic.Measure

false negative rate.

FALSE_NEGATIVE_RATE - adams.flow.core.EvaluationStatistic

FALSE_NEGATIVE_RATE - adams.flow.core.ExperimentStatistic

FALSE_POS - adams.flow.sink.WekaThresholdCurve.AttributeName

FALSE_POS_RATE - adams.opt.genetic.Measure

false positive rate.

FALSE_POSITIVE_RATE - adams.flow.core.EvaluationStatistic

FALSE_POSITIVE_RATE - adams.flow.core.ExperimentStatistic

FARTHEST_FIRST - Static variable in class weka.clusterers.SAXKMeans

farthestFirstInit(Instances) - Method in class weka.clusterers.SAXKMeans

Initialize with the fartherst first centers

fastDistanceCalcTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

FastICA - Class in adams.data.instancesanalysis

Performs independent components analysis and allows access to components and sources.

FastICA() - Constructor for class adams.data.instancesanalysis.FastICA

FastWavelet - Class in weka.filters.unsupervised.attribute

A filter for wavelet transformation using the JSci library's fast wavelet transform (FWT) algorithms.

For more information see:

(2009).

FastWavelet() - Constructor for class weka.filters.unsupervised.attribute.FastWavelet

default constructor.

favorZeroesTipText() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the tip text for this property.

featureSelectorTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the featureSelector option.

FFT - Class in weka.filters.unsupervised.attribute

A filter that transforms the data with Fast Fourier Transform.

Pads with zeroes.
For more information see:

Mark Hale (2009).

FFT() - Constructor for class weka.filters.unsupervised.attribute.FFT

fieldsTipText() - Method in class adams.data.conversion.ReportToWekaInstance

Returns the tip text for this property.

fieldsTipText() - Method in interface adams.data.instances.InstanceGeneratorWithFields

Returns the tip text for this property.

fileChooserTitleTipText() - Method in class adams.flow.source.WekaSelectDataset

Returns the tip text for this property.

FileContainer - Class in adams.gui.tools.wekainvestigator.data

File-based dataset.

FileContainer(AbstractFileLoader, PlaceholderFile) - Constructor for class adams.gui.tools.wekainvestigator.data.FileContainer

Loads the data using the specified loader.

FileContainer(AbstractFileLoader, File) - Constructor for class adams.gui.tools.wekainvestigator.data.FileContainer

Loads the data using the specified loader.

FileContainer(AbstractFileLoader, File, Instances) - Constructor for class adams.gui.tools.wekainvestigator.data.FileContainer

Uses the provided data, but also stores the reader/file for reloading it.

FileName - Class in adams.data.weka.relationname

Suggests the file name (without extension) as the relation name.

FileName() - Constructor for class adams.data.weka.relationname.FileName

FILENAME - Static variable in class adams.gui.application.WekaPluginManagerExtensions

FILENAME - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the name of the props file.

FILENAME - Static variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the name of the props file with the general properties.

FILENAME - Static variable in class adams.gui.visualization.instance.InstanceComparePanel

the name of the props file.

FILENAME - Static variable in class adams.gui.visualization.instance.InstanceExplorer

the name of the props file.

FILENAME_SHORTCUTS - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the name of the shortcut props file.

FileResultsHandler - Class in adams.gui.tools.wekamultiexperimenter.experiment

Writes the experiment results to a file.

FileResultsHandler() - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

fillCovariance() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

fillWithAttributeNames(SelectOptionPanel, int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation

Fills the panel for selection options with the attributes from the specified data container.

filter(Instance) - Method in class weka.classifiers.meta.FilteredClassifierExt

Filters the Instance through the remove filter if necessary.

filter(Instances) - Method in class weka.classifiers.meta.FilteredClassifierExt

Filters the dataset through the remove filter if necessary.

filter(Instances, List<Integer>) - Method in class adams.flow.transformer.WekaChooseAttributes

Filters the data.

filter(Filter, Instance) - Method in class weka.classifiers.meta.FilteredClassifierExt

Filters the Instance through the specified filter.

FILTER_NONE - Static variable in class weka.classifiers.functions.GaussianProcessesAdaptive

no filter

FILTER_NONE - Static variable in class weka.classifiers.functions.GaussianProcessesNoWeights

no filter

FILTER_NONE - Static variable in class weka.classifiers.functions.GaussianProcessesWeighted

no filter

FILTER_NONE - Static variable in class weka.classifiers.functions.GPD

no filter

FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.GaussianProcessesAdaptive

normalizes the data

FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.GaussianProcessesNoWeights

normalizes the data

FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.GaussianProcessesWeighted

normalizes the data

FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.GPD

normalizes the data

FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.GaussianProcessesAdaptive

standardizes the data

FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.GaussianProcessesNoWeights

standardizes the data

FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.GaussianProcessesWeighted

standardizes the data

FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.GPD

standardizes the data

FilteredClassifierExt - Class in weka.classifiers.meta

Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.

FilteredClassifierExt() - Constructor for class weka.classifiers.meta.FilteredClassifierExt

FilteredFilter - Class in weka.filters

First applies the pre-filter to the data and the generated data is fed into the main filter.

FilteredFilter() - Constructor for class weka.filters.FilteredFilter

FilteredIQR - Class in adams.data.weka.rowfinder

Returns indices of rows that got identified as outliers/extreme values.

FilteredIQR() - Constructor for class adams.data.weka.rowfinder.FilteredIQR

FilteredSearch - Class in weka.core.neighboursearch

Class implementing the brute force search algorithm for nearest neighbour search, filtered using PLS.

FilteredSearch() - Constructor for class weka.core.neighboursearch.FilteredSearch

Constructor.

FilteredSearch(Instances) - Constructor for class weka.core.neighboursearch.FilteredSearch

Constructor that uses the supplied set of instances.

FilteredSearchWithIndices - Class in weka.core.neighboursearch

FilteredSearch with index support.

FilteredSearchWithIndices() - Constructor for class weka.core.neighboursearch.FilteredSearchWithIndices

filterInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Filters an instance.

filterSearchTipText() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Returns the tip text for this property.

filtersTipText() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Returns the tip text for this property.

filtersTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Returns the tip text for this property.

filterTestData(Instances) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Filters the data accordingly to the selected attribute range.

filterTipText() - Method in class adams.data.spreadsheet.filter.WekaFilter

Returns the tip text for this property.

filterTipText() - Method in class adams.data.weka.rowfinder.FilteredIQR

Returns the tip text for this property.

filterTipText() - Method in class adams.flow.transformer.WekaFilter

Returns the tip text for this property.

filterTipText() - Method in class adams.flow.transformer.WekaStreamFilter

Returns the tip text for this property.

filterTipText() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the tip text for this property

filterTipText() - Method in class weka.classifiers.functions.PLSClassifierWeighted

Returns the tip text for this property

filterTipText() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

filterTipText() - Method in class weka.core.neighboursearch.FilteredSearch

Returns the tip text for this property

filterTipText() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Returns the tip text for this property.

filterTrainTipText() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Returns the tip text for this property.

filterTypeTipText() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Returns the tip text for this property

filterTypeTipText() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Returns the tip text for this property

filterTypeTipText() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Returns the tip text for this property

filterTypeTipText() - Method in class weka.classifiers.functions.GPD

Returns the tip text for this property.

finalModelTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the tip text for this property.

FIND - Static variable in class weka.filters.unsupervised.attribute.NominalToNumeric

findAttributeIndexOfUniqueID(Instances) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Finds the index of the unique ID attribute in the given dataset.

findBestLeaf(double[], RuleNode2[]) - Method in class weka.classifiers.trees.m5.RuleNode2

Find the leaf with greatest coverage

findBestModel() - Method in class weka.classifiers.functions.LinearRegressionJ

Performs a greedy search for the best regression model using Akaike's criterion.

findBestRegression() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Finds the best regression generated from m_samples random samples from the training data.

findBestRegression() - Method in class weka.classifiers.meta.LeastMedianSq

Finds the best regression generated from m_samples random samples from the training data.

findCallableActor() - Method in class adams.flow.source.WekaSelectDataset

Tries to find the callable actor referenced by its callable name.

findCallableActor() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Tries to find the callable actor referenced by its callable name.

findClosestAttributeIndex(Instance, double) - Method in class adams.gui.visualization.instance.InstancePointHitDetector

Returns the closest attribute index for the given x.

findClosestX(List<InstancePoint>, int) - Static method in class adams.data.instance.InstanceUtils

Returns the index in m_Points closest to the given x value.

findColumns(Instances) - Method in class adams.data.weka.columnfinder.AbstractColumnFinder

Returns the columns of interest in the dataset.

findColumns(Instances) - Method in interface adams.data.weka.columnfinder.ColumnFinder

Returns the columns of interest in the dataset.

findEnclosingAttributeIndices(Instance, double) - Method in class adams.gui.visualization.instance.InstancePointHitDetector

Determines the enclosing attribute indices for the given x value.

findEnclosingXs(List<InstancePoint>, int) - Static method in class adams.data.instance.InstanceUtils

Returns the indices of points in m_Points that enclose the given x value.

findersTipText() - Method in class adams.data.weka.columnfinder.MultiColumnFinder

Returns the tip text for this property.

findersTipText() - Method in class adams.data.weka.rowfinder.MultiRowFinder

Returns the tip text for this property.

findInstancePoint(Instance, int) - Method in class adams.gui.visualization.instance.InstancePointHitDetector

Returns the Instance point at the specified position.

findRandomSplit(Instances, Random, int) - Method in class weka.classifiers.trees.RandomRegressionForest.Node

determines a random split for the data, tries 10 pairs.

findResiduals() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Finds residuals (squared) for the current regression.

findResiduals() - Method in class weka.classifiers.meta.LeastMedianSq

Finds residuals (squared) for the current regression.

findRows(Instances) - Method in class adams.data.weka.rowfinder.AbstractRowFinder

Returns the rows of interest in the dataset.

findRows(Instances) - Method in interface adams.data.weka.rowfinder.RowFinder

Returns the rows of interest in the dataset.

findThreshold() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

Finds the user-defined threshold and sets other internal variables accordingly.

findThreshold() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

Finds the user-defined threshold and sets other internal variables accordingly.

findThreshold(Vector<IntervalEstimatorBased.SortedInterval>) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Finds the threshold based on the collected data.

findThreshold(Vector<T>) - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

Finds the threshold based on the collected data.

findTipText() - Method in class adams.flow.transformer.WekaRenameRelation

Returns the tip text for this property.

findTipText() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the tip text for this property.

findX(List<InstancePoint>, int) - Static method in class adams.data.instance.InstanceUtils

Returns the index in m_Points of the given x value.

findX(List<InstancePoint>, InstancePoint) - Static method in class adams.data.instance.InstanceUtils

Returns the index in m_Points of the given sequence point.

finishExecution() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Stops the execution.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Finishes up the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Finishes up the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Finishes up the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Finishes up the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Finishes up the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Finishes up the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

Finalizes the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

Finalizes the initialization.

finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

finishes the initialization.

finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

Finalizes the initialization.

finishInit() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Finishes the initialization.

finishInit() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

finishes the initialization.

finishInit() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

finishes the initialization.

finishInit() - Method in class weka.gui.explorer.MultiExplorer

finishes the initialization.

fireDataChange() - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource

Notifies all the tabs that the data has changed.

fireDataChange(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Notifies all the tabs that the data has changed.

fireDataChange(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Notifies all the tabs that the data has changed.

fireDataChange(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Notifies all the tabs that the data has changed.

fireDataChange(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Notifies all the tabs that the data has changed.

fireDataChange(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Notifies all the tabs that the data has changed.

fireSetupChanged() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Fires a ChangeEvent that the setup has changed.

firstAttributeRangeTipText() - Method in class adams.gui.InstanceCompare

Returns the tip text for this property.

firstAttributeTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Returns the tip text for this property.

firstDatasetTipText() - Method in class adams.gui.InstanceCompare

Returns the tip text for this property.

firstInstance() - Method in class weka.core.InstancesView

Returns the first instance in the set.

firstRangeTipText() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Returns the tip text for this property.

firstRowIndexTipText() - Method in class adams.gui.InstanceCompare

Returns the tip text for this property.

fitnessChanged(GeneticFitnessChangeEvent) - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Gets called when the fitness of the genetic algorithm changed.

fitnessChanged(GeneticFitnessChangeEvent) - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot

Adds the fitness measure to the plot.

FixedClassifierErrors - Class in weka.gui.visualize.plugins

Displays the classifier errors using Weka panels, but with a fixed size of the error plots.

FixedClassifierErrors() - Constructor for class weka.gui.visualize.plugins.FixedClassifierErrors

FixedClassifierErrorsPlot - Class in weka.gui.visualize.plugins

Displays the classifier errors using an ADAMS plot with fixed size crosses.

FixedClassifierErrorsPlot() - Constructor for class weka.gui.visualize.plugins.FixedClassifierErrorsPlot

FixedSizeErrorScaler - Class in adams.data.weka.predictions

Scales the errors to a fixed size.

FixedSizeErrorScaler() - Constructor for class adams.data.weka.predictions.FixedSizeErrorScaler

flowFileTipText() - Method in class weka.filters.FlowFilter

Returns the tip text for this property.

FlowFilter - Class in weka.filters

Processes the data with a flow.

FlowFilter() - Constructor for class weka.filters.FlowFilter

flowPauseStateChanged(FlowPauseStateEvent) - Method in class adams.flow.transformer.WekaClassifierRanker

Gets called when the pause state of the flow changes.

flowPauseStateChanged(FlowPauseStateEvent) - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Gets called when the pause state of the flow changes.

FMEASURE - adams.flow.sink.WekaThresholdCurve.AttributeName

foldsTipText() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

Returns the tip text for this property.

foldsTipText() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the tip text for this property.

foldsTipText() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns the tip text for this property.

foldsTipText() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the tip text for this property.

foldsTipText() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Returns the tip text for this property.

foldsTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the tip text for this property.

foldsTipText() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the tip text for this property.

foldsTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the tip text for this property.

foldsTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

Returns the tip text for this property.

foldsTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

foldsTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the tip text for this property.

forceCompressionTipText() - Method in class weka.core.converters.SimpleArffLoader

Tip text suitable for displaying int the GUI

forCommandLine(String) - Static method in class adams.data.instances.AbstractInstanceGenerator

Instantiates the generator from the given commandline (i.e., classname and optional options).

forCommandLine(String) - Static method in class adams.data.weka.columnfinder.AbstractColumnFinder

Instantiates the column finder from the given commandline (i.e., classname and optional options).

forCommandLine(String) - Static method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Instantiates the evaluator from the given commandline (i.e., classname and optional options).

forCommandLine(String) - Static method in class adams.data.weka.predictions.AbstractErrorScaler

Instantiates the scaler from the given commandline (i.e., classname and optional options).

forCommandLine(String) - Static method in class adams.data.weka.rowfinder.AbstractRowFinder

Instantiates the row finder from the given commandline (i.e., classname and optional options).

forCommandLine(String) - Static method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Instantiates the genetic algorithm from the given commandline (i.e., classname and optional options).

FOREST - weka.classifiers.trees.XGBoost.NormaliseType

formatDate(double) - Method in class adams.flow.transformer.WekaInstancesInfo

Formats date stats.

formatOutput(Instances, Instances) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Handles merging of output datasets and formatting.

formatTipText() - Method in class weka.filters.unsupervised.attribute.StringToDate

Returns the tip text for this property.

forName(String) - Method in class adams.core.classmanager.WekaClassManager

Instantiates the class by its name.

forName(String, String[]) - Static method in class adams.data.instances.AbstractInstanceGenerator

Instantiates the generator with the given options.

forName(String, String[]) - Static method in class adams.data.weka.columnfinder.AbstractColumnFinder

Instantiates the column finder with the given options.

forName(String, String[]) - Static method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Instantiates the evaluator with the given options.

forName(String, String[]) - Static method in class adams.data.weka.predictions.AbstractErrorScaler

Instantiates the scaler with the given options.

forName(String, String[]) - Static method in class adams.data.weka.rowfinder.AbstractRowFinder

Instantiates the row finder with the given options.

forName(String, String[]) - Static method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Instantiates the genetic algorithm with the given options.

foundUsefulAttribute() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns true if a usable attribute was found.

FourInOnePlot - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Generates the 4-in-1 plot: normal plot, histogram, residuals vs fit and vs order.

FourInOnePlot() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

FP_RATE - adams.flow.sink.WekaThresholdCurve.AttributeName

FROM_LABEL - weka.filters.unsupervised.attribute.NominalToNumeric.ConversionType

fromArray(String[], MessageCollection) - Method in class adams.core.option.WekaCommandLineHandler

Generates an object from the commandline options.

fromBits(int) - Method in class adams.opt.optimise.genetic.PackDataDef.DataInfo

fromBytes(byte[]) - Method in class weka.classifiers.meta.socketfacade.Simple

Turns the bytes back into a JSON object.

fromCommandLine(Class<T>, String) - Static method in class weka.core.WekaOptionUtils

Turns a commandline into an object.

fromCommandLine(String, MessageCollection) - Method in class adams.core.option.WekaCommandLineHandler

Generates an object from the specified commandline.

fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaAttributeIndexEditor

Returns an object created from the custom string representation.

fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaAttributeRangeEditor

Returns an object created from the custom string representation.

fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaExperimentFileEditor

Returns an object created from the custom string representation.

fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaLabelIndexEditor

Returns an object created from the custom string representation.

fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaLabelRangeEditor

Returns an object created from the custom string representation.

fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaUnorderedAttributeRangeEditor

Returns an object created from the custom string representation.

FromPredictions - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation

Loads predictions from a spreadsheet for evaluation.

FromPredictions - Class in weka.classifiers.functions

Encapsulates predictions from a spreadsheet.

FromPredictions() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

FromPredictions() - Constructor for class weka.classifiers.functions.FromPredictions

fromString(String) - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Not used.

fromString(String) - Method in class adams.gui.goe.WekaGenericObjectEditorPanel

Converts the string representation into its object representation.

FULL - adams.flow.transformer.WekaInstancesInfo.InfoType

full stats.

FULL_ATTRIBUTE - adams.flow.transformer.WekaInstancesInfo.InfoType

full attribute stats (nominal/numeric).

FULL_CLASS - adams.flow.transformer.WekaInstancesInfo.InfoType

full class attribute stats (nominal/numeric).

FusionJsonCommunicationProcessor - Class in adams.data.wekapyroproxy

Turns Instances/Instance into fusion JSON.

FusionJsonCommunicationProcessor() - Constructor for class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

G

GAJob(GeneticAlgorithm, FitnessFunction, int[]) - Constructor for class adams.opt.optimise.GeneticAlgorithm.GAJob

Constructor.

GAMMA_REGRESSION - weka.classifiers.trees.XGBoost.Objective

gammaTipText() - Method in class weka.classifiers.functions.GPD

Returns the tip text for this property.

gammaTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the gamma option.

GaussianProcessesAdaptive - Class in weka.classifiers.functions

Implements Gaussian Processes for regression without hyperparameter-tuning.

GaussianProcessesAdaptive() - Constructor for class weka.classifiers.functions.GaussianProcessesAdaptive

the default constructor

GaussianProcessesNoWeights - Class in weka.classifiers.functions

* Implements Gaussian processes for regression without hyperparameter-tuning.

GaussianProcessesNoWeights() - Constructor for class weka.classifiers.functions.GaussianProcessesNoWeights

GaussianProcessesWeighted - Class in weka.classifiers.functions

Implements Gaussian Processes for regression without hyperparameter-tuning.

GaussianProcessesWeighted() - Constructor for class weka.classifiers.functions.GaussianProcessesWeighted

the default constructor

GBLINEAR - weka.classifiers.trees.XGBoost.BoosterType

GBTREE - weka.classifiers.trees.XGBoost.BoosterType

generate() - Method in class weka.gui.explorer.ExplorerExt

Pops up a dialog that allows the user to generate data.

generate(AbstractClassifierEvaluation, Instances, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.AbstractFinalModelGenerator

Builds the final model and stores it in the result item.

generate(AbstractClassifierEvaluation, Instances, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.Null

Builds the final model and stores it in the result item.

generate(AbstractClassifierEvaluation, Instances, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.Simple

Builds the final model and stores it in the result item.

generate(AbstractClassifierEvaluation, Instances, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds

Builds the final model and stores it in the result item.

generate(Class) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator

Generates and returns the help for the specified class.

generate(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator

Generates the ensemble from the input.

generate(Object) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator

Generates and returns the help for the specified object.

generate(T) - Method in class adams.data.instances.AbstractInstanceGenerator

Returns the generated data, generates it if necessary.

generateClassifier(int, int[]) - Method in class adams.opt.genetic.Hermione

Generate the classifier from current bit array

generateContainers() - Method in class weka.classifiers.MultiLevelSplitGenerator

Generates the containers.

generateDatasetList(List<DataContainer>) - Static method in class adams.gui.tools.wekainvestigator.evaluation.DatasetHelper

Generates the list of datasets for a combobox.

generateGroups(Instances, int, String, String) - Method in class weka.classifiers.MultiLevelSplitGenerator

Generates the groups from the data by applying the regexp/group.

generateHeader(T) - Method in class adams.data.instances.AbstractInstanceGenerator

Generates the header of the output data.

generateHeader(Instance) - Method in class adams.flow.transformer.WekaInstanceEvaluator

Generates the new header for the data.

generateLine(T, double[]) - Method in class adams.data.baseline.AbstractLinearRegressionBased

Generates fake data for the plotting the line.

generateLineTipText() - Method in class adams.data.baseline.AbstractLinearRegressionBased

Returns the tip text for this property.

generateNumPointsLabel(int) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Generates the string for the label displaying the number of points that are currently selected.

generateOutput(double, Instances, Classifier, int, int[]) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Generates the output requested output.

generateOutput(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput

Generates the data.

generateOutput(AbstractOutputGenerator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and then generates the output.

generateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Generates the output from the item.

generateOutput(AbstractOutputGenerator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and then generates the output.

generateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Generates the output from the item.

generateOutput(AbstractOutputGenerator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and then generates the output.

generateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Generates the output from the item.

generateOutput(AbstractOutputGenerator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and then generates the output.

generateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Generates the output from the item.

generateOutput(AbstractOutputGenerator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Prompts the user with a GOE for configuring the output generator and then generates the output.

generateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Generates the output from the item.

generateOutput(T) - Method in class adams.data.instances.AbstractInstanceGenerator

Generates the actual data.

generateOutput(T) - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator

Generates output and adds it to the ResultItem.

generateOutput(Instances, List<Integer>) - Method in class adams.flow.transformer.WekaChooseAttributes

Creates the output token with the subset of data.

generateOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractSelectionProcessor

Returns the format for the output data.

generateOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.Average

Returns the format for the output data.

generateOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.PassThrough

Returns the format for the output data.

generateReducedData(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Generates the reduced data.

generateRulesTipText() - Method in class weka.classifiers.trees.m5.M5Base2

Returns the tip text for this property

generates() - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.AdamsInstanceToWekaInstance

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.MapToWekaInstance

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.ReportToWekaInstance

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.SpreadSheetToWekaInstances

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.WekaCapabilitiesToInstances

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.WekaCapabilitiesToSpreadSheet

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.WekaEvaluationToCostCurve

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.WekaEvaluationToMarginCurve

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.WekaInstanceToAdamsInstance

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.WekaInstanceToMap

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.WekaPackageToMap

Returns the class that is generated as output.

generates() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the class that is generated as output.

generates() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.source.WekaAssociatorSetup

Returns the class of objects that it generates.

generates() - Method in class adams.flow.source.WekaClassifierSetup

Returns the class of objects that it generates.

generates() - Method in class adams.flow.source.WekaClustererSetup

Returns the class of objects that it generates.

generates() - Method in class adams.flow.source.WekaDatabaseReader

Returns the class of objects that it generates.

generates() - Method in class adams.flow.source.WekaDataGenerator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.source.WekaNewExperiment

Returns the class of objects that it generates.

generates() - Method in class adams.flow.source.WekaNewInstances

Returns the class of objects that it generates.

generates() - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction

The types of data the action generates.

generates() - Method in class adams.flow.source.WekaPackageManagerAction

Returns the class of objects that it generates.

generates() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

The types of data the action generates.

generates() - Method in class adams.flow.transformer.AbstractInstanceGenerator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.AbstractWekaModelReader

Returns the class that the producer generates.

generates() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

The generated classes.

generates() - Method in class adams.flow.transformer.WekaAccumulatedError

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaAggregateEvaluations

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaAttributeSelectionSummary

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaChooseAttributes

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaClassifierInfo

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaClassifierOptimizer

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaClassifying

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaClassSelector

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaClusterAssignments

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaClustererInfo

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaClustererPostProcessor

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaClustering

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaDatasetsMerge

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaDatasetSplit

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator

Returns the output data the generator generates.

generates() - Method in class adams.flow.transformer.WekaEnsembleGenerator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels

Returns the output data the generator generates.

generates() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels

Returns the output data the generator generates.

generates() - Method in class adams.flow.transformer.WekaEvaluationInfo

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaEvaluationValues

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaExperiment

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaExperimentExecution

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaExperimentFileReader

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaExtractArray

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaExtractPLSMatrix

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaFileReader

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaFilter

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaGetCapabilities

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaGetInstancesValue

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaGetInstanceValue

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaInstancesAppend

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaInstancesStatistic

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaNewInstance

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction

The types of data the action generates.

generates() - Method in class adams.flow.transformer.WekaPackageManagerAction

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromFile

The types of data the action generates.

generates() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromURL

The types of data the action generates.

generates() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

The types of data the action generates.

generates() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallPackage

The types of data the action generates.

generates() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall

The types of data the action generates.

generates() - Method in class adams.flow.transformer.WekaPredictionsToInstances

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaPredictionsToSpreadSheet

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaPrincipalComponents

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaRegexToRange

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaRelationName

Deprecated.

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaRenameRelation

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput

Returns the class that it generates.

generates() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Returns the class that it generates.

generates() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Returns the class that it generates.

generates() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Returns the class that it generates.

generates() - Method in class adams.flow.transformer.WekaSetInstancesValue

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaSetInstanceValue

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaStoreInstance

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaStreamFilter

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaSubsets

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaTextDirectoryReader

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaTrainAssociator

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaTrainClassifier

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaTrainClusterer

Returns the class of objects that it generates.

generates() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

Returns the class of objects that it generates.

generateSplits(Instances, int, String, String) - Method in class weka.classifiers.MultiLevelSplitGenerator

Generates the train/test splits.

generateSubset(Instances, Range) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

generates a subset of the dataset with only the attributes from the range (class is always added if present).

generatorTipText() - Method in class adams.flow.transformer.AbstractInstanceGenerator

Returns the tip text for this property.

generatorTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the tip text for this property.

generatorTipText() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the tip text for this property.

generatorTipText() - Method in class adams.flow.transformer.WekaEnsembleGenerator

Returns the tip text for this property.

generatorTipText() - Method in class adams.flow.transformer.WekaRandomSplit

Returns the tip text for this property.

generatorTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the tip text for this property.

generatorTipText() - Method in class adams.flow.transformer.WekaSplitGenerator

Returns the tip text for this property.

generatorTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

Returns the tip text for this property.

generatorTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Returns the tip text for this property.

generatorTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

GenericDoubleResolution - Class in adams.core.discovery.genetic

Generic handler for double properties (using resolution).

GenericDoubleResolution() - Constructor for class adams.core.discovery.genetic.GenericDoubleResolution

GenericFloatResolution - Class in adams.core.discovery.genetic

Generic handler for float properties (using resolution).

GenericFloatResolution() - Constructor for class adams.core.discovery.genetic.GenericFloatResolution

GenericInteger - Class in adams.core.discovery.genetic

Generic handler for integer properties.

GenericInteger() - Constructor for class adams.core.discovery.genetic.GenericInteger

GenericPLSMatrixAccess - Interface in weka.core

For classes that allow access to PLS matrices.

GenericString - Class in adams.core.discovery.genetic

Generic handler for string properties.

GenericString() - Constructor for class adams.core.discovery.genetic.GenericString

GeneticAlgorithm - Class in adams.opt.optimise

Morticia (GEX).

GeneticAlgorithm - Class in weka.classifiers.functions

Applies the specified genetic algorithm to the training data and uses the best setup for the final model.

GeneticAlgorithm() - Constructor for class adams.opt.optimise.GeneticAlgorithm

The default constructor.

GeneticAlgorithm() - Constructor for class weka.classifiers.functions.GeneticAlgorithm

GeneticAlgorithm.GAJob - Class in adams.opt.optimise

Class for multithreading the ga.

genRegression(Random) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Generates a LinearRegression classifier from the current m_SubSample.

genRegression(Random) - Method in class weka.classifiers.meta.LeastMedianSq

Generates a LinearRegression classifier from the current m_SubSample.

get(int) - Method in class weka.core.InstancesView

Returns the instance at the given position.

get(String) - Method in class adams.opt.optimise.genetic.PackData

get(String) - Method in class adams.opt.optimise.genetic.PackDataDef

get(String) - Method in class weka.core.InstanceGrouping

Returns the group.

getAbsErr() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Gets the threshold for the max error when predicting a numeric class.

getAbsErr() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Gets the threshold for the max error when predicting a numeric class.

getAbsolute() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Returns whether the absolute values of coefficients are returned.

getAbsoluteDifference() - Method in class adams.flow.transformer.WekaAccumulatedError.SortablePrediction

Returns the absolute difference between actual and predicted value.

getAbstentionClassification(Instance) - Method in interface weka.classifiers.AbstainingClassifier

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.lazy.AbstainingLWL

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainAttributePercentile

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainAverage

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainMinimumProbability

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainVote

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.Consensus

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.ConsensusOrVote

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.FilteredClassifierExt

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.MinMaxLimits

The prediction that made the classifier abstain.

getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper

The prediction that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in interface weka.classifiers.AbstainingClassifier

The class distribution that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in class weka.classifiers.lazy.AbstainingLWL

The class distribution that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainAttributePercentile

The class distribution that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainAverage

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

The class distribution that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

The class distribution that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainMinimumProbability

The class distribution that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainVote

The class distribution that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.Consensus

The class distribution that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.ConsensusOrVote

The class distribution that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.FilteredClassifierExt

The class distribution that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.MinMaxLimits

The class distribution that made the classifier abstain.

getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper

The class distribution that made the classifier abstain.

getAcceptListener() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the listener for the event that the user accepts the input.

getAction() - Method in class adams.flow.source.WekaPackageManagerAction

Returns the action in use.

getAction() - Method in class adams.flow.standalone.WekaPackageManagerAction

Returns the action in use.

getAction() - Method in class adams.flow.transformer.WekaPackageManagerAction

Returns the action in use.

getActionMethod(String) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Returns the method associated with the specified action.

getActions() - Static method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Returns the available actions.

getActions() - Static method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Returns the available actions.

getActions() - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Returns the available actions to list.

getActor() - Method in class adams.gui.menu.PlotAttributeVsAttribute

Used to create an instance of a specific actor.

getActual() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the column with the actual values.

getActual() - Method in class weka.classifiers.functions.FromPredictions

Returns the column with the actual values.

getActualClass() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the class that is being handled.

getActualClass() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the class that is being handled.

getActualClass() - Method in class adams.core.discovery.genetic.GenericInteger

Returns the class that is being handled.

getActualClass() - Method in class adams.core.discovery.genetic.GenericString

Returns the class that is being handled.

getActualComponentAt(int) - Method in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane

Returns the actual component at the position.

getActualFilter() - Method in class weka.filters.SerializedFilter

Returns the actual filter in use, loads it if necessary.

getActualFolds() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the actual number of folds used.

getActualIndex() - Method in class weka.classifiers.functions.FromPredictions

Returns the actual 0-based index.

getActualIndex(int) - Method in class weka.classifiers.meta.SubsetEnsemble

Returns the actual index in the data of the feature attribute.

getActualMax() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the upper limit in use for the actual values.

getActualMin() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the lower limit in use for the actual values.

getActualNumFolds() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns the actual number of folds used (eg when using LOO).

getActualNumFolds() - Method in interface weka.classifiers.CrossValidationFoldGenerator

Returns the actual number of folds used (eg when using LOO).

getActualNumFolds() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns the actual number of folds used (eg when using LOO).

getActualNumFolds() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the actual number of folds used (eg when using LOO).

getActualNumFolds() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the actual number of folds used (eg when using LOO).

getActualNumFolds() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns the actual number of folds used (eg when using LOO).

getActualParentComponent() - Method in class adams.flow.source.WekaSelectDataset

Returns the parent component to use.

getActualTitle() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Returns the actual title in use.

getAddAttributeInformation() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

Returns whether to add attribute information to the metadata.

getAddClassification() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns whether to add the numeric classification (label index for nominal classes).

getAddClassificationLabel() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns whether to add the classification label (only for nominal classes).

getAddDatabaseID() - Method in class adams.data.instances.AbstractInstanceGenerator

Returns whether the database ID is added.

getAddDatasetInformation() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

Returns whether to add dataset information to the metadata.

getAddDistribution() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns whether to add the class distribution (only for nominal classes).

getAddIndex() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns whether to add the dataset index number to the prefix.

getAdditional() - Method in class weka.classifiers.functions.FromPredictions

Returns the additional columns to add to the plot containers.

getAdditionalAcceptedClasses() - Method in class adams.flow.sink.AbstractWekaModelWriter

Returns additional classes that are accepted as input.

getAdditionalAcceptedClasses() - Method in class adams.flow.sink.WekaModelWriter

Returns additional classes that are accepted as input (WEKA classifiers and clusterers).

getAdditionalAttributeIndices(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Returns the additional attribute indices.

getAdditionalAttributeIndices(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Returns the additional attribute indices.

getAdditionalAttributeIndices(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Returns the additional attribute indices.

getAdditionalAttributes() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns the stored additional attributes data.

getAdditionalAttributes() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the attributes indices of the original dataset to include in the reports.

getAdditionalErrorInformation() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Returns additional information to be added to the error message.

getAdditionalFieldName(AbstractField) - Static method in class adams.data.weka.ArffUtils

Returns the name of an attribute for an additional field.

getAdditionalFields() - Method in interface adams.data.instances.InstanceGeneratorWithAdditionalFields

Returns the additional fields to add.

getAdditionalIndices() - Method in class weka.classifiers.functions.FromPredictions

Returns the 0-based indices of the additional columns.

getAdditionalInformation() - Method in class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor

Returns the additional information.

getAddLabelIndex() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns whether to show the error as well.

getAddLabelIndex() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Returns whether to show the error as well.

getAddOne() - Method in class weka.filters.unsupervised.attribute.LogTransform

Returns whether to add '1' to the values before log-transform.

getAdjustToVisibleData() - Method in class adams.gui.visualization.instance.InstancePanel

Returns whether the display is adjusted to only the visible spectrums or all of them.

getAlgorithm() - Method in class adams.data.instancesanalysis.PLS

Returns the algorithm to use.

getAlgorithm() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns the genetic algorithm to apply to the dataset.

getAlgorithm() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns the binning algorithm.

getAlgorithm() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Returns the binning algorithm.

getAlgorithm() - Method in class weka.classifiers.functions.GeneticAlgorithm

Returns the seed value for the random values.

getAlgorithm() - Method in class weka.classifiers.functions.PLSWeighted

Get the PLS algorithm.

getAlgorithm() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the binning algorithm.

getAlgorithm() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns the binning algorithm.

getAlgorithm() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the PLS algorithm to use.

getAlgorithm() - Method in class weka.filters.supervised.attribute.PLS

Returns the PLS algorithm to use.

getAlgorithm() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Gets the type of algorithm to use.

getAlgorithms() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Returns the binning algorithms to choose from.

getAll(Instances) - Static method in class weka.core.matrix.MatrixHelper

returns the data as matrix

getAllDatabaseIDs(int) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Returns all database IDs.

getAllVisible() - Method in class adams.gui.visualization.instance.InstanceContainerManager

Returns (a copy of) all currently stored containers.

getAlpha() - Method in class weka.classifiers.trees.XGBoost

Gets the L1 regularisation term on weights.

getAlpha() - Method in class weka.filters.supervised.attribute.YGradientEPO

Returns the alpha parameter.

getAlpha() - Method in class weka.filters.supervised.attribute.YGradientGLSW

Returns the alpha parameter.

getAlwaysShowMarkers() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Returns whether marker shapes are always drawn.

getAlwaysUseContainer() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Returns whether to always use an evaluation container as output.

getAmount() - Method in class weka.filters.unsupervised.instance.LatestRecords

Returns the amount of records to keep.

getAnalysisName() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

Returns the name to display in the GUI.

getAnalysisName() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Returns the name to display in the GUI.

getAnalysisPanel() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Returns the analysis panel.

getAscending() - Method in class adams.data.instances.InstanceComparator

Returns whether a column is sorted in ascending or descending order.

getAssignments() - Method in class weka.clusterers.SAXKMeans

Gets the assignments for each instance.

getAssociator() - Method in class adams.flow.source.WekaAssociatorSetup

Returns the associator in use.

getAssociator() - Method in class adams.flow.transformer.WekaTrainAssociator

Returns the name of the callable associator in use.

getAssociatorInstance() - Method in class adams.flow.transformer.WekaTrainAssociator

Returns an instance of the callable associator.

getAttRange() - Method in class weka.filters.unsupervised.instance.KennardStone

Returns the attribute range to use for distance calculation (after applying pre-filter).

getAttRegExp() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns the regular expression used for identifying the attributes to process.

getAttRegExp() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns the regular expression used for identifying the attributes to process.

getAttribute() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

Returns the currently set index.

getAttribute() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Returns the attribute being displayed.

getAttribute() - Method in class weka.classifiers.meta.AbstainAttributePercentile

getAttribute(int) - Method in class adams.gui.visualization.instance.InstanceTableModel

Returns the attribute for the given column.

getAttributeAt(int) - Method in class adams.gui.visualization.instances.InstancesTableModel

returns the attribute at the given index, can be NULL if not an attribute column

getAttributeColumn(String) - Method in class adams.gui.visualization.instances.InstancesTableModel

returns the column of the given attribute name, -1 if not found

getAttributeIndex() - Method in class adams.data.weka.rowfinder.ByLabel

Returns the index of the attribute to perform the matching on.

getAttributeIndex() - Method in class adams.data.weka.rowfinder.ByNumericRange

Returns the index of the column to perform the matching on.

getAttributeIndex() - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns the index of the column to perform the matching on.

getAttributeIndex() - Method in class adams.flow.transformer.WekaInstancesInfo

Returns the attribute index to use for attribute specific information.

getAttributeIndex() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Returns the index of the attribute to use for indexing.

getAttributeIndex() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns the index of the attribute used in the regression.

getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.SpellChecker

Returns the 1-based index of the attribute to process.

getAttributeIndex() - Method in class weka.filters.unsupervised.instance.SortOnAttribute

Returns the 1-based index of the attribute to sort on.

getAttributeIndex(String) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Returns the attribute index for the specified attribute name.

getAttributeName() - Method in class adams.flow.transformer.WekaGetInstanceValue

Returns the name of the attribute to get the value for.

getAttributeName() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Get the name of the attribute to be created.

getAttributeName() - Method in class weka.filters.unsupervised.instance.LatestRecords

Returns the name of the attribute containing the numeric database ID.

getAttributeNames() - Method in class adams.flow.source.WekaNewInstances

Returns the list of attribute names.

getAttributeNames() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Gets the names of the attributes.

getAttributePrefix() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Returns the prefix to use for the generated attributes.

getAttributeRange() - Method in class adams.data.instancesanalysis.FastICA

Returns the attribute range parameter.

getAttributeRange() - Method in class adams.data.instancesanalysis.PCA

Returns the attribute range parameter.

getAttributeRange() - Method in class adams.data.instancesanalysis.PLS

Returns the attribute range parameter.

getAttributeRange() - Method in class adams.data.weka.rowfinder.FilteredIQR

Returns the attribute range to work on.

getAttributeRange() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Returns the current range of attributes.

getAttributeRange() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Returns the range of attributes to compute the matrix for.

getAttributeRange() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Returns the 1-based range of the attributes to work on.

getAttributeRange() - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Returns the 1-based range of the attributes to combine.

getAttributeRange() - Method in class weka.filters.unsupervised.attribute.LogTransform

Returns the range of attributes to process.

getAttributeRange() - Method in class weka.filters.unsupervised.attribute.SetMissingValue

Returns the range of attributes to compute the matrix for.

getAttributeRange() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Returns the range of attributes to detrend.

getAttributeRenamesExp() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the array of attribute rename expressions.

getAttributeRenamesFormat() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the array of format strings used for attribute renaming.

getAttributes() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Returns the range of attributes to create plot containers for.

getAttributeSelection() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Returns the stored AttributeSelection object.

getAttributeSelection() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns how the attributes get selected.

getAttributeSelectionMethod() - Method in class weka.classifiers.functions.LinearRegressionJ

Gets the method used to select attributes for use in the linear regression.

getAttributeSelectionPanel() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Returns the attribute selection panel.

getAttributeStats(Instances, int) - Method in class adams.flow.transformer.WekaInstancesInfo

Generates attributes statistics.

getAttributeTypes() - Method in class adams.flow.source.WekaNewInstances

Returns the list of attribute types.

getAttributeX() - Method in class adams.flow.sink.WekaInstancesPlot

Returns the attribute to show on the X axis.

getAttributeX() - Method in class adams.flow.sink.WekaThresholdCurve

Returns the attribute to show on the X axis.

getAttributeX() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Returns the attribute to show on the X axis.

getAttributeY() - Method in class adams.flow.sink.WekaInstancesPlot

Returns the attribute to show on the Y axis.

getAttributeY() - Method in class adams.flow.sink.WekaThresholdCurve

Returns the attribute to show on the Y axis.

getAttributeY() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Returns the attribute to show on the Y axis.

getAutoKeyGeneration() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns whether a primary key is automatically generated.

getAverageWidth() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval

Returns the average width of the stored intervals.

getAxisX() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the setup for the X axis.

getAxisY() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the setup for the Y axis.

getBase() - Method in class adams.data.instancesanalysis.pls.OPLS

Sets the base PLS algorithm to use.

getBase() - Method in class weka.classifiers.meta.Fallback

Returns the base classifier.

getBaseScore() - Method in class weka.classifiers.trees.XGBoost

Gets the initial prediction score of all instances (global bias).

getBatchSize() - Method in class weka.classifiers.functions.PyroProxy

Get the batch size to use.

getBestClassifier() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Returns the best classifier found.

getBestClassifier(Classifier, Classifier) - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

In case of GridSearch/MultiSearch the best setup is returned, otherwise the classifier itself.

getBestRange() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the best range of attributes.

getbHat() - Method in class weka.filters.supervised.attribute.PLSFilterExtended

getBias() - Method in class weka.classifiers.meta.VotedImbalance

Gets the bias towards a uniform class.

getBinCalculation() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns how the number of bins is calculated.

getBins() - Method in class weka.core.SAXDistance

Returns the nth point setting.

getBins() - Method in class weka.filters.unsupervised.attribute.SAX

Returns the nth point setting.

getBinWidth() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the bin width in use (for some calculations).

getBits() - Method in class adams.opt.optimise.genetic.PackData

getBits() - Method in class adams.opt.optimise.GeneticAlgorithm

Gets the number of bits.

getBits(String) - Method in class adams.opt.optimise.genetic.PackData

getBitsForPosition(int[], List<Integer>, List<Integer>, int) - Method in class adams.opt.genetic.Hermione

get bit array for parameter at pos.

getBitsPerGene() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the currently set number of bits per gene.

getBitstring() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

getBooster() - Method in class weka.classifiers.trees.XGBoost

Gets the type of booster to use.

getBorder() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the thickness of the border.

getBorderTitle() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Returns the title of the border.

getBufferSize() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns the number of instances to buffer before writing them to disk.

getBuildRegressionTree() - Method in class weka.classifiers.trees.m5.M5Base2

Get the value of regressionTree.

getBuildWait() - Method in class weka.classifiers.functions.FakeClassifier

Returns the time in msec to wait when calling buildClassifier.

getC() - Method in class adams.data.instancesanalysis.pls.PRM

Returns the tuning parameter.

getCallableActor() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns the currently set callable actor.

getCallableName() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns the name of the callable sink in use.

getCancelListener() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the listener for the event that the user discarded the input.

getCanChangeClassInDialog(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler

Returns whether the class can be changed in the dialog.

getCanChangeClassInDialog(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorPopupMenu

Returns whether the class can be changed in the editor.

getCanopyMaxNumCanopiesToHoldInMemory() - Method in class weka.clusterers.SAXKMeans

Get the maximum number of candidate canopies to retain in memory during training.

getCanopyMinimumCanopyDensity() - Method in class weka.clusterers.SAXKMeans

Get the minimum T2-based density below which a canopy will be pruned during periodic pruning.

getCanopyPeriodicPruningRate() - Method in class weka.clusterers.SAXKMeans

Get the how often to prune low density canopies during training (if using canopy clustering)

getCanopyT1() - Method in class weka.clusterers.SAXKMeans

Get the t1 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs

getCanopyT2() - Method in class weka.clusterers.SAXKMeans

Get the t2 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs

getCapabilities() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the Capabilities of this filter.

getCapabilities() - Method in class adams.data.weka.columnfinder.AbstractColumnFinderWithCapabilities

Returns the capabilities of this object.

getCapabilities() - Method in class adams.data.weka.predictions.AbstractErrorScaler

Returns the capabilities of this object.

getCapabilities() - Method in class adams.data.weka.predictions.AutoScaler

Returns the capabilities of this object.

getCapabilities() - Method in class adams.data.weka.predictions.FixedSizeErrorScaler

Returns the capabilities of this object.

getCapabilities() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference

Returns the capabilities of this object.

getCapabilities() - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler

Returns the capabilities of this object.

getCapabilities() - Method in class adams.data.weka.predictions.RoundErrorScaler

Returns the capabilities of this object.

getCapabilities() - Method in class adams.data.weka.rowfinder.AbstractRowFinderWithCapabilities

Returns the capabilities of this object.

getCapabilities() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Returns the capabilities.

getCapabilities() - Method in class adams.ml.model.classification.WekaClassifier

Returns the algorithm's capabilities in terms of data.

getCapabilities() - Method in class adams.ml.model.clustering.WekaClusterer

Returns the algorithm's capabilities in terms of data.

getCapabilities() - Method in class adams.ml.model.regression.WekaRegressor

Returns the algorithm's capabilities in terms of data.

getCapabilities() - Method in class weka.attributeSelection.LinearRegressionAttributeEval

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the Capabilities of this classifier.

getCapabilities() - Method in class weka.classifiers.functions.FakeClassifier

Returns the Capabilities of this classifier.

getCapabilities() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.GeneticAlgorithm

Returns the Capabilities of this classifier.

getCapabilities() - Method in class weka.classifiers.functions.GPD

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.LinearRegressionJ

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.MathExpressionClassifier

Returns the Capabilities of this classifier.

getCapabilities() - Method in class weka.classifiers.functions.PLSClassifierWeighted

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.PLSWeighted

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.functions.PyroProxy

Returns the Capabilities of this classifier.

getCapabilities() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.AbstainAttributePercentile

Returns default capabilities of the base classifier.

getCapabilities() - Method in class weka.classifiers.meta.AbstainAverage

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Returns default capabilities of the base classifier.

getCapabilities() - Method in class weka.classifiers.meta.AbstainMinimumProbability

Returns default capabilities of the base classifier.

getCapabilities() - Method in class weka.classifiers.meta.AbstainVote

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.ClassificationViaRegressionD

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.ClassifierCascade

Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.

getCapabilities() - Method in class weka.classifiers.meta.ConsensusOrVote

Returns the ensemble's capabilities.

getCapabilities() - Method in class weka.classifiers.meta.Fallback

Returns the Capabilities of this classifier.

getCapabilities() - Method in class weka.classifiers.meta.FilteredClassifierExt

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.meta.HighLowSplit

Returns default capabilities of the base classifier.

getCapabilities() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

Returns default capabilities of the base classifier.

getCapabilities() - Method in class weka.classifiers.meta.LeastMedianSq

Returns default capabilities of the base classifier.

getCapabilities() - Method in class weka.classifiers.meta.MinMaxLimits

Returns default capabilities of the base classifier.

getCapabilities() - Method in class weka.classifiers.meta.PartitionedStacking

Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.

getCapabilities() - Method in class weka.classifiers.meta.SocketFacade

Returns the Capabilities of this classifier.

getCapabilities() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns the ensemble's capabilities.

getCapabilities() - Method in class weka.classifiers.meta.Veto

Returns the ensemble's capabilities.

getCapabilities() - Method in class weka.classifiers.meta.VotedImbalance

Returns default capabilities of the base classifier.

getCapabilities() - Method in class weka.classifiers.simple.AbstractSimpleClassifier

Returns the Capabilities of this classifier.

getCapabilities() - Method in class weka.classifiers.trees.m5.M5Base2

Returns default capabilities of the classifier, i.e., of LinearRegression.

getCapabilities() - Method in class weka.classifiers.trees.RandomModelTrees

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.trees.RandomRegressionForest

Returns default capabilities of the classifier.

getCapabilities() - Method in class weka.classifiers.trees.XGBoost

Returns the Capabilities of this classifier.

getCapabilities() - Method in class weka.clusterers.SAXKMeans

Returns default capabilities of the clusterer.

getCapabilities() - Method in class weka.core.converters.SimpleArffSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.core.converters.SpreadSheetSaver

Returns the Capabilities of this saver.

getCapabilities() - Method in class weka.filters.FilteredFilter

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.FlowFilter

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.SerializedFilter

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.attribute.PLS

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.attribute.YGradientEPO

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.attribute.YGradientGLSW

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the ensemble's capabilities.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.AnyToString

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.Detrend

getCapabilities() - Method in class weka.filters.unsupervised.attribute.DownSample

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.FFT

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.LogTransform

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

getCapabilities() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

getCapabilities() - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.PAA

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Returns the capabilities of this evaluator.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.RowSum

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.SAX

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.SetMissingValue

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

getCapabilities() - Method in class weka.filters.unsupervised.attribute.SpellChecker

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.attribute.StringToDate

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.AlignDataset

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.KeepRange

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.KennardStone

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.LatestRecords

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.RowNorm

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.Scale

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.Sort

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.SortOnAttribute

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns the Capabilities of this filter.

getCapabilities(Instances) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Returns the Capabilities of this filter, customized based on the data.

getCaseIndex(Actor, Token) - Method in class adams.flow.condition.bool.WekaClassification

Returns the index of the case that should get executed.

getCategory() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.AbstractWekaMenuItemDefinition

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.AppendDatasets

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.ArffViewer

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.BatchFilterDatasets

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.BoundaryVisualizer

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.CostCurve

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.DatasetCompatibility

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.GraphVisualizer

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.InstanceCompare

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.InstanceExplorer

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.InstancesPlot

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.MakeCompatibleDatasets

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.MarginCurve

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.MergeDatasets

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.PackageManager

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.PlotAttributeVsAttribute

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.ROC

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.SqlViewer

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.TreeVisualizer

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.WekaCommandToCode

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.menu.WekaInvestigator

Returns the category of the menu item in which it should appear, i.e., the name of the menu.

getCategory() - Method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem

The category for grouping menu items.

getCategory() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.CompareModels

The category for grouping menu items.

getCategory() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation

The category for grouping menu items.

getCategory() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem

The category for grouping menu items.

getCategory() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.CopySetup

The category for grouping menu items.

getCategory() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation

The category for grouping menu items.

getCell(int) - Method in class adams.ml.data.InstancesHeaderRow

Returns the cell with the given index, null if not found.

getCell(int) - Method in class adams.ml.data.InstanceView

Returns the cell with the given index, null if not found.

getCell(int, int) - Method in class adams.ml.data.InstancesView

Returns the corresponding cell or null if not found.

getCell(String) - Method in class adams.ml.data.InstancesHeaderRow

Returns the cell with the given key, null if not found.

getCell(String) - Method in class adams.ml.data.InstanceView

Returns the cell with the given key, null if not found.

getCellCount() - Method in class adams.ml.data.InstancesHeaderRow

Returns the number of cells stored in the row.

getCellCount() - Method in class adams.ml.data.InstanceView

Returns the number of cells stored in the row.

getCellEditor(int, int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTable

Returns the cell editor for the specified cell.

getCellIndex(String) - Method in class adams.ml.data.InstancesView

Returns the cell index of the specified cell (in the header row).

getCellKey(int) - Method in class adams.ml.data.InstancesHeaderRow

Returns the cell key with the given column index.

getCellKey(int) - Method in class adams.ml.data.InstanceView

Returns the cell key with the given column index.

getCellPadding() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the cell padding for the table.

getCellPopupMenuCustomizer() - Method in class adams.gui.visualization.instances.InstancesTable

Returns the current popup menu customizer (for the cells).

getCellPosition(String, String) - Method in class adams.ml.data.InstancesView

Returns the position of the cell or null if not found.

getCellRenderer(int, int) - Method in class adams.gui.visualization.instances.InstancesTable

Returns the renderer for this cell.

getCellRenderingCustomizer() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Returns the cell rendering customizer.

getCellSpacing() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the cell spacing for the table.

getCellValues(int) - Method in class adams.ml.data.InstancesView

Returns the unique string values of the specified column.

getCellValues(String) - Method in class adams.ml.data.InstancesView

Returns the unique string values of the specified column.

getCenterData() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Get whether to center (rather than standardize) the data.

getCharSet() - Method in class adams.flow.transformer.WekaTextDirectoryReader

Returns the character set in use.

getCheckBoxBatchFilter() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Returns the batch filter checkbox.

getCheckBoxKeepName() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Returns the keep name checkbox.

getCheckBoxReplace() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Returns the replace checkbox.

getCheckHeader() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns whether the header gets checked or not.

getCheckHeader() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns whether the header gets checked or not.

getClassAttribute() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the heuristic for determining the class attribute (if not explicitly set).

getClassAttributeHeuristic() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns the current class attribute heuristic.

getClassAttributeIndices() - Method in class adams.ml.data.InstancesView

Returns all the class attributes that are currently set.

getClassAttributeKeys() - Method in class adams.ml.data.InstancesView

Returns all the class attributes that are currently set.

getClassAttributeNames() - Method in class adams.ml.data.InstancesView

Returns all the class attributes that are currently set.

getClassAttributes() - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

Returns the regular expression for identifying the class attributes (besides an explicitly set one).

getClassCrossReferences() - Method in class adams.flow.transformer.WekaClustererPostProcessor

Returns the cross-referenced classes.

getClassCrossReferences() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the cross-referenced classes.

getClassCrossReferences() - Method in class adams.flow.transformer.WekaPredictionsToSpreadSheet

Returns the cross-referenced classes.

getClassCrossReferences() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the cross-referenced classes.

getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaASEvaluator

Returns the description of the class used in errors/undo points.

getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaASSearch

Returns the description of the class used in errors/undo points.

getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaClassifier

Returns the description of the class used in errors/undo points.

getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaClusterer

Returns the description of the class used in errors/undo points.

getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaDataGenerator

Returns the description of the class used in errors/undo points.

getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaFilter

Returns the description of the class used in errors/undo points.

getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaStreamableFilter

Returns the description of the class used in errors/undo points.

getClassDetails() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns whether the class details are output as well.

getClassDetails() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Returns whether the class details are output as well.

getClassDistribution() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the columns with the class distribution (nominal class).

getClassDistribution() - Method in class weka.classifiers.functions.FromPredictions

Returns the class distribution columns.

getClassDistributionIndices() - Method in class weka.classifiers.functions.FromPredictions

Returns the 0-based indices of the class distribution columns.

getClassFinder() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the finder to use for finding class attributes in the source datasets.

getClassificationEntry() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the value for the 'Name' column for the numeric classification.

getClassificationLabelEntry() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the value for the 'Name' column for the classification label.

getClassifier() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Returns the classifier.

getClassifier() - Method in class adams.flow.source.WekaClassifierSetup

Returns the classifier in use.

getClassifier() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

Returns the name of the callable classifier in use.

getClassifier() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns the name of the callable classifier in use.

getClassifier() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Returns the name of the callable classifier in use.

getClassifier() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Returns the classifier being used.

getClassifier() - Method in class adams.flow.transformer.WekaTrainClassifier

Returns the name of the callable classifier in use.

getClassifier() - Method in class adams.ml.model.classification.WekaClassifier

Returns the classifier to use.

getClassifier() - Method in class adams.ml.model.regression.WekaRegressor

Returns the classifier to use.

getClassifier() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the classifier in use.

getClassifier() - Method in class adams.multiprocess.WekaCrossValidationJob

Returns the classifier (should be built after the job finished).

getClassifier() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the currently set classifier.

getClassifier() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the currently set classifier.

getClassifier() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the classifier.

getClassifier() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Gets the classifier used by the filter.

getClassifier() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Gets the classifier used by the filter.

getClassifier(int) - Method in class weka.classifiers.meta.ClassificationViaRegressionD

Returns the classifier for the specified label index (0-based).

getClassifier(int) - Method in class weka.classifiers.meta.LeanMultiScheme

Gets a single classifier from the set of available classifiers.

getClassifierInstance() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

Returns an instance of the callable classifier.

getClassifierInstance() - Method in class adams.flow.transformer.WekaStreamEvaluator

Returns an instance of the callable classifier.

getClassifierInstance() - Method in class adams.flow.transformer.WekaTrainClassifier

Returns an instance of the callable classifier.

getClassifierInstance(MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns an instance of the callable classifier.

getClassifierInstance(MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Returns an instance of the callable classifier.

getClassifiers() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the classifiers.

getClassifiers() - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

Returns the current classifiers.

getClassifiers() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the classifiers per fold.

getClassifierSpec() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Gets the classifier specification string, which contains the class name of the classifier and any options to the classifier.

getClassifierSpec() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Gets the classifier specification string, which contains the class name of the classifier and any options to the classifier.

getClassifierWeights() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

getClassifyTab() - Method in class weka.gui.explorer.ExplorerExt

Returns the classify tab, if available.

getClassIndex() - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Returns the current index of class label (1-based).

getClassIndex() - Method in class adams.flow.source.WekaNewInstances

Returns the index of the class attribute.

getClassIndex() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the current index of class label (1-based).

getClassIndex() - Method in class adams.flow.transformer.WekaClassSelector

Returns the class index.

getClassIndex() - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Returns the current class label index (1-based).

getClassIndex() - Method in class adams.flow.transformer.WekaEvaluationValues

Returns the current range of class label indices (1-based).

getClassIndex() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Returns the current index of class label (1-based).

getClassIndex() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis

Returns the current index of class label (1-based).

getClassIndex() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Returns the current index of class label (1-based).

getClassIndex() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the current class index.

getClassIndex() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the current class index.

getClassIndex() - Method in class weka.classifiers.meta.ClassifierCascade

the class index.

getClassIndex() - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive

getClassIndex() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Gets the attribute on which misclassifications are based.

getClassIndex() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Gets the attribute on which misclassifications are based.

getClassLabel() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the class label index to use for class-specific measures.

getClassLabelIndex() - Method in class adams.data.conversion.WekaEvaluationToCostCurve

Returns the class label index (1-based index).

getClassLabelIndex() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve

Returns the class label index (1-based index).

getClassLabelIndex() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the index of the class label to use when generating per-class statistics.

getClassLabelIndex() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the index of the class label to use for statistics that work on a per-label-basis.

getClassLabelRange() - Method in class adams.flow.sink.WekaCostCurve

Returns the class label indices.

getClassLabelRange() - Method in class adams.flow.sink.WekaThresholdCurve

Returns the class label indices.

getClassLabelRange() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve

Returns the class label indices.

getClassLabelRange() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Returns the class label indices.

getClassLabels() - Method in class weka.classifiers.AggregateEvaluations

Returns the currently set class labels, if any.

getClassname() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the classname to be the handler for.

getClassname() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the classname to be the handler for.

getClassname() - Method in class adams.core.discovery.genetic.GenericInteger

Returns the classname to be the handler for.

getClassname() - Method in class adams.core.discovery.genetic.GenericString

Returns the classname to be the handler for.

getClassname() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode

Returns the classanme to use.

getClassName() - Method in class adams.flow.source.WekaNewInstances

Returns the name of the class attribute.

getClassName() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the name of the attribute to use as the class attribute for supervised summary filters.

getClassNoise() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Get the value of noise for the class.

getClassPathAugmentation() - Method in class adams.core.management.WekaPackagesClassPathAugmenter

Returns the classpath parts (jars, directories) to add to the classpath.

getClassType() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel

Returns the class type.

getClassType(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler

Returns the class type currently in use.

getClassWeightedAverageStatistic(String) - Method in class weka.classifiers.evaluation.Dice

Get the weighted (by class) average for this statistic.

getCleaner() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns the cleaner to use for cleaning the tokens from the initial tokenization.

getCleaners() - Method in class weka.core.tokenizers.cleaners.MultiCleaner

Returns the cleaners to use.

getClearBuffer() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns whether to clear the buffer once the dataset has been forwarded.

getClone() - Method in class adams.data.weka.WekaAttributeIndex

Returns a clone of the object.

getClone() - Method in class adams.data.weka.WekaAttributeRange

Returns a clone of the object.

getClone() - Method in class adams.data.weka.WekaLabelIndex

Returns a clone of the object.

getClone() - Method in class adams.data.weka.WekaLabelRange

Returns a clone of the object.

getClone() - Method in class adams.data.weka.WekaUnorderedAttributeRange

Returns a clone of the object.

getClone() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

Returns a clone of the object.

getClone() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel

Returns a clone of the object.

getClone() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Returns a clone of the object.

getClone() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel

Returns a clone of the object.

getClone() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

Returns a clone of the object.

getClone() - Method in class adams.ml.data.InstancesView

Returns a clone of itself.

getClone(SpreadSheet) - Method in class adams.ml.data.InstancesHeaderRow

Returns a clone of itself.

getClone(SpreadSheet) - Method in class adams.ml.data.InstanceView

Returns a clone of itself.

getClusterCentroids() - Method in class weka.clusterers.SAXKMeans

Gets the cluster centroids.

getClusterer() - Method in class adams.flow.source.WekaClustererSetup

Returns the clusterer in use.

getClusterer() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator

Returns the name of the callable clusterer in use.

getClusterer() - Method in class adams.flow.transformer.WekaTrainClusterer

Returns the clusterer in use.

getClusterer() - Method in class adams.ml.model.clustering.WekaClusterer

Returns the clusterer to use.

getClustererInstance() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator

Returns an instance of the callable clusterer.

getClustererInstance() - Method in class adams.flow.transformer.WekaTrainClusterer

Returns an instance of the callable clusterer.

getClusterNominalCounts() - Method in class weka.clusterers.SAXKMeans

Returns for each cluster the frequency counts for the values of each nominal attribute.

getClusterSizes() - Method in class weka.clusterers.SAXKMeans

Gets the number of instances in each cluster.

getClusterStandardDevs() - Method in class weka.clusterers.SAXKMeans

Gets the standard deviations of the numeric attributes in each cluster.

getClusterTab() - Method in class weka.gui.explorer.ExplorerExt

Returns the cluster tab, if available.

getCoefficients() - Method in class weka.filters.unsupervised.attribute.PublicPrincipalComponents

Get the components from the principal components model

getCoeffs() - Method in class weka.classifiers.meta.Corr

getColName() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

Returns the spreadsheet column with the name.

getColName() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall

Returns the spreadsheet column with the name.

getColor() - Method in class adams.gui.visualization.instance.InstanceContainer

Returns the current color in use.

getColor(int) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Returns the color for the data with the given index.

getColor(int) - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Returns the color for the data with the given index.

getColor(int) - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet

Returns the color for the data with the given index.

getColor(InstanceContainer) - Method in class adams.gui.visualization.instance.InstanceContainerManager

Returns the color for the container.

getColorBox() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Returns the class selection combo box if the parent component wants to place it in itself or in some component other than this component.

getColorField() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Returns the report field that contains the color.

getColoringIndex() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Get the coloring (class) index for the plot

getColorList() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Returns the list of colors to use.

getColorProvider() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the color provider in use.

getColorProvider() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Returns the color provider for the plots.

getColorProvider() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Returns the color provider to use.

getColorProvider() - Method in class adams.gui.visualization.instance.InstanceContainerManager

Returns the color provider to use.

getColumn() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the list of fields that identify a column.

getColumn() - Method in class adams.flow.transformer.WekaGetInstancesValue

Returns the column.

getColumn() - Method in class adams.flow.transformer.WekaSetInstancesValue

Returns the column index.

getColumn() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the list of fields that identify a column.

getColumn() - Method in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer

Returns the column index.

getColumnClass(int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

Returns the class type for the column.

getColumnClass(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel

Gets the class of elements in a column.

getColumnClass(int) - Method in class adams.gui.visualization.instance.InstanceTableModel

Returns the class for the column.

getColumnClass(int) - Method in class adams.gui.visualization.instances.InstancesTableModel

returns the most specific superclass for all the cell values in the column (always String)

getColumnCount() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

The number of columns.

getColumnCount() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel

Gets the number of columns: 3

getColumnCount() - Method in class adams.gui.visualization.instance.InstanceTableModel

Returns the number of columns in the table.

getColumnCount() - Method in class adams.gui.visualization.instances.InstancesTableModel

returns the number of columns in the model

getColumnCount() - Method in class adams.ml.data.InstancesView

Returns the number of columns.

getColumnFinder() - Method in class adams.data.weka.columnfinder.AbstractFilteredColumnFinder

Returns the column finder in use.

getColumnFinder() - Method in class adams.data.weka.datasetsplitter.ColumnSplitter

Gets the column finder.

getColumnFinder() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Returns the column finder used by the filter.

getColumnFinder() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the column finder which selects the attributes for summarisation.

getColumnFinders() - Static method in class adams.data.weka.columnfinder.AbstractColumnFinder

Returns a list with classnames of column finders.

getColumnName() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

Returns the selected column name.

getColumnName(int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

Returns the column name.

getColumnName(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel

Gets the name for a column.

getColumnName(int) - Method in class adams.gui.visualization.instance.InstanceTableModel

Returns the name of the column.

getColumnName(int) - Method in class adams.gui.visualization.instances.InstancesTableModel

returns the name of the column at columnIndex

getColumnName(int) - Method in class adams.ml.data.InstancesView

Returns the name of the specified column.

getColumnNames() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Returns the column names in use.

getColumnNames() - Method in class adams.ml.data.InstancesView

Returns a list of the names of all columns (i.e., the content the header row cells).

getColumns() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the size.

getColumns() - Method in class adams.data.weka.columnfinder.Constant

Gets the constant set of columns to find.

getColumns() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

getColumnSampleByLevel() - Method in class weka.classifiers.trees.XGBoost

Gets the sub-sample ratio of columns for each level.

getColumnSampleByNode() - Method in class weka.classifiers.trees.XGBoost

Gets the sub-sample ratio of columns for each node (split).

getColumnSampleByTree() - Method in class weka.classifiers.trees.XGBoost

Gets the sub-sample ratio of columns when constructing each tree.

getColVersion() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

Returns the (optional) spreadsheet column with the version.

getCombination() - Method in class adams.data.weka.columnfinder.MultiColumnFinder

Returns how the indices are combined.

getCombination() - Method in class adams.data.weka.rowfinder.MultiRowFinder

Returns how the indices are combined.

getCombination() - Method in class weka.classifiers.meta.ClassifierCascade

how to combine the statistics.

getCombinationRule() - Method in class weka.classifiers.meta.AbstainVote

Gets the combination rule used

getCombinationRule() - Method in class weka.classifiers.meta.SubsetEnsemble

Gets the combination rule used

getCombinationRule() - Method in class weka.classifiers.meta.VotedImbalance

Gets the combination rule used

getComment() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary

Returns the comment to output in the summary.

getComment() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the comment to output in the summary.

getComments() - Method in class adams.ml.data.InstancesView

Returns the comments.

getCommunication() - Method in class weka.classifiers.functions.PyroProxy

Returns the model proxy to use for communication.

getCommunication() - Method in interface weka.core.PyroProxyObject

Returns the handler for the communication.

getComparator() - Method in class adams.data.instance.Instance

Returns the comparator in use.

getComparator() - Static method in class adams.data.instance.InstanceUtils

Returns the comparator used for finding X values.

getComparator() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the comparator to use.

getComparator() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Returns a comparator for sorting the Instances.

getComparator() - Method in class weka.classifiers.AggregateEvaluations

Returns the comparator to use.

getComparators(int) - Method in class weka.classifiers.trees.RandomModelTrees

getComparisonField() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the comparison field.

getComparisonField() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the comparison field.

getCompleteRowsOnly() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Gets whether incomplete rows should be skipped.

getComplexityStatistics() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns whether the complexity stats are output as well.

getComplexityStatistics() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Returns whether the complexity stats are output as well.

getComponent() - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel

Returns the embedded component.

getComponent() - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel

Returns the embedded component.

getComponent() - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel

Returns the embedded component.

getComponentRange() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Returns the range of components to be used.

getComponents() - Method in class adams.data.instancesanalysis.FastICA

Returns the components.

getConfidenceLevel() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Returns the confidence level.

getConfusionMatrix() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns whether to output the confusion matrix as well.

getConfusionMatrix() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Returns whether to output the confusion matrix as well.

getContainer() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob

Returns the generated model container.

getContainer() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob

Returns the generated model container.

getContainerKeys() - Method in class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor

Returns the keys that the processor adds/modifies.

getContainerKeys() - Method in class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor

Returns the keys that the processor adds/modifies.

getContainerKeys() - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient

Returns the keys that the processor adds/modifies.

getContainerKeys() - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor

Returns the keys that the processor adds/modifies.

getContainerKeys() - Method in class adams.flow.transformer.wekaclusterer.PassThrough

Returns the keys that the processor adds/modifies.

getContainerManager() - Method in class adams.gui.visualization.instance.InstanceExplorer

Returns the current container manager.

getContainerPaintlet() - Method in class adams.gui.visualization.instance.InstancePanel

Returns the paintlet used for painting the containers.

getContainerPanel() - Method in class adams.gui.visualization.instance.InstanceZoomOverviewPaintlet

Returns the panel to obtain plot and containers from.

getContent() - Method in class adams.ml.data.DataCellView

Returns the content of the cell.

getContent(int) - Method in class adams.ml.data.InstancesHeaderRow

Returns the cell content with the given index.

getContent(int) - Method in class adams.ml.data.InstanceView

Returns the cell content with the given index.

getContentType() - Method in class adams.ml.data.DataCellView

Returns the content type.

getContentType(int) - Method in class adams.ml.data.InstancesView

Returns the pure content type of the given column, if available.

getContentTypes(int) - Method in class adams.ml.data.InstancesView

Returns the all content types of the given column, if available.

getConversion() - Method in class adams.core.base.AttributeTypeList

Returns the conversion of the string before setting its value.

getConversion() - Method in class weka.core.converters.SpreadSheetLoader

Returns the conversion in use for converting the spreadsheet into an Instances object.

getConverter() - Method in class adams.data.conversion.WekaCommandToCode

Returns the converter to use.

getCorrect() - Method in class weka.filters.unsupervised.attribute.SpellChecker

Returns the correct label.

getCorrection() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns the correction scheme to apply.

getCorrection() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns the correction scheme to apply.

getCorrection() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Returns the correction scheme to apply.

getCorrelation(Instance, Instance) - Method in class adams.tools.CompareDatasets

Returns the correlation between the two rows.

getCorrespondingReader() - Method in class adams.data.io.output.AbstractAdamsExperimentWriter

Returns, if available, the corresponding reader.

getCorrespondingReader() - Method in class adams.data.io.output.ArffSpreadSheetWriter

Returns, if available, the corresponding reader.

getCorrespondingReader() - Method in class adams.data.io.output.JsonAdamsExperimentWriter

Returns, if available, the corresponding reader.

getCorrespondingReader() - Method in class adams.data.io.output.JSONSpreadSheetWriter

Returns, if available, the corresponding reader.

getCorrespondingReader() - Method in class adams.data.io.output.LibSVMSpreadSheetWriter

Returns, if available, the corresponding reader.

getCorrespondingReader() - Method in class adams.data.io.output.MatlabSpreadSheetWriter

Returns, if available, the corresponding reader.

getCorrespondingReader() - Method in class adams.data.io.output.NestedAdamsExperimentWriter

Returns, if available, the corresponding reader.

getCorrespondingReader() - Method in class adams.data.io.output.SerializedAdamsExperimentWriter

Returns, if available, the corresponding reader.

getCorrespondingReader() - Method in class adams.data.io.output.SVMLightSpreadSheetWriter

Returns, if available, the corresponding reader.

getCorrespondingReader() - Method in class adams.data.io.output.XrffSpreadSheetWriter

Returns, if available, the corresponding reader.

getCorrespondingWriter() - Method in class adams.data.io.input.AbstractAdamsExperimentReader

Returns, if available, the corresponding writer.

getCorrespondingWriter() - Method in class adams.data.io.input.ArffSpreadSheetReader

Returns, if available, the corresponding writer.

getCorrespondingWriter() - Method in class adams.data.io.input.JsonAdamsExperimentReader

Returns, if available, the corresponding writer.

getCorrespondingWriter() - Method in class adams.data.io.input.JSONSpreadSheetReader

Returns, if available, the corresponding writer.

getCorrespondingWriter() - Method in class adams.data.io.input.LibSVMSpreadSheetReader

Returns, if available, the corresponding writer.

getCorrespondingWriter() - Method in class adams.data.io.input.MatlabSpreadSheetReader

Returns, if available, the corresponding writer.

getCorrespondingWriter() - Method in class adams.data.io.input.NestedAdamsExperimentReader

Returns, if available, the corresponding writer.

getCorrespondingWriter() - Method in class adams.data.io.input.SerializedAdamsExperimentReader

Returns, if available, the corresponding writer.

getCorrespondingWriter() - Method in class adams.data.io.input.SVMLightSpreadSheetReader

Returns, if available, the corresponding writer.

getCorrespondingWriter() - Method in class adams.data.io.input.XrffSpreadSheetReader

Returns, if available, the corresponding writer.

getCreateView() - Method in interface adams.data.weka.InstancesViewCreator

Returns whether to create only a view.

getCreateView() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns whether to create only a view.

getCreateView() - Method in class adams.flow.transformer.WekaRandomSplit

Returns whether to create only a view.

getCrossValidationSeed() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the current seed value for cross-validation.

getCrossValidationSeed() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the current seed value for cross-validation.

getCurrent() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog

Returns the current object.

getCurrent() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Returns the current value.

getCurrent() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

Returns the current object.

getCurrent() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel

Returns the current value.

getCurrent() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

Returns the current algorithm in use.

getCurrent() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the current file.

getCurrent() - Method in class adams.gui.wizard.WekaSelectDatasetPage

Returns the current value.

getCurrent() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

Returns the current files.

getCurrentAttributeRange() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the current range of attributes to use.

getCurrentClassIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the currently selected class index.

getCurrentDirectory() - Method in class adams.gui.chooser.DatasetFileChooserPanel

Returns the current directory in use by the file chooser.

getCurrentDirectory() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the current directory in use by the file chooser.

getCurrentDirectory() - Method in class adams.gui.wizard.WekaSelectDatasetPage

Returns the current directory in use by the file chooser.

getCurrentDirectory() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

Returns the current directory in use by the file chooser.

getCurrentFile() - Method in class weka.gui.explorer.ExplorerExt

Returns the current file.

getCurrentFitness() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the currently best fitness.

getCurrentIDIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the currently selected ID index.

getCurrentSortIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the currently selected sort index.

getCustomLoader() - Method in class adams.flow.transformer.WekaFileReader

Returns the custom loader in use.

getCustomLoader() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the custom loader in use.

getCustomLoader() - Method in class weka.filters.unsupervised.instance.AlignDataset

Returns the custom loader to use (if enabled).

getCustomLoader() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the custom loader to use (if enabled).

getCustomPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the custom paintlet.

getCustomPanel(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler

Returns the custom panel of the editor.

getCustomPropsFile() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the custom properties file to use for initializing the database setup instead of WEKA's default one.

getCustomPropsFile() - Method in class adams.flow.source.WekaDatabaseReader

Returns the custom properties file to use for initializing the database setup instead of WEKA's default one.

getCustomSaver() - Method in class adams.flow.sink.WekaFileWriter

Returns the custom saver in use.

getCustomStopMessage() - Method in class adams.flow.source.WekaSelectDataset

Returns the custom message to use when stopping the flow.

getCustomSupplyTextMenuItemCaption() - Method in class adams.flow.sink.WekaInstancesDisplay

Returns the text for the menu item.

getCustomSupplyTextMenuItemCaption() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the text for the menu item.

getCustomTextFileFilter() - Method in class adams.flow.sink.WekaInstancesDisplay

Returns a custom file filter for the file chooser.

getCustomTextFileFilter() - Method in class adams.flow.sink.WekaInstanceViewer

Returns a custom file filter for the file chooser.

getData() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

Returns the data to use for training and so forth.

getData() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Returns the actual underlying data.

getData() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer

Returns the actual underlying data.

getData() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Returns the currently loaded data.

getData() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

Returns the underlying data.

getData() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns the currently loaded data.

getData() - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource

Returns the currently loaded data.

getData() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Returns the currently loaded data.

getData() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Returns the currently loaded data.

getData() - Method in class adams.gui.visualization.instance.InstanceContainer

Returns the stored instance.

getData() - Method in class adams.gui.visualization.instance.InstanceContainerTableColumnNameGenerator

Returns the name of the column with the actual data in it.

getData() - Method in class adams.gui.visualization.instance.InstanceTable

Returns the underlying Instances object.

getData() - Method in class adams.gui.visualization.instance.InstanceTableModel

Returns the underlying data.

getData() - Method in class adams.ml.data.InstancesHeaderRow

Returns the underlying Instance.

getData() - Method in class adams.ml.data.InstancesView

Returns the underlying Instances.

getData() - Method in class adams.ml.data.InstanceView

Returns the underlying Instance.

getData() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the data in use.

getData() - Method in class weka.classifiers.AbstractSplitGenerator

Returns the original data.

getData() - Method in interface weka.classifiers.SplitGenerator

Returns the original data.

getData() - Method in class weka.core.InstanceGrouping

Returns the underlying data.

getData(Experiment) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Loads the experimental results.

getDatabaseConnection() - Method in class adams.data.instances.AbstractInstanceGenerator

Returns the currently used database connection object, can be null.

getDatabaseConnection() - Method in class adams.flow.transformer.AbstractInstanceGenerator

Returns the database connection to use.

getDatabaseID() - Method in class adams.gui.visualization.instance.InstanceContainer

Returns the database ID.

getDatabaseIDColumnIndex() - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Returns the index of the column with the database ID.

getDataDef() - Method in class adams.opt.genetic.PackDataGeneticAlgorithm

getDataDef() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection

getDataDef() - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm

getDataDef() - Method in class adams.opt.optimise.GeneticAlgorithm

getDataGenerator() - Method in class adams.flow.source.WekaDataGenerator

Returns the data generator in use.

getDataHashcode() - Method in class weka.gui.explorer.ExplorerExt

Returns the hashcode of the current dataset.

getDataPaintlet() - Method in class adams.gui.visualization.instance.InstancePanel

Returns the paintlet for painting the instance.

getDataRowClass() - Method in class adams.ml.data.InstancesView

Returns the class used for rows.

getDataRowType() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet

Returns the type of data row to use.

getDataset() - Method in class adams.flow.transformer.WekaStoreInstance

Returns the name of the dataset in internal storage to append to.

getDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Returns the dataset to index.

getDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Return the currently selected dataset.

getDataset() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the full dataset, can be null if none loaded.

getDataset() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the currently set filename of the dataset for cross-validation.

getDataSet() - Method in class weka.core.converters.SimpleArffLoader

Returns the full dataset.

getDataSet() - Method in class weka.core.converters.SpreadSheetLoader

Return the full data set.

getDataset1() - Method in class adams.tools.CompareDatasets

Returns the first dataset for the comparison.

getDataset2() - Method in class adams.tools.CompareDatasets

Returns the second dataset for the comparison.

getDatasetFormat() - Method in class adams.data.featureconverter.Weka

Returns the class of the dataset that the converter generates.

getDatasetHeader() - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader

Acquires the dataset header.

getDatasetHeader() - Method in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader

Acquires the header.

getDatasetHeader() - Method in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader

Acquires the header.

getDatasetHeader() - Method in class adams.data.instance.Instance

Returns the header of the underlying dataset.

getDatasetInfo() - Method in class adams.ml.model.classification.WekaClassificationModel

Returns information about the dataset used for building the model.

getDatasetInfo() - Method in class adams.ml.model.clustering.WekaClusteringModel

Returns information about the dataset used for building the model.

getDatasetInfo() - Method in class adams.ml.model.regression.WekaRegressionModel

Returns information about the dataset used for building the model.

getDatasetNames() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the list of names to use in attribute renaming in place of the {DATASET} keyword.

getDatasets() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

The datasets in use.

getDataSetups() - Method in class adams.opt.genetic.PackDataGeneticAlgorithm

getDataSetups() - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm

getDataSetups() - Method in class adams.opt.optimise.GeneticAlgorithm

getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Returns the list selection mode to use.

getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab

Returns the list selection mode to use.

getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Returns the list selection mode to use.

getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.DataTab

Returns the list selection mode to use.

getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab

Returns the list selection mode to use.

getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Returns the list selection mode to use.

getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

Returns the list selection mode to use.

getDataType() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns what type of data to retrieve from the Instances object.

getDataType() - Method in class adams.flow.transformer.WekaInstancesStatistic

Returns what type of data to retrieve from the Instances object.

getDataWidth() - Method in class adams.gui.visualization.instance.InstanceContainerTableColumnNameGenerator

Returns the width of the data column.

getDateFormat() - Method in class adams.ml.data.InstancesView

Returns the date formatter.

getDateTimeFormat() - Method in class adams.ml.data.InstancesView

Returns the date/time formatter.

getDateTimeMsecFormat() - Method in class adams.ml.data.InstancesView

Returns the date/time msec formatter.

getDBIDName() - Static method in class adams.data.weka.ArffUtils

Returns the name of the attribute containing the database ID.

getDebug() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Returns whether or not debugging output shouild be printed

getDebug() - Method in class weka.classifiers.meta.LeastMedianSq

Returns whether or not debugging output shouild be printed

getDebug() - Method in class weka.core.converters.SpreadSheetLoader

Gets whether additional debug information is printed.

getDebug() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

Returns whether to output debugging information.

getDefaultAlgorithm() - Method in class weka.classifiers.functions.PLSWeighted

Returns the default PLS filter.

getDefaultAlgorithm() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the default algorithm.

getDefaultAlgorithm() - Method in class weka.filters.supervised.attribute.PLS

Returns the default algorithm.

getDefaultAlpha() - Method in class weka.filters.supervised.attribute.YGradientEPO

Returns the default algorithm.

getDefaultAlpha() - Method in class weka.filters.supervised.attribute.YGradientGLSW

Returns the default algorithm.

getDefaultAttRegExp() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns the default regular expression for identifying the attributes to process.

getDefaultAttRegExp() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns the default regular expression for identifying the attributes to process.

getDefaultAttributeRange() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the default range of attributes to use.

getDefaultAttributeRange() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Returns the default regular expression for identifying the attributes to process.

getDefaultAttributeSelection() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the default attribute selection.

getDefaultAxisX() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot

Returns the setup for the X axis.

getDefaultAxisX() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the setup for the X axis.

getDefaultAxisY() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot

Returns the setup for the Y axis.

getDefaultAxisY() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the setup for the Y axis.

getDefaultBase() - Method in class weka.classifiers.meta.Fallback

Returns the default base classifier.

getDefaultBorder() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the default border thickness of the table.

getDefaultCaseIndex(Actor, Token) - Method in class adams.flow.condition.bool.WekaClassification

Returns the index of the default case.

getDefaultCellPadding() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the default cell padding for the table.

getDefaultCellSpacing() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the default cell spacing for the table.

getDefaultClassAttributes() - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

Returns the default regular expression for the class attributes.

getDefaultClassifier() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the default classifier to use.

getDefaultClassifier() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the default classifier.

getDefaultClassIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the default class index in use.

getDefaultClassname() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the default classname.

getDefaultClassname() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the default classname.

getDefaultClassname() - Method in class adams.core.discovery.genetic.GenericInteger

Returns the default classname.

getDefaultClassname() - Method in class adams.core.discovery.genetic.GenericString

Returns the default classname.

getDefaultClassName() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the name of the default attribute to use as the class attribute for supervised summary filters.

getDefaultCleaner() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns the default cleaner.

getDefaultCleaners() - Method in class weka.core.tokenizers.cleaners.MultiCleaner

Returns the default token cleaners.

getDefaultColor() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Returns the default color to use when no color information in the report.

getDefaultColorProvider() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Returns the default color provider to use.

getDefaultColorProvider() - Static method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Returns the default color provider to use.

getDefaultColumnFinder() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the default column finder which selects the attributes for summarisation.

getDefaultColumns() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the default size.

getDefaultColumns() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix

The number of PLS components

getDefaultCorrection() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns the default correction scheme.

getDefaultCorrection() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns the default correction scheme.

getDefaultCorrection() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Returns the default correction scheme.

getDefaultDatabaseConnection() - Method in class adams.data.instances.AbstractInstanceGenerator

Returns the default database connection.

getDefaultDatabaseConnection() - Method in class adams.gui.visualization.instance.InstancePanel

Returns the default database connection.

getDefaultDefaultClass() - Method in class adams.flow.source.valuedefinition.WekaGOEValueDefinition

Returns the default default class.

getDefaultDetector() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the default detector.

getDefaultDialogTitle() - Method in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceList

Returns the default title to use for dialogs.

getDefaultDialogTitle() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterEntryPanel

Returns the default title to use for dialogs.

getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixAdamsCSV

returns the default of whether column names are prefixed with the index.

getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixMediaWiki

returns the default of whether column names are prefixed with the index.

getDefaultExperiment() - Method in class adams.flow.source.WekaNewExperiment

Returns the default experiment.

getDefaultFallback() - Method in class weka.classifiers.meta.Fallback

Returns the default fallback classifier.

getDefaultFilter() - Method in class weka.classifiers.functions.PLSClassifierWeighted

Returns the default PLS filter.

getDefaultFilter() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings

Returns the default PLS filter.

getDefaultFind() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the default regular expression for finding tokens to clean.

getDefaultFormatExtension() - Method in class adams.data.io.input.AbstractAdamsExperimentReader

Returns the default extension of the format.

getDefaultFormatExtension() - Method in class adams.data.io.output.AbstractAdamsExperimentWriter

Returns the default extension of the format.

getDefaultGenerator() - Method in class adams.flow.transformer.AbstractInstanceGenerator

Returns the default generator.

getDefaultHandler() - Method in class adams.flow.sink.WekaExperimentFileWriter

Returns the default IO handler.

getDefaultHandler() - Method in class adams.flow.transformer.WekaExperimentFileReader

Returns the default IO handler.

getDefaultHeight() - Method in class adams.flow.sink.WekaAttributeSummary

Returns the default height for the dialog.

getDefaultHeight() - Method in class adams.flow.sink.WekaClassifierErrors

Returns the default height for the dialog.

getDefaultHeight() - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Returns the default height for the dialog.

getDefaultHeight() - Method in class adams.flow.sink.WekaCostCurve

Returns the default height for the dialog.

getDefaultHeight() - Method in class adams.flow.sink.WekaInstancesDisplay

Returns the default height for the dialog.

getDefaultHeight() - Method in class adams.flow.sink.WekaInstancesPlot

Returns the default height for the dialog.

getDefaultHeight() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the default height for the dialog.

getDefaultHeight() - Method in class adams.flow.sink.WekaMarginCurve

Returns the default height for the dialog.

getDefaultHeight() - Method in class adams.flow.sink.WekaThresholdCurve

Returns the default height for the dialog.

getDefaultIDIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the default ID index in use.

getDefaultIgnoredAttributes() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Returns the default regular expression for ignored/skipped attributes.

getDefaultInclueAttributes(int) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the default for the specified attribute type.

getDefaultIndex() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the default attribute index.

getDefaultIndex() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Returns the default index.

getDefaultIndex() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns the default attribute index.

getDefaultInitialSetupsProvider() - Method in class adams.opt.genetic.PackDataGeneticAlgorithm

Returns the default initial setups provider.

getDefaultLabel() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns the default label index.

getDefaultLabel() - Method in class weka.classifiers.meta.Veto

Returns the default label index.

getDefaultLabelRegExp() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns the default label regular expression.

getDefaultList() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the default list.

getDefaultList() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the default list.

getDefaultList() - Method in class adams.core.discovery.genetic.GenericInteger

Returns the default list.

getDefaultList() - Method in class adams.core.discovery.genetic.GenericString

Returns the default list.

getDefaultList() - Method in class adams.core.discovery.genetic.GPDGamma

Returns the default list.

getDefaultList() - Method in class adams.core.discovery.genetic.GPDNoise

Returns the default list.

getDefaultList() - Method in class adams.core.discovery.genetic.PLSFilterNumComponents

Returns the default list.

getDefaultList() - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints

Returns the default list.

getDefaultLocal() - Method in class weka.classifiers.meta.SocketFacade

Returns the default address of the return address.

getDefaultMainFilter() - Method in class weka.filters.FilteredFilter

Returns the default main filter.

getDefaultMaximum() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the default maximum.

getDefaultMaximum() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the default maximum.

getDefaultMaximum() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the default maximum.

getDefaultMaximum() - Method in class adams.core.discovery.genetic.GenericInteger

Returns the default maximum.

getDefaultMaximum() - Method in class adams.core.discovery.genetic.GPDGamma

Returns the default maximum.

getDefaultMaximum() - Method in class adams.core.discovery.genetic.GPDNoise

Returns the default maximum.

getDefaultMaximum() - Method in class adams.core.discovery.genetic.PLSFilterNumComponents

Returns the default maximum.

getDefaultMaximum() - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints

Returns the default maximum.

getDefaultMaximum() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix

Returns the default maximum.

getDefaultMenuItem() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

Returns the default name for the menu item.

getDefaultMenuItem() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

Returns the default name for the menu item.

getDefaultMenuItem() - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic

Returns the default name for the menu item.

getDefaultMenuItem() - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights

Returns the default name for the menu item.

getDefaultMenuItem() - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset

Returns the default name for the menu item.

getDefaultMinimum() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the default minimum.

getDefaultMinimum() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the default minimum.

getDefaultMinimum() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the default minimum.

getDefaultMinimum() - Method in class adams.core.discovery.genetic.GenericInteger

Returns the default minimum.

getDefaultMinimum() - Method in class adams.core.discovery.genetic.GPDGamma

Returns the default minimum.

getDefaultMinimum() - Method in class adams.core.discovery.genetic.GPDNoise

Returns the default minimum.

getDefaultMinimum() - Method in class adams.core.discovery.genetic.PLSFilterNumComponents

Returns the default minimum.

getDefaultMinimum() - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints

Returns the default minimum.

getDefaultMinimum() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix

Returns the default minimum.

getDefaultMinProbability() - Method in class weka.classifiers.meta.AbstainMinimumProbability

Returns the default minimum probability that the chosen class label must meet.

getDefaultMinProbability() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns the default minimum probability.

getDefaultMinSamples() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Returns the default minimum number of samples.

getDefaultN() - Method in class weka.filters.supervised.attribute.YGradientEPO

Returns the default algorithm.

getDefaultNumFolds() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the default number of folds to use in CV.

getDefaultNumPoints() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the default number of points.

getDefaultNumThreads() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the default number of threads to use for cross-validation.

getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaASEvaluator

Returns the default object to use.

getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaASSearch

Returns the default object to use.

getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaClassifier

Returns the default object to use.

getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaClusterer

Returns the default object to use.

getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaDataGenerator

Returns the default object to use.

getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaFilter

Returns the default object to use.

getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaStreamableFilter

Returns the default object to use.

getDefaultOutputType() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the default output type to use.

getDefaultOutputType() - Method in class adams.opt.genetic.DarkLord

Returns the default output type to use.

getDefaultOutputType() - Method in class adams.opt.genetic.Hermione

Returns the default output type to use.

getDefaultPackage() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Returns the default package of the types of setups to generate.

getDefaultPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Returns the default paintlet to use.

getDefaultPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the default paintlet to use.

getDefaultParameters() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Returns the default parameters.

getDefaultParameters() - Method in class adams.flow.source.WekaClassifierGenerator

Returns the default parameters.

getDefaultParameters() - Method in class adams.flow.source.WekaClustererGenerator

Returns the default parameters.

getDefaultParameters() - Method in class adams.flow.source.WekaFilterGenerator

Returns the default parameters.

getDefaultPostTokenizer() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns the default (post) token tokenizer.

getDefaultPreFilter() - Method in class weka.filters.FilteredFilter

Returns the default pre-filter.

getDefaultPrefix() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the default prefix for the new attributes.

getDefaultPreparation() - Method in class weka.classifiers.meta.SocketFacade

Returns the default data preparation scheme to use.

getDefaultPreprocessingType() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the default preprocessing type.

getDefaultPreprocessingType() - Method in class adams.data.instancesanalysis.pls.PRM

Returns the default preprocessing type.

getDefaultPreprocessingType() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns the default preprocessing type.

getDefaultPreTokenizer() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns the default (pre) token tokenizer.

getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixAdamsCSV

returns the default of whether column names or numbers instead are printed.

getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixMediaWiki

returns the default of whether column names or numbers instead are printed.

getDefaultProperty() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the default property.

getDefaultProperty() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the default property.

getDefaultProperty() - Method in class adams.core.discovery.genetic.GenericInteger

Returns the default property.

getDefaultProperty() - Method in class adams.core.discovery.genetic.GenericString

Returns the default property.

getDefaultRange() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the default attribute range.

getDefaultRange() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor

Returns the default range.

getDefaultRangePaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the default paintlet to use for the lower/upper statistics.

getDefaultReader() - Method in class adams.flow.transformer.WekaInstanceFileReader

Returns the default reader to use.

getDefaultReader() - Method in class adams.gui.chooser.AdamsExperimentFileChooser

Returns the default reader.

getDefaultReader() - Method in class adams.gui.chooser.WekaFileChooser

Returns the default reader.

getDefaultRegExp() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the default regular expression for identifying attributes.

getDefaultRegExp() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Returns the default regular expression.

getDefaultRemote() - Method in class weka.classifiers.meta.SocketFacade

Returns the default address of the remote process.

getDefaultReplace() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the default expression for replacing matching tokens with.

getDefaultRowFinder() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the default training data row selector.

getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixAdamsCSV

returns the default width for the row names.

getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixMediaWiki

returns the default width for the row names.

getDefaultRows() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the default size.

getDefaultRows() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix

This is the number of attributes

getDefaultRowSelection() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Returns the default row selection scheme.

getDefaultSampleSize() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Returns the default sample size.

getDefaultSeed() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the default seed value.

getDefaultSelectionProcessor() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Returns the default selection processor.

getDefaultSetup() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Returns the default setup.

getDefaultSetup() - Method in class adams.flow.source.WekaClassifierGenerator

Returns the default setup.

getDefaultSetup() - Method in class adams.flow.source.WekaClustererGenerator

Returns the default setup.

getDefaultSetup() - Method in class adams.flow.source.WekaFilterGenerator

Returns the default setup.

getDefaultSortIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the default sort index in use.

getDefaultSplits() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the default splits.

getDefaultSplits() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the default splits.

getDefaultSplits() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the default splits.

getDefaultSplits() - Method in class adams.core.discovery.genetic.GPDGamma

Returns the default splits.

getDefaultSplits() - Method in class adams.core.discovery.genetic.GPDNoise

Returns the default splits.

getDefaultSplits() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix

getDefaultSummaryFilter() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the default filter to use to summarise the attributes.

getDefaultSuperClass() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Returns the default super class, the same as the type "T" when defining the generics.

getDefaultSuperClass() - Method in class adams.flow.source.valuedefinition.WekaGOEValueDefinition

Returns the default super class.

getDefaultSuperClass() - Method in class adams.flow.source.WekaClassifierGenerator

Returns the default super class, the same as the type "T" when defining the generics.

getDefaultSuperClass() - Method in class adams.flow.source.WekaClustererGenerator

Returns the default super class, the same as the type "T" when defining the generics.

getDefaultSuperClass() - Method in class adams.flow.source.WekaFilterGenerator

Returns the default super class, the same as the type "T" when defining the generics.

getDefaultSupport() - Method in class weka.classifiers.meta.ConsensusOrVote

Returns the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.

getDefaultSupport() - Method in class weka.classifiers.meta.Veto

Returns the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.

getDefaultTimeout() - Method in class weka.classifiers.meta.SocketFacade

The default timeout in milli-second.

getDefaultTitle() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns the default title.

getDefaultTitle() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Returns the default title.

getDefaultTokenizers() - Method in class weka.core.tokenizers.MultiTokenizer

Returns the default token tokenizers.

getDefaultType() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the default regular expression for finding tokens to clean.

getDefaultWaveNoRegExp() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns the default regular expression for extracting the wave numbers.

getDefaultWaveNoRegExp() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns the default regular expression for extracting the wave numbers.

getDefaultWidth() - Method in class adams.flow.sink.WekaAttributeSummary

Returns the default width for the dialog.

getDefaultWidth() - Method in class adams.flow.sink.WekaClassifierErrors

Returns the default width for the dialog.

getDefaultWidth() - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Returns the default width for the dialog.

getDefaultWidth() - Method in class adams.flow.sink.WekaCostCurve

Returns the default width for the dialog.

getDefaultWidth() - Method in class adams.flow.sink.WekaInstancesDisplay

Returns the default width for the dialog.

getDefaultWidth() - Method in class adams.flow.sink.WekaInstancesPlot

Returns the default width for the dialog.

getDefaultWidth() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the default width for the dialog.

getDefaultWidth() - Method in class adams.flow.sink.WekaMarginCurve

Returns the default width for the dialog.

getDefaultWidth() - Method in class adams.flow.sink.WekaThresholdCurve

Returns the default width for the dialog.

getDefaultWorkspaceName() - Method in class adams.gui.tools.wekainvestigator.InvestigatorManagerPanel

The default name for a workspace.

getDefaultWorkspaceName() - Method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter

The default name for a workspace.

getDefaultWriter() - Method in class adams.gui.chooser.AdamsExperimentFileChooser

Returns the default writer.

getDefaultWriter() - Method in class adams.gui.chooser.WekaFileChooser

Returns the default writer.

getDefaultWriter() - Method in class weka.experiment.ResultMatrixAdamsCSV

Returns the default writer to use.

getDefaultXRegExp() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the default X regexp.

getDefaultYRegExp() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the default Y regexp.

getDeflationMode() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns the deflation mode to use.

getDerivativeOrder() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns the order of the derivative.

getDerivativeOrder() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns the order of the derivative.

getDesignVersion() - Method in class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors

Get the specific version of Weka the class is designed for.

getDesignVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrors

Get the specific version of Weka the class is designed for.

getDesignVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrorsPlot

Get the specific version of Weka the class is designed for.

getDesignVersion() - Method in class weka.gui.visualize.plugins.SaveGraph

Get the specific version of Weka the class is designed for.

getDesignVersion() - Method in class weka.gui.visualize.plugins.SaveTree

Get the specific version of Weka the class is designed for.

getDesignVersion() - Method in class weka.gui.visualize.plugins.ThresholdCurves

Get the specific version of Weka the class is designed for.

getDetector() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the detector.

getDev() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

getDialog(Dialog, Dialog.ModalityType) - Static method in class adams.gui.visualization.instance.HistogramFactory

Returns a new dialog for displaying histograms.

getDialog(Frame, boolean) - Static method in class adams.gui.visualization.instance.HistogramFactory

Returns a new dialog for displaying displaying histograms.

getDialogTitle() - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Returns the title for the dialog.

getDiameter() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the diameter of the cross.

getDiffer() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Gets the type of strategy to apply if the two values differ.

getDiffer() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Gets the type of strategy to apply if the two values differ.

getDisabled() - Static method in class adams.gui.goe.WekaEditorsRegistration.AccessiblePluginManager

Returns the disabled plugins.

getDiscardPredictions() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

Returns whether to discard the predictions in order to preserve memory.

getDiscardPredictions() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns whether to discard the predictions in order to preserve memory.

getDiscardPredictions() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Returns whether to discard the predictions in order to preserve memory.

getDiscardPredictions() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns whether to discard the predictions in order to preserve memory.

getDiscardPredictions() - Method in class adams.multiprocess.WekaCrossValidationJob

Returns whether the predictions are discarded.

getDisplay(InstanceContainer) - Method in class adams.gui.visualization.instance.InstanceContainerDisplayIDGenerator

Returns the display ID for the sequence.

getDisplayID() - Method in class adams.gui.visualization.instance.InstanceContainer

Returns the displayed container's ID.

getDisplayName() - Method in class weka.experiment.ResultMatrixAdamsCSV

returns the name of the output format.

getDisplayName() - Method in class weka.experiment.ResultMatrixMediaWiki

returns the name of the output format.

getDisplayStdDevs() - Method in class weka.clusterers.SAXKMeans

Gets whether standard deviations and nominal count.

getDistanceFunction() - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient

Returns the distance function to use.

getDistanceFunction() - Method in class weka.clusterers.SAXKMeans

returns the distance function currently in use.

getDistances() - Method in class weka.core.neighboursearch.NewNNSearch

Returns the distances of the k nearest neighbours.

getDistributionFormat() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the format for the 'Name' column for the numeric classification.

getDistributionSorting() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the format for the 'Name' column for the numeric classification.

getDominantEigenVector(Matrix) - Static method in class weka.core.matrix.MatrixHelper

determines the dominant eigenvector for the given matrix and returns it

getDontReplaceMissingValues() - Method in class weka.clusterers.SAXKMeans

Gets whether missing values are to be replaced.

getDropAbove() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Returns the threshold of the weights above which to drop instances.

getDropAtMost() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns the maximum percentage of instances to drop.

getDropBelow() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Returns the threshold of the weights below which to drop instances.

getDropBelow() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns the threshold of the normalized weights below which to drop instances.

getDropNonClassYs() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns whether to remove Y attributes from the output that are not the class attribute.

getEditor() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog

Returns the underlying editor.

getEditor() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

Returns the underlying editor.

getEliminateColinearAttributes() - Method in class weka.classifiers.functions.LinearRegressionJ

Get the value of EliminateColinearAttributes.

getEncoding() - Method in class adams.data.io.input.NestedAdamsExperimentReader

Returns the encoding to use.

getEncoding() - Method in class weka.core.converters.SimpleArffLoader

Returns the encoding to use.

getEncoding() - Method in class weka.core.converters.SimpleArffSaver

Returns the encoding to use.

getEnsureEqualValues() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets whether to check all data-sources for a merged attribute have the same value.

getEntryPanel() - Method in class weka.gui.explorer.MultiExplorer

Returns the panel with the explorer panel entries.

getError() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

getError() - Method in class weka.classifiers.meta.LeastMedianSq

getErrorAtPct(int) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

finds the median residual squared for the current regression.

getErrorAtPct(int) - Method in class weka.classifiers.meta.LeastMedianSq

finds the median residual squared for the current regression.

getErrorCalculation() - Method in class adams.flow.transformer.WekaBootstrapping

Returns how to calculate the errors for the percentiles.

getErrorScaler() - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator

Returns the scaling scheme.

getErrorScaler() - Method in class adams.flow.sink.WekaClassifierErrors

Returns the scheme to use for scaling the errors.

getErrorScalers() - Static method in class adams.data.weka.predictions.AbstractErrorScaler

Returns a list with classnames of scalers.

getEta() - Method in class weka.classifiers.trees.XGBoost

Gets the step size shrinkage to use in updates to prevent overfitting.

getEvaluation() - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator

Returns the underlying Evaluation object.

getEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

Returns the stored Evaluation object.

getEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns the stored Evaluation object.

getEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns the stored Evaluation object.

getEvaluation() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the generated (aggregated) evaluation.

getEvaluation() - Method in class adams.multiprocess.WekaCrossValidationJob

Returns the generated evaluation object.

getEvaluation(Token) - Method in class adams.flow.sink.WekaClassifierErrors

Returns the Evaluation object from the token.

getEvaluation(Token) - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Returns the Evaluation object from the token.

getEvaluation(Token) - Method in class adams.flow.sink.WekaCostCurve

Returns the Evaluation object from the token.

getEvaluation(Token) - Method in class adams.flow.sink.WekaMarginCurve

Returns the Evaluation object from the token.

getEvaluation(Token) - Method in class adams.flow.sink.WekaThresholdCurve

Returns the Evaluation object from the token.

getEvaluationPostProcessor() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the post-processing scheme for the evaluation.

getEvaluations() - Static method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation

Returns the available actions.

getEvaluations() - Static method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation

Returns the available actions.

getEvaluations() - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation

Returns the available actions.

getEvaluations() - Static method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation

Returns the available actions.

getEvaluations() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the generated evaluations (if multi-threaded or separated).

getEvaluationType() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the type of evaluation to perform.

getEvaluator() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns the evaluation method in use.

getEvaluator() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Returns the evaluator to use.

getEvaluator() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Returns the stored evaluator object.

getEvaluators() - Static method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Returns a list with classnames of evaluators.

getExactMatch() - Method in class adams.data.conversion.SwapPLS

Returns whether to use the complete command-line for comparison rather than just the class name.

getExample() - Method in class adams.data.weka.WekaAttributeIndex

Returns the example.

getExample() - Method in class adams.data.weka.WekaAttributeRange

Returns the example.

getExample() - Method in class adams.data.weka.WekaLabelIndex

Returns the example.

getExample() - Method in class adams.data.weka.WekaLabelRange

Returns the example.

getExample() - Method in class adams.data.weka.WekaUnorderedAttributeRange

Returns the example.

getExcludeClass() - Method in class weka.core.AbstractHashableInstance

Returns whether the class is excluded from the hashcode computation.

getExcludedAttributes() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the prefix separator string.

getExcludeWeight() - Method in class weka.core.AbstractHashableInstance

Returns whether the weight is excluded from the hashcode computation.

getExperiment() - Method in class adams.flow.source.WekaNewExperiment

Returns the experiment setup.

getExperiment() - Method in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog

Returns the experiment.

getExperiment() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

Returns the stored Evaluation object.

getExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Returns the current experiment.

getExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

Returns the current experiment.

getExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

Returns the current experiment.

getExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

Returns the current experiment.

getExperimentClass() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractAdamsExperimentIO

Returns the experiment superclass/interface.

getExperimentClass() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO

Returns the experiment superclass/interface.

getExperimentClass() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractWekaExperimentIO

Returns the experiment superclass/interface.

getExperimentClass() - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO

Returns the experiment superclass/interface.

getExperimentFile() - Method in class adams.flow.transformer.WekaExperiment

Returns the file the experiment is stored in.

getExperimentIO() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

Returns the handler for the IO, i.e., loading/saving of experiments.

getExperimentType() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the type of experiment to perform.

getExplorer() - Method in class weka.gui.explorer.ExperimentPanel

returns the parent Explorer frame.

getExplorer() - Method in class weka.gui.explorer.SqlPanel

returns the parent Explorer frame

getExplorerOptions(Explorer) - Static method in class weka.gui.explorer.WorkspaceHelper

Obtains the options from the explorer to be saved in the workspace.

getExplorerPanel() - Method in class weka.gui.explorer.panels.AbstractAdditionalExplorerPanel

Returns the panel to display.

getExplorerPanel() - Method in interface weka.gui.explorer.panels.AdditionalExplorerPanel

Returns the panel to display.

getExplorerPanelHandler() - Method in class weka.gui.explorer.panels.AbstractAdditionalExplorerPanel

Returns the associated panel handler.

getExplorerPanelHandler() - Method in interface weka.gui.explorer.panels.AdditionalExplorerPanel

Returns the associated panel handler.

getExpression() - Method in class weka.classifiers.functions.MathExpressionClassifier

Returns the mathematical expression to evaluate.

getExtensions() - Method in class adams.gui.tools.previewbrowser.InstanceExplorerHandler

Returns the list of extensions (without dot) that this handler can take care of.

getExtensions() - Method in class adams.gui.tools.previewbrowser.WekaDatasetHandler

Returns the list of extensions (without dot) that this handler can take care of.

getFallback() - Method in class weka.classifiers.meta.Fallback

Returns the fallback classifier.

getFastDistanceCalc() - Method in class weka.clusterers.SAXKMeans

Gets whether to use faster distance calculation.

getFavoritesClass() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

The class to use for the favorites (can be array class).

getFavoritesClass() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel

The class to use for the favorites (can be array class).

getFavorZeroes() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns whether 0s are favored over 1s.

getFeatureSelector() - Method in class weka.classifiers.trees.XGBoost

Gets the feature selection and ordering method.

getField() - Method in enum adams.flow.core.EvaluationStatistic

Returns the display string without the "numeric" or "nominal" in parentheses.

getField() - Method in enum adams.flow.core.ExperimentStatistic

Returns the display string without the "numeric" or "nominal" in parentheses.

getFieldName(AbstractField) - Static method in class adams.data.weka.ArffUtils

Returns the name of an attribute for a field.

getFields() - Method in class adams.data.conversion.ReportToWekaInstance

Returns the fields in use.

getFields() - Method in interface adams.data.instances.InstanceGeneratorWithFields

Returns the targets to add.

getFile() - Method in class adams.env.InstanceCompareDefinition

Returns the properties file name (no path) this definition is for.

getFile() - Method in class adams.env.InstanceExplorerDefinition

Returns the properties file name (no path) this definition is for.

getFile() - Method in class adams.env.WekaInvestigatorDefinition

Returns the properties file name (no path) this definition is for.

getFile() - Method in class adams.env.WekaInvestigatorShortcutsDefinition

Returns the properties file name (no path) this definition is for.

getFileChooser() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu

Returns the filechooser to use.

getFileChooser() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO

Returns the file chooser to use.

getFileChooser() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

Returns the file chooser to use for loading/saving of props files.

getFileChooser() - Method in class weka.gui.explorer.ExplorerExt

Returns the file chooser in use.

getFileChooserParameters() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Returns the file chooser for parameters.

getFileChooserTitle() - Method in class adams.flow.source.WekaSelectDataset

Returns the title for the file chooser dialog.

getFileDescription() - Method in class weka.core.converters.AArffLoader

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.SimpleArffLoader

Get a one line description of the type of file

getFileDescription() - Method in class weka.core.converters.SimpleArffSaver

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.SpreadSheetLoader

Returns a description of the file type.

getFileDescription() - Method in class weka.core.converters.SpreadSheetSaver

Returns a description of the file type.

getFileExtension() - Method in class weka.core.converters.SimpleArffLoader

Get the file extension used for this type of file

getFileExtension() - Method in class weka.core.converters.SpreadSheetLoader

Get the file extension used for this type of file

getFileExtension() - Method in class weka.core.converters.SpreadSheetSaver

Get the file extension used for this type of file

getFileExtensions() - Method in class weka.core.converters.SimpleArffLoader

Gets all the file extensions used for this type of file

getFileExtensions() - Method in class weka.core.converters.SimpleArffSaver

Gets all the file extensions used for this type of file

getFileExtensions() - Method in class weka.core.converters.SpreadSheetLoader

Gets all the file extensions used for this type of file

getFileExtensions() - Method in class weka.core.converters.SpreadSheetSaver

Gets all the file extensions used for this type of file

getFilename() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the currently selected filename, "" if none selected.

getFiles() - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

Returns the current files.

getFilter() - Method in class adams.data.spreadsheet.filter.WekaFilter

Returns the filter in use.

getFilter() - Method in class adams.data.weka.rowfinder.FilteredIQR

Returns the IQR filter.

getFilter() - Method in class adams.flow.transformer.WekaFilter

Returns the filter in use.

getFilter() - Method in class adams.flow.transformer.WekaStreamFilter

Returns the filter in use.

getFilter() - Method in class weka.classifiers.functions.ClassificationViaPLS

Get the PLS filter.

getFilter() - Method in class weka.classifiers.functions.PLSClassifierWeighted

Get the PLS filter.

getFilter() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

getFilter() - Method in class weka.core.neighboursearch.FilteredSearch

Gets the filter used.

getFilter() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Get the preprocessing filter.

getFilter(int) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Gets a single filter from the set of available filters.

getFilter(int) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Gets a single filter from the set of available filters.

getFilter(int, int) - Method in class weka.classifiers.meta.VotedImbalance

Gets a filter for a particular index.

getFilter(int, int, boolean) - Method in class weka.classifiers.meta.SubsetEnsemble

Gets a filter for a particular index.

getFilteredData() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob

Returns the filtered data.

getFilters() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Gets the list of possible filters to choose from.

getFilters() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Gets the list of possible filters to choose from.

getFilterSearch() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Returns the filter to generate the data for the search.

getFiltersInitialized() - Method in class adams.gui.chooser.AdamsExperimentFileChooser

Returns whether the filters have already been initialized.

getFiltersInitialized() - Method in class adams.gui.chooser.WekaFileChooser

Returns whether the filters have already been initialized.

getFilterSpec() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

getFilterSpec() - Method in class weka.core.neighboursearch.FilteredSearch

Gets the filter specification string, which contains the class name of the filter and any options to the filter

getFilterSpec(Filter) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

returns the filter classname and the options as one string.

getFilterSpec(Filter) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

returns the filter classname and the options as one string.

getFilterTrain() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Returns the filter to use for to generate the training data for the base classifier.

getFilterType() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Gets how the training data will be transformed.

getFilterType() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Gets how the training data will be transformed.

getFilterType() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Gets how the training data will be transformed.

getFilterType() - Method in class weka.classifiers.functions.GPD

Gets how the training data will be transformed.

getFinalModel() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns whether to build a final model on the full dataset.

getFind() - Method in class adams.flow.transformer.WekaRenameRelation

Returns the string to find.

getFind() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the regular expression to use for extracting the numeric part from the label.

getFinders() - Method in class adams.data.weka.columnfinder.MultiColumnFinder

Returns the column finders in use.

getFinders() - Method in class adams.data.weka.rowfinder.MultiRowFinder

Returns the row finders in use.

getFirstAttribute() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Gets the name of the first attribute.

getFirstAttributeRange() - Method in class adams.gui.InstanceCompare

Returns the first attribute range.

getFirstAttributeRange() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Returns the first attribute range.

getFirstDataset() - Method in class adams.gui.InstanceCompare

Returns the first dataset.

getFirstDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Returns the first dataset.

getFirstRange() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Returns the first attribute range to use (regular expression on attribute names).

getFirstRowIndex() - Method in class adams.gui.InstanceCompare

Returns the first row index.

getFirstRowIndex() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Returns the first row index.

getFitness() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the current fitness values.

getFlowContext() - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction

Returns the flow context, if any.

getFlowContext() - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction

Returns the flow context, if any.

getFlowContext() - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction

Returns the flow context, if any.

getFlowContext() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the flow context, if any.

getFlowContext() - Method in class adams.multiprocess.WekaCrossValidationJob

Returns the flow context, if any.

getFlowContext() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Return the flow context, if any.

getFlowContext() - Method in class weka.classifiers.functions.PyroProxy

Returns the flow context, if any.

getFlowFile() - Method in class weka.filters.FlowFilter

Returns the flow to process the data with.

getFold() - Method in class adams.multiprocess.WekaCrossValidationJob

Returns the fold index.

getFoldEvaluations() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns the stored Evaluation objects per fold.

getFoldModels() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns the stored Classifier objects per fold.

getFolds() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

Returns the number of folds for cross-validation.

getFolds() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the number of folds to use (only CV).

getFolds() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns the number of folds.

getFolds() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the number of folds to use.

getFolds() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Returns the number of folds.

getFolds() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Returns the number of folds.

getFolds() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the number of folds.

getFolds() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the number of folds to generate.

getFolds() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the number of folds.

getFolds() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Returns the number of folds.

getFolds() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

Returns the number of folds.

getFolds() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the number of folds.

getFolds() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Returns the number of cross-validation folds.

getFolds() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the number of folds to use in cross-validation.

getFolds() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the number of folds to use in cross-validation.

getForceCompression() - Method in class weka.core.converters.SimpleArffLoader

Gets whether the file gets interpreted as gzip-compressed ARFF file.

getFormat() - Method in class weka.filters.unsupervised.attribute.StringToDate

Returns the parse format to use.

getFormatDescription() - Method in class adams.data.io.input.AbstractAdamsExperimentReader

Returns a string describing the format (used in the file chooser).

getFormatDescription() - Method in class adams.data.io.input.AbstractWekaSpreadSheetReader

Returns a string describing the format (used in the file chooser).

getFormatDescription() - Method in class adams.data.io.input.InstanceReader

Returns a string describing the format (used in the file chooser).

getFormatDescription() - Method in class adams.data.io.input.JsonAdamsExperimentReader

Returns a string describing the format (used in the file chooser).

getFormatDescription() - Method in class adams.data.io.input.NestedAdamsExperimentReader

Returns a string describing the format (used in the file chooser).

getFormatDescription() - Method in class adams.data.io.input.SerializedAdamsExperimentReader

Returns a string describing the format (used in the file chooser).

getFormatDescription() - Method in class adams.data.io.output.AbstractAdamsExperimentWriter

Returns a string describing the format (used in the file chooser).

getFormatDescription() - Method in class adams.data.io.output.AbstractWekaSpreadSheetWriter

Returns a string describing the format (used in the file chooser).

getFormatDescription() - Method in class adams.data.io.output.JsonAdamsExperimentWriter

Returns a string describing the format (used in the file chooser).

getFormatDescription() - Method in class adams.data.io.output.NestedAdamsExperimentWriter

Returns a string describing the format (used in the file chooser).

getFormatDescription() - Method in class adams.data.io.output.SerializedAdamsExperimentWriter

Returns a string describing the format (used in the file chooser).

getFormatDescription() - Method in class adams.gui.visualization.debug.objectexport.WekaInstancesExporter

Returns a string describing the format (used in the file chooser).

getFormatExtensions() - Method in class adams.data.io.input.AbstractAdamsExperimentReader

Returns the extension(s) of the format.

getFormatExtensions() - Method in class adams.data.io.input.AbstractWekaSpreadSheetReader

Returns the extension(s) of the format.

getFormatExtensions() - Method in class adams.data.io.input.InstanceReader

Returns the extension(s) of the format.

getFormatExtensions() - Method in class adams.data.io.input.JsonAdamsExperimentReader

Returns the extension(s) of the format.

getFormatExtensions() - Method in class adams.data.io.input.NestedAdamsExperimentReader

Returns the extension(s) of the format.

getFormatExtensions() - Method in class adams.data.io.input.SerializedAdamsExperimentReader

Returns the extension(s) of the format.

getFormatExtensions() - Method in class adams.data.io.output.AbstractAdamsExperimentWriter

Returns the extension(s) of the format.

getFormatExtensions() - Method in class adams.data.io.output.AbstractWekaSpreadSheetWriter

Returns the extension(s) of the format.

getFormatExtensions() - Method in class adams.data.io.output.JsonAdamsExperimentWriter

Returns the extension(s) of the format.

getFormatExtensions() - Method in class adams.data.io.output.NestedAdamsExperimentWriter

Returns the extension(s) of the format.

getFormatExtensions() - Method in class adams.data.io.output.SerializedAdamsExperimentWriter

Returns the extension(s) of the format.

getFormatExtensions() - Method in class adams.gui.visualization.debug.objectexport.WekaInstancesExporter

Returns the extension(s) of the format.

getFormula() - Method in class adams.ml.data.DataCellView

Returns the formula.

getFull() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Returns the full dataset if present.

getGamma() - Method in class weka.classifiers.functions.GPD

Returns the gamma for the RBF kernel.

getGamma() - Method in class weka.classifiers.trees.XGBoost

Gets the minimum loss reduction required to make a further partition on a leaf node of the tree.

getGene(int, int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the value of the specified gene.

getGenerateLine() - Method in class adams.data.baseline.AbstractLinearRegressionBased

Returns whether to return the line as fake data or the corrected data.

getGenerateRules() - Method in class weka.classifiers.trees.m5.M5Base2

get whether rules are being generated rather than a tree

getGenerator() - Method in class adams.flow.transformer.AbstractInstanceGenerator

Returns the generator in use.

getGenerator() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the scheme for generating the folds.

getGenerator() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the scheme for generating the folds.

getGenerator() - Method in class adams.flow.transformer.WekaEnsembleGenerator

Returns the ensemble generator to use.

getGenerator() - Method in class adams.flow.transformer.WekaRandomSplit

Returns the scheme for generating the split.

getGenerator() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the scheme for generating the folds.

getGenerator() - Method in class adams.flow.transformer.WekaSplitGenerator

Returns the scheme for generating the split.

getGenerator() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

Returns the scheme for generating the folds.

getGenerator() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Returns the scheme for generating the split.

getGenerator() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the generator to use for generating the folds.

getGenerator() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the scheme for generating the folds.

getGenerators() - Static method in class adams.data.instances.AbstractInstanceGenerator

Returns a list with classnames of generators.

getGeneticAlgorithms() - Static method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns a list with classnames of genetic algorithms.

getGlue() - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Returns the glue to use.

getGOEEditor() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

Returns the underlying GOE editor.

getGrid() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Returns the grid size.

getGroup() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the replacement string to use as group (eg '$2').

getGroup() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns the replacement string to use as group (eg '$2').

getGroup() - Method in class adams.gui.visualization.instance.containerlistpopup.SaveAs

The group this customizer belongs to.

getGroup() - Method in class adams.gui.visualization.instance.containerlistpopup.ViewAsTable

The group this customizer belongs to.

getGroup() - Method in class adams.gui.visualization.instance.plotpopup.Adjust

The group this customizer belongs to.

getGroup() - Method in class adams.gui.visualization.instance.plotpopup.Histogram

The group this customizer belongs to.

getGroup() - Method in class adams.gui.visualization.instance.plotpopup.SaveVisible

The group this customizer belongs to.

getGroup() - Method in class adams.gui.visualization.instance.plotpopup.Viewport

The group this customizer belongs to.

getGroup() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the replacement string to use as group (eg '$2').

getGroup() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns the replacement string to use as group (eg '$2').

getGroup() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the replacement string to use as group (eg '$2').

getGroup() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns the replacement string to use as group (eg '$2').

getGroup() - Method in class weka.core.InstanceGrouping

The group expression, i.e., replacement string (eg '$2').

getGroup() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Returns the replacement string to use as group (eg '$2').

getGroups() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns the groups to generate.

getGrowPolicy() - Method in class weka.classifiers.trees.XGBoost

Gets the way new nodes are added to the tree.

getHandler() - Method in class adams.flow.sink.WekaExperimentFileWriter

Returns the IO handler.

getHandler() - Method in class adams.flow.transformer.WekaExperimentFileReader

Returns the IO handler.

getHandlers() - Method in class adams.opt.genetic.Hermione

Returns the currently set discovery handlers.

getHandlers() - Static method in class weka.gui.explorer.AbstractExplorerPanelHandler

Returns a list with classnames of handlers.

getHandlers() - Static method in class weka.gui.explorer.WorkspaceHelper

Returns all available handlers, with the DefaultHandler being the last one.

getHeader() - Method in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader

Returns the file to load the dataset header from.

getHeader() - Method in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader

Returns the name of the storage value representing the dataset header.

getHeader() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

Returns the stored training set header.

getHeader() - Method in class adams.ml.data.InstancesView

Returns the a spreadsheet with the same header and comments.

getHeaderPopupMenuCustomizer() - Method in class adams.gui.visualization.instances.InstancesTable

Returns the current popup menu customizer (for the header).

getHeaderRow() - Method in class adams.ml.data.InstancesView

Returns the header row.

getHiClassifier() - Method in class weka.classifiers.meta.HighLowSplit

getHiLopoint() - Method in class weka.classifiers.meta.HighLowSplit

getHistogramOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Get the options for the histogram.

getHistory() - Method in class weka.gui.explorer.MultiExplorer

Returns the underlying history panel.

getHitDetector() - Method in class adams.gui.visualization.instance.InstancePanel

Returns the hit detector.

getHoldOutPercentage() - Method in class weka.classifiers.meta.ClassifierCascade

the percentage to use for validation set to determine termination criterion (0-100).

getICA() - Method in class adams.data.instancesanalysis.FastICA

Returns the ICA analysis.

getIconName() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

Returns the file name of the icon.

getIconName() - Method in class adams.gui.menu.AbstractWekaMenuItemDefinition

Returns the file name of the icon.

getIconName() - Method in class adams.gui.menu.AppendDatasets

Returns the file name of the icon.

getIconName() - Method in class adams.gui.menu.BatchFilterDatasets

Returns the file name of the icon.

getIconName() - Method in class adams.gui.menu.BayesNetEditor

Returns the file name of the icon.

getIconName() - Method in class adams.gui.menu.DatasetCompatibility

Returns the file name of the icon.

getIconName() - Method in class adams.gui.menu.InstanceCompare

Returns the file name of the icon.

getIconName() - Method in class adams.gui.menu.InstanceExplorer

Returns the file name of the icon.

getIconName() - Method in class adams.gui.menu.MakeCompatibleDatasets

Returns the file name of the icon.

getIconName() - Method in class adams.gui.menu.MergeDatasets

Returns the file name of the icon.

getIconName() - Method in class adams.gui.menu.WekaInvestigator

Returns the file name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotColumn

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotRow

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.Binning

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.DataSort

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.Histogram

Returns the name of the icon.

getIconName() - Method in interface adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItem

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Returns the name of the icon.

getIconName() - Method in class adams.gui.visualization.instances.instancestable.ViewCell

Returns the name of the icon.

getID() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the name of the attribute/field to use as ID in the display.

getID() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Returns the container ID.

getID() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer

Returns the container ID.

getID() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Returns the ID to use for the returned instances.

getID() - Method in class adams.gui.visualization.instance.InstanceContainer

Returns the container's ID.

getID() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Returns the attribute name/index of attribute with IDs.

getID() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the attribute name/index to use for identifying rows.

getIDAttributeName(Instances) - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Returns a unique attribute name for the ID attribute.

getIDName() - Static method in class adams.data.weka.ArffUtils

Returns the name of the attribute containing the ID of the data container.

getIDs(Instances, int) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Retrieves the IDs from the dataset.

getIDTest() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the attribute name/index to use for identifying rows in the test set.

getIgnoreClass() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

Gets whether to ignore the class.

getIgnoredAttributes() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Returns the regular expression for ignored/skipped attributes.

getIncludeAttributes(int) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns whether only numeric attributes should be used.

getIncludeClass() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns whether to include the class attribute in the comparison.

getIncludeClass() - Method in class weka.filters.unsupervised.instance.Sort

Returns whether to include the class attribute in the comparison.

getIncorrect() - Method in class weka.filters.unsupervised.attribute.SpellChecker

Returns the incorrect labels, blank-separated list.

getIncremental() - Method in class adams.flow.source.WekaDatabaseReader

Returns whether to output single Instance objects or just one Instances object.

getIndex() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer

Returns the index.

getIndex() - Method in class adams.data.weka.classattribute.AttributeIndex

Returns the index of the attribute to select.

getIndex() - Method in class adams.data.weka.relationname.AttributeIndex

Returns the index of the attribute to select.

getIndex() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the attribute index to use for grouping.

getIndex() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns the attribute index to use for grouping.

getIndex() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Returns the index of the classifier in the actor's input array.

getIndex() - Method in class adams.flow.transformer.WekaExtractArray

Returns the type of extraction to perform.

getIndex() - Method in class adams.flow.transformer.WekaGetInstanceValue

Returns the 1-based index of the attribuate value to retrieve from the Instance.

getIndex() - Method in class adams.flow.transformer.WekaSetInstanceValue

Returns the 1-based attribute index to set in the Instance.

getIndex() - Method in class adams.flow.transformer.WekaSubsets

Returns the index of the attribute to split on.

getIndex() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Returns the index, generates it if necessary.

getIndex() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the attribute index to use for grouping.

getIndex() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns the attribute index to use for grouping.

getIndex() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the attribute index to use for grouping.

getIndex() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns the attribute index to use for grouping.

getIndex() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Returns the attribute index to use for grouping.

getIndex() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the index of the attribute to convert.

getIndex() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Returns the attribute index to use for grouping.

getIndex() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns the index of the attribute to convert.

getIndices() - Method in class adams.data.instances.InstanceComparator

Returns the indices used for sorting.

getIndices() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Returns the indices of the (actual) selected rows.

getIndices() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns the attribute indices.

getInitialDirectory() - Method in class adams.flow.source.WekaSelectDataset

Returns the initial directory.

getInitialFiles() - Method in class adams.flow.source.WekaSelectDataset

Returns the initial files.

getInitializationMethod() - Method in class weka.clusterers.SAXKMeans

Get the initialization method to use

getInitializeOnce() - Method in class adams.flow.transformer.WekaFilter

Returns whether the filter gets initialized only with the first batch.

getInitializeOnce() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns whether the internal reorder filter gets initialized only with the first batch.

getInitialSetups() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

getInitialSetups() - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm

getInitialSetups(T) - Method in class adams.opt.genetic.initialsetups.PackDataInitialSetupsProvider

Provides the initial gene setup.

getInlineValue() - Method in class adams.gui.goe.WekaExperimentFileEditor

Returns the current value.

getInput() - Method in class adams.flow.transformer.WekaDatasetsMerge

Gets the input Instances to merge.

getInputs() - Method in class adams.ml.data.InstancesView

Returns a spreadsheet containing only the input columns, not class columns.

getInputType() - Method in class adams.data.io.input.AbstractWekaSpreadSheetReader

Returns how to read the data, from a file, stream or reader.

getInstance() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer

Returns the stored Instance.

getInstance(Instances, int, String, TIntList) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Returns the instance from the dataset with the specified ID.

getInstanceClass() - Method in class adams.flow.transformer.WekaNewInstance

Returns the class name of the Instance object to create.

getInstanceContainerList() - Method in class adams.gui.visualization.instance.InstanceExplorer

Returns the panel listing the instances.

getInstancePanel() - Method in class adams.gui.visualization.instance.AbstractInstancePaintlet

Returns the instance panel currently in use.

getInstancePanel() - Method in class adams.gui.visualization.instance.InstanceExplorer

Returns the panel for painting the instances.

getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel

Returns the underlying instances.

getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Returns the currently displayed instances.

getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

Returns the currently set data.

getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Returns the underlying data.

getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

Returns the instances currently in use.

getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

Returns the instances currently in use.

getInstances() - Method in class adams.gui.visualization.instance.InstancePanel

Returns the currently visible instances.

getInstances() - Method in class adams.gui.visualization.instances.InstancesPanel

Returns the currently displayed data.

getInstances() - Method in class adams.gui.visualization.instances.InstancesTable

returns the data

getInstances() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Returns the Instances to use.

getInstances() - Method in class adams.gui.visualization.instances.InstancesTableModel

returns the data

getInstances() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Returns the instances in use by the genetic algorithm.

getInstances() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the currently set dataset for cross-validation.

getInstances() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the currently set dataset for cross-validation.

getInstances(T) - Method in class adams.data.baseline.AbstractLinearRegressionBased

Returns a dataset containing the x and y values.

getInstancesActor() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Returns the callable actor from which to retrieve Instances in case of AbstractDatasetInstanceEvaluator-derived evaluators.

getInstancesHeader() - Method in class adams.ml.model.classification.WekaClassificationModel

Returns the Instances header used for building the model.

getInstancesHeader() - Method in class adams.ml.model.clustering.WekaClusteringModel

Returns the Instances header used for building the model.

getInstancesHeader() - Method in class adams.ml.model.regression.WekaRegressionModel

Returns the Instances header used for building the model.

getInstancesIndices() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Gets ranges of instances selected.

getInstancesValueAt(int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel

returns the double value of the underlying Instances object at the given position, -1 if out of bounds

getInt(int[], int, int) - Method in class adams.opt.optimise.genetic.PackData

getIntercept() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns the intercept of the function.

getInterceptSE() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns the standard error intercept of the function.

getInterval() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns the interval for outputting the Instances objects.

getInterval() - Method in class adams.flow.transformer.WekaStreamEvaluator

Returns the output interval.

getIntervals() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval

Returns the stored intervals.

getInverseTransform() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Gets whether to use the inverse transform.

getInverseTransform() - Method in class weka.filters.unsupervised.attribute.FFT

Returns whether to compute inverse.

getInvert() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Returns whether the matching sense of the capabilities is inverted.

getInvert() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns whether to invert the matching sense.

getInvert() - Method in class adams.flow.transformer.WekaRegexToRange

Get invert match?

getInvert() - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

Returns whether to invert the matching sense, ie keep only the emoticons rather than removing them.

getInvert() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Returns whether the invert the column indices.

getInvert() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Returns whether the invert the row indices.

getInvert() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Get whether selection is inverted.

getInvert() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Get whether selection is inverted.

getInvert() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns whether to invert the matching sense (ie keep rather than remove).

getInvert() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns whether to invert the matching sense.

getInvertMatchingSense() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns whether to invert the matching sense.

getInvertSelection() - Method in class weka.filters.unsupervised.instance.KennardStone

Gets if selection is to be inverted.

getInvertSelection() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Gets if selection is to be inverted.

getIqr() - Method in class adams.data.weka.rowfinder.FilteredIQR

Returns the iqr multiplier.

getItem() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane

Returns the underlying result item.

getItemClass() - Method in class adams.flow.source.WekaSelectDataset

Returns the base class of the items.

getItemClass() - Method in class adams.flow.source.WekaSelectObjects

Returns the based class of the items.

getItemClass() - Method in class adams.flow.transformer.WekaAttributeIterator

Returns the base class of the items.

getItemClass() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor

Returns the base class of the items.

getItemClass() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns the base class of the items.

getItemClass() - Method in class adams.flow.transformer.WekaInstanceFileReader

Returns the base class of the items.

getItemClass() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the base class of the items.

getItemClass() - Method in class adams.flow.transformer.WekaInstancesInfo

Returns the base class of the items.

getItemClass() - Method in class adams.flow.transformer.WekaRandomSplit

Returns the base class of the items.

getItemClass() - Method in class adams.flow.transformer.WekaSplitGenerator

Returns the base class of the items.

getItems(Class) - Static method in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper

Returns a sorted list of popup menu items for the specified superclass.

getIterations() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Gets the iterations use.

getJavaInitializationString() - Method in class adams.gui.goe.WekaExperimentFileEditor

Returns a representation of the current property value as java source.

getJobRunner() - Method in class adams.flow.transformer.WekaExperimentExecution

Returns the jobrunner for the experiment.

getJobRunner() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the jobrunner for the experiment.

getJobRunner() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the JobRunner, if any.

getJobRunnerSetup() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the JobRunnerSetup, if any.

getJobRunnerSetup() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the jobrunner setup in use.

getKeepAttributeNames() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns whether to keep the original attribute names.

getKeepAttributeNames() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns whether to keep the original attribute names.

getKeepExisting() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns whether any existing file is kept on first execution.

getKeepNumComponents() - Method in class adams.data.conversion.SwapPLS

Returns whether the 'number of components' of the old filter are retained.

getKeepOnlySingleUniqueID() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns whether to keep only a single instance of the unique ID attribute.

getKeepRelationName() - Method in class adams.flow.transformer.WekaFilter

Returns whether the filter doesn't change the relation name.

getKeepRelationName() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns whether the filter doesn't change the relation name.

getKeepRelationName() - Method in class adams.flow.transformer.WekaStreamFilter

Returns whether the filter doesn't change the relation name.

getKeepSupervisedClass() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets whether to keep the class attribute of the summary attributes in the final dataset.

getKernel() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Sets the kernel to use.

getKernel() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Gets the kernel to use.

getKernel() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Gets the kernel to use.

getKernel() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Gets the kernel to use.

getKey() - Method in class adams.env.InstanceCompareDefinition

Returns the key this definition is for.

getKey() - Method in class adams.env.InstanceExplorerDefinition

Returns the key this definition is for.

getKey() - Method in class adams.env.WekaInvestigatorDefinition

Returns the key this definition is for.

getKey() - Method in class adams.env.WekaInvestigatorShortcutsDefinition

Returns the key this definition is for.

getKeys() - Method in class adams.flow.source.WekaDatabaseReader

Returns the keys to use for identifying a single row (comma-separated list).

getKeySet() - Method in class adams.opt.optimise.genetic.PackData

getKNN() - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Gets the number of neighbours used for kernel bandwidth setting.

getKNN() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Gets the number of neighbours used for kernel bandwidth setting.

getLabel() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns the label index.

getLabel() - Method in class weka.classifiers.meta.Veto

Returns the label index.

getLabelIndex() - Method in class adams.flow.transformer.WekaInstancesInfo

Returns the index of the label to use.

getLabelIndex() - Method in class weka.classifiers.functions.ClassificationViaPLS

Get the label index of the class attribute to get the PLS matrices for.

getLabelMatch() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Returns the label for the matching rows.

getLabelNonMatch() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Returns the label for the non-matching rows.

getLabelRegExp() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns the regular expression for matching the labels to remove.

getLabelString() - Method in class weka.classifiers.functions.ClassificationViaPLS

Get the class attribute's label to get the PLS matrices for.

getLambda() - Method in class adams.data.instancesanalysis.pls.DIPLS

Returns the lambda.

getLambda() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns the sparsity parameter; determines sparseness.

getLambda() - Method in class adams.data.instancesanalysis.pls.VCPLS

Returns the lambda parameter.

getLambda() - Method in class weka.classifiers.trees.XGBoost

Gets the L2 regularisation term on weights.

getLastError() - Method in class weka.classifiers.AggregateEvaluations

Returns the error that occurred during the last operation.

getLastSetup(Class, boolean, boolean) - Method in class adams.gui.visualization.instances.InstancesTable

Returns any last setup if available.

getLenient() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns whether to tolerate attributes that are missing in the incoming data.

getLimit() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the limit to impose on the axes.

getListType() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

Returns the type of list to generate.

getLoader() - Method in class adams.gui.chooser.DatasetFileChooserPanel

Returns the current loader.

getLoadings() - Method in class adams.data.instancesanalysis.PCA

Returns the loadings.

getLoadings() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the loadings, if available.

getLoadings() - Method in class adams.data.instancesanalysis.pls.DIPLS

Returns the loadings, if available.

getLoadings() - Method in class adams.data.instancesanalysis.PLS

Returns the loadings.

getLoadings() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Returns the loadings, if available.

getLoadings() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns the loadings, if available.

getLoadings() - Method in class adams.data.instancesanalysis.pls.OPLS

Returns the loadings, if available.

getLoadings() - Method in class adams.data.instancesanalysis.pls.PLS1

Returns the loadings, if available.

getLoadings() - Method in class adams.data.instancesanalysis.pls.PRM

Returns the loadings, if available.

getLoadings() - Method in class adams.data.instancesanalysis.pls.SIMPLS

Returns the loadings, if available.

getLoadings() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns the loadings, if available.

getLoadings() - Method in class adams.data.instancesanalysis.pls.VCPLS

Returns the loadings, if available.

getLoadings() - Method in class weka.classifiers.functions.PLSWeighted

Returns the loadings, if available.

getLoadings() - Method in interface weka.core.GenericPLSMatrixAccess

Returns the loadings, if available.

getLoadings() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the loadings, if available.

getLoadings() - Method in class weka.filters.supervised.attribute.PLS

Returns the loadings, if available.

getLoadingsCalculations() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

returns the maximum number of attributes to use.

getLocal() - Method in class weka.classifiers.meta.SocketFacade

Returns the return address for the remote process to use.

getLocale() - Method in class adams.ml.data.InstancesView

Returns the current locale.

getLocations() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the locations of the data (indices/regular expressions on attribute name).

getLocations() - Method in class adams.flow.transformer.WekaInstancesStatistic

Returns the locations of the data (indices/regular expressions on attribute name).

getLoClassifier() - Method in class weka.classifiers.meta.HighLowSplit

getLog() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns the internal log buffer.

getLogPanel() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

Returns the log panel.

getLoHipoint() - Method in class weka.classifiers.meta.HighLowSplit

getLoHipoint() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

getLower() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Returns the lower value to output.

getLower() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Returns the lower value to output.

getLower() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Returns the lower value to output.

getLower() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the lower value to output.

getM5RootNode() - Method in class weka.classifiers.trees.m5.M5Base2

getM5RootNode() - Method in class weka.classifiers.trees.m5.Rule2

getMainFilter() - Method in class weka.filters.FilteredFilter

Returns the main filter in use.

getMakeClassLast() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns whether to make the class attribute the last attribute.

getMakeThreadSafe() - Method in class adams.flow.transformer.WekaModelReader

Returns whether to wrap classifier inside a threadsafe ThreadSafeClassifierWrapper wrapper.

getManualClassifier() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns the manual to use instead of obtaining it from the flow.

getManualClassifier() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Returns the manual to use instead of obtaining it from the flow.

getManualMax() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the maximum to use when using manual binning with user-supplied max/max enabled.

getManualMin() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the minimum to use when using manual binning with user-supplied min/max enabled.

getMappedAttributeName(AbstractMerge.SourceAttribute) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the name of the attribute in the merged dataset that the given source attribute maps to.

getMappedAttributeName(AbstractMerge.SourceAttribute) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Gets the name of the attribute in the merged dataset that the given source attribute maps to.

getMarkerExtent() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Returns the current marker extent (which is the width and height of the shape).

getMarkerShape(int) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Determines the shape to paint around the data points, based on the index of the data.

getMaskAsString() - Method in class adams.opt.genetic.DarkLord.DarkLordJob

Returns the "mask" of attributes as range string.

getMatrix() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess

Returns the name of matrix to extract.

getMatrix() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter

getMatrix() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

getMatrix(String) - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the matrix with the specified name.

getMatrix(String) - Method in class adams.data.instancesanalysis.pls.DIPLS

Returns the matrix with the specified name.

getMatrix(String) - Method in class adams.data.instancesanalysis.pls.KernelPLS

Returns the matrix with the specified name.

getMatrix(String) - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns the matrix with the specified name.

getMatrix(String) - Method in class adams.data.instancesanalysis.pls.OPLS

Returns the matrix with the specified name.

getMatrix(String) - Method in class adams.data.instancesanalysis.pls.PLS1

Returns the matrix with the specified name.

getMatrix(String) - Method in class adams.data.instancesanalysis.pls.PRM

Returns the matrix with the specified name.

getMatrix(String) - Method in class adams.data.instancesanalysis.pls.SIMPLS

Returns the matrix with the specified name.

getMatrix(String) - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns the matrix with the specified name.

getMatrix(String) - Method in class adams.data.instancesanalysis.pls.VCPLS

Returns the matrix with the specified name.

getMatrix(String) - Method in class weka.classifiers.functions.PLSWeighted

Returns the matrix with the specified name.

getMatrix(String) - Method in interface weka.core.GenericPLSMatrixAccess

Returns the matrix with the specified name.

getMatrix(String) - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the matrix with the specified name.

getMatrix(String) - Method in class weka.filters.supervised.attribute.PLS

Returns the matrix with the specified name.

getMatrix(Classifier) - Method in class adams.flow.transformer.WekaExtractPLSMatrix

Returns the spreadsheet representation of the chosen from the classifier.

getMatrix(Classifier) - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess

Returns the spreadsheet representation of the chosen from the classifier.

getMatrix(GenericPLSMatrixAccess) - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess

Returns the spreadsheet representation of the chosen from the classifier/filter.

getMatrix(PLSMatrixAccess) - Method in class adams.flow.transformer.WekaExtractPLSMatrix

Returns the spreadsheet representation of the chosen from the classifier/filter.

getMatrixNames() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the all the available matrices.

getMatrixNames() - Method in class adams.data.instancesanalysis.pls.DIPLS

Returns the all the available matrices.

getMatrixNames() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Returns the all the available matrices.

getMatrixNames() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns the all the available matrices.

getMatrixNames() - Method in class adams.data.instancesanalysis.pls.OPLS

Returns the all the available matrices.

getMatrixNames() - Method in class adams.data.instancesanalysis.pls.PLS1

Returns the all the available matrices.

getMatrixNames() - Method in class adams.data.instancesanalysis.pls.PRM

Returns the all the available matrices.

getMatrixNames() - Method in class adams.data.instancesanalysis.pls.SIMPLS

Returns the all the available matrices.

getMatrixNames() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns the all the available matrices.

getMatrixNames() - Method in class adams.data.instancesanalysis.pls.VCPLS

Returns the all the available matrices.

getMatrixNames() - Method in class weka.classifiers.functions.PLSWeighted

Returns the all the available matrices.

getMatrixNames() - Method in interface weka.core.GenericPLSMatrixAccess

Returns the all the available matrices.

getMatrixNames() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the all the available matrices.

getMatrixNames() - Method in class weka.filters.supervised.attribute.PLS

Returns the all the available matrices.

getMatrixType() - Method in class adams.flow.transformer.WekaExtractPLSMatrix

Returns the type of matrix to extract.

getMatrixValues() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Returns the type of values to generate.

getMax() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the maximum number of top-ranked classifiers to forward.

getMax() - Method in class weka.classifiers.trees.RandomModelTrees

getMax() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

getMax() - Method in class weka.filters.unsupervised.instance.Scale

Returns the maximum for the values.

getMaxAttributeNames() - Method in class adams.data.instancesanalysis.PCA

Returns the maximum number of attribute names.

getMaxAttributes() - Method in class adams.data.instancesanalysis.PCA

Returns the maximum attributes.

getMaxBin() - Method in class weka.classifiers.trees.XGBoost

Gets the maximum number of discrete bins to bucket continuous features.

getMaxClassRangePercentage() - Method in class weka.classifiers.meta.MinMaxLimits

Get the percentage of leeway to apply to the upper limit determaxed by the range of the class attribute in the training data.

getMaxDecimalPlaces() - Method in class weka.core.converters.SimpleArffSaver

Returns the maximum number of decimal places to print

getMaxDepth() - Method in class weka.classifiers.trees.XGBoost

Gets the maximum depth of a tree.

getMaxDifference() - Method in class weka.classifiers.meta.AbstainAverage

gets number of samples

getMaxDifference() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

gets number of samples

getMaxDifference() - Method in class weka.classifiers.meta.AbstainVote

gets number of samples

getMaxDisplayItems() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Returns the maximum number of array items to display via toString().

getMaxFactor() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns the upper limit for the multiplication factor for instances.

getMaxHandling() - Method in class weka.classifiers.meta.MinMaxLimits

Get how the upper limit is handled.

getMaximum() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the maximum.

getMaximum() - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns the maximum.

getMaximum() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Returns the maximum.

getMaximumAttributeNames() - Method in class adams.flow.transformer.WekaPrincipalComponents

Gets maximum number of attribute names to use.

getMaximumAttributeNames() - Method in class weka.core.neighboursearch.PCANNSearch

Gets maximum number of attributes to include in transformed attribute names.

getMaximumAttributeNames() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Gets maximum number of attributes to include in transformed attribute names.

getMaximumAttributes() - Method in class adams.flow.transformer.WekaPrincipalComponents

Gets maximum number of PC attributes to retain.

getMaximumAttributes() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Gets maximum number of PC attributes to retain.

getMaximumDeltaStep() - Method in class weka.classifiers.trees.XGBoost

Gets the maximum delta step we allow each leaf output to be.

getMaximumIncluded() - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns whether the maximum is included.

getMaximumIncluded() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Returns whether the maximum is included.

getMaxIter() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Sets the inner NIPALS loop improvement tolerance.

getMaxIter() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns the NIPALS loop maximum number of iterations.

getMaxIter() - Method in class adams.data.instancesanalysis.pls.PRM

Returns the NIPALS loop maximum number of iterations.

getMaxIter() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns the NIPALS loop maximum number of iterations.

getMaxIterations() - Method in class weka.clusterers.SAXKMeans

gets the number of maximum iterations to be executed.

getMaxIterations() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Gets the maximum number of cleansing iterations performed

getMaxIterations() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Gets the maximum number of cleansing iterations performed

getMaxLabels() - Method in class adams.data.conversion.SpreadSheetToWekaInstances

Returns the name of the global actor in use.

getMaxLabels() - Method in class adams.data.spreadsheet.filter.WekaFilter

Returns the name of the global actor in use.

getMaxLeaves() - Method in class weka.classifiers.trees.XGBoost

Gets the maximum number of nodes to be added.

getMaxLevels() - Method in class weka.classifiers.meta.ClassifierCascade

the maximum number of levels in the cascade.

getMaxManual() - Method in class weka.classifiers.meta.MinMaxLimits

Get the manual upper limit.

getMaxNeighbors() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns the maximum number of neighbors to find.

getMaxSize() - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler

Returns the maximum size for the errors.

getMaxTrainTime() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the maximum number of seconds to perform training.

getMaxVal() - Method in class adams.opt.optimise.genetic.PackDataDef.DataInfo

getMaxVersion() - Method in class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors

Get the maximum version of Weka, exclusive, the class is designed to work with.

getMaxVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrors

Get the maximum version of Weka, exclusive, the class is designed to work with.

getMaxVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrorsPlot

Get the maximum version of Weka, exclusive, the class is designed to work with.

getMaxVersion() - Method in class weka.gui.visualize.plugins.SaveGraph

Get the maximum version of Weka, exclusive, the class is designed to work with.

getMaxVersion() - Method in class weka.gui.visualize.plugins.SaveTree

Get the maximum version of Weka, exclusive, the class is designed to work with.

getMaxVersion() - Method in class weka.gui.visualize.plugins.ThresholdCurves

Get the maximum version of Weka, exclusive, the class is designed to work with.

getMeanStdev(Instance) - Method in class weka.filters.unsupervised.attribute.PAA

Return an array where the 1st value is the mean, and the 2nd the standard deviation of the attribute values.

getMeanStdev(Instance) - Method in class weka.filters.unsupervised.attribute.SAX

Return an array where the 1st value is the mean, and the 2nd the standard deviation of the attribute values.

getMeasure() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the measure used for ranking the classifiers.

getMeasure() - Method in enum adams.flow.transformer.WekaClassifierRanker.Measure

Returns the associated measure.

getMeasure() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Returns the measure for ranking.

getMeasure() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Returns the measure used for evaluating the fitness.

getMeasure() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the current measure for evaluating the fitness.

getMeasure() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the current measure for evaluating the fitness.

getMeasure(String) - Method in class weka.classifiers.trees.m5.M5Base2

Returns the value of the named measure

getMeasuresPrefix() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the prefix for the measure attributes.

getMenuBar() - Method in class adams.gui.tools.DatasetCompatibilityPanel

Creates a menu bar (singleton per panel object).

getMenuBar() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Creates a menu bar (singleton per panel object).

getMenuBar() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Creates a menu bar (singleton per panel object).

getMenuBar() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Creates a menu bar (singleton per panel object).

getMenuBar() - Method in class adams.gui.visualization.instance.InstanceExplorer

Creates a menu bar (singleton per panel object).

getMenuBar() - Method in class weka.gui.explorer.ExplorerExt

Creates a menu bar (singleton per panel object).

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

Returns the name for the menu item.

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

Returns the name for the menu item.

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.AttributeStatistics

Returns the name for the menu item.

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.Binning

Returns the name for the menu item.

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight

Returns the name for the menu item.

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.ColumnStatistic

Returns the name for the menu item.

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.DataSort

Returns the name for the menu item.

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.Histogram

Returns the name for the menu item.

getMenuItem() - Method in interface adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItem

Returns the name for the menu item.

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Returns the name for the menu item.

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.RowStatistic

Returns the name for the menu item.

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Returns the name for the menu item.

getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.ViewCell

Returns the name for the menu item.

getMenuItemText() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

Returns the (optional) cuistom menu item text.

getMenuItemText() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

Returns the (optional) cuistom menu item text.

getMergedIndex() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Gets the position for the merged attribute.

getMergedIndex() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Gets the position for the merged attribute.

getMergeMethod() - Method in class adams.flow.transformer.WekaDatasetsMerge

Gets the currently-set merge method.

getMessage() - Method in class adams.flow.transformer.WekaChooseAttributes

Returns the message to display to the user (variables get expanded).

getMetaDataColor() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the scheme for extracting the color from the meta-data.

getMetaLevelClassifier() - Method in class weka.classifiers.meta.PartitionedStacking

Returns the meta-level classifier.

getMethodNamePrediction() - Method in class weka.classifiers.functions.PyroProxy

Returns the name of the method to call for predictions.

getMethodNameTrain() - Method in class weka.classifiers.functions.PyroProxy

Returns the name of the method to call for training.

getMetricDescription() - Method in class weka.classifiers.evaluation.Bias

Get a short description of this metric (algorithm, forumulas etc.).

getMetricDescription() - Method in class weka.classifiers.evaluation.Dice

Get a short description of this metric (algorithm, forumulas etc.).

getMetricDescription() - Method in class weka.classifiers.evaluation.MSLE

Get a short description of this metric (algorithm, forumulas etc.).

getMetricDescription() - Method in class weka.classifiers.evaluation.RPD

Get a short description of this metric (algorithm, formulas etc.).

getMetricDescription() - Method in class weka.classifiers.evaluation.RSquared

Get a short description of this metric (algorithm, forumulas etc.).

getMetricDescription() - Method in class weka.classifiers.evaluation.SDR

Get a short description of this metric (algorithm, formulas etc.).

getMetricName() - Method in class weka.classifiers.evaluation.Bias

Get the name of this metric

getMetricName() - Method in class weka.classifiers.evaluation.Dice

Get the name of this metric

getMetricName() - Method in class weka.classifiers.evaluation.MSLE

Get the name of this metric

getMetricName() - Method in class weka.classifiers.evaluation.RPD

Get the name of this metric

getMetricName() - Method in class weka.classifiers.evaluation.RSquared

Get the name of this metric

getMetricName() - Method in class weka.classifiers.evaluation.SDR

Get the name of this metric

getMiddle(double[]) - Method in class weka.core.SAXDistance

Returns value in the middle of the two parameter values.

getMiddle(double[]) - Method in class weka.core.WeightedEuclideanDistance

Returns value in the middle of the two parameter values.

getMiddle(double[]) - Method in class weka.core.WeightedEuclideanDistanceRidge

Returns value in the middle of the two parameter values.

getMin() - Method in class weka.classifiers.trees.RandomRegressionForest

Gets the current leaf threshold.

getMin() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

getMin() - Method in class weka.filters.unsupervised.instance.Scale

Returns the minimum for the values.

getMinChildWeight() - Method in class weka.classifiers.trees.XGBoost

Gets the minimum sum of instance weights (hessian) needed in a child.

getMinClassRangePercentage() - Method in class weka.classifiers.meta.MinMaxLimits

Get the percentage of leeway to apply to the lower limit determined by the range of the class attribute in the training data.

getMinHandling() - Method in class weka.classifiers.meta.MinMaxLimits

Get how the lower limit is handled.

getMinimal() - Method in class weka.attributeSelection.LinearRegressionAttributeEval

Returns whether to be more memory conservative or being able to output the model as string.

getMinimal() - Method in class weka.classifiers.functions.LinearRegressionJ

Returns whether to be more memory conservative or being able to output the model as string.

getMinImprovement() - Method in class weka.classifiers.meta.ClassifierCascade

the minimum improvement between levels that the statistic must improve.

getMinimum() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the minimum.

getMinimum() - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns the minimum.

getMinimum() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Returns the minimum.

getMinimumIncluded() - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns whether the minimum is included.

getMinimumIncluded() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Returns whether the minimum is included.

getMinManual() - Method in class weka.classifiers.meta.MinMaxLimits

Get the manual lower limit.

getMinNumInstances() - Method in class weka.classifiers.trees.m5.M5Base2

Get the minimum number of instances to allow at a leaf node

getMinNumInstances() - Method in class weka.classifiers.trees.m5.Rule2

Get the minimum number of instances to allow at a leaf node

getMinNumInstances() - Method in class weka.classifiers.trees.m5.RuleNode2

Get the minimum number of instances to allow at a leaf node

getMinProbability() - Method in class weka.classifiers.meta.AbstainMinimumProbability

Returns the minimum probability that the chosen class label must meet.

getMinProbability() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns the minimum probability for the selected label.

getMinSamples() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Returns the minimum number of samples that are required for calculating IQR stats.

getMinVersion() - Method in class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors

Get the minimum version of Weka, inclusive, the class is designed to work with.

getMinVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrors

Get the minimum version of Weka, inclusive, the class is designed to work with.

getMinVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrorsPlot

Get the minimum version of Weka, inclusive, the class is designed to work with.

getMinVersion() - Method in class weka.gui.visualize.plugins.SaveGraph

Get the minimum version of Weka, inclusive, the class is designed to work with.

getMinVersion() - Method in class weka.gui.visualize.plugins.SaveTree

Get the minimum version of Weka, inclusive, the class is designed to work with.

getMinVersion() - Method in class weka.gui.visualize.plugins.ThresholdCurves

Get the minimum version of Weka, inclusive, the class is designed to work with.

getMissing() - Method in class adams.tools.CompareDatasets

Returns the first dataset for the comparison.

getModel() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

Returns the stored model object.

getModel() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns the stored model object.

getModel() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns the stored model object.

getModel() - Method in class adams.gui.visualization.instances.InstancesPanel

Returns the model in use.

getModel() - Method in class weka.classifiers.trees.m5.RuleNode2

Get the linear model at this node

getModel(Report) - Static method in class adams.gui.visualization.instance.InstanceReportFactory

Returns a new model for the given report.

getModelActor() - Method in class adams.flow.condition.bool.WekaClassification

Returns the callable actor to obtain the model from if model file is pointing to a directory.

getModelActor() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the filter source actor.

getModelActor() - Method in class adams.flow.transformer.WekaFilter

Returns the filter source actor.

getModelContainerClass() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the model container class that is supported.

getModelDescription() - Method in class adams.ml.model.classification.WekaClassificationModel

Gets a short string description of the model.

getModelDescription() - Method in class adams.ml.model.clustering.WekaClusteringModel

Gets a short string description of the model.

getModelDescription() - Method in class adams.ml.model.regression.WekaRegressionModel

Gets a short string description of the model.

getModelFile() - Method in class adams.flow.condition.bool.WekaClassification

Returns the file to load the model from.

getModelFile() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the file to load the model from.

getModelFile() - Method in class adams.flow.transformer.WekaFilter

Returns the file to load the model from.

getModelFromContainer(AbstractContainer) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Retrieves the model from the container.

getModelFromContainer(AbstractContainer, MessageCollection) - Method in class adams.flow.core.WekaClassifierModelLoader

Retrieves the model from the container.

getModelFromContainer(AbstractContainer, MessageCollection) - Method in class adams.flow.core.WekaClustererModelLoader

Retrieves the model from the container.

getModelFromContainer(AbstractContainer, MessageCollection) - Method in class adams.flow.core.WekaFilterModelLoader

Retrieves the model from the container.

getModelLoadingType() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the loading type.

getModelLoadingType() - Method in class adams.flow.transformer.WekaFilter

Returns the loading type.

getModelName() - Method in class weka.classifiers.functions.PyroProxy

Returns the name of the model to use.

getModelResetVariable() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the variable to monitor for changes in order to reset the model.

getModelStorage() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the filter storage item.

getModelStorage() - Method in class adams.flow.transformer.WekaFilter

Returns the filter storage item.

getMorphologies() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Returns the morphologies to apply.

getMultiplier() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev

Returns the multiplier for the stdev..

getN() - Method in class weka.core.SAXDistance

Returns the nth point setting.

getN() - Method in class weka.filters.supervised.attribute.YGradientEPO

Returns the number of eigenvectors to keep.

getName() - Method in class adams.data.weka.classattribute.ByExactName

Returns the name in use.

getName() - Method in class adams.data.weka.columnfinder.ByExactName

Returns the name in use.

getName() - Method in class adams.gui.goe.popupmenu.EncloseClassifier

The name used for sorting.

getName() - Method in class adams.gui.goe.popupmenu.EncloseClusterer

The name used for sorting.

getName() - Method in class adams.gui.goe.popupmenu.InvertInstancesColumnFinder

The name used for sorting.

getName() - Method in class adams.gui.goe.popupmenu.InvertInstancesRowFinder

The name used for sorting.

getName() - Method in class adams.gui.goe.popupmenu.PullUpClassifier

The name used for sorting.

getName() - Method in class adams.gui.goe.popupmenu.PullUpClusterer

The name used for sorting.

getName() - Method in class adams.gui.goe.popupmenu.PullUpInstancesColumnFinder

The name used for sorting.

getName() - Method in class adams.gui.goe.popupmenu.PullUpInstancesRowFinder

The name used for sorting.

getName() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

Returns the name of the item.

getName() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Returns the name of the evaluation (displayed in combobox).

getName() - Method in class adams.gui.visualization.instance.containerlistpopup.SaveAs

The name.

getName() - Method in class adams.gui.visualization.instance.containerlistpopup.ViewAsTable

The name.

getName() - Method in class adams.gui.visualization.instance.plotpopup.Adjust

The name.

getName() - Method in class adams.gui.visualization.instance.plotpopup.Histogram

The name.

getName() - Method in class adams.gui.visualization.instance.plotpopup.SaveVisible

The name.

getName() - Method in class adams.gui.visualization.instance.plotpopup.Viewport

The name.

getName() - Method in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer

Returns the name of the column.

getName() - Method in class adams.ml.data.InstancesView

Returns the name of the spreadsheet.

getName() - Method in class adams.opt.optimise.genetic.PackDataDef.DataInfo

getName(Attribute, int) - Method in class adams.data.weka.WekaLabelIndex

Returns the label name at the specified index.

getName(Attribute, int) - Method in class adams.data.weka.WekaLabelRange

Returns the column name at the specified index.

getName(Instances, int) - Method in class adams.data.weka.WekaAttributeIndex

Returns the column name at the specified index.

getName(Instances, int) - Method in class adams.data.weka.WekaAttributeRange

Returns the column name at the specified index.

getName(Instances, int) - Method in class adams.data.weka.WekaUnorderedAttributeRange

Returns the column name at the specified index.

getNameLowerCase() - Method in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer

Returns the name of the column in lowercase.

getNames() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Returns the names to use for the fusion subsets (corresponds to the subsets).

getNameServer() - Method in class weka.classifiers.functions.PyroProxy

Returns the address of the Pyro nameserver.

getNameServer() - Method in interface weka.core.PyroProxyObject

Returns the address of the Pyro nameserver.

getNameSuffix() - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem

Returns the name suffix of the item.

getNative() - Method in class adams.ml.data.DataCellView

Returns the cell as native object, according to its type.

getNearestNeighbourSearchAlgorithm() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns the current nearestNeighbourSearch algorithm in use.

getNestedItem(String) - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem

Returns the nested items by its name.

getNewFilter() - Method in class adams.data.conversion.SwapPLS

Returns the new PLS filter to replace with.

getNextInstance(Instances) - Method in class weka.core.converters.SimpleArffLoader

Not supported.

getNextInstance(Instances) - Method in class weka.core.converters.SpreadSheetLoader

SpreadSheetLoader is unable to process a data set incrementally.

getNextSelectedIndex(int[], int) - Method in class adams.data.weka.datasetsplitter.RowSplitter

Gets the next index selected by the row-finder.

getNoAdditionalFieldsPrefix() - Method in interface adams.data.instances.InstanceGeneratorWithAdditionalFields

Returns whether to drop the prefix for the additional fields.

getNoCheck() - Method in class adams.flow.transformer.WekaExperiment

Returns whether to avoid the check at setUp time whether the experiment file is present or not.

getNoise() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Get the value of noise.

getNoise() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Get the value of noise.

getNoise() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Get the value of noise.

getNoise() - Method in class weka.classifiers.functions.GPD

Get the value of noise.

getNominal() - Method in class weka.filters.unsupervised.attribute.SAX

Gets whether output numeric or nominal values.

getNoReplacement() - Method in class weka.classifiers.meta.VotedImbalance

Gets whether instances are drawn with or without replacement.

getNormaliseType() - Method in class weka.classifiers.trees.XGBoost

Gets the type of normalisation algorithm.

getNormalize() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns whether to normalize the data before generating the histogram.

getNormalPlotOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

get the options for the normal plot.

getNormYWeights() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns whether to normalize Y weights.

getNoteName(String) - Static method in class adams.data.weka.ArffUtils

Returns the name of an attribute for a note.

getNotes() - Method in class adams.data.instance.Instance

Returns the currently stored notes.

getNotes() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the notes for the experiment.

getNoUpdate() - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Returns whether to suppress the update of the nearest-neighbor search algorithm when making predictions.

getNoUpdate() - Method in class weka.classifiers.lazy.LWLSynchro

Returns whether to suppress the update of the nearest-neighbor search algorithm when making predictions.

getNoUpdate() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

Returns whether to suppress the update of the nearest-neighbor search algorithm when making predictions.

getNoUpdate() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Returns whether to suppress the update of the nearest-neighbor search algorithm when making predictions.

getNoUpdate() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns whether to suppress the update of the nearest-neighbor search algorithm when making predictions.

getNthPoint() - Method in class weka.filters.unsupervised.attribute.DownSample

Returns the nth point setting.

getNumattrs() - Method in class weka.classifiers.meta.Corr

getNumBalanced() - Method in class weka.classifiers.meta.VotedImbalance

Returns the number of balanced datasets to generate (= #classifiers).

getNumberFormat() - Method in class adams.ml.data.InstancesView

Returns the number formatter.

getNumberInSubset() - Method in class weka.filters.unsupervised.instance.KennardStone

Returns the number of rows to select in subset.

getNumberOfParallelTrees() - Method in class weka.classifiers.trees.XGBoost

Gets the number of parallel trees constructed during each iteration.

getNumberOfRounds() - Method in class weka.classifiers.trees.XGBoost

Gets the number of boosting rounds to perform.

getNumBins() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the number of bins to use in manual calculation.

getNumBits() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the number of required bits.

getNumBits(AbstractGeneticDiscoveryHandler[]) - Method in class adams.opt.genetic.Hermione

Get total number of bits for params

getNumBitsForAll(AbstractGeneticDiscoveryHandler[]) - Method in class adams.opt.genetic.Hermione

Get List containing number of bits used for params

getNumChrom() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the number of chromosomes to use.

getNumClusters() - Method in class weka.clusterers.SAXKMeans

gets the number of clusters to generate.

getNumCoefficients() - Method in class adams.data.instancesanalysis.pls.SIMPLS

returns the number of coefficients of W matrix to keep (rest gets zeroed).

getNumComponents() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

returns the maximum number of attributes to use.

getNumComponents() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

returns the maximum number of attributes to use.

getNumComponents() - Method in class weka.core.neighboursearch.PLSNNSearch

getNumComponents(Object) - Method in class adams.data.conversion.SwapPLS

Retrieves the number of components from the filter.

getNumCycles() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Returns the number of cycles to apply.

getNumDecimals() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the number of decimals to show in the bin description.

getNumDecimals() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Returns the currently set number of decimals.

getNumDecimals() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Returns the number of decimals to use for numeric values.

getNumDecimals() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Returns the number of decimals to use for numeric values.

getNumEvaluationBins() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Returns the number of bins to use during evaluation.

getNumExecutionSlots() - Method in class weka.classifiers.meta.SubsetEnsemble

Get the number of execution slots (threads) to use for building the members of the ensemble.

getNumExecutionSlots() - Method in class weka.classifiers.meta.VotedImbalance

Get the number of execution slots (threads) to use for building the members of the ensemble.

getNumExecutionSlots() - Method in class weka.clusterers.SAXKMeans

Get the degree of parallelism to use.

getNumFolds() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Returns the number of folds.

getNumFolds() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the number of folds.

getNumFolds() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns the number of folds.

getNumFolds() - Method in interface weka.classifiers.CrossValidationFoldGenerator

Returns the number of folds.

getNumFolds() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns the number of folds.

getNumFolds() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the number of folds.

getNumFolds() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the number of folds.

getNumFolds() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns the number of folds.

getNumFolds() - Method in class weka.classifiers.meta.ClassifierCascade

the number of folds for cross-validation.

getNumFolds() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the number of folds to use in CV.

getNumFolds() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Gets the number of cross-validation folds used by the filter.

getNumFolds() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Gets the number of cross-validation folds used by the filter.

getNumGenes() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the number of genes to use.

getNumInstances() - Method in class weka.classifiers.trees.m5.RuleNode2

Return the number of instances that reach this node.

getNumIterations() - Method in class weka.classifiers.trees.RandomModelTrees

Gets the number of iterations.

getNumIterations() - Method in class weka.classifiers.trees.RandomRegressionForest

Gets the number of iterations

getNumNames(Attribute) - Method in class adams.data.weka.WekaLabelIndex

Returns the number of labels that the attribute has.

getNumNames(Attribute) - Method in class adams.data.weka.WekaLabelRange

Returns the number of columns the dataset has.

getNumNames(Instances) - Method in class adams.data.weka.WekaAttributeIndex

Returns the number of columns the dataset has.

getNumNames(Instances) - Method in class adams.data.weka.WekaAttributeRange

Returns the number of columns the dataset has.

getNumNames(Instances) - Method in class adams.data.weka.WekaUnorderedAttributeRange

Returns the number of columns the dataset has.

getNumPoints() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

Returns the number of points to generate.

getNumPoints() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the number of points to output.

getNumPoints() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns the number of points to the left of a data point.

getNumPointsLeft() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns the number of points to the left of a data point.

getNumPointsRight() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns the number of points to the right of a data point.

getNumRandomFeatures() - Method in class weka.classifiers.meta.SubsetEnsemble

Returns the number of additional random features to use.

getNumRegressions() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

gets number of samples

getNumRegressions() - Method in class weka.classifiers.meta.LeastMedianSq

gets number of samples

getNumRows() - Method in class adams.data.conversion.WekaCapabilitiesToInstances

Returns the number of data rows to generate.

getNumSimplsCoefficients() - Method in class adams.data.instancesanalysis.pls.PRM

Returns the number of SIMPLS coefficients to keep.

getNumSubSamples() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the number of sub-samples to generate.

getNumThreads() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the number of threads in use.

getNumThreads() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the number of threads to use for cross-validation.

getNumThreads() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the number of threads to use for cross-validation.

getNumThreads() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the number of threads to use for cross-validation (only used if no JobRunnerSetup/JobRunner set).

getNumThreads() - Method in class weka.classifiers.meta.ClassifierCascade

the number of threads to use.

getNumThreads() - Method in class weka.classifiers.trees.XGBoost

Gets the number of parallel threads used to run XGBoost.

getNumThreads() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the number of threads to use for cross-validation.

getNumZeroes() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Returns the number of zeroes a row must have at least in order to be removed.

getObject() - Method in class adams.ml.data.DataCellView

Returns the object.

getObjective() - Method in class weka.classifiers.trees.XGBoost

Gets the learning objective.

getOffline() - Method in class adams.data.instances.AbstractInstanceGenerator

Returns whether the generator operates in offline mode.

getOldFilter() - Method in class adams.data.conversion.SwapPLS

Returns the old PLS filter to replace.

getOneDrop() - Method in class weka.classifiers.trees.XGBoost

Sets whether at least one tree is always dropped during the dropout.

getOneMissing() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Gets the type of strategy to apply if one of the values is missing.

getOneMissing() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Gets the type of strategy to apply if one of the values is missing.

getOnlyFirstBatch() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Returns whether to apply row finder during first batch.

getOnTheFly() - Method in class adams.flow.condition.bool.WekaClassification

Returns whether the model file gets built on the fly and might not be present at start up time.

getOnTheFly() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns whether the model file gets built on the fly and might not be present at start up time.

getOnTheFly() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns whether the reference file gets built on the fly and might not be present at start up time.

getOpenFileFilters() - Method in class adams.gui.chooser.AdamsExperimentFileChooser

Returns the file filters for opening files.

getOpenFileFilters() - Method in class adams.gui.chooser.WekaFileChooser

Returns the file filters for opening files.

getOperation() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns the way the buffer operates.

getOptimizer() - Method in class adams.flow.transformer.WekaClassifierOptimizer

Returns the optimizer in use.

getOptional() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns whether the callable sink is optional.

getOptions() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.attributeSelection.LinearRegressionAttributeEval

getOptions() - Method in class weka.classifiers.functions.ClassificationViaPLS

returns the options of the current setup

getOptions() - Method in class weka.classifiers.functions.FakeClassifier

returns the options of the current setup

getOptions() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.GeneticAlgorithm

returns the options of the current setup

getOptions() - Method in class weka.classifiers.functions.GPD

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.LinearRegressionJ

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.functions.MathExpressionClassifier

returns the options of the current setup

getOptions() - Method in class weka.classifiers.functions.PLSClassifierWeighted

returns the options of the current setup

getOptions() - Method in class weka.classifiers.functions.PLSWeighted

returns the options of the current setup

getOptions() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.lazy.LWLSynchro

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.meta.AbstainAttributePercentile

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.AbstainAverage

Gets the current settings of Vote.

getOptions() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Gets the current settings of Vote.

getOptions() - Method in class weka.classifiers.meta.AbstainingCascade

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.AbstainMinimumProbability

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.AbstainVote

Gets the current settings of Vote.

getOptions() - Method in class weka.classifiers.meta.ClassifierCascade

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.meta.Consensus

Gets the current settings of Vote.

getOptions() - Method in class weka.classifiers.meta.ConsensusOrVote

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.Corr

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.Fallback

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.FilteredClassifierExt

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.HighLowSplit

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.InputSmearing

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.LeastMedianSq

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.MinMaxLimits

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.meta.PartitionedStacking

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.meta.SocketFacade

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.meta.SubsetEnsemble

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.meta.SuppressModelOutput

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.Veto

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.classifiers.meta.VotedImbalance

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.trees.m5.M5Base2

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.trees.M5P2

Gets the current settings of the classifier.

getOptions() - Method in class weka.classifiers.trees.RandomModelTrees

Gets the current settings of the Classifier.

getOptions() - Method in class weka.classifiers.trees.RandomRegressionForest

Gets the current settings of the Classifier.

getOptions() - Method in class weka.clusterers.SAXKMeans

Gets the current settings of SimpleKMeans.

getOptions() - Method in class weka.core.AbstractSimpleOptionHandler

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.core.converters.SimpleArffLoader

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.core.converters.SimpleArffSaver

returns the options of the current setup

getOptions() - Method in class weka.core.converters.SpreadSheetLoader

Gets the setting

getOptions() - Method in class weka.core.converters.SpreadSheetSaver

returns the options of the current setup

getOptions() - Method in class weka.core.neighboursearch.FilteredSearch

getOptions() - Method in class weka.core.neighboursearch.NewNNSearch

Gets the current settings.

getOptions() - Method in class weka.core.neighboursearch.PCANNSearch

getOptions() - Method in class weka.core.neighboursearch.PLSNNSearch

getOptions() - Method in class weka.core.SAXDistance

Gets the current settings of the filter.

getOptions() - Method in class weka.core.tokenizers.cleaners.AbstractTokenCleaner

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.core.tokenizers.cleaners.MultiCleaner

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.core.tokenizers.MultiTokenizer

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.core.WeightedEuclideanDistanceRidge

Gets the current settings of the classifier.

getOptions() - Method in class weka.experiment.ResultMatrixMediaWiki

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.filters.FilteredFilter

Gets the current settings of the classifier.

getOptions() - Method in class weka.filters.FlowFilter

returns the options of the current setup.

getOptions() - Method in class weka.filters.SerializedFilter

returns the options of the current setup.

getOptions() - Method in class weka.filters.supervised.attribute.MultiPLS

returns the options of the current setup

getOptions() - Method in class weka.filters.supervised.attribute.PLS

returns the options of the current setup

getOptions() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.filters.supervised.attribute.YGradientEPO

returns the options of the current setup

getOptions() - Method in class weka.filters.supervised.attribute.YGradientGLSW

returns the options of the current setup

getOptions() - Method in class weka.filters.supervised.instance.RemoveOutliers

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Gets the current settings of the classifier.

getOptions() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.AnyToString

Gets the current settings of the Classifier.

getOptions() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

returns the options of the current setup

getOptions() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

returns the options of the current setup.

getOptions() - Method in class weka.filters.unsupervised.attribute.Detrend

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.filters.unsupervised.attribute.DownSample

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.filters.unsupervised.attribute.FastWavelet

returns the options of the current setup.

getOptions() - Method in class weka.filters.unsupervised.attribute.FFT

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Gets the current settings of the Classifier.

getOptions() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.LogTransform

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

returns the options of the current setup.

getOptions() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

returns the options of the current setup.

getOptions() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Gets the current settings of the Classifier.

getOptions() - Method in class weka.filters.unsupervised.attribute.PAA

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.SAX

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.SetMissingValue

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.filters.unsupervised.attribute.SpellChecker

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.attribute.StringToDate

Gets the current settings of the Classifier.

getOptions() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Gets the current settings of the classifier.

getOptions() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Gets the current settings of the classifier.

getOptions() - Method in class weka.filters.unsupervised.instance.AlignDataset

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Gets the current settings of the classifier.

getOptions() - Method in class weka.filters.unsupervised.instance.KeepRange

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.KennardStone

Gets the current settings of the classifier.

getOptions() - Method in class weka.filters.unsupervised.instance.LatestRecords

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

Gets the current option settings for the OptionHandler.

getOptions() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Gets the current settings of the classifier.

getOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor

Gets the current settings of the classifier.

getOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Gets the current settings of the classifier.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

returns the options of the current setup.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.Scale

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.Sort

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.SortOnAttribute

Gets the current settings of the filter.

getOptions() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Gets the current settings of the filter.

getOptions(Object) - Method in class adams.core.option.WekaCommandLineHandler

Returns the commandline options (without classname) of the specified object.

getOriginalIndices() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns the stored original indices.

getOriginalIndices() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the original indices.

getOtherParameters() - Method in class weka.classifiers.trees.XGBoost

Gets any other XGBoost parameters the user has set.

getOutput() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Returns the prediction output generator in use.

getOutput() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput

Returns the output generator in use.

getOutput() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the prediction output generator in use.

getOutputAdditionalStats() - Method in class weka.attributeSelection.LinearRegressionAttributeEval

Get whether to output additional statistics (such as std.

getOutputAdditionalStats() - Method in class weka.classifiers.functions.LinearRegressionJ

Get whether to output additional statistics (such as std.

getOutputAdditionalStats() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Get whether to output additional statistics (such as std.

getOutputArray() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Returns whether to output an array or a sequence of classifier setups.

getOutputBestSetup() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns whether to output the best setup for optimizers like GridSearch and MultiSearch.

getOutputBestSetup() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Returns whether the best setup is output in case of optimizers like GridSearch/MultiSearch.

getOutputBuffer() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the output buffer.

getOutputContainer() - Method in class adams.flow.transformer.WekaFilter

Returns whether to output a container with the filter alongside the filtered data or just the filtered data.

getOutputDirectory() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the currently set directory for the generated ARFF files.

getOutputDirectory() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the currently set directory for the generated ARFF files.

getOutputDistribution() - Method in class adams.flow.transformer.wekaclusterer.AddCluster

Returns whether to output the cluster distribution instead of the cluster index.

getOutputFile() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the file to store the experiment in.

getOutputFile() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Get output file.

getOutputFile() - Method in class adams.tools.CompareDatasets

Returns the first dataset for the comparison.

getOutputFormat() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the output format.

getOutputFormat() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

Returns the type of output format to generate.

getOutputFormat() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the output format in use for generating the output.

getOutputFormat() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns the current output format.

getOutputFormat() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the output format in use for generating the output.

getOutputGenerator() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem

Returns the output generator.

getOutputGenerator() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane

Returns the underlying output generator.

getOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Returns the current output generators.

getOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Returns the current output generators.

getOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Returns the current output generators.

getOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Returns the current output generators.

getOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Returns the current output generators.

getOutputHeader() - Method in class adams.data.instances.AbstractInstanceGenerator

Returns the current header.

getOutputHeader() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns whether to output the header of the result matrix as well.

getOutputHeader() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns whether to output the header of the result matrix as well.

getOutputIndices() - Method in class adams.flow.transformer.WekaAttributeIterator

Returns whether to output 1-based indices of matches instead of the names.

getOutputInstance() - Method in class adams.flow.transformer.WekaClassifying

Returns whether Instance objects are output instead of PredictionContainer ones.

getOutputModel() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Returns whether to output the clusterer model as well.

getOutputModel() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

Returns whether to output the clusterer model as well.

getOutputName() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the name to use for the merged dataset.

getOutputName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel

Returns the name to display in the GUI.

getOutputName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel

Returns the name to display in the GUI.

getOutputName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel

Returns the name to display in the GUI.

getOutputName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel

Returns the name to display in the GUI.

getOutputName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel

Returns the name to display in the GUI.

getOutputOnlyModel() - Method in class adams.flow.transformer.AbstractWekaModelReader

Returns whether only the model is output instead of the container.

getOutputPrefix() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns the current output prefix.

getOutputPrefixType() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the type of prefix to use for the output.

getOutputRelationName() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns whether the relation name is output as well.

getOutputs() - Method in class adams.ml.data.InstancesView

Returns a spreadsheet containing only output columns, i.e., the class columns.

getOutputType() - Method in class adams.data.io.output.AbstractWekaSpreadSheetWriter

Returns how the data is written.

getOutputType() - Method in class adams.flow.transformer.WekaFileReader

Returns how to output the data.

getOutputType() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the type of output to generate.

getOverlays() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the overlays to use in the plot.

getOverride() - Method in class adams.flow.transformer.WekaClassSelector

Returns whether any existing class index will be overriden or not.

getOverrideJobRunner() - Method in class adams.flow.transformer.WekaExperimentExecution

Returns whether to override the jobrunner of the experiment.

getOwner() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot

Returns the current owner.

getOwner() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Returns the owner.

getOwner() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Returns the owner.

getOwner() - Method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem

Returns the owner.

getOwner() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob

Returns the owner.

getOwner() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob

Returns the owner.

getOwner() - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource

Returns the owner of this source.

getOwner() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Returns the owner of this tab.

getOwner() - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane

Returns the owner.

getOwner() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Returns the owner.

getOwner() - Method in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel

Returns the experimenter this panel belongs to.

getOwner() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

Returns the setup panel this option panel belongs to.

getOwner() - Method in class adams.gui.visualization.instance.InstanceContainerManager

Returns the owning panel.

getOwner() - Method in class adams.gui.visualization.instance.InstancePointHitDetector

Returns the owner.

getOwner() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

Returns the owning panel.

getOwner() - Method in class adams.ml.data.DataCellView

Returns the row this cell belongs to.

getOwner() - Method in class adams.ml.data.InstanceView

Returns the spreadsheet this row belongs to.

getOwner() - Method in class adams.opt.optimise.GeneticAlgorithm.GAJob

Returns the owner.

getPackages() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

Returns the packages to output.

getPadding() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Gets the type of Padding to use.

getPaintlet() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the paintlet in use.

getPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Returns the paintlet to use for the plot.

getPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the paintlet to use.

getPaintMoment() - Method in class adams.gui.visualization.instance.AbstractInstancePaintlet

Returns when this paintlet is to be executed.

getPanel() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Returns a panel with options to display.

getPanel() - Static method in class adams.gui.visualization.instance.HistogramFactory

Returns an instance of a new panel for displaying histograms.

getPanel(Report) - Static method in class adams.gui.visualization.instance.InstanceReportFactory

Returns a new panel for the given report.

getPanel(String) - Method in class weka.gui.explorer.MultiExplorer

Returns the panel with the specified name.

getPanel(List<ReportContainer>) - Static method in class adams.gui.visualization.instance.InstanceReportFactory

Returns a new table for the given reports.

getPanelEvaluator() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Returns the panel with the evaluator.

getPanelForReports(List) - Static method in class adams.gui.visualization.instance.InstanceReportFactory

Returns a new table for the given reports.

getPanelGOE() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Returns the panel with the algorithm.

getPanelGOE() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Returns the panel with the algorithm.

getPanelGOE() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Returns the panel with the algorithm.

getPanelLeft() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Returns the left panel.

getPanelLeft() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Returns the left panel.

getPanelLeft() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Returns the left panel.

getPanelLeft() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Returns the left panel.

getPanelLeft() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Returns the left panel.

getPanelRight() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Returns the right panel.

getPanelRight() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Returns the right panel.

getPanelRight() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Returns the right panel.

getPanelRight() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Returns the right panel.

getPanelRight() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Returns the right panel.

getPanelRight() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Returns the panel on the right (for the analysis display).

getPanels() - Static method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

Returns a list with classnames of panels.

getPanels() - Static method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

Returns a list with classnames of panels.

getPanels() - Static method in class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel

Returns a list with classnames of panels.

getPanels() - Static method in class weka.gui.explorer.panels.AbstractAdditionalExplorerPanel

Returns a list with classnames of panels.

getPanelSearch() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Returns the panel with the search.

getParameterPanel() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

Returns the underlying property sheet panel.

getParameters() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Returns the setup parameters.

getParentComponentActor() - Method in class adams.flow.source.WekaSelectDataset

Returns the (optional) callable actor to use as parent component instead of the flow panel.

getParser() - Method in class weka.classifiers.functions.MathExpressionClassifier

Returns the parser to use.

getPassword() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the database password.

getPassword() - Method in class adams.flow.source.WekaDatabaseReader

Returns the database password.

getPct() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

getPct() - Method in class weka.classifiers.meta.LeastMedianSq

getPercent() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst

Returns the percentage to remove.

getPercentage() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns the split percentage.

getPercentage() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Returns the split percentage.

getPercentage() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the percentage (0-1).

getPercentage() - Method in class adams.flow.transformer.WekaRandomSplit

Returns the percentage (0-1).

getPercentage() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Returns the split percentage.

getPercentage() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Returns the split percentage.

getPercentage() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Returns the split percentage.

getPercentage() - Method in class weka.classifiers.DefaultRandomSplitGenerator

Returns the split percentage.

getPercentage() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns the split percentage.

getPercentage() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns the split percentage.

getPercentage() - Method in interface weka.classifiers.RandomSplitGenerator

Returns the split percentage.

getPercentile() - Method in class weka.classifiers.meta.AbstainAttributePercentile

getPercentiles() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the percentiles to calculate for the errors.

getPerformance() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

The generated performance.

getPerformTraining() - Method in class weka.classifiers.functions.PyroProxy

Returns whether to train the model as well.

getPlotData() - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator

Assembles and returns the plot.

getPlotInstances() - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator

Returns the generated dataset that is plotted.

getPlotName() - Method in class adams.flow.transformer.WekaAccumulatedError

Returns the current plot name.

getPLS() - Method in class weka.classifiers.trees.RandomRegressionForest

Gets the current number of PLS components to generate.

getPLS1bHat() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the PLS1 b "hat" matrix.

getPLS1bHat() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings

Returns the PLS1 b "hat" matrix.

getPLS1bHat() - Method in interface weka.core.PLSMatrixAccess

Returns the PLS1 b "hat" matrix.

getPLS1bHat() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings

Returns the PLS1 b "hat" matrix.

getPLS1P() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the PLS1 P matrix.

getPLS1P() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings

Returns the PLS1 P matrix.

getPLS1P() - Method in interface weka.core.PLSMatrixAccess

Returns the PLS1 P matrix.

getPLS1P() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings

Returns the PLS1 P matrix.

getPLS1RegVector() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the reg vector.

getPLS1RegVector() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings

Returns the reg vector.

getPLS1RegVector() - Method in interface weka.core.PLSMatrixAccess

Returns the reg vector.

getPLS1RegVector() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings

Returns the reg vector.

getPLS1W() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the PLS1 W matrix.

getPLS1W() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings

Returns the PLS1 W matrix.

getPLS1W() - Method in interface weka.core.PLSMatrixAccess

Returns the PLS1 W matrix.

getPLS1W() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings

Returns the PLS1 W matrix.

getPlugins() - Static method in class adams.gui.goe.WekaEditorsRegistration.AccessiblePluginManager

Returns the plugins.

getPolynomialOrder() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns the polynominal order.

getPolynomialOrder() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns the polynominal order.

getPopupMenu() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Generates the right-click popup menu.

getPopupMenu() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel

Generates the right-click popup menu.

getPopupMenu() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Creates and returns the popup menu.

getPostProcessor() - Method in class adams.flow.transformer.WekaClustererPostProcessor

Returns the post-processor in use.

getPostProcessor() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor

Returns the post-processor in use.

getPostProcessor() - Method in class adams.flow.transformer.WekaTrainClusterer

Returns the post-processor in use.

getPostProcessors() - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor

Returns the distance function to use.

getPostProcessors() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor

Returns the post-processors in use.

getPostTokenizer() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns the tokenizer to use for the final tokenization (after cleaning).

getPredicted() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the column with the predicted values.

getPredicted() - Method in class weka.classifiers.functions.FromPredictions

Returns the column with the predicted values.

getPredictedIndex() - Method in class weka.classifiers.functions.FromPredictions

Returns the predicted 0-based index.

getPredictedMax() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the upper limit in use for the predicted values.

getPredictedMin() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the lower limit in use for the predicted values.

getPrediction() - Method in class adams.flow.transformer.WekaAccumulatedError.SortablePrediction

Returns the stored prediction.

getPredictions() - Method in class weka.classifiers.AggregateEvaluations

Returns all the currently stored predictions.

getPredictions() - Method in class weka.classifiers.functions.FromPredictions

Returns the predictions that were loaded.

getPredictionsFile() - Method in class weka.classifiers.functions.FromPredictions

Returns the file with the predictions.

getPredictionType() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the type of prediction to perform.

getPredictMax() - Method in class weka.classifiers.functions.FakeClassifier

Returns the maximum value to predict.

getPredictMin() - Method in class weka.classifiers.functions.FakeClassifier

Returns the minimum value to predict.

getPredictor() - Method in class weka.classifiers.meta.Consensus

Returns the index of the classifier for making the actual predictions.

getPredictor() - Method in class weka.classifiers.trees.XGBoost

Gets the type of predictor algorithm to use.

getPredictWait() - Method in class weka.classifiers.functions.FakeClassifier

Returns the time in msec to wait when calling classifyInstance.

getPreferJobRunner() - Method in class adams.flow.transformer.WekaFilter

Returns whether to offload processing to a JobRunner instance if available.

getPreferJobRunner() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Returns whether to offload processing to a JobRunner instance if available.

getPreferJobRunner() - Method in class adams.flow.transformer.WekaTrainAssociator

Returns whether to offload processing to a JobRunner instance if available.

getPreferJobRunner() - Method in class adams.flow.transformer.WekaTrainClassifier

Returns whether to offload processing to a JobRunner instance if available.

getPreferJobRunner() - Method in class adams.flow.transformer.WekaTrainClusterer

Returns whether to offload processing to a JobRunner instance if available.

getPreferJobRunner() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator

Returns whether to offload processing to a JobRunner instance if available.

getPreFilter() - Method in class adams.data.weka.rowfinder.FilteredIQR

Returns the pre filter.

getPreFilter() - Method in class weka.filters.FilteredFilter

Returns the pre-filter in use.

getPreFilter() - Method in class weka.filters.unsupervised.instance.KennardStone

Returns the pre-filter to apply to the data to perform the search on.

getPrefix() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the optional prefix string.

getPrefix() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the prefix for the new attributes.

getPrefixDatasetsWithIndex() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns whether to prefix the datasets with the index.

getPrefixDatasetsWithIndex() - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ExperimentWithCustomizableRelationNames

Returns whether to prefix the datasets with the index.

getPrefixDatasetsWithIndex() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Returns whether to use the filename as relation name.

getPrefixDatasetsWithIndex() - Method in class weka.experiment.ExtExperiment

Returns whether to prefix the datasets with the index.

getPrefixes() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Gets the list of prefixes to use.

getPrefixes() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Gets the list of prefixes to use.

getPrefixSeparator() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the prefix separator string.

getPreparation() - Method in class weka.classifiers.meta.SocketFacade

Returns the data preparation scheme to use.

getPreprocessing() - Method in class weka.core.neighboursearch.PLSNNSearch

Gets the type of preprocessing to use

getPreprocessingType() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the type of preprocessing to perform.

getPreprocessingType() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Returns the type of preprocessing to perform.

getPreSelectedIndices(Instances) - Method in class adams.flow.transformer.WekaChooseAttributes

Returns the pre-selected indices.

getPreserveIDColumn() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets whether the first non-summary attribute should be treated as an ID and moved to the first attribute position.

getPreserveInstancesOrder() - Method in class weka.clusterers.SAXKMeans

Gets whether order of instances must be preserved.

getPreserveOrder() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns whether to preserve the order.

getPreserveOrder() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Returns whether to preserve the order.

getPreserveOrder() - Method in class adams.flow.transformer.WekaRandomSplit

Returns whether to preserve order and suppress randomization.

getPreserveOrder() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Returns whether to preserve the order.

getPreserveOrder() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Returns whether to preserve the order.

getPreserveOrder() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Returns whether to preserve the order.

getPreserveOrder() - Method in class weka.classifiers.DefaultRandomSplitGenerator

Returns whether to preserve the order.

getPreserveOrder() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns whether to preserve the order.

getPreserveOrder() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns whether to preserve the order.

getPreserveOrder() - Method in interface weka.classifiers.RandomSplitGenerator

Returns whether to preserve the order.

getPreTokenizer() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns the tokenizer to use for the initial tokenization (before cleaning).

getProbability() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer

Returns the probability.

getProcessor() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor

Returns the processor for the incoming classifier arrays.

getProcessType() - Method in class weka.classifiers.trees.XGBoost

Gets the type of boosting process to run.

getProperties() - Static method in class adams.gui.goe.WekaEditorsRegistration.AccessibleGenericObjectEditor

Returns the editor properties.

getProperties() - Static method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Returns the properties that define the editor.

getProperties() - Static method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns the properties that define the investigator.

getProperties() - Static method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Returns the properties that define the editor.

getProperties() - Static method in class adams.gui.visualization.instance.InstanceComparePanel

Returns the properties that define the editor.

getProperties() - Static method in class adams.gui.visualization.instance.InstanceExplorer

Returns the properties that define the editor.

getProperties() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

Returns the content of the page (ie parameters) as properties.

getProperties() - Method in class adams.gui.wizard.WekaSelectDatasetPage

Returns the content of the page (ie parameters) as properties.

getProperties() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

Returns the content of the page (ie parameters) as properties.

getProperty() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the property to manage.

getProperty() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the property to manage.

getProperty() - Method in class adams.core.discovery.genetic.GenericInteger

Returns the property to manage.

getProperty() - Method in class adams.core.discovery.genetic.GenericString

Returns the property to manage.

getPropertyDescriptor() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the property descriptor for the handled property.

getPropertyDescriptor() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the property descriptor for the handled property.

getPropertyDescriptor() - Method in class adams.core.discovery.genetic.GenericInteger

Returns the property descriptor for the handled property.

getPropertyDescriptor() - Method in class adams.core.discovery.genetic.GenericString

Returns the property descriptor for the handled property.

getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaASEvaluator

Returns the property name to look for.

getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaASSearch

Returns the property name to look for.

getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaClassifier

Returns the property name to look for.

getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaClusterer

Returns the property name to look for.

getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaDataGenerator

Returns the property name to look for.

getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaFilter

Returns the property name to look for.

getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaStreamableFilter

Returns the property name to look for.

getQuery() - Method in class adams.flow.source.WekaDatabaseReader

Returns the query to execute.

getQuickInfo() - Method in class adams.data.conversion.MapToWekaInstance

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.data.conversion.SwapPLS

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.data.spreadsheet.filter.WekaFilter

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Returns the quick info string to be displayed in the flow editor.

getQuickInfo() - Method in class adams.flow.condition.bool.WekaClassification

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.sink.WekaAttributeSummary

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.sink.WekaClassifierErrors

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.sink.WekaCostCurve

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.sink.WekaExperimentFileWriter

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.sink.WekaFileWriter

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.sink.WekaInstancesPlot

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.sink.WekaThresholdCurve

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.WekaAssociatorSetup

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.WekaClassifierSetup

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.WekaClustererSetup

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.WekaDatabaseReader

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.WekaDataGenerator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.WekaNewExperiment

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.WekaNewInstances

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.WekaPackageManagerAction

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.source.WekaSelectDataset

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.standalone.WekaPackageManagerAction

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.AbstractInstanceGenerator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.AbstractWekaModelReader

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaAccumulatedError

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaAttributeIterator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaBootstrapping

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaChooseAttributes

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaClassifierInfo

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaClassSelector

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaClustererInfo

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaClustererPostProcessor

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaDatasetsMerge

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaDatasetSplit

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaEnsembleGenerator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaEvaluationInfo

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaEvaluationValues

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaExperiment

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaExperimentExecution

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaExperimentFileReader

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaExtractArray

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaExtractPLSMatrix

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaFileReader

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaFilter

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaGetInstancesValue

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaGetInstanceValue

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaInstancesInfo

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaInstancesStatistic

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaModelReader

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaNewInstance

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaPackageManagerAction

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaPrincipalComponents

getQuickInfo() - Method in class adams.flow.transformer.WekaRandomSplit

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaRegexToRange

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaRenameRelation

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Returns a quick info about the object, which can be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaSetInstancesValue

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaSetInstanceValue

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaSplitGenerator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaStoreInstance

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaStreamEvaluator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaStreamFilter

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaSubsets

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaTextDirectoryReader

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaTrainAssociator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaTrainClassifier

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaTrainClusterer

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

Returns a quick info about the actor, which will be displayed in the GUI.

getQuickInfo() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator

Returns a quick info about the actor, which will be displayed in the GUI.

getRandom() - Method in class weka.classifiers.functions.FakeClassifier

Returns the random number generator to use.

getRandomize() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Returns whether to randomize the data.

getRandomize() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns whether to randomize the data.

getRandomize() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns whether to randomize the data.

getRandomize() - Method in interface weka.classifiers.CrossValidationFoldGenerator

Returns whether to randomize the data.

getRandomize() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns whether to randomize the data.

getRandomize() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns whether to randomize the data.

getRandomize() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns whether to randomize the data.

getRandomize() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns whether to randomize the data.

getRandomize() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Returns whether to randomize the data.

getRandomize() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns whether to include the class attribute in the comparison.

getRandomSeed() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

get the seed for the random number generator

getRandomSeed() - Method in class weka.classifiers.meta.LeastMedianSq

get the seed for the random number generator

getRange() - Method in class adams.flow.sink.WekaAttributeSummary

Returns the range of attributes to visualize.

getRange() - Method in class adams.flow.transformer.WekaAttributeIterator

Returns the range of attributes to operate on.

getRange() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Returns the range of attributes to use.

getRange() - Method in class weka.filters.unsupervised.attribute.AnyToString

Returns the attribute range to use.

getRange() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the attribute range.

getRange() - Method in class weka.filters.unsupervised.attribute.StringToDate

Returns the first attribute range to use (regular expression on attribute names).

getRange() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor

Returns the attribute range to work on.

getRange(int) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Gets a single Range from the set of available Ranges.

getRange(SelectOptionPanel) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Turns the selected attributes into a range string.

getRange1() - Method in class adams.tools.CompareDatasets

Returns the range of attributes of the first dataset.

getRange2() - Method in class adams.tools.CompareDatasets

Returns the range of attributes of the second dataset.

getRangePaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the paintlet to use for the lower/upper statistics.

getRanges() - Method in class adams.data.weka.rowfinder.ByNumericRange

Returns the intervals.

getRanges() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange

Returns the ranges to include.

getRanges() - Method in class weka.classifiers.meta.PartitionedStacking

Returns the attribute ranges for the base-classifiers.

getRanges() - Method in class weka.filters.unsupervised.attribute.detrend.RangeBased

Returns the wave number ranges.

getRanges() - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased

Returns the wave number ranges.

getRanges() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Gets the list of possible Ranges to choose from.

getRateDrop() - Method in class weka.classifiers.trees.XGBoost

Gets the dropout rate (a fraction of previous trees to drop during the dropout).

getReader() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Returns the spreadsheet reader to use.

getReader() - Method in class weka.classifiers.functions.FromPredictions

Returns the spreadsheet reader to use.

getReader() - Method in class weka.core.converters.SpreadSheetLoader

Returns the spreadsheet reader in use.

getReaderClass() - Method in class adams.gui.chooser.AdamsExperimentFileChooser

Returns the reader superclass for the GOE.

getReaderClass() - Method in class adams.gui.chooser.WekaFileChooser

Returns the reader superclass for the GOE.

getReaderForFile(File) - Method in class adams.gui.chooser.AdamsExperimentFileChooser

Returns the reader for the specified file.

getReaderForFile(File) - Method in class adams.gui.chooser.WekaFileChooser

Returns the reader for the specified file.

getReaders() - Static method in class adams.data.io.input.AbstractAdamsExperimentReader

Returns a list with classes of readers.

getReal() - Method in class weka.filters.unsupervised.attribute.FFT

Returns whether to return real or imaginary part.

getReduceNumberOfDistanceCalcsViaCanopies() - Method in class weka.clusterers.SAXKMeans

Get whether to use canopies to reduce the number of distance computations required

getReferenceActor() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the callable actor to obtain the reference dataset from if reference file is pointing to a directory.

getReferenceDataset() - Method in class weka.filters.unsupervised.instance.AlignDataset

Returns the file containing the reference dataset.

getReferenceError() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference

Returns the absolute value of the reference error.

getReferenceFile() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the file to load the reference dataset from.

getReferenceSize() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference

Returns the size for the reference error.

getRegex() - Method in class adams.flow.transformer.WekaRegexToRange

Returns the regular expression for attribute matching.

getRegexName() - Method in class adams.flow.transformer.WekaClassSelector

Returns the regular expression for selecting the attributes.

getRegExp() - Method in class adams.data.weka.classattribute.ByName

Returns the regular expression to use for locating the class attribute.

getRegExp() - Method in class adams.data.weka.columnfinder.ByName

Returns the regular expression in use.

getRegExp() - Method in class adams.data.weka.rowfinder.ByLabel

Returns the regular expression in use.

getRegExp() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

getRegExp() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

getRegExp() - Method in class adams.flow.transformer.WekaAttributeIterator

Returns the regular expression for the name.

getRegExp() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns the regular expression to match the strings against.

getRegExp() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

getRegExp() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

getRegExp() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

getRegExp() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

getRegExp() - Method in class weka.core.InstanceGrouping

Returns the regular expression in use (eg '(.*)-([0-9]+)-(.*)').

getRegExp() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the regular expression for identifying attributes.

getRegExp() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Gets the list of regular expressions.

getRegExp() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

getRegExp(int) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Gets a single BaseRegExp from the set of available expressions.

getRegExps() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Returns the regular expression to apply to the attribute names for identifying the fusion subsets (incl class).

getRegExps() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns the regular expressions to use for extracting the groups.

getRegressionTree() - Method in class weka.classifiers.trees.m5.Rule2

Get the value of regressionTree.

getRegressionTree() - Method in class weka.classifiers.trees.m5.RuleNode2

Get the value of regressionTree.

getRegVector() - Method in class weka.filters.supervised.attribute.PLSFilterExtended

getRelationName() - Method in class adams.flow.source.WekaNewInstances

Returns the name of the relation.

getRelationName() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the pattern used for renaming the relation.

getRelationName() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns the relation name template.

getRelationName() - Method in interface weka.classifiers.CrossValidationFoldGenerator

Returns the relation name template.

getRelationName() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns the relation name template.

getRelationName() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the relation name template.

getRelationName() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the relation name template.

getRelationName() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns the relation name template.

getRelationName() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Returns the relation name template.

getRelationNameHeuristic() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns the current relation name heuristic.

getRelativeWidths() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Returns whether the calculated widths are divided by the class value.

getRemote() - Method in class weka.classifiers.meta.SocketFacade

Returns the address of the remote process.

getRemoteObjectName() - Method in class weka.classifiers.functions.PyroProxy

Returns the name of the remote object to use.

getRemoteObjectName() - Method in interface weka.core.PyroProxyObject

Returns the name of the remote object to use.

getRemove() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns whether to remove if not all present

getRemoveAsString() - Method in class adams.opt.genetic.DarkLord.DarkLordJob

Generates a range string of attributes to keep (= one has to use the inverse matching sense with the Remove filter).

getRemoveAsString(int[]) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection

Generates a range string of attributes to keep (= one has to use the inverse matching sense with the Remove filter).

getRemoveAttributeIndices() - Method in class weka.classifiers.meta.FilteredClassifierExt

Returns the attributes indices that are removed before applying the actual filter.

getRemoveChars() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Gets the characters to remove from start/end of the generated name.

getRemoveChars() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Gets the characters to remove from start/end of the generated name.

getRemoveTrain() - Method in class weka.classifiers.meta.AbstainAttributePercentile

getRemoveUnused() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Gets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.

getRemoveUnused() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Gets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.

getReplace() - Method in class adams.flow.transformer.WekaRenameRelation

Returns the replacement string.

getReplace() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the expression to use for assembling the numeric part.

getReplaceMissing() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Gets whether missing values are replace.

getReplaceMissing() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Gets whether missing values are replaced.

getReport() - Method in class adams.data.instance.Instance

Returns the report.

getResetResults() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns whether to clear the results before starting the experiment.

getResetResults() - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ResettableExperiment

Returns whether to clear the results before starting the experiment.

getResetResults() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Returns whether to reset the results.

getResources() - Static method in class adams.gui.goe.WekaEditorsRegistration.AccessiblePluginManager

Returns the resources.

getResult() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog

Returns whether the dialog got cancelled or approved.

getResult() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

Returns whether the dialog got cancelled or approved.

getResult(String) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns a value from the cache.

getResult(String) - Method in class adams.opt.optimise.GeneticAlgorithm

Returns a value from the cache.

getResultFile() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the file to store the experimental results in.

getResultFormat() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the data format the results are stored in.

getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel

Returns the configured ResultListener.

getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel

Returns the configured ResultListener.

getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel

Returns the configured ResultListener.

getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel

Returns the configured ResultListener.

getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel

Returns the configured ResultListener.

getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel

Returns the configured ResultListener.

getResultMatrix() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Returns the result matrix.

getResults() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

Returns the currently set results.

getResults() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

Returns the current set results.

getResultsHandler() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the results handler to use.

getResultsName() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel

Returns the name to display in the GUI.

getResultsName() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel

Returns the name to display in the GUI.

getResultsName() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

Returns the name to display in the GUI.

getResultType() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

Returns whether the dialog got cancelled or approved.

getRetainStringValues() - Method in class weka.core.converters.AArffLoader.AArffReader

Returns whether to retain string values.

getReverse() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns whether to reverse the sorting.

getReverse() - Method in class weka.classifiers.AggregateEvaluations

Returns whether to reverse the sorting.

getRevision() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.FakeClassifier

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

getRevision() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.GeneticAlgorithm

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.GPD

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.LinearRegressionJ

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.MathExpressionClassifier

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.PLSClassifierWeighted

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.PLSWeighted

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.SimpleLinearRegressionIntervalEstimator

Returns the revision string.

getRevision() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.LWLIntervalEstimator

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.LWLSynchro

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

Returns the revision string.

getRevision() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.AbstainAttributePercentile

getRevision() - Method in class weka.classifiers.meta.AbstainAverage

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.AbstainVote

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.ClassificationViaRegressionD

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.ClassifierCascade

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.Corr

getRevision() - Method in class weka.classifiers.meta.FilteredClassifierExt

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.HighLowSplit

getRevision() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

getRevision() - Method in class weka.classifiers.meta.InputSmearing

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.LeastMedianSq

getRevision() - Method in class weka.classifiers.meta.LogClassRegressor

getRevision() - Method in class weka.classifiers.meta.LogTargetRegressor

getRevision() - Method in class weka.classifiers.meta.MinMaxLimits

getRevision() - Method in class weka.classifiers.meta.PartitionedStacking

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.PeakTransformed

getRevision() - Method in class weka.classifiers.meta.SubsetEnsemble

Returns the revision string.

getRevision() - Method in class weka.classifiers.meta.SumTransformed

getRevision() - Method in class weka.classifiers.meta.VotedImbalance

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.m5.Rule2

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.m5.RuleNode2

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.M5P2

Returns the revision string.

getRevision() - Method in class weka.classifiers.trees.RandomModelTrees

getRevision() - Method in class weka.classifiers.trees.RandomRegressionForest

getRevision() - Method in class weka.clusterers.SAXKMeans

Returns the revision string.

getRevision() - Method in class weka.core.converters.SimpleArffLoader

Returns the revision string.

getRevision() - Method in class weka.core.converters.SimpleArffSaver

Returns the revision string.

getRevision() - Method in class weka.core.converters.SpreadSheetLoader

Returns the revision string.

getRevision() - Method in class weka.core.converters.SpreadSheetSaver

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.FilteredSearchWithIndices

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.NewNNSearch

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.NewNNSearchWithIndices

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.PCANNSearchWithIndices

Returns the revision string.

getRevision() - Method in class weka.core.neighboursearch.PLSNNSearchWithIndices

Returns the revision string.

getRevision() - Method in class weka.core.SAXDistance

Returns the revision string.

getRevision() - Method in class weka.core.tokenizers.MultiTokenizer

Returns the revision string.

getRevision() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns the revision string.

getRevision() - Method in class weka.core.WeightedEuclideanDistance

Returns the revision string.

getRevision() - Method in class weka.core.WeightedEuclideanDistanceRidge

Returns the revision string.

getRevision() - Method in class weka.experiment.ResultMatrixAdamsCSV

Returns the revision string.

getRevision() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the revision string.

getRevision() - Method in class weka.filters.FilteredFilter

Returns the revision string.

getRevision() - Method in class weka.filters.SerializedFilter

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.PLS

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.YGradientEPO

Returns the revision string.

getRevision() - Method in class weka.filters.supervised.attribute.YGradientGLSW

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.AnyToString

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.DatasetCleaner

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.DownSample

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.FFT

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.LogTransform

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive

getRevision() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.PAA

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.RowSum

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.SAX

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.SetMissingValue

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.SpellChecker

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.attribute.StringToDate

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.AlignDataset

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.DatasetCleaner

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.KeepRange

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.LatestRecords

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.RowNorm

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.Scale

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.Sort

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.SortOnAttribute

Returns the revision string.

getRevision() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns the revision string.

getRidge() - Method in class adams.data.baseline.AbstractLinearRegressionBased

Returns the ridge parameter.

getRidge() - Method in class weka.attributeSelection.LinearRegressionAttributeEval

Get the value of Ridge.

getRidge() - Method in class weka.classifiers.functions.LinearRegressionJ

Get the value of Ridge.

getRidge() - Method in class weka.classifiers.trees.RandomModelTrees

getRidge() - Method in class weka.core.WeightedEuclideanDistanceRidge

Get the value of Ridge.

getRow() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the list of fields that identify a row.

getRow() - Method in class adams.flow.transformer.WekaGetInstancesValue

Returns the 1-based index of the row.

getRow() - Method in class adams.flow.transformer.WekaSetInstancesValue

Returns the 1-based index of the row.

getRow() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the list of fields that identify a row.

getRow(int) - Method in class adams.ml.data.InstancesView

Returns the row at the specified index.

getRow(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Returns the Instance for the row.

getRow(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Returns the row to display.

getRow(String) - Method in class adams.ml.data.InstancesView

Returns the row associated with the given row key, null if not found.

getRowAttribute1() - Method in class adams.tools.CompareDatasets

Returns the index of the attribute used for identifying rows to compare against each other (first dataset).

getRowAttribute2() - Method in class adams.tools.CompareDatasets

Returns the index of the attribute used for identifying rows to compare against each other (second dataset).

getRowCount() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

The number of datasets loaded.

getRowCount() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel

Gets the number of attributes.

getRowCount() - Method in class adams.gui.visualization.instance.InstanceTableModel

Returns the number of rows.

getRowCount() - Method in class adams.gui.visualization.instances.InstancesTableModel

returns the number of rows in the model

getRowCount() - Method in class adams.ml.data.InstancesView

Returns the number of rows currently stored.

getRowFinder() - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder

Returns the row finder in use.

getRowFinder() - Method in class adams.data.weka.datasetsplitter.RowSplitter

Gets the row-finder to use to select rows for the first dataset.

getRowFinder() - Method in class adams.data.weka.rowfinder.AbstractFilteredRowFinder

Returns the row finder in use.

getRowFinder() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the training data row selector.

getRowFinder() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Returns the row finder used by the filter.

getRowFinder() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns the row finder scheme.

getRowFinderEnabled() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns whether to use the row finder.

getRowFinders() - Static method in class adams.data.weka.rowfinder.AbstractRowFinder

Returns a list with classnames of row finders.

getRowFormat() - Method in class adams.data.featureconverter.Weka

Returns the class of the row that the converter generates.

getRowID(int) - Method in class adams.tools.CompareDatasets

Returns either the ID for the row, either the row index of the actual row attribute ID for that position.

getRowIndex() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Returns the currently selected.

getRowIndex(String) - Method in class adams.ml.data.InstancesView

Returns the row index of the specified row.

getRowKey(int) - Method in class adams.ml.data.InstancesView

Returns the row key at the specified index.

getRowRange() - Method in class weka.filters.unsupervised.instance.KeepRange

Returns the unordered range of rows to keep.

getRows() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the size.

getRows() - Method in class adams.data.weka.rowfinder.Constant

Gets the constant set of rows to find.

getRows() - Method in class adams.gui.event.WekaInvestigatorDataEvent

The affected rows.

getRows() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Returns a list of row IDs.

getRows() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Returns a list of row IDs.

getRows() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

getRowSelection() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Returns the row selection scheme in use.

getRowSetEnumeration() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Allows specific merge methods to specify the order in which rows are placed into the merged dataset, and which rows from the source datasets are used for the source data.

getRowSetEnumeration() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Allows specific merge methods to specify the order in which rows are placed into the merged dataset, and which rows from the source datasets are used for the source data.

getRowSetEnumeration() - Method in class adams.flow.transformer.wekadatasetsmerge.Simple

Allows specific merge methods to specify the order in which rows are placed into the merged dataset, and which rows from the source datasets are used for the source data.

getRunEvaluations() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns the stored Evaluation objects per run.

getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

Returns the stored run information.

getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics

Returns whether the run information is output as well.

getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Returns the stored run information.

getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Returns whether the run information is output as well.

getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns the stored run information.

getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics

Returns whether the run information is output as well.

getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns the stored run information.

getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns whether the run information is output as well.

getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

Returns the stored run information.

getRunModels() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns the stored Classifier objects per run.

getRunOriginalIndices() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns the stored original indices per run.

getRuns() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the number of runs to perform.

getRuns() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the number of runs to perform.

getRuns() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the number of runs.

getSampleSize() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Returns the sample size to use.

getSampleType() - Method in class weka.classifiers.trees.XGBoost

Gets the type of sampling algorithm.

getSaveFileFilters() - Method in class adams.gui.chooser.AdamsExperimentFileChooser

Returns the file filters for writing files.

getSaveFileFilters() - Method in class adams.gui.chooser.WekaFileChooser

Returns the file filters for writing files.

getSaveInstances() - Method in class weka.classifiers.trees.M5P2

Get whether instance data is being save.

getSaver() - Method in class adams.gui.chooser.DatasetFileChooserPanel

Returns the current saver.

getScale() - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive

getScalePositiveWeights() - Method in class weka.classifiers.trees.XGBoost

Gets the positive-weights scale factor.

getScaler() - Method in class adams.data.weka.predictions.AutoScaler

Returns the scaler for numeric data.

getScores() - Method in class adams.data.instancesanalysis.PCA

Returns the scores.

getScores() - Method in class adams.data.instancesanalysis.PLS

Returns the scores.

getScriptingEngine() - Method in class adams.gui.visualization.instance.InstancePanel

Returns the current scripting engine, can be null.

getSearch() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns the evaluation method in use.

getSearch() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns the search algorithm.

getSearch() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Returns the stored search object.

getSearchAlgorithm() - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Returns the current nearestNeighbourSearch algorithm in use.

getSearchPanel() - Method in class adams.gui.visualization.instances.InstancesPanel

Returns the underlying search panel.

getSecondAttribute() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Gets the name of the second attribute.

getSecondAttributeRange() - Method in class adams.gui.InstanceCompare

Returns the second attribute range.

getSecondAttributeRange() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Returns the second attribute range.

getSecondCrossValidationSeed() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Returns the current seed value for cross-validation (second evaluation).

getSecondDataset() - Method in class adams.gui.InstanceCompare

Returns the second dataset.

getSecondDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Returns the second dataset.

getSecondFitness() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob

Returns the fitness (second evaluation).

getSecondFolds() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob

Returns the number of cross-validation folds (second evaluation).

getSecondFolds() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Returns the number of folds to use in cross-validation (second evaluation).

getSecondRange() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Returns the second attribute range to use (regular expression on attribute names).

getSecondResult(String) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Returns a value from the cache (second evaluation).

getSecondRowIndex() - Method in class adams.gui.InstanceCompare

Returns the second row index.

getSecondRowIndex() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Returns the second row index.

getSecondSeed() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob

Returns the cross-validation seed (second evaluation).

getSeed() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

Returns the seed value for cross-validation.

getSeed() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Returns the seed value.

getSeed() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the seed value.

getSeed() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns the seed value.

getSeed() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Returns the seed value.

getSeed() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns the seed value.

getSeed() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the seed value.

getSeed() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the seed value.

getSeed() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Returns the seed value.

getSeed() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Returns the seed value.

getSeed() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the seed value.

getSeed() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the seed value.

getSeed() - Method in class adams.flow.transformer.WekaRandomSplit

Returns the seed value.

getSeed() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the seed value.

getSeed() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Returns the cross-validation seed.

getSeed() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the current seed value.

getSeed() - Method in class weka.classifiers.AbstractSplitGenerator

Returns the seed value.

getSeed() - Method in class weka.classifiers.functions.FakeClassifier

Returns the seed value for the random values.

getSeed() - Method in class weka.classifiers.trees.XGBoost

Gets the random number seed.

getSeed() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the seed value.

getSeed() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Gets the seed for the random number generations

getSeed() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Gets the seed for the random number generations

getSeed() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Gets the seed for the random number generations

getSelectedAttributes() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Gets an array containing the indices of all selected (ie checked) attributes.

getSelectedClassifier() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the specified base classifier.

getSelectedColumn(int[], int) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter

Gets the column number of the selected column at the given index.

getSelectedData() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Returns the currently selected data containers.

getSelectedData() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Returns the currently selected data containers.

getSelectedDatabaseID(int) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Returns the database ID of the currently selected item.

getSelectedDatabaseIDs(int) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Returns the database IDs of the currently selected items.

getSelectedRows() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Returns the currently selected data containers.

getSelectedRows() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Returns the selected rows.

getSelectedRows() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Returns the currently selected data containers.

getSelectedRows() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Gets an array containing the indices of all selected rows.

getSelectedTag() - Method in enum adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType

Returns the corresponding Vote selected tag.

getSelectionModel() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Gets the selection model used by the table.

getSelectionProcessor() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Returns the selection processor scheme in use.

getSendToClasses() - Method in class adams.flow.sink.WekaInstancesDisplay

Returns the classes that the supporter generates.

getSendToClasses() - Method in class adams.gui.tools.DatasetCompatibilityPanel

Returns the classes that the supporter generates.

getSendToClasses() - Method in class adams.gui.visualization.instance.InstanceExplorer

Returns the classes that the supporter generates.

getSendToClasses() - Method in class adams.gui.visualization.instances.InstancesTable

Returns the classes that the supporter generates.

getSendToClasses() - Method in class weka.gui.explorer.ExplorerExt

Returns the classes that the supporter generates.

getSendToItem(Class[]) - Method in class adams.flow.sink.WekaInstancesDisplay

Returns the object to send.

getSendToItem(Class[]) - Method in class adams.gui.tools.DatasetCompatibilityPanel

Returns the object to send.

getSendToItem(Class[]) - Method in class adams.gui.visualization.instance.InstanceExplorer

Returns the object to send.

getSendToItem(Class[]) - Method in class adams.gui.visualization.instances.InstancesTable

Returns the object to send.

getSendToItem(Class[]) - Method in class weka.gui.explorer.ExplorerExt

Returns the object to send.

getSeparateFolds() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns whether to separate the folds, an Evaluation object per fold.

getSequenceManager() - Method in class adams.gui.visualization.instance.InstancePanel

Returns the current container manager.

getSerialized() - Method in class weka.filters.SerializedFilter

Returns the serialized filter file.

getServer() - Method in class weka.classifiers.meta.SocketFacade

Returns the server socket, instantiates it if necessary.

getSetup() - Method in class adams.flow.source.WekaClassifierGenerator

Returns the base classifier.

getSetup() - Method in class adams.flow.source.WekaClustererGenerator

Returns the base clusterer.

getSetup() - Method in class adams.flow.source.WekaFilterGenerator

Returns the base clusterer.

getSetup() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Returns the property in the incoming properties that contains the commandline of the genetic algorithm.

getSetup() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

Returns the genetic algorithm setup to use.

getSetup() - Method in class adams.gui.menu.DarkLord

Returns the genetic algorithm setup to use.

getSetup() - Method in class adams.gui.menu.Hermione

Returns the genetic algorithm setup to use.

getSetupDialog(Dialog, Dialog.ModalityType) - Static method in class adams.gui.visualization.instance.HistogramFactory

Returns an instance of a setup dialog for displaying histograms.

getSetupDialog(Frame, boolean) - Static method in class adams.gui.visualization.instance.HistogramFactory

Returns an instance of a setup dialog for displaying histograms.

getSetupName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

Returns the name for this setup panel.

getSetupName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

Returns the name for this setup panel.

getSetupName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

Returns the name for this setup panel.

getSetups() - Static method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup

Returns the available actions.

getSetupUpload() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the scheme for uploading the currently best job setup.

getSharedStringsTable() - Method in class adams.ml.data.InstancesView

Returns the table for shared strings.

getShortcutProperties() - Static method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns the properties that define the shortcuts.

getShowAboutBox() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage.CustomPropertySheetPanel

Returns whether the about box is displayed.

getShowAttributeIndex() - Method in class adams.gui.visualization.instances.InstancesTableModel

Returns whether to display the attribute index in the header.

getShowAttributeWeights() - Method in class adams.gui.visualization.instances.InstancesTable

Returns whether to display attribute weights.

getShowAttributeWeights() - Method in class adams.gui.visualization.instances.InstancesTableModel

Returns whether to display attribute weights.

getShowDistribution() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns whether to show the class distribution as well.

getShowDistribution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Returns whether to show the class distribution as well.

getShowError() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns whether to show the error as well.

getShowError() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Returns whether to show the error as well.

getShowProbability() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns whether to show the probability as well.

getShowProbability() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Returns whether to show the probability as well.

getShowWeight() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns whether to show the weight as well.

getShowWeight() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Returns whether to show the weight as well.

getShowWeightsColumn() - Method in class adams.gui.visualization.instances.InstancesTable

Returns whether to display a weights column.

getShowWeightsColumn() - Method in class adams.gui.visualization.instances.InstancesTableModel

Returns whether to display a weights column.

getShowZeroInstancesAsUnknown() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

Get whether to show zero instances as unknown (i.e.

getSidePanel() - Method in class adams.gui.visualization.instance.InstanceExplorer

Returns the side panel.

getSignificance() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the current significance level (0-1).

getSignificance() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the current significance level (0-1).

getSilent() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns whether to suppress error messages.

getSimpleAttributeNames() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Get whether to just number the attributes rather than compiling names.

getSimplsB() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the SIMPLS B matrix.

getSimplsB() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings

Returns the SIMPLS B matrix.

getSimplsB() - Method in interface weka.core.PLSMatrixAccess

Returns the SIMPLS B matrix.

getSimplsB() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings

Returns the SIMPLS B matrix.

getSimplsW() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the SIMPLS W matrix.

getSimplsW() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings

Returns the SIMPLS W matrix.

getSimplsW() - Method in interface weka.core.PLSMatrixAccess

Returns the SIMPLS W matrix.

getSimplsW() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings

Returns the SIMPLS W matrix.

getSize() - Method in class adams.data.weka.predictions.FixedSizeErrorScaler

Returns the size for the errors.

getSizeLimit() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns the threshold of the normalized weights below which to drop instances.

getSkipBuild() - Method in class adams.flow.transformer.WekaTrainClassifier

Returns whether to skip the buildClassifier call for incremental classifiers.

getSkipDrop() - Method in class weka.classifiers.trees.XGBoost

Gets the probability of skipping the dropout procedure during a boosting iteration.

getSkipHistory() - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Returns whether history panels are skipped.

getSkipIdentical() - Method in class weka.core.neighboursearch.NewNNSearch

Gets whether if identical instances are skipped from the neighbourhood.

getSkipNominal() - Method in class adams.data.instancesanalysis.PCA

Returns whether to skip NOMINAL attributes from the PCA process by turning them into STRING attributes.

getSkipTrain() - Method in class weka.classifiers.meta.SocketFacade

Returns whether to skip training, eg when using a pre-built model.

getSlope() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns the slope of the function.

getSlopeSE() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns the standard error of slope of the function.

getSmoothing() - Method in class weka.classifiers.trees.m5.Rule2

Get whether or not smoothing has been turned on

getSortAttributeNames() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns whether to sort the attribute names.

getSortAttributes() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTable

Returns whether to sort the attributes alphabetically for the dropdown list.

getSortAttributes() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableWithButtons

Returns whether to sort the attributes alphabetically for the dropdown list.

getSortDefinitionPanel() - Method in class adams.gui.event.InstancesSortSetupEvent

Returns the SortDefinitionPanel that was added/removed.

getSortLabels() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns whether to store the labels with the specified comparator.

getSortLabels() - Method in class weka.classifiers.AggregateEvaluations

Returns whether to store the labels with the specified comparator.

getSortPanel() - Method in class adams.gui.event.InstancesSortSetupEvent

Returns the SortPanel that triggered the event

getSource() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute

Gets the actual source attribute from the source datasets.

getSource() - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer

Returns the source of the data item.

getSource() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer

Returns the source of the data item.

getSource() - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer

Returns the source of the data item.

getSource() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer

Returns the source of the data item.

getSource() - Method in class adams.gui.tools.wekainvestigator.data.MemoryContainer

Returns the source of the data item.

getSource() - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer

Returns the source of the data item.

getSource() - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer

Returns the source of the data item.

getSourceCodeClass() - Method in class adams.flow.transformer.WekaClassifierInfo

Returns the class name for the generated source code.

getSources() - Method in class adams.data.instancesanalysis.FastICA

Returns the sources.

getSparseFormat() - Method in class adams.flow.source.WekaDatabaseReader

Returns whether data is output in sparse format.

getSplitPercentage() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the split percentage (only train/test splits).

getSplitpoint() - Method in class weka.classifiers.meta.HighLowSplit

getSplitpoint() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

getSplits() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the minimum.

getSplits() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

getSplitter() - Method in class adams.flow.transformer.WekaDatasetSplit

Gets the splitter to use.

getSpreadSheet() - Method in class adams.ml.data.DataCellView

Returns the spreadsheet this cell belongs to.

getSpreadSheetType() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet

Returns the type of spreadsheet to use.

getSpreadSheetWriter() - Method in class weka.core.converters.SpreadSheetSaver

Returns the spreadsheet writer in use.

getSquaredError() - Method in class weka.clusterers.SAXKMeans

Gets the squared error for all clusters.

getStandardDeviation(Instance) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Gives the variance of the prediction at the given instance

getStandardDeviation(Instance) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Gives standard deviation of the prediction at the given instance.

getStandardDeviation(Instance) - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Gives the variance of the prediction at the given instance

getStartPage() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

Returns the start page for the wizard.

getStartPage() - Method in class adams.gui.menu.DarkLord

Returns the start page for the wizard.

getStartPage() - Method in class adams.gui.menu.Hermione

Returns the start page for the wizard.

getStartPoints(AbstractGeneticDiscoveryHandler[]) - Method in class adams.opt.genetic.Hermione

Get List of start positions in bit string

getState(InstancesTable, MouseEvent, TableRowRange) - Static method in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper

Determines the state of the table.

getStatistic() - Method in class adams.flow.transformer.WekaInstancesStatistic

Returns the statistic in use.

getStatistic() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Returns the statistic to output.

getStatistic() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Returns the statistic to output.

getStatistic() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Returns the statistic to output.

getStatistic() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the statistic to output.

getStatistic() - Method in class weka.classifiers.meta.ClassifierCascade

the statistic to use for termination.

getStatistic(String) - Method in class weka.classifiers.evaluation.Bias

Get the value of the named statistic

getStatistic(String) - Method in class weka.classifiers.evaluation.Dice

Get the value of the named statistic - for the first class label.

getStatistic(String) - Method in class weka.classifiers.evaluation.MSLE

Get the value of the named statistic

getStatistic(String) - Method in class weka.classifiers.evaluation.RPD

Get the value of the named statistic

getStatistic(String) - Method in class weka.classifiers.evaluation.RSquared

Get the value of the named statistic

getStatistic(String) - Method in class weka.classifiers.evaluation.SDR

Get the value of the named statistic

getStatistic(String, int) - Method in class weka.classifiers.evaluation.Dice

Get the value of the named statistic for the given class index.

getStatisticNames() - Method in class weka.classifiers.evaluation.Bias

Get a list of the names of the statistics that this metrics computes.

getStatisticNames() - Method in class weka.classifiers.evaluation.Dice

Get a list of the names of the statistics that this metrics computes.

getStatisticNames() - Method in class weka.classifiers.evaluation.MSLE

Get a list of the names of the statistics that this metrics computes.

getStatisticNames() - Method in class weka.classifiers.evaluation.RPD

Get a list of the names of the statistics that this metrics computes.

getStatisticNames() - Method in class weka.classifiers.evaluation.RSquared

Get a list of the names of the statistics that this metrics computes.

getStatisticNames() - Method in class weka.classifiers.evaluation.SDR

Get a list of the names of the statistics that this metrics computes.

getStatistics() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Returns the statistics to output.

getStatistics() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Returns the statistics to output.

getStatisticValue() - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Returns the value to extract.

getStatisticValues() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the values to extract.

getStatisticValues() - Method in class adams.flow.transformer.WekaEvaluationValues

Returns the values to extract.

getStatusMessageHandler() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the current status message handler in use.

getStatusMessageHandler() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns the status message handler for outputting notifications.

getStatusMessageHandler() - Method in class adams.multiprocess.WekaCrossValidationJob

Returns the status message handler.

getStdDev() - Method in class weka.classifiers.meta.InputSmearing

Gets the multiplier for the standard deviation to use for input smearing.

getStdDev() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Gets the multiplier for the standard deviation to use for input smearing.

getStopFlowIfCanceled() - Method in class adams.flow.source.WekaSelectDataset

Returns whether to stop the flow if dialog canceled.

getStopMode() - Method in class adams.flow.source.WekaSelectDataset

Returns the stop mode.

getStorage() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns the data storage item.

getStorageName() - Method in class adams.data.conversion.MapToWekaInstance

Returns the name of the stored Instances object to use as template.

getStorageName() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Returns the name for the data in the internal storage.

getStoreFilename() - Method in class adams.flow.transformer.WekaTextDirectoryReader

Returns whether the filename gets stored in extra attribute.

getStratify() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Returns whether to stratify the data (in case of nominal class).

getStratify() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns whether to stratify the data (in case of nominal class).

getStratify() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns whether to stratify the data (in case of nominal class).

getStratify() - Method in interface weka.classifiers.CrossValidationFoldGenerator

Returns whether to stratify the data (in case of nominal class).

getStratify() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns whether to stratify the data (in case of nominal class).

getStratify() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns whether to stratify the data (in case of nominal class).

getStratify() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns whether to stratify the data (in case of nominal class).

getStratify() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns whether to stratify the data (in case of nominal class).

getStrict() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns whether to enforce uniqueness in IDs.

getStructure() - Method in class weka.core.converters.AArffLoader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure() - Method in class weka.core.converters.SimpleArffLoader

Returns the structure of the dataset.

getStructure() - Method in class weka.core.converters.SpreadSheetLoader

Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.

getStructure(Instances, String, TIntList) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Returns the dataset structure.

getSubsampleRatio() - Method in class weka.classifiers.trees.XGBoost

Gets the sub-sample ratio of the training instances.

getSubset() - Method in class weka.classifiers.meta.Corr

getSubset(Instances) - Method in class weka.classifiers.meta.Corr

getSummaryFilter() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the filter to use to summarise the attributes.

getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaASEvaluator

The abstract superclass to use.

getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaASSearch

The abstract superclass to use.

getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaClassifier

The abstract superclass to use.

getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaClusterer

The abstract superclass to use.

getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaDataGenerator

The abstract superclass to use.

getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaFilter

The abstract superclass to use.

getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaStreamableFilter

The abstract superclass to use.

getSupplementaryData() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns the stored Supplementary object.

getSupplementaryName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns the stored Supplementary name.

getSuppliedPrefix() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the prefix to use in case of OutputPrefixType.SUPPLIED.

getSuppliedReferenceDataset() - Method in class weka.filters.unsupervised.instance.AlignDataset

Returns the manually set reference dataset instead of loading one from disk.

getSuppliedTestSet() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the manually set test set instead of loading one from disk.

getSupport() - Method in class weka.classifiers.meta.ConsensusOrVote

Returns the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.

getSupport() - Method in class weka.classifiers.meta.Veto

Returns the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.

getSupportedFileExtensions(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractAdamsExperimentIO

Returns the supported file extensions.

getSupportedFileExtensions(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO

Returns the supported file extensions.

getSupportedFileExtensions(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractWekaExperimentIO

Returns the supported file extensions.

getSuppressModelOutput() - Method in class weka.classifiers.meta.AbstainingCascade

Returns whether to output the model with the toString() method or not.

getSuppressModelOutput() - Method in class weka.classifiers.meta.ConsensusOrVote

Returns whether to output the model with the toString() method or not.

getSuppressModelOutput() - Method in class weka.classifiers.meta.SuppressModelOutput

Returns whether to output the model with the toString() method or not.

getSuppressModelOutput() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns whether to output the model with the toString() method or not.

getSuppressModelOutput() - Method in class weka.classifiers.meta.Veto

Returns whether to output the model with the toString() method or not.

getSuppressModelOutput() - Method in class weka.classifiers.meta.VotedImbalance

Returns whether to output the model with the toString() method or not.

getSuppressModelOutput() - Method in interface weka.core.ModelOutputHandler

Returns whether to output the model with the toString() method or not.

getSwapAxes() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns whether to swap the axes.

getSwapRowsAndColumns() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns whether to swap rows and columns.

getSwapRowsAndColumns() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns whether to swap rows and columns.

getTabbedPane() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns the underlying tabbed pane.

getTabbedPane() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

The tabbed pane for the results.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.DataTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.LogTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

Returns the icon name for the tab icon.

getTabIcon() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

Returns the icon to use in the tabbed pane.

getTabIcon() - Method in class adams.gui.tools.wekamultiexperimenter.LogPanel

Returns the icon to use in the tabbed pane.

getTabIcon() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

Returns the icon to use in the tabbed pane.

getTable() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Returns the table.

getTable() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Returns the table.

getTable() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Returns the table.

getTable() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Returns the table.

getTable() - Method in class adams.gui.visualization.instances.InstancesPanel

Returns the underlying table.

getTable(Report) - Static method in class adams.gui.visualization.instance.InstanceReportFactory

Returns a new table for the given report.

getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class adams.gui.visualization.instances.AttributeValueCellRenderer

Returns the default table cell renderer.

getTableEpilog() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the epilog for a table.

getTableModel() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Get the table model in use (or null if no instances have been set yet).

getTableModelClass() - Method in class adams.gui.visualization.instance.InstanceTable

Returns the class of the table model that the models need to be derived from.

getTableName() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the table name to store the data in.

getTableProlog() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns the prolog of a table.

getTabTitle() - Method in class weka.gui.explorer.ExperimentPanel

Returns the title for the tab in the Explorer.

getTabTitle() - Method in class weka.gui.explorer.SqlPanel

Returns the title for the tab in the Explorer

getTabTitleToolTip() - Method in class weka.gui.explorer.ExperimentPanel

Returns the tooltip for the tab in the Explorer.

getTabTitleToolTip() - Method in class weka.gui.explorer.SqlPanel

Returns the tooltip for the tab in the Explorer

getTarget() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

Returns the current object.

getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.DIPLS

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.OPLS

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.PLS1

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.PRM

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.SIMPLS

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.VCPLS

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.functions.GPD

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.AbstainVote

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.ClassificationViaRegressionD

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.meta.InputSmearing

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.trees.m5.M5Base2

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.classifiers.trees.XGBoost

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.clusterers.SAXKMeans

getTechnicalInformation() - Method in class weka.core.SAXDistance

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.WeightedEuclideanDistance

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.core.WeightedEuclideanDistanceRidge

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.supervised.attribute.PLS

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.FFT

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.

getTemplate() - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels

Returns the MultipleClassifiersCombiner template to use.

getTemplate() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels

Returns the Vote template to use.

getTemplate() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

Returns the stored template object.

getTemplate() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds

Returns the Vote template to use.

getTemplate() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns the stored template object.

getTemplate() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns the stored template object.

getTemplate() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

Returns the stored template object.

getTest() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the name of the callable actor to obtain the test set.

getTest() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

The test data.

getTest() - Method in class adams.multiprocess.WekaCrossValidationJob

Returns the test set.

getTestAttributes() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the range of attributes from the test to add to the output.

getTestBase() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the index of the test base.

getTestBase() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the index of the test base.

getTestData() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns the (optional) storage item that contains the test data; cross-validation is performed if not present.

getTester() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the Tester in use.

getTester() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the Tester in use.

getTester() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Returns the tester.

getTester(Instances) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Sets up the testing algorithm and returns it.

getTestingUpdateInterval() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Returns the interval to use for outputting progress info during testing.

getTestInstances() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Returns the test instances in use by the genetic algorithm.

getTestInstances() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the currently set test set (if null, cross-validation is used).

getTestset() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Returns the name of the callable clusterer in use.

getTestset() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Returns the name of the callable classifier in use.

getTestSet() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the file containing the test set to remove from the data passing through the filter.

getTestSplitName() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns the name of the split to use for testing.

getTestSplitName() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Returns the name of the split to use for testing, ie generating predictions.

getThreshold() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

Returns the threshold.

getThreshold() - Method in class adams.tools.CompareDatasets

Returns the threshold for the correlation coefficient.

getThreshold() - Method in class weka.classifiers.meta.ClassifierCascade

the threshold for the statistic for termination.

getThreshold() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Gets the threshold for the max error when predicting a numeric class.

getThreshold() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Gets the threshold for the max error when predicting a numeric class.

getThresholdCheck() - Method in class weka.classifiers.meta.ClassifierCascade

whether to go below or above the threshold.

getThresholds() - Method in class weka.classifiers.meta.VotedImbalance

Returns the pairs of threshold/number of resampled models.

getTimeFormat() - Method in class adams.ml.data.InstancesView

Returns the time formatter.

getTimeMsecFormat() - Method in class adams.ml.data.InstancesView

Returns the time/msec formatter.

getTimeout() - Method in class weka.classifiers.meta.SocketFacade

Returns the timeout in milli-second to wait for new connections.

getTimestampPrefix() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Return the timestamp prefix for logs.

getTimeZone() - Method in class adams.ml.data.InstancesView

Returns the currently used timezone.

getTipText() - Method in class adams.core.base.AttributeTypeList

Returns a tool tip for the GUI editor (ignored if null is returned).

getTitle() - Method in class adams.gui.application.WekaExperimenterPreferencesPanel

The title of the preferences.

getTitle() - Method in class adams.gui.application.WekaExplorerPreferencesPanel

The title of the preferences.

getTitle() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel

The title of the preferences.

getTitle() - Method in class adams.gui.application.WekaPluginManagerExtensions

The title of the initialization.

getTitle() - Method in class adams.gui.application.WekaSystemProperties

The title of the initialization.

getTitle() - Method in class adams.gui.menu.AppendDatasets

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.ArffViewer

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.BatchFilterDatasets

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.BayesNetEditor

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.BoundaryVisualizer

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.CostCurve

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.DarkLord

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.DatasetCompatibility

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.Experimenter

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.Explorer

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.GraphVisualizer

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.Hermione

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.InstanceCompare

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.InstanceExplorer

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.InstancesPlot

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.MakeCompatibleDatasets

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.MarginCurve

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.MergeDatasets

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.MultiExplorer

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.PackageManager

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.PlotAttributeVsAttribute

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.ROC

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.SqlViewer

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.TreeVisualizer

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.WekaCommandToCode

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.WekaInvestigator

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.WekaMultiExperimenter

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.WekaSimpleCLI

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.menu.Workbench

Returns the title of the window (and text of menuitem).

getTitle() - Method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem

The menu item title.

getTitle() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob

Returns the title of the job.

getTitle() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob

Returns the title of the job.

getTitle() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Returns the title of this tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.ModelOutput

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.Rules

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.RunInformation

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.ReducedData

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.RunInformation

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.CompareModels

The menu item title.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation

The menu item title.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.GraphSource

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyClassifierErrors

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyGraphVisualizer

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyMarginCurve

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyTreeVisualizer

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ModelOutput

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem

The menu item title.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.CopySetup

The menu item title.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation

The menu item title.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsFitted

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsPredictor

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.RunInformation

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeVisualizer

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ClusterAssignments

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.GraphSource

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.LegacyTreeVisualizer

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ModelOutput

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.RunInformation

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.DataTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.RunInformation

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

The title to use for the tab.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.LogTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Returns the title of this table.

getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

Returns the title of this table.

getTitle() - Method in class weka.gui.explorer.ExplorerExt

Returns the base title in use by the title generator.

getTitleClassDetails() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the title to use for the class details.

getTitleGenerator() - Method in class weka.gui.explorer.ExplorerExt

Returns the title generator in use.

getTitleMatrix() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the title to use for the confusion matrix.

getTitleNameColumn() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the title of the "Name" column, i.e., the first column.

getTitleSummary() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the title to use for the summary.

getTitleValueColumn() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the title of the "Value" column, i.e., the first column.

getTokenizers() - Method in class weka.core.tokenizers.MultiTokenizer

Returns the tokenizers to use.

getTol() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Sets the inner NIPALS loop maximum number of iterations.

getTol() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns the inner NIPALS loop improvement tolerance.

getTol() - Method in class adams.data.instancesanalysis.pls.PRM

Returns the inner NIPALS loop improvement tolerance.

getTol() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns the inner NIPALS loop improvement tolerance.

getTolerateHeaderChanges() - Method in class adams.data.instances.AbstractInstanceGenerator

Returns whether to tolerate header changes and merely re-generating the header instead of throwing an exception.

getToolTipsEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Returns whether to show tool tips.

getToolTipsEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Returns whether to show tool tips.

getToolTipsEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Returns whether to show tool tips.

getToolTipsEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Returns whether to show tool tips.

getToolTipsEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Returns whether to show tool tips.

getToolTipText(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Returns "<nominal value> [<nominal value count>]" if displaying a bar plot and mouse is on some bar.

getTopK() - Method in class weka.classifiers.trees.XGBoost

Gets the number of top features to select when using the greedy or thrifty feature selector.

getTrain() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the name of the callable actor to obtain the training set.

getTrain() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

The training data.

getTrain() - Method in class adams.multiprocess.WekaCrossValidationJob

Returns the training set.

getTrain() - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Returns the training data in use.

getTrainingSet(int) - Method in class weka.classifiers.meta.InputSmearing

Returns a training set for a particular iteration.

getTrainingSet(int, int) - Method in class weka.classifiers.meta.SubsetEnsemble

Gets a training set for a particular index.

getTrainingSet(int, int) - Method in class weka.classifiers.meta.VotedImbalance

Gets a training set for a particular index.

getTrainSplitName() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns the name of the split to use for training.

getTrainSplitName() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Returns the name of the split to use for training.

getTransformedInstances() - Method in class weka.core.neighboursearch.TransformNNSearch

getTreeMethod() - Method in class weka.classifiers.trees.XGBoost

Gets the tree construction algorithm used in XGBoost.

getTrials() - Method in class weka.classifiers.trees.RandomModelTrees

getTurnOffAbstaining() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Returns whether abstaining of the base classifier is turned off.

getTweedieVariancePower() - Method in class weka.classifiers.trees.XGBoost

Gets the parameter that controls the variance of the Tweedie distribution.

getType() - Method in class adams.flow.transformer.WekaClassifierInfo

Returns the type of information to generate.

getType() - Method in enum adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType

Returns the corresponding Vote type.

getType() - Method in class adams.flow.transformer.WekaClustererInfo

Returns the type of information to generate.

getType() - Method in class adams.flow.transformer.WekaEvaluationInfo

Returns the type of information to generate.

getType() - Method in class adams.flow.transformer.WekaExtractArray

Returns the type of extraction to perform.

getType() - Method in class adams.flow.transformer.WekaInstancesInfo

Returns the type of information to generate.

getType() - Method in class adams.gui.event.InstancesSortSetupEvent

Returns the event type.

getType() - Method in class adams.gui.event.WekaInvestigatorDataEvent

Returns the type.

getType() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the conversion type to use.

getType(int) - Method in class adams.gui.visualization.instances.InstancesTableModel

returns the TYPE of the attribute at the given position

getType(int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel

returns the TYPE of the attribute at the given position

getUndo() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Returns the current undo manager.

getUndo() - Method in class adams.gui.visualization.instance.InstancePanel

Returns the current undo manager, can be null.

getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Returns the data to store in the undo.

getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer

Returns the data to store in the undo.

getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer

Returns the data to store in the undo.

getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer

Returns the data to store in the undo.

getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer

Returns the data to store in the undo.

getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer

Returns the data to store in the undo.

getUndoHandler() - Method in class adams.gui.visualization.instances.InstancesTable

Returns the undo handler in use.

getUndoHandler() - Method in class adams.gui.visualization.instances.InstancesTableModel

Returns the undo handler in use.

getUniqueID() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Gets the name of the unique ID attribute that the merge is joining on.

getUniqueID() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the attribute (string/numeric) to use for uniquely identifying rows.

getUnpruned() - Method in class weka.classifiers.trees.m5.M5Base2

Get whether unpruned tree/rules are being generated

getUnpruned() - Method in class weka.classifiers.trees.m5.Rule2

Get whether unpruned tree/rules are being generated

getUnselectedColumns(int[], int) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter

Creates an int[] which contains the unselected columns.

getUnset() - Method in class adams.flow.transformer.WekaClassSelector

Returns whether to unset the class attribute.

getUpdateContainerColor() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Returns whether to update the container's color with the color determined by this paintlet.

getUpdateHeader() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns whether to remove the labels also from the attribute definition.

getUpdateInterval() - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater

Returns the number of tokens after which the display is being updated.

getUpdater() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the updater in use.

getUpdater() - Method in class weka.classifiers.trees.XGBoost

Gets the choice of algorithm to fit the linear model.

getUpdateRelationName() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns whether to update the relation name with the new class attribute.

getUpdateWait() - Method in class weka.classifiers.functions.FakeClassifier

Returns the time in msec to wait when calling updateClassifier.

getUpper() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Returns the upper value to output.

getUpper() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Returns the upper value to output.

getUpper() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Returns the upper value to output.

getUpper() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the upper value to output.

getURL() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the query to execute.

getURL() - Method in class adams.flow.source.WekaDatabaseReader

Returns the query to execute.

getUseAbsoluteError() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns whether to use an absolute error (ie no direction).

getUseAbsoluteError() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Returns whether to use an absolute error (ie no direction).

getUseColumnNamesAsClassLabels() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns whether to use the names of the class distribution columns as labels in the fake evaluation.

getUseCustomLoader() - Method in class adams.flow.transformer.WekaFileReader

Returns whether a custom loader is used or not.

getUseCustomLoader() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns whether a custom loader is used or not.

getUseCustomLoader() - Method in class weka.filters.unsupervised.instance.AlignDataset

Returns whether to use a custom loader or automatic loading.

getUseCustomLoader() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns whether to use a custom loader or automatic loading.

getUseCustomPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns whether to use the custom paintlet.

getUseCustomSaver() - Method in class adams.flow.sink.WekaFileWriter

Returns whether a custom saver is used or not.

getUseError() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns whether to use the error for the cross size.

getUseFilename() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns whether to use the filename (w/o path) instead of the relationname.

getUseFilename() - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ExperimentWithCustomizableRelationNames

Returns whether to use the filename (w/o path) instead of the relationname.

getUseFilename() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Returns whether to use the filename as relation name.

getUseFilename() - Method in class weka.experiment.ExtExperiment

Returns whether to use the filename (w/o path) instead of the relationname.

getUseFixedMinMax() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns whether to use user-supplied min/max for bin calculation rather than obtain min/max from data.

getUseMedian() - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters

Returns whether to use the median instead of the mean.

getUseModelResetVariable() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the whether to use a variable to monitor for changes in order to reset the model.

getUseOriginalIndices() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns whether to align with original data (requires: WekaEvaluationContainer as input and original indices in container).

getUseOuterWindow() - Method in class adams.flow.source.WekaSelectDataset

Returns whether to use the outer window as parent.

getUsePrefix() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns whether to use prefixes.

getUseProbabilities() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Returns whether to use probabilities instead of 0 and 1 for the counts.

getUser() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the database user.

getUser() - Method in class adams.flow.source.WekaDatabaseReader

Returns the database user.

getUseRelationNameAsFilename() - Method in class adams.flow.sink.WekaFileWriter

Returns whether the relation name is used as filename.

getUseRelationNameAsFilename() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns whether the relation name is used as filename.

getUseRelationNameAsTable() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns whether to output single Instance objects or just one Instances object.

getUserMode() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.AppendDatasets

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.ArffViewer

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.BatchFilterDatasets

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.BayesNetEditor

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.BoundaryVisualizer

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.CostCurve

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.DatasetCompatibility

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.Experimenter

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.Explorer

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.GraphVisualizer

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.InstanceCompare

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.InstanceExplorer

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.InstancesPlot

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.MakeCompatibleDatasets

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.MarginCurve

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.MergeDatasets

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.MultiExplorer

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.PackageManager

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.PlotAttributeVsAttribute

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.ROC

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.SqlViewer

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.TreeVisualizer

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.WekaCommandToCode

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.WekaInvestigator

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.WekaMultiExperimenter

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.WekaSimpleCLI

Returns the user mode, which determines visibility as well.

getUserMode() - Method in class adams.gui.menu.Workbench

Returns the user mode, which determines visibility as well.

getUseRowAttribute() - Method in class adams.tools.CompareDatasets

Returns whether to use the row attribute or the order in the datasets for matching up the rows.

getUseSaveDialog() - Method in class adams.gui.wizard.WekaSelectDatasetPage

Returns whether the save or open dialog is used.

getUseSecondEvaluation() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob

Returns the whether to use second evaluation.

getUseSecondEvaluation() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Returns whether to use the second evaluation.

getUseThread() - Method in class adams.gui.menu.PlotAttributeVsAttribute

Whether to use a simple runnable for launching or a separate thread.

getUseTree() - Method in class weka.classifiers.trees.m5.Rule2

get whether an m5 tree is being used rather than rules

getUseUnsmoothed() - Method in class weka.classifiers.trees.m5.M5Base2

Get whether or not smoothing is being used

getUseViews() - Method in interface adams.data.weka.InstancesViewSupporter

Returns whether to use views.

getUseViews() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns whether to use views instead of dataset copies, in order to conserve memory.

getUseViews() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns whether to use views instead of dataset copies, in order to conserve memory.

getUseViews() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns whether to use views instead of dataset copies, in order to conserve memory.

getUseViews() - Method in class weka.classifiers.AbstractSplitGenerator

Returns whether to use views.

getValue() - Method in class adams.flow.transformer.WekaSetInstancesValue

Returns the value to set in the report.

getValue() - Method in class adams.flow.transformer.WekaSetInstanceValue

Returns the value to set in the report.

getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the integer value from the property container.

getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the double value from the property container.

getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the float value from the property container.

getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GenericInteger

Returns the double value from the property container.

getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GenericString

Returns the string value from the property container.

getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GPDGamma

Returns the double value from the property container.

getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GPDNoise

Returns the double value from the property container.

getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.PLSFilterNumComponents

Returns the integer value from the property container.

getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints

Returns the integer value from the property container.

getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix

Returns the matrix value from the property container.

getValue(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler

Returns the value currently being edited.

getValue(Map, String, Object) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Returns the specified default value if the map doesn't contain a value for the specified key.

getValue(Evaluation, EvaluationStatistic, int) - Static method in class adams.flow.core.EvaluationHelper

Returns a statistical value from the evaluation object.

getValue(Instance, int) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the value of the specified attribute from the given Instance.

getValueAt(int, int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

Returns the value at the specified position.

getValueAt(int, int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel

Gets a table cell

getValueAt(int, int) - Method in class adams.gui.visualization.instance.InstanceTableModel

Returns the value at the given position.

getValueAt(int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel

returns the value for the cell at columnindex and rowIndex

getValueEnsureEqual(int[], List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the value of the mapped attribute, ensuring that all possible sources either provide a missing value or the same value as each other.

getValueFirstAvailable(int[], List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the first encountered source value for a merged attribute.

getVariableName() - Method in class adams.flow.template.InstanceDumperVariable

Returns the variable name to generate the sub-flow for.

getVariableName() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns the name of the variable to monitor.

getVariableName() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns the name of the variable to monitor.

getVariance() - Method in class adams.data.instancesanalysis.PCA

Returns the variance.

getVariance() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

getVarianceCovered() - Method in class adams.flow.transformer.WekaPrincipalComponents

Gets the proportion of total variance to account for when retaining principal components.

getVarianceCovered() - Method in class weka.core.neighboursearch.PCANNSearch

Gets the proportion of total variance to account for when retaining principal components.

getVarianceCovered() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Gets the proportion of total variance to account for when retaining principal components.

getVector(Matrix, int) - Static method in class weka.core.matrix.MatrixHelper

returns the (column) vector of the matrix at the specified index

getVerbosity() - Method in class weka.classifiers.trees.XGBoost

Gets the verbosity level.

getVersusFitOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Get the options for the vsfit plot.

getVersusOrderOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Get the options for the vsorder plot.

getVisible(int) - Method in class adams.gui.visualization.instance.InstanceContainerManager

Returns the nth visible container.

getVisibleIndices() - Method in class adams.gui.visualization.instance.InstanceContainerManager

Returns the indices of all visible containers.

getVisualizeMenuItem(String, String) - Method in class weka.gui.visualize.plugins.SaveGraph

Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the graph in XML BIF format.

getVisualizeMenuItem(String, String) - Method in class weka.gui.visualize.plugins.SaveTree

Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the tree in GraphViz's dotty format.

getVisualizeMenuItem(ArrayList<Prediction>, Attribute) - Method in class weka.gui.visualize.plugins.ThresholdCurves

Get a JMenu or JMenuItem which contain action listeners that perform the visualization, using some but not necessarily all of the data.

getVisualizeMenuItem(Instances) - Method in class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors

Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the classifier errors.

getVisualizeMenuItem(Instances) - Method in class weka.gui.visualize.plugins.FixedClassifierErrors

Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the classifier errors.

getVisualizeMenuItem(Instances) - Method in class weka.gui.visualize.plugins.FixedClassifierErrorsPlot

Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the classifier errors.

getVotingType() - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs

Returns the type of voting in use.

getWaitForJobs() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns whether to wait for jobs to finish when terminating.

getWaveNoRegExp() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns the regular expression used for extracting the wave number from the attribute name (using the first group).

getWaveNoRegExp() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns the regular expression used for extracting the wave number from the attribute name (using the first group).

getWeight() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the (optional) column with the instance weight values.

getWeight() - Method in class weka.classifiers.functions.FromPredictions

Returns the column with the weight values.

getWeightIndex() - Method in class weka.classifiers.functions.FromPredictions

Returns the weight 0-based index.

getWeightingKernel() - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Gets the kernel weighting method to use.

getWeightingKernel() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Gets the kernel weighting method to use.

getWeights() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Returns the optional property in the incoming properties for the initial weights to use.

getWeights(OptData) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection

getWindows() - Method in class weka.filters.unsupervised.attribute.PAA

Returns the nth point setting.

getWindows() - Method in class weka.filters.unsupervised.attribute.SAX

Returns the nth point setting.

getWithReplacement() - Method in class adams.flow.transformer.WekaBootstrapping

Returns whether to draw predictions using replacement.

getWriter() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Returns the spreadsheet writer to use.

getWriterClass() - Method in class adams.gui.chooser.AdamsExperimentFileChooser

Returns the writer superclass for the GOE.

getWriterClass() - Method in class adams.gui.chooser.WekaFileChooser

Returns the writer superclass for the GOE.

getWriterForFile(File) - Method in class adams.gui.chooser.AdamsExperimentFileChooser

Returns the writer for the specified file.

getWriterForFile(File) - Method in class adams.gui.chooser.WekaFileChooser

Returns the writer for the specified file.

getWriters() - Static method in class adams.data.io.output.AbstractAdamsExperimentWriter

Returns a list with classes of writers.

getX() - Method in class adams.data.instance.InstancePoint

Returns the X value.

getX(Instance) - Static method in class weka.core.matrix.MatrixHelper

returns the data minus the class column as matrix

getX(Instances) - Static method in class weka.core.matrix.MatrixHelper

returns the data minus the class column as matrix

getX(Instances) - Method in class weka.filters.supervised.attribute.PLSFilterExtended

Override superclass method in order to deal with multiple y

getXRegExp() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the regular expression to identify the X attributes.

getxWeights() - Method in class weka.filters.supervised.attribute.PLSFilterExtended

getY() - Method in class adams.data.instance.InstancePoint

Returns the Y value.

getY(Instance) - Static method in class weka.core.matrix.MatrixHelper

returns the data class column as matrix

getY(Instances) - Static method in class weka.core.matrix.MatrixHelper

returns the data class column as matrix

getY(Instances) - Method in class weka.filters.supervised.attribute.PLSFilterExtended

Override superclass method in order to deal with multiple y

getY(Instances, int[]) - Static method in class weka.core.matrix.MatrixHelper

returns the data class columns as matrix

getYRegExp() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the regular expression to identify the Y attributes.

getZoomOverview() - Method in class adams.flow.sink.WekaInstanceViewer

Returns whether the zoom overview gets displayed.

getZoomOverviewPanel() - Method in class adams.gui.visualization.instance.InstancePanel

Returns the zoom overview panel.

globalInfo() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns a string describing the object.

globalInfo() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns a string describing the object.

globalInfo() - Method in class adams.core.discovery.genetic.GenericInteger

Returns a string describing the object.

globalInfo() - Method in class adams.core.discovery.genetic.GenericString

Returns a string describing the object.

globalInfo() - Method in class adams.core.discovery.genetic.GPDGamma

Returns a string describing the object.

globalInfo() - Method in class adams.core.discovery.genetic.GPDNoise

Returns a string describing the object.

globalInfo() - Method in class adams.core.discovery.genetic.PLSFilterNumComponents

Returns a string describing the object.

globalInfo() - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints

Returns a string describing the object.

globalInfo() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix

Returns a string describing the object.

globalInfo() - Method in class adams.core.management.WekaHomeEnvironmentModifier

Returns a string describing the object.

globalInfo() - Method in class adams.core.management.WekaPackagesClassPathAugmenter

Returns a string describing the object.

globalInfo() - Method in class adams.data.baseline.AbstractLinearRegressionBased

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.AdamsInstanceToWekaInstance

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.MapToWekaInstance

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.ReportToWekaInstance

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.SpreadSheetToWekaInstances

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.SwapPLS

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaCapabilitiesToInstances

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaCapabilitiesToSpreadSheet

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaCommandToCode

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaDrawableToString

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaEvaluationToCostCurve

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaEvaluationToMarginCurve

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaInstanceToAdamsInstance

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaInstanceToMap

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaPackageToMap

Returns a string describing the object.

globalInfo() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns a string describing the object.

globalInfo() - Method in class adams.data.featureconverter.Weka

Returns a string describing the object.

globalInfo() - Method in class adams.data.indexedsplits.InstancesIndexedSplitsRunsCompatibility

Returns a string describing the object.

globalInfo() - Method in class adams.data.instancesanalysis.FastICA

Returns a string describing the object.

globalInfo() - Method in class adams.data.instancesanalysis.PCA

Returns a string describing the object.

globalInfo() - Method in class adams.data.instancesanalysis.pls.DIPLS

Returns a string describing the object.

globalInfo() - Method in class adams.data.instancesanalysis.PLS

Returns a string describing the object.

globalInfo() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Returns a string describing the object.

globalInfo() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns a string describing the object.

globalInfo() - Method in class adams.data.instancesanalysis.pls.OPLS

Returns a string describing the object.

globalInfo() - Method in class adams.data.instancesanalysis.pls.PLS1

Returns a string describing this class.

globalInfo() - Method in class adams.data.instancesanalysis.pls.PRM

Returns a string describing the object.

globalInfo() - Method in class adams.data.instancesanalysis.pls.SIMPLS

Returns a string describing this class.

globalInfo() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns a string describing the object.

globalInfo() - Method in class adams.data.instancesanalysis.pls.VCPLS

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.input.ArffSpreadSheetReader

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.input.InstanceReader

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.input.JsonAdamsExperimentReader

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.input.JSONSpreadSheetReader

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.input.LibSVMSpreadSheetReader

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.input.MatlabSpreadSheetReader

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.input.NestedAdamsExperimentReader

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.input.SerializedAdamsExperimentReader

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.input.SVMLightSpreadSheetReader

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.input.XrffSpreadSheetReader

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.output.ArffSpreadSheetWriter

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.output.JsonAdamsExperimentWriter

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.output.JSONSpreadSheetWriter

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.output.LibSVMSpreadSheetWriter

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.output.MatlabSpreadSheetWriter

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.output.NestedAdamsExperimentWriter

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.output.SerializedAdamsExperimentWriter

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.output.SVMLightSpreadSheetWriter

Returns a string describing the object.

globalInfo() - Method in class adams.data.io.output.XrffSpreadSheetWriter

Returns a string describing the object.

globalInfo() - Method in class adams.data.spreadsheet.filter.WekaFilter

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.classattribute.AttributeIndex

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.classattribute.ByExactName

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.classattribute.ByName

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.classattribute.LastAttribute

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.classattribute.NoClassAttribute

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.columnfinder.AllFinder

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.columnfinder.ByExactName

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.columnfinder.ByName

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.columnfinder.Class

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.columnfinder.Constant

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.columnfinder.Invert

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.columnfinder.MultiColumnFinder

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.columnfinder.NullFinder

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.datasetsplitter.ColumnSplitter

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.datasetsplitter.RowSplitter

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.evaluator.PassThrough

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.predictions.AutoScaler

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.predictions.FixedSizeErrorScaler

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.predictions.RoundErrorScaler

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.relationname.AttributeIndex

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.relationname.ClassAttribute

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.relationname.FileName

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.relationname.NoChange

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.rowfinder.AllFinder

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.rowfinder.ByLabel

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.rowfinder.ByNumericRange

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.rowfinder.Constant

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.rowfinder.FilteredIQR

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.rowfinder.Invert

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.rowfinder.MultiRowFinder

Returns a string describing the object.

globalInfo() - Method in class adams.data.weka.rowfinder.NullFinder

Returns a string describing the object.

globalInfo() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Returns a string describing the object.

globalInfo() - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor

Returns a string describing the object.

globalInfo() - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor

Returns a string describing the object.

globalInfo() - Method in class adams.flow.condition.bool.AdamsInstanceCapabilities

Returns a string describing the object.

globalInfo() - Method in class adams.flow.condition.bool.WekaCapabilities

Returns a string describing the object.

globalInfo() - Method in class adams.flow.condition.bool.WekaClassification

Returns a string describing the object.

globalInfo() - Method in class adams.flow.core.WekaClassifierModelLoader

Returns a string describing the object.

globalInfo() - Method in class adams.flow.core.WekaClustererModelLoader

Returns a string describing the object.

globalInfo() - Method in class adams.flow.core.WekaFilterModelLoader

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaAttributeSummary

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaClassifierErrors

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaCostCurve

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaExperimentFileWriter

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaFileWriter

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaGraphVisualizer

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaInstancesDisplay

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaInstancesPlot

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaInstanceViewer

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaMarginCurve

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaModelWriter

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaThresholdCurve

Returns a string describing the object.

globalInfo() - Method in class adams.flow.sink.WekaTreeVisualizer

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.valuedefinition.WekaGOEValueDefinition

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaAssociatorSetup

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaClassifierGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaClassifierSetup

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaClustererGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaClustererSetup

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaDatabaseReader

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaDataGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaFilterGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaNewExperiment

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaNewInstances

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaPackageManagerAction

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaSelectDataset

Returns a string describing the object.

globalInfo() - Method in class adams.flow.source.WekaSelectObjects

Returns a string describing the object.

globalInfo() - Method in class adams.flow.standalone.WekaPackageManagerAction

Returns a string describing the object.

globalInfo() - Method in class adams.flow.standalone.wekapackagemanageraction.RefreshCache

Returns a string describing the object.

globalInfo() - Method in class adams.flow.template.InstanceDumperVariable

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.AbstractInstanceGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaAccumulatedError

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaAggregateEvaluations

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaAttributeIterator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaAttributeSelectionSummary

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaBootstrapping

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaChooseAttributes

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaClassifierInfo

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaClassifierOptimizer

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.PassThrough

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaClassifying

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaClassSelector

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaClusterAssignments

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaclusterer.AddCluster

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaclusterer.ClusterCounts

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaclusterer.ClusterStatistics

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaclusterer.PassThrough

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaClustererInfo

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaClustererPostProcessor

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaClustering

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaDatasetsMerge

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekadatasetsmerge.Simple

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaDatasetSplit

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaEnsembleGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaEvaluationInfo

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.PassThrough

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaEvaluationValues

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaExperiment

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaExperimentExecution

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaExperimentFileReader

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaExtractArray

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaExtractPLSMatrix

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaFileReader

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaFilter

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaGetCapabilities

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaGetInstancesValue

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaGetInstanceValue

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaInstanceFileReader

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaInstancesAppend

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaInstancesInfo

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaInstancesStatistic

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaModelReader

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaNewInstance

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaPackageManagerAction

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromFile

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromURL

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallPackage

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaPredictionsToInstances

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaPredictionsToSpreadSheet

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaPrincipalComponents

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaRandomSplit

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaRegexToRange

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaRelationName

Deprecated.

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaRenameRelation

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaSetInstancesValue

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaSetInstanceValue

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaSplitGenerator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaStoreInstance

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaStreamEvaluator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaStreamFilter

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaSubsets

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaTextDirectoryReader

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaTrainAssociator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaTrainClassifier

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaTrainClusterer

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

Returns a string describing the object.

globalInfo() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.previewbrowser.GraphSource

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.previewbrowser.GraphVisualizer

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.previewbrowser.InstanceExplorerHandler

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.previewbrowser.InterQuartileRangeViewer

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.previewbrowser.TreeVisualizer

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.previewbrowser.WekaDatasetHandler

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.ModelOutput

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.Rules

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.RunInformation

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.ReducedData

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.RunInformation

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.Null

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.Simple

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.GraphSource

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyClassifierErrors

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyGraphVisualizer

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyMarginCurve

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyTreeVisualizer

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ModelOutput

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsFitted

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsPredictor

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.RunInformation

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeVisualizer

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ClusterAssignments

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.GraphSource

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.LegacyTreeVisualizer

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ModelOutput

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.RunInformation

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.RunInformation

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultAdamsExperimentIO

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultWekaExperimentIO

Returns a string describing the object.

globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instance.InstancePointHitDetector

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.AttributeStatistics

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.Binning

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.ColumnStatistic

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.DataSort

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.Histogram

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.RowStatistic

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Returns a string describing the object.

globalInfo() - Method in class adams.gui.visualization.instances.instancestable.ViewCell

Returns a string describing the object.

globalInfo() - Method in class adams.ml.model.classification.WekaClassifier

Returns a string describing the object.

globalInfo() - Method in class adams.ml.model.clustering.WekaClusterer

Returns a string describing the object.

globalInfo() - Method in class adams.ml.model.regression.WekaRegressor

Returns a string describing the object.

globalInfo() - Method in class adams.opt.genetic.DarkLord

Returns a string describing the object.

globalInfo() - Method in class adams.opt.genetic.Hermione

Returns a string describing the object.

globalInfo() - Method in class adams.opt.genetic.initialsetups.PackDataInitialSetupsProvider

Returns a string describing the object.

globalInfo() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

globalInfo() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection

globalInfo() - Method in class adams.opt.optimise.GeneticAlgorithm

Returns a string describing the object.

globalInfo() - Method in class adams.tools.CompareDatasets

Returns a string describing the object.

globalInfo() - Method in class weka.attributeSelection.LinearRegressionAttributeEval

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.attributeSelection.PLS1AttributeEval

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.attributeSelection.SIMPLSAttributeEval

Returns a string describing this attribute evaluator

globalInfo() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.DefaultRandomSplitGenerator

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.FakeClassifier

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.FromPredictions

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.GeneticAlgorithm

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.GPD

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.LinearRegressionJ

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.functions.MathExpressionClassifier

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.PLSClassifierWeighted

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.PLSWeighted

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.functions.PyroProxy

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.functions.SimpleLinearRegressionIntervalEstimator

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.lazy.AbstainingLWL

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.meta.AbstainAttributePercentile

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.AbstainAverage

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.AbstainingCascade

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.AbstainMinimumProbability

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.AbstainVote

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.ClassificationViaRegressionD

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.ClassifierCascade

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.Consensus

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.ConsensusOrVote

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.Corr

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.Fallback

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.FilteredClassifierExt

Returns a string describing this classifier.

globalInfo() - Method in class weka.classifiers.meta.HighLowSplit

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.InputSmearing

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.LeanMultiScheme

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.LeastMedianSq

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.LogClassRegressor

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.LogTargetRegressor

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.MinMaxLimits

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.PartitionedStacking

Returns a string describing this classifier.

globalInfo() - Method in class weka.classifiers.meta.PeakTransformed

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.RangeCheck

Returns a string describing this classifier.

globalInfo() - Method in class weka.classifiers.meta.SocketFacade

Returns a string describing this classifier.

globalInfo() - Method in class weka.classifiers.meta.socketfacade.Simple

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.meta.SubsetEnsemble

Returns a string describing the classifier.

globalInfo() - Method in class weka.classifiers.meta.SumTransformed

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.SuppressModelOutput

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.meta.Veto

Returns a string describing classifier

globalInfo() - Method in class weka.classifiers.meta.VotedImbalance

Returns a string describing the classifier.

globalInfo() - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper

Returns a string describing the classifier.

globalInfo() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns a string describing the object.

globalInfo() - Method in class weka.classifiers.trees.m5.M5Base2

returns information about the classifier

globalInfo() - Method in class weka.classifiers.trees.RandomModelTrees

Returns a string describing classifier.

globalInfo() - Method in class weka.classifiers.trees.RandomRegressionForest

Returns a string describing this classifier.

globalInfo() - Method in class weka.classifiers.trees.XGBoost

Returns a string describing the object.

globalInfo() - Method in class weka.clusterers.SAXKMeans

Returns a string describing this clusterer.

globalInfo() - Method in class weka.core.converters.SimpleArffLoader

Description of loader.

globalInfo() - Method in class weka.core.converters.SimpleArffSaver

Returns a string describing this Saver

globalInfo() - Method in class weka.core.converters.SpreadSheetLoader

Returns a string describing this loader

globalInfo() - Method in class weka.core.converters.SpreadSheetSaver

Returns a string describing this Saver

globalInfo() - Method in class weka.core.neighboursearch.FilteredSearchWithIndices

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.NewNNSearch

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.NewNNSearchWithIndices

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.PCANNSearchWithIndices

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.neighboursearch.PLSNNSearchWithIndices

Returns a string describing this nearest neighbour search algorithm.

globalInfo() - Method in class weka.core.SAXDistance

Returns a string describing this object.

globalInfo() - Method in class weka.core.tokenizers.cleaners.AbstractTokenCleaner

Returns a string describing the cleaner.

globalInfo() - Method in class weka.core.tokenizers.cleaners.MultiCleaner

Returns a string describing the cleaner.

globalInfo() - Method in class weka.core.tokenizers.cleaners.NormalizeDuplicateChars

Returns a string describing the cleaner.

globalInfo() - Method in class weka.core.tokenizers.cleaners.PassThrough

Returns a string describing the cleaner.

globalInfo() - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

Returns a string describing the cleaner.

globalInfo() - Method in class weka.core.tokenizers.MultiTokenizer

Returns a string describing the stemmer

globalInfo() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns a string describing the stemmer

globalInfo() - Method in class weka.core.WeightedEuclideanDistance

Returns a string describing this object.

globalInfo() - Method in class weka.core.WeightedEuclideanDistanceRidge

Returns a string describing this object.

globalInfo() - Method in class weka.experiment.ResultMatrixAdamsCSV

Returns a string describing the matrix.

globalInfo() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns a string describing the matrix.

globalInfo() - Method in class weka.filters.FilteredFilter

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.FlowFilter

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.SerializedFilter

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.supervised.attribute.PLS

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.supervised.attribute.YGradientEPO

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.supervised.attribute.YGradientGLSW

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.AnyToString

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.DatasetCleaner

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.detrend.Mean

Returns a string describing the object.

globalInfo() - Method in class weka.filters.unsupervised.attribute.detrend.RangeBased

Returns a string describing the object.

globalInfo() - Method in class weka.filters.unsupervised.attribute.DownSample

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.FFT

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.LogTransform

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased

Returns a string describing the object.

globalInfo() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.PAA

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.attribute.RowSum

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.SAX

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.SetMissingValue

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.attribute.SpellChecker

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.attribute.StringToDate

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.AlignDataset

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.instance.DatasetCleaner

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.KeepRange

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.KennardStone

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.instance.LatestRecords

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

Returns a string describing the processor.

globalInfo() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.Average

Returns a string describing the processor.

globalInfo() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.PassThrough

Returns a string describing the processor.

globalInfo() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Returns a string describing the row selection scheme.

globalInfo() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.IndividualRows

Returns a string describing the row selection scheme.

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.RowNorm

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Returns a string describing this filter

globalInfo() - Method in class weka.filters.unsupervised.instance.Scale

Returns a string describing this filter.

globalInfo() - Method in class weka.filters.unsupervised.instance.Sort

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.SortOnAttribute

Returns a string describing this classifier.

globalInfo() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns a string describing this classifier.

glueTipText() - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Returns the tip text for this property.

GPD - Class in weka.classifiers.functions

Implements Gaussian Processes for regression without hyperparameter-tuning, with an inline RBF kernel.
For more information see

David J.C.

GPD() - Constructor for class weka.classifiers.functions.GPD

GPDGamma - Class in adams.core.discovery.genetic

GPD gamma handler.

GPDGamma() - Constructor for class adams.core.discovery.genetic.GPDGamma

GPDNoise - Class in adams.core.discovery.genetic

GPD noise handler.

GPDNoise() - Constructor for class adams.core.discovery.genetic.GPDNoise

GPU - weka.classifiers.trees.XGBoost.Predictor

GPU_EXACT - weka.classifiers.trees.XGBoost.TreeMethod

GPU_HIST - weka.classifiers.trees.XGBoost.TreeMethod

graph() - Method in class weka.classifiers.trees.M5P2

Return a dot style String describing the tree.

graph(StringBuffer) - Method in class weka.classifiers.trees.m5.RuleNode2

Assign a unique identifier to each node in the tree and then calls graphTree

GRAPH - adams.flow.transformer.WekaClassifierInfo.InfoType

graph (if available).

GRAPH - adams.flow.transformer.WekaClustererInfo.InfoType

graph (if available).

GraphHelper - Class in adams.gui.tools.wekainvestigator.output

Helper class for graphs.

GraphHelper() - Constructor for class adams.gui.tools.wekainvestigator.output.GraphHelper

GraphSource - Class in adams.gui.tools.previewbrowser

Displays the source of a weka.core.Drawable graph.

GraphSource - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Displays the source code of the graph (dot or XML BIF).

GraphSource - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output

Displays the source code of the graph (dot or XML BIF).

GraphSource() - Constructor for class adams.gui.tools.previewbrowser.GraphSource

GraphSource() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.GraphSource

GraphSource() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.GraphSource

graphTree(StringBuffer) - Method in class weka.classifiers.trees.m5.RuleNode2

Return a dotty style string describing the tree

graphType() - Method in class weka.classifiers.trees.M5P2

Returns the type of graph this classifier represents.

GraphVisualizer - Class in adams.gui.menu

Displays data in the graph visualizer.

GraphVisualizer - Class in adams.gui.tools.previewbrowser

Displays BayesNet graphs.

GraphVisualizer() - Constructor for class adams.gui.menu.GraphVisualizer

Initializes the menu item with no owner.

GraphVisualizer() - Constructor for class adams.gui.tools.previewbrowser.GraphVisualizer

GraphVisualizer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.GraphVisualizer

Initializes the menu item.

GREEDY - weka.classifiers.trees.XGBoost.FeatureSelector

gridTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Returns the tip text for this property.

GROUP - Static variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

GroupedBinnedNumericClassCrossValidationFoldGenerator - Class in weka.classifiers

Helper class for generating cross-validation folds.

GroupedBinnedNumericClassCrossValidationFoldGenerator() - Constructor for class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Initializes the generator.

GroupedBinnedNumericClassCrossValidationFoldGenerator(Instances, int, long, boolean) - Constructor for class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Initializes the generator.

GroupedBinnedNumericClassCrossValidationFoldGenerator(Instances, int, long, boolean, boolean, String) - Constructor for class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Initializes the generator.

GroupedBinnedNumericClassRandomSplitGenerator - Class in weka.classifiers

Generates random splits of datasets with numeric classes using a binning algorithm.

GroupedBinnedNumericClassRandomSplitGenerator() - Constructor for class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Initializes the generator.

GroupedBinnedNumericClassRandomSplitGenerator(Instances, double) - Constructor for class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Initializes the generator.

GroupedBinnedNumericClassRandomSplitGenerator(Instances, long, double) - Constructor for class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Initializes the generator.

GroupedBinnedNumericClassRandomSplitGenerator(Instances, long, double, boolean) - Constructor for class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Initializes the generator.

GroupedClassValueBinValueExtractor() - Constructor for class adams.data.binning.BinnableInstances.GroupedClassValueBinValueExtractor

GroupedCrossValidationFoldGenerator - Class in weka.classifiers

Helper class for generating cross-validation folds.

GroupedCrossValidationFoldGenerator() - Constructor for class weka.classifiers.GroupedCrossValidationFoldGenerator

Initializes the generator.

GroupedCrossValidationFoldGenerator(Instances, int, long, boolean, boolean, WekaAttributeIndex, BaseRegExp, String) - Constructor for class weka.classifiers.GroupedCrossValidationFoldGenerator

Initializes the generator.

GroupedCrossValidationFoldGeneratorUsingNumericClassValues - Class in weka.classifiers

Helper class for generating cross-validation folds.
Uses the string representation of the numeric class values as grouping.

GroupedCrossValidationFoldGeneratorUsingNumericClassValues() - Constructor for class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Initializes the generator.

GroupedCrossValidationFoldGeneratorUsingNumericClassValues(Instances, int, long, boolean) - Constructor for class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Initializes the generator.

GroupedRandomSplitGenerator - Class in weka.classifiers

Generates random splits of datasets, making sure that groups of instances stay together (identified via a regexp).

GroupedRandomSplitGenerator() - Constructor for class weka.classifiers.GroupedRandomSplitGenerator

Initializes the generator.

GroupedRandomSplitGenerator(Instances, long, double, boolean, WekaAttributeIndex, BaseRegExp, String) - Constructor for class weka.classifiers.GroupedRandomSplitGenerator

Initializes the generator.

GroupExpression - Class in weka.filters.unsupervised.instance.multirowprocessor.selection

Identifies groups in strings using regular expressions.

GroupExpression() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

groups() - Method in class weka.core.InstanceGrouping

Returns the groups.

groupsTipText() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns the tip text for this property.

groupTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the tip text for this property.

groupTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns the tip text for this property.

groupTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

groupTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

groupTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the tip text for this property.

groupTipText() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns the tip text for this property.

groupTipText() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Returns the tip text for this property.

growPolicyTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the growPolicy option.

GUI - adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption

H

handleException(String, Throwable) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Logs the error and returns a compiled error string.

handlersTipText() - Method in class adams.opt.genetic.Hermione

Returns the tip text for this property.

handlerTipText() - Method in class adams.flow.sink.WekaExperimentFileWriter

Returns the tip text for this property.

handlerTipText() - Method in class adams.flow.transformer.WekaExperimentFileReader

Returns the tip text for this property.

handles(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput

Checks whether the cross-validation results can be processed.

handles(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Checks whether the cross-validation results can be processed.

handles(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Checks whether the cross-validation results can be processed.

handles(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Checks whether the cross-validation results can be processed.

handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.EncloseClassifier

Customizes the GOE popup menu.

handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.EncloseClusterer

Customizes the GOE popup menu.

handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.InvertInstancesColumnFinder

Customizes the GOE popup menu.

handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.InvertInstancesRowFinder

Customizes the GOE popup menu.

handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpClassifier

Customizes the GOE popup menu.

handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpClusterer

Customizes the GOE popup menu.

handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpInstancesColumnFinder

Customizes the GOE popup menu.

handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpInstancesRowFinder

Customizes the GOE popup menu.

handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.containerlistpopup.SaveAs

Checks whether this action can handle the panel.

handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.containerlistpopup.ViewAsTable

Checks whether this action can handle the panel.

handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Adjust

Checks whether this action can handle the panel.

handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Histogram

Checks whether this action can handle the panel.

handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.SaveVisible

Checks whether this action can handle the panel.

handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Viewport

Checks whether this action can handle the panel.

handles(Class) - Method in class adams.core.option.WekaCommandLineHandler

Checks whether the given class can be processed.

handles(Class) - Method in class adams.flow.core.WekaPropertyValueConverter

Checks whether this converter handles the particular class.

handles(Class) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler

Checks whether the given class can be processed.

handles(Class) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator

Returns whether this class is handled by this generator.

handles(Class) - Method in class adams.gui.visualization.debug.inspectionhandler.WekaEvaluation

Checks whether the handler can handle the specified class.

handles(Class) - Method in class adams.gui.visualization.debug.inspectionhandler.WekaInstances

Checks whether the handler can handle the specified class.

handles(Class) - Method in class adams.gui.visualization.debug.objectexport.WekaInstancesExporter

Checks whether the exporter can handle the specified class.

handles(Class) - Method in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer

Checks whether the renderer can handle the specified class.

handles(Object) - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Checks whether this object is handled by this discovery handler.

handles(Object) - Method in class adams.core.discovery.genetic.GenericFloatResolution

Checks whether this object is handled by this discovery handler.

handles(Object) - Method in class adams.core.discovery.genetic.GenericInteger

Checks whether this object is handled by this discovery handler.

handles(Object) - Method in class adams.core.discovery.genetic.GenericString

Checks whether this object is handled by this discovery handler.

handles(Object) - Method in class adams.core.discovery.genetic.GPDGamma

Checks whether this object is handled by this discovery handler.

handles(Object) - Method in class adams.core.discovery.genetic.GPDNoise

Checks whether this object is handled by this discovery handler.

handles(Object) - Method in class adams.core.discovery.genetic.PLSFilterNumComponents

Checks whether this object is handled by this discovery handler.

handles(Object) - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints

Checks whether this object is handled by this discovery handler.

handles(Object) - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix

Checks whether this object is handled by this discovery handler.

handles(Object) - Method in class adams.gui.tools.previewbrowser.GraphSource

Returns whether viewer handles this object.

handles(Object) - Method in class adams.gui.tools.previewbrowser.GraphVisualizer

Returns whether viewer handles this object.

handles(Object) - Method in class adams.gui.tools.previewbrowser.InterQuartileRangeViewer

Returns whether viewer handles this object.

handles(Object) - Method in class adams.gui.tools.previewbrowser.TreeVisualizer

Returns whether viewer handles this object.

handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Checks whether this handler can process the given panel.

handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AssociationsHandler

Checks whether this handler can process the given panel.

handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AttributeSelectionHandler

Checks whether this handler can process the given panel.

handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ClassifierHandler

Checks whether this handler can process the given panel.

handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ClustererHandler

Checks whether this handler can process the given panel.

handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.DefaultHandler

Checks whether this handler can process the given panel.

handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ExperimentHandler

Checks whether this handler can process the given panel.

handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.PreprocessHandler

Checks whether this handler can process the given panel.

handlesExperiment(AbstractExperiment) - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

Checks whether the experiment can be handled.

handlesExperiment(Object) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Checks whether the experiment can be handled.

handlesExperiment(T) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

Checks whether the experiment can be handled.

handlesExperiment(Experiment) - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

Checks whether the experiment can be handled.

handlesResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel

Returns whether this panel handles the specified ResultListener.

handlesResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel

Returns whether this panel handles the specified ResultListener.

handlesResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel

Returns whether this panel handles the specified ResultListener.

handlesResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel

Returns whether this panel handles the specified ResultListener.

handlesResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel

Returns whether this panel handles the specified ResultListener.

handlesResults(Instances) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

Checks whether the results can be handled at all.

handlesResults(Instances) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Checks whether the results can be handled at all.

handlesResults(Instances) - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

Checks whether the results can be handled at all.

handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.AttributeStatistics

Checks whether the row range can be handled.

handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.Binning

Checks whether the row range can be handled.

handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight

Checks whether the row range can be handled.

handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.ColumnStatistic

Checks whether the row range can be handled.

handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.DataSort

Checks whether the row range can be handled.

handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.Histogram

Checks whether the row range can be handled.

handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Checks whether the row range can be handled.

handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Checks whether the row range can be handled.

hasAdditionalAttributes() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns whether additional attributes data is present.

hasAttributeIndex() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Checks whether an attribute index has been set.

hasCallableActor() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Checks whether a reference to the callable actor is currently available.

hasCell(int) - Method in class adams.ml.data.InstancesHeaderRow

Returns whether the row alread contains the cell at the specified location.

hasCell(int) - Method in class adams.ml.data.InstanceView

Returns whether the row alread contains the cell at the specified location.

hasCell(int, int) - Method in class adams.ml.data.InstancesView

Checks whether the cell with the given indices already exists.

hasCell(String) - Method in class adams.ml.data.InstancesHeaderRow

Returns whether the row alread contains the cell with the given key.

hasCell(String) - Method in class adams.ml.data.InstanceView

Returns whether the row alread contains the cell with the given key.

hasChanged(DataContainer) - Method in class adams.gui.tools.wekainvestigator.datatable.action.Revert

Checks whether the container got changed or the source has changed.

hasClassifyTab() - Method in class weka.gui.explorer.ExplorerExt

Returns whether the classify tab is present.

hasClusterTab() - Method in class weka.gui.explorer.ExplorerExt

Returns whether the cluster tab is present.

hasCustomPanel(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler

Checks whether the editor supplies its own panel.

hasDataChanged(List<String>, ComboBoxModel<String>) - Static method in class adams.gui.tools.wekainvestigator.evaluation.DatasetHelper

Checks whether the data has changed and the model needs updating.

hasDataChanged(List<String>, ComboBoxModel<String>) - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Checks whether the data has changed and the model needs updating.

hasDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Checks whether an existing file has been set.

hasDatasetHeader() - Method in class adams.data.instance.Instance

Returns whether a header of a dataset is available.

hasEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

Returns whether an Evaluation object is present.

hasEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns whether an Evaluation object is present.

hasEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns whether an Evaluation object is present.

hasExperiment() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

Returns whether an Evaluation object is present.

hasFoldEvaluations() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns whether Evaluation objects per fold are present.

hasFoldModels() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns whether Classifier objects per fold are present.

hasFull() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Checks whether a full dataset is present.

hasGraph(Drawable) - Static method in class adams.gui.tools.wekainvestigator.output.GraphHelper

Checks whether an actual graph is available.

HashableInstanceUsingString - Class in weka.core

TODO: what this class does

HashableInstanceUsingString(Instance) - Constructor for class weka.core.HashableInstanceUsingString

Initializes the wrapper.

HashableInstanceUsingSum - Class in weka.core

Computes the hashcode as sum of the internal double values.

HashableInstanceUsingSum(Instance) - Constructor for class weka.core.HashableInstanceUsingSum

Initializes the wrapper.

hashCode() - Method in class adams.gui.visualization.instance.InstanceContainer

Returns the hashcode of the instance.

hashCode() - Method in class weka.core.AbstractHashableInstance

Returns the hashcode of this Instance, computes it if neccessary.

hasHeader() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

Returns whether an training set header is present.

hasLastError() - Method in class weka.classifiers.AggregateEvaluations

Returns whether an error was encountered during the last operation.

hasLoadings() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class adams.data.instancesanalysis.pls.DIPLS

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class adams.data.instancesanalysis.pls.NIPALS

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class adams.data.instancesanalysis.pls.OPLS

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class adams.data.instancesanalysis.pls.PLS1

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class adams.data.instancesanalysis.pls.PRM

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class adams.data.instancesanalysis.pls.SIMPLS

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class adams.data.instancesanalysis.pls.VCPLS

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class weka.classifiers.functions.PLSWeighted

Whether the algorithm supports return of loadings.

hasLoadings() - Method in interface weka.core.GenericPLSMatrixAccess

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class weka.filters.supervised.attribute.MultiPLS

Whether the algorithm supports return of loadings.

hasLoadings() - Method in class weka.filters.supervised.attribute.PLS

Whether the algorithm supports return of loadings.

hasMissingValue() - Method in class weka.core.AbstractHashableInstance

Tests whether an instance has a missing value.

hasModel() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

Returns whether an model object is present.

hasModel() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns whether an model object is present.

hasModel() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns whether an model object is present.

hasMoreData() - Method in class adams.data.io.input.InstanceReader

Returns whether there is more data available.

hasMoreElements() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID.UniqueIDEnumeration

hasMoreElements() - Method in class adams.flow.transformer.wekadatasetsmerge.Simple.SimpleRowSetIterator

hasMoreElements() - Method in class weka.core.tokenizers.MultiTokenizer

Tests if this enumeration contains more elements.

hasMoreElements() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Tests if this enumeration contains more elements.

hasMoreZeroes(BitSet, BitSet) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

return if a has more zeroes than b.

hasName() - Method in class adams.ml.data.InstancesView

Returns whether the spreadsheet has a name.

hasNestedItems() - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem

Returns whether nested items are present.

hasNext() - Method in class weka.classifiers.AbstractSplitGenerator

Returns true if the iteration has more elements.

hasNext() - Method in interface weka.classifiers.SplitGenerator

Returns true if the iteration has more elements.

hasOriginalIndices() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns whether the original indices are present.

hasPendingOutput() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Checks whether there is pending output to be collected after executing the flow item.

hasPendingOutput() - Method in class adams.flow.source.WekaDatabaseReader

Checks whether there is pending output to be collected after executing the flow item.

hasPendingOutput() - Method in class adams.flow.transformer.WekaAccumulatedError

Checks whether there is pending output to be collected after executing the flow item.

hasPendingOutput() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Checks whether there is pending output to be collected after executing the flow item.

hasPendingOutput() - Method in class adams.flow.transformer.WekaFileReader

Checks whether there is pending output to be collected after executing the flow item.

hasPendingOutput() - Method in class adams.flow.transformer.WekaInstanceBuffer

Checks whether there is pending output to be collected after executing the flow item.

hasPendingOutput() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Checks whether there is pending output to be collected after executing the flow item.

hasPendingOutput() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Checks whether there is pending output to be collected after executing the flow item.

hasPendingOutput() - Method in class adams.flow.transformer.WekaSubsets

Checks whether there is pending output to be collected after executing the flow item.

hasPredictionsAvailable(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Checks whether any predictions are available from the selected items.

hasReadOnlyTable() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Returns whether a readonly table is used.

hasReadOnlyTable() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

Returns whether a readonly table is used.

hasReadOnlyTable() - Method in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab

Returns whether a readonly table is used.

hasReadOnlyTable() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Returns whether a readonly table is used.

hasReadOnlyTable() - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab

Returns whether a readonly table is used.

hasRegistered() - Method in class adams.gui.goe.WekaEditorsRegistration

Returns whether registration already occurred.

hasReport() - Method in class adams.data.instance.Instance

Checks whether a report is present.

hasResults() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

Checks whether there are any results available.

hasRow(int) - Method in class adams.ml.data.InstancesView

Returns whether the spreadsheet already contains the row with the given index.

hasRow(String) - Method in class adams.ml.data.InstancesView

Returns whether the spreadsheet already contains the row with the given key.

hasRunEvaluations() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns whether Evaluation objects per run are present.

hasRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

Returns whether run information is present.

hasRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Returns whether run information is present.

hasRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns whether run information is present.

hasRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns whether run information is present.

hasRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

Returns whether run information is present.

hasRunModels() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns whether Classifier objects per run are present.

hasRunOriginalIndices() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns whether the original indices per run are present.

hasSendToItem(Class[]) - Method in class adams.gui.tools.DatasetCompatibilityPanel

Checks whether something to send is available.

hasSendToItem(Class[]) - Method in class adams.gui.visualization.instance.InstanceExplorer

Checks whether something to send is available.

hasSendToItem(Class[]) - Method in class adams.gui.visualization.instances.InstancesTable

Checks whether something to send is available.

hasSendToItem(Class[]) - Method in class weka.gui.explorer.ExplorerExt

Checks whether something to send is available.

hasSourceChanged() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer

Returns true if the source has changed.

hasSourceChanged() - Method in interface adams.gui.tools.wekainvestigator.data.MonitoringDataContainer

Returns true if the source has changed.

hasSupplementaryData() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns whether an Supplementary object is present.

hasSupplementaryName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns whether a name for the Supplementary object is present.

hasValue() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Checks whether the value of text field is different from the default value, i.e., a proper value.

HEADER - adams.flow.transformer.WekaEvaluationInfo.InfoType

HEADER - adams.flow.transformer.WekaFileReader.OutputType

only the header.

HEADER - adams.flow.transformer.WekaInstancesInfo.InfoType

the header (as string).

headerTipText() - Method in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader

Returns the tip text for this property.

headerTipText() - Method in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader

Returns the tip text for this property.

Hermione - Class in adams.gui.menu

For optimizing datasets (parameter selection) using genetic algorithm.

Hermione - Class in adams.opt.genetic

Hermione.

Hermione() - Constructor for class adams.gui.menu.Hermione

Initializes the menu item with no owner.

Hermione() - Constructor for class adams.opt.genetic.Hermione

Hermione(AbstractApplicationFrame) - Constructor for class adams.gui.menu.Hermione

Initializes the menu item.

Hermione.HermioneJob - Class in adams.opt.genetic

A job class specific to Hermione.

HermioneJob(Hermione, int, int[], Instances, Instances) - Constructor for class adams.opt.genetic.Hermione.HermioneJob

Initializes the job.

hiClassifierTipText() - Method in class weka.classifiers.meta.HighLowSplit

hide(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, List<InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Viewport

Allows the user to hide the instances.

hideButtons(Container) - Method in class weka.gui.explorer.ExplorerExt

Hides the buttons of the preprocess panel.

hideOthers(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, List<InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Viewport

Allows the user to hide all other instances.

HighLowSplit - Class in weka.classifiers.meta

Uses base classifier to get guess, then get prediction from either lo/hi classifier

Valid options are:

HighLowSplit() - Constructor for class weka.classifiers.meta.HighLowSplit

HighLowSplitSingleClassifier - Class in weka.classifiers.meta

Uses base classifier to get guess, then get prediction from either lo/hi classifier

Valid options are:

HighLowSplitSingleClassifier() - Constructor for class weka.classifiers.meta.HighLowSplitSingleClassifier

hiLopointTipText() - Method in class weka.classifiers.meta.HighLowSplit

HINGE_LOSS_FOR_BINARY_CLASSIFICATION - weka.classifiers.trees.XGBoost.Objective

HIST - weka.classifiers.trees.XGBoost.TreeMethod

HistCalc() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel.HistCalc

Histogram - Class in adams.gui.visualization.instance.plotpopup

Generates histograms from the visible containers.

Histogram - Class in adams.gui.visualization.instances.instancestable

Allows to generate a histogram from a column or row.

Histogram() - Constructor for class adams.gui.visualization.instance.plotpopup.Histogram

Histogram() - Constructor for class adams.gui.visualization.instances.instancestable.Histogram

HistogramFactory - Class in adams.gui.visualization.instance

A factory for histogram related objects.

HistogramFactory() - Constructor for class adams.gui.visualization.instance.HistogramFactory

HistogramFactory.Dialog - Class in adams.gui.visualization.instance

Dialog for displaying histograms generated from instances.

HistogramFactory.Panel - Class in adams.gui.visualization.instance

A panel for displaying a histogram based on the GC data of a instance.

HistogramFactory.SetupDialog - Class in adams.gui.visualization.instance

A dialog that queries the user about parameters for displaying histograms.

histogramOptionsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Tip text for the histogram options property.

HISTORY - adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption

historyEntrySelected(AbstractNamedHistoryPanel.HistoryEntrySelectionEvent) - Method in class weka.gui.explorer.MultiExplorer

Gets called whenever a history entry gets selected.

HistoryPanel(AssociateTab) - Constructor for class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Initializes the history.

HistoryPanel(AttributeSelectionTab) - Constructor for class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Initializes the history.

HistoryPanel(ClassifyTab) - Constructor for class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Initializes the history.

HistoryPanel(ClusterTab) - Constructor for class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Initializes the history.

HistoryPanel(ExperimentTab) - Constructor for class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Initializes the history.

HistoryPanel(DefaultAnalysisPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel.HistoryPanel

Initializes the history.

HOLDOUT_PERCENTAGE - Static variable in class weka.classifiers.meta.ClassifierCascade

holdOutPercentageTipText() - Method in class weka.classifiers.meta.ClassifierCascade

Returns the tip text for this property.

I

ICATipText() - Method in class adams.data.instancesanalysis.FastICA

Returns the tip text for this property.

IDTestTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the tip text for this property.

IDTipText() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the tip text for this property.

IDTipText() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Returns the tip text for this property.

IDTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the tip text for this property.

ignoreClassTipText() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

Returns the tip text for this property.

IGNORED_ATTRIBUTES - Static variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

ignoredAttributesTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Returns the tip text for this property.

implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.functions.PyroProxy

Returns true if this BatchPredictor can generate batch predictions in an efficient manner.

includeClassTipText() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns the tip text for this property.

includeClassTipText() - Method in class weka.filters.unsupervised.instance.Sort

Returns the tip text for this property.

incorrectTipText() - Method in class weka.filters.unsupervised.attribute.SpellChecker

Returns the tip text for this property.

incProgress() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Increments and updates the progress.

INCREMENTAL - adams.flow.transformer.WekaFileReader.OutputType

row by row.

incrementalTipText() - Method in class adams.flow.source.WekaDatabaseReader

Returns the tip text for this property.

IndependentComponentsTab - Class in adams.gui.tools.wekainvestigator.tab

Visualizes the ICA components/sources and ICA space calculated from the selected dataset.

IndependentComponentsTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

index() - Method in class adams.ml.data.DataCellView

Returns the column this cell is in.

index(int) - Method in class weka.core.AbstractHashableInstance

Returns the index of the attribute stored at the given position in the sparse representation.

INDEX - Static variable in class weka.filters.unsupervised.attribute.NominalToNumeric

INDEX - Static variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

INDEX - Static variable in class weka.filters.unsupervised.instance.RemoveWithLabels

IndexedSplitsRunsEvaluation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation

Performs the evaluation according to the provided indexed splits.

IndexedSplitsRunsEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

indexOf(Cell) - Method in class adams.ml.data.InstancesHeaderRow

Returns the column this particular cell is in (must belong to this row!).

indexOf(Cell) - Method in class adams.ml.data.InstanceView

Returns the column this particular cell is in (must belong to this row!).

indexOf(String) - Method in class adams.gui.visualization.instance.InstanceContainerManager

Determines the index of the sequence with the specified ID.

indexOfColumn(String) - Method in class adams.ml.data.InstancesView

Returns the index of the column using the specified name.

indexOfDataset(List<DataContainer>, String) - Static method in class adams.gui.tools.wekainvestigator.evaluation.DatasetHelper

Determines the index of the old dataset name in the current dataset model.

indexOfUnescaped(String, char, int) - Method in class weka.core.converters.SimpleArffLoader

Finds the index of an unescaped (ie not preceded by backslash) character starting with the provided starting position.

indexTipText() - Method in class adams.data.weka.classattribute.AttributeIndex

Returns the tip text for this property.

indexTipText() - Method in class adams.data.weka.relationname.AttributeIndex

Returns the tip text for this property.

indexTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the tip text for this property.

indexTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns the tip text for this property.

indexTipText() - Method in class adams.flow.transformer.WekaExtractArray

Returns the tip text for this property.

indexTipText() - Method in class adams.flow.transformer.WekaGetInstanceValue

Returns the tip text for this property.

indexTipText() - Method in class adams.flow.transformer.WekaSetInstanceValue

Returns the tip text for this property.

indexTipText() - Method in class adams.flow.transformer.WekaSubsets

Returns the tip text for this property.

indexTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

indexTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

indexTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the tip text for this property.

indexTipText() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns the tip text for this property.

indexTipText() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Returns the tip text for this property.

indexTipText() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the tip text for this property.

indexTipText() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Returns the tip text for this property.

indexTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns the tip text for this property.

indicesTipText() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns the tip text for this property.

IndividualRows - Class in weka.filters.unsupervised.instance.multirowprocessor.selection

Just selects each row by itself.

IndividualRows() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.selection.IndividualRows

INFO - weka.classifiers.trees.XGBoost.Verbosity

init() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

init(int) - Method in class adams.opt.genetic.PackDataGeneticAlgorithm

init(int) - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm

init(int, int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Initializes the algorithm.

init(Associator) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation

Initializes the result item.

init(Associator) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

Initializes the result item.

init(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation

Initializes the result item.

init(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

Initializes the result item.

init(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Initializes the result item.

init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Initializes the result item.

init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation

Initializes the result item.

init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

Initializes the result item.

init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Initializes the result item.

init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

Initializes the result item.

init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Initializes the result item.

init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

Initializes the result item.

init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

Initializes the result item.

initActions() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Initializes the actions.

initActualFilter(Instances) - Method in class adams.flow.transformer.WekaFilter

Initializes the actual filter to use.

initExecute() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Initializes the experiment.

initFilters(boolean, Class[]) - Static method in class adams.gui.chooser.AdamsExperimentFileChooser

initializes the filters.

initFilters(boolean, Class[]) - Static method in class adams.gui.chooser.WekaFileChooser

initializes the SpreadSheetFileExtensionFilters.

initForDisplay() - Method in class adams.gui.goe.WekaExperimentFileEditor

Initializes the display of the value.

initGUI() - Method in class adams.gui.application.WekaExperimenterPreferencesPanel

initGUI() - Method in class adams.gui.application.WekaExplorerPreferencesPanel

initGUI() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel

initGUI() - Method in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog

Sets up the GUI components.

initGUI() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog

For initializing the GUI.

initGUI() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

For initializing the GUI.

initGUI() - Method in class adams.gui.InstanceCompare

Initializes the widgets.

initGUI() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.DatasetCompatibilityPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.weka.AbstractPanelWithFile

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.weka.AppendDatasetsPanel

For initializing the GUI.

initGUI() - Method in class adams.gui.tools.weka.BatchFilterDatasetsPanel

For initializing the GUI.

initGUI() - Method in class adams.gui.tools.weka.CostCurvePanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTable

Initializes some GUI-related things.

initGUI() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Initializes the panel.

initGUI() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.LogTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.StatisticsTable

Initializes the table.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

For initializing the GUI.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

For initializing the GUI.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

For initializing the GUI.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.LogPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.tools.WekaOptionsConversionPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Initializes the widgets.

initGUI() - Method in class adams.gui.visualization.instance.InstanceExplorer

Initializes the widgets.

initGUI() - Method in class adams.gui.visualization.instance.InstancePanel

Initializes the GUI.

initGUI() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Initializes the GUI elements.

initGUI() - Method in class adams.gui.visualization.instances.InstancesPanel

Initializes the members.

initGUI() - Method in class adams.gui.visualization.instances.InstancesTable

Initializes the widget.

initGUI() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Initializes the widgets.

initGUI() - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Sets up the GUI components.

initGUI() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

Initializes the widets.

initGUI() - Method in class adams.gui.wizard.WekaSelectDatasetPage

Initializes the widets.

initGUI() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

Initializes the widets.

initGUI() - Method in class weka.gui.explorer.ExplorerExt

Initializes the widgets.

initGUI() - Method in class weka.gui.explorer.MultiExplorer

For initializing the GUI.

initGUI() - Method in class weka.gui.explorer.SqlPanel

initializes the GUI

initGUI(JComponent, boolean) - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel

Initializes the panel with the specified component.

initGUI(JComponent, boolean) - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel

Initializes the panel with the specified component.

initGUI(JComponent, boolean, boolean) - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel

Initializes the panel with the specified component.

initHelp() - Method in class adams.flow.container.WekaAssociatorContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaAttributeSelectionContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaClusterEvaluationContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaClusteringContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaEvaluationContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaExperimentContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaFilterContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaGeneticAlgorithmContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaGeneticAlgorithmInitializationContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaModelContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaNearestNeighborSearchContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaPredictionContainer

Initializes the help strings.

initHelp() - Method in class adams.flow.container.WekaTrainTestSetContainer

Initializes the help strings.

initialDirectoryTipText() - Method in class adams.flow.source.WekaSelectDataset

Returns the tip text for this property.

initialFilesTipText() - Method in class adams.flow.source.WekaSelectDataset

Returns the tip text for this property.

initialiseW(Instances) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter

initialiseW(Instances) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

initialiseWeights() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter

initialiseWeights() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

initializationMethodTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

initialize() - Method in class adams.data.conversion.WekaEvaluationToCostCurve

Initializes the members.

initialize() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve

Initializes the members.

initialize() - Method in class adams.data.instances.AbstractInstanceGenerator

Initializes the members.

initialize() - Method in class adams.data.io.input.AbstractWekaSpreadSheetReader

Initializes the members.

initialize() - Method in class adams.data.io.output.AbstractWekaSpreadSheetWriter

Initializes the members.

initialize() - Method in class adams.data.weka.rowfinder.FilteredIQR

Initializes the members.

initialize() - Method in class adams.flow.core.WekaPropertyValueConverter

Initializes member variables.

initialize() - Method in class adams.flow.sink.WekaCostCurve

Initializes the members.

initialize() - Method in class adams.flow.sink.WekaThresholdCurve

Initializes the members.

initialize() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Initializes the members.

initialize() - Method in class adams.flow.source.WekaNewInstances

Initializes the members.

initialize() - Method in class adams.flow.source.WekaSelectDataset

Initializes the members.

initialize() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

initialize() - Method in class adams.flow.transformer.WekaChooseAttributes

Initializes the members.

initialize() - Method in class adams.flow.transformer.WekaClassifierRanker

Initializes the members.

initialize() - Method in class adams.flow.transformer.WekaClassSelector

Initializes the members.

initialize() - Method in class adams.flow.transformer.WekaExtractArray

Initializes the member variables.

initialize() - Method in class adams.flow.transformer.WekaFilter

Initializes the members.

initialize() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Initializes the members.

initialize() - Method in class adams.flow.transformer.WekaGetInstancesValue

Initializes the members.

initialize() - Method in class adams.flow.transformer.WekaGetInstanceValue

Initializes the members.

initialize() - Method in class adams.flow.transformer.WekaInstanceDumper

Initializes the members.

initialize() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Initializes the members.

initialize() - Method in class adams.flow.transformer.WekaSetInstancesValue

Initializes the members.

initialize() - Method in class adams.flow.transformer.WekaSetInstanceValue

Initializes the members.

initialize() - Method in class adams.flow.transformer.WekaSubsets

Initializes the members.

initialize() - Method in class adams.gui.chooser.DatasetFileChooserPanel

Initializes the members.

initialize() - Method in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog

Initializes its members.

initialize() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog

For initializing members.

initialize() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Initializes the members.

initialize() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

For initializing members.

initialize() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel

Initializes the members.

initialize() - Method in class adams.gui.InstanceCompare

For initializing members.

initialize() - Method in class adams.gui.menu.AbstractParameterHandlingWekaMenuItemDefinition

Initializes the members.

initialize() - Method in class adams.gui.menu.BoundaryVisualizer

Initializes members.

initialize() - Method in class adams.gui.menu.CostCurve

Initializes members.

initialize() - Method in class adams.gui.menu.GraphVisualizer

Initializes members.

initialize() - Method in class adams.gui.menu.InstancesPlot

Initializes members.

initialize() - Method in class adams.gui.menu.MarginCurve

Initializes members.

initialize() - Method in class adams.gui.menu.ROC

Initializes members.

initialize() - Method in class adams.gui.menu.TreeVisualizer

Initializes members.

initialize() - Method in class adams.gui.tools.DatasetCompatibilityPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Save

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Initializes the widgets.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Initializes the widgets.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Initializes the widgets.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.DataTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

Initializes the members.

initialize() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

For initializing members.

initialize() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

For initializing members.

initialize() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

For initializing members.

initialize() - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

Initializes the members.

initialize() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel

Initializes the members.

initialize() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Initializes the indexer, if necessary.

initialize() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Initializes the members.

initialize() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Initializes the members.

initialize() - Method in class adams.gui.visualization.instance.InstanceContainer

Initializes members.

initialize() - Method in class adams.gui.visualization.instance.InstanceContainerModel

Initializes the members.

initialize() - Method in class adams.gui.visualization.instance.InstanceExplorer

Initializes the members.

initialize() - Method in class adams.gui.visualization.instance.InstancePanel

Initializes the members.

initialize() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Initializes the members.

initialize() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Initializes the members.

initialize() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

Initializes the members.

initialize() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Initializes the members.

initialize() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Initializes the members.

initialize() - Method in class adams.opt.optimise.GeneticAlgorithm

Initializes the members.

initialize() - Method in class adams.tools.CompareDatasets

Initializes the members.

initialize() - Method in class weka.classifiers.AbstractSplitGenerator

Initializes the members.

initialize() - Method in class weka.classifiers.AggregateEvaluations

Initializes the members.

initialize() - Method in class weka.classifiers.MultiLevelSplitGenerator

Initializes the members.

initialize() - Method in class weka.core.InstanceGrouping

Initializes the grouping.

initialize() - Method in class weka.core.SAXDistance

initializes the ranges and the attributes being used.

initialize() - Method in class weka.core.WeightedEuclideanDistance

initializes the ranges and the attributes being used.

initialize() - Method in class weka.core.WeightedEuclideanDistanceRidge

initializes the ranges and the attributes being used.

initialize() - Method in class weka.gui.explorer.ExplorerEntryPanel

Initializes the members.

initialize() - Method in class weka.gui.explorer.ExplorerExt

Initializes the members.

initialize() - Method in class weka.gui.explorer.MultiExplorer

initialize(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Converts the instance into a different format.

initializeConverters(File) - Method in class adams.gui.chooser.DatasetFileChooserPanel

Initializes the converters.

initializeDialog() - Method in class adams.flow.source.WekaSelectObjects

Initializes the interactive dialog with the

initializeIterator() - Method in class weka.classifiers.AbstractSplitGenerator

Initializes the iterator, randomizes the data if required.

initializeIterator() - Method in interface weka.classifiers.SplitGenerator

Initializes the iterator (gets implicitly called, when calling next()).

initializeOnceTipText() - Method in class adams.flow.transformer.WekaFilter

Returns the tip text for this property.

initializeOnceTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the tip text for this property.

initialSortNewTableModel() - Method in class adams.gui.visualization.instance.InstanceTable

Returns the initial setting of whether to sort new models.

initialUseOptimalColumnWidths() - Method in class adams.gui.visualization.instance.InstanceTable

Returns the initial setting of whether to set optimal column widths.

initLookup() - Method in class adams.tools.CompareDatasets

Initializes the lookup table of indices for the second dataset, if necessary.

initOutputBuffer() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Initializes the output buffer.

initOutputBuffer() - Method in class adams.multiprocess.WekaCrossValidationExecution

Initializes the output buffer.

initProgress() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Initializes progress.

initResults() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Initializes the results.

initServer() - Method in class weka.classifiers.meta.SocketFacade

Initializes the server socket if necessary.

input(Instance) - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Input an instance for filtering.

input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Input an instance for filtering.

InputSmearing - Class in weka.classifiers.meta

Extended version of weka.classifiers.meta.Bagging, which allows input smearing of numeric attributes.
Class for bagging a classifier to reduce variance.

InputSmearing - Class in weka.filters.unsupervised.attribute

InputSmearing() - Constructor for class weka.classifiers.meta.InputSmearing

InputSmearing() - Constructor for class weka.filters.unsupervised.attribute.InputSmearing

insertAttributeAt(int) - Method in class weka.core.AbstractHashableInstance

Inserts an attribute at the given position (0 to numAttributes()).

insertAttributeAt(Attribute, int) - Method in class weka.core.InstancesView

Inserts an attribute at the given position (0 to numAttributes()) and sets all values to be missing.

insertColumn(int, String) - Method in class adams.ml.data.InstancesView

Inserts a column at the specified location.

insertColumn(int, String, String) - Method in class adams.ml.data.InstancesView

Inserts a column at the specified location.

insertColumn(int, String, String, boolean) - Method in class adams.ml.data.InstancesView

Inserts a column at the specified location.

insertInstance(int) - Method in class adams.gui.visualization.instances.InstancesTableModel

insertInstance(int, boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel

insertRow(int) - Method in class adams.ml.data.InstancesView

Inserts a row at the specified location.

insertUpdate(DocumentEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationDocumentListener

inspect(Object) - Method in class adams.gui.visualization.debug.inspectionhandler.WekaEvaluation

Returns further inspection values.

inspect(Object) - Method in class adams.gui.visualization.debug.inspectionhandler.WekaInstances

Returns further inspection values.

INSTALLED - adams.flow.source.wekapackagemanageraction.ListPackages.ListType

InstallFromFile - Class in adams.flow.transformer.wekapackagemanageraction

Action that installs packages from files.

InstallFromFile() - Constructor for class adams.flow.transformer.wekapackagemanageraction.InstallFromFile

InstallFromURL - Class in adams.flow.transformer.wekapackagemanageraction

Action that installs packages from URLs.

InstallFromURL() - Constructor for class adams.flow.transformer.wekapackagemanageraction.InstallFromURL

installLinearModels() - Method in class weka.classifiers.trees.m5.RuleNode2

Traverses the tree and installs linear models at each node.

InstallOfficial - Class in adams.flow.transformer.wekapackagemanageraction

Action that installs official packages via their name and (optional) version.

InstallOfficial() - Constructor for class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

InstallPackage - Class in adams.flow.transformer.wekapackagemanageraction

Action that installs the incoming package.

InstallPackage() - Constructor for class adams.flow.transformer.wekapackagemanageraction.InstallPackage

installSmoothedModels() - Method in class weka.classifiers.trees.m5.RuleNode2

instance(int) - Method in class weka.core.InstancesView

Returns the instance at the given position.

Instance - Class in adams.data.instance

Stores values from weka.core.Instance objects, with X being the attribute index (integer) and Y being the internal value (double).

Instance() - Constructor for class adams.data.instance.Instance

Initializes the sequence.

INSTANCE_TO_INSTANCES - adams.flow.transformer.WekaInstanceBuffer.Operation

Instance -> Instances.

instanceClassTipText() - Method in class adams.flow.transformer.WekaNewInstance

Returns the tip text for this property.

InstanceComparator - Class in adams.data.instances

For comparing instance objects.

InstanceComparator(int[]) - Constructor for class adams.data.instances.InstanceComparator

Initializes the comparator.

InstanceComparator(int[], boolean[]) - Constructor for class adams.data.instances.InstanceComparator

Initializes the comparator.

InstanceCompare - Class in adams.gui

Stand-alone version of the Instance Compare utility.

InstanceCompare - Class in adams.gui.menu

For comparing two datasets visually.

InstanceCompare() - Constructor for class adams.gui.InstanceCompare

InstanceCompare() - Constructor for class adams.gui.menu.InstanceCompare

Initializes the menu item with no owner.

InstanceCompare(AbstractApplicationFrame) - Constructor for class adams.gui.menu.InstanceCompare

Initializes the menu item.

InstanceCompareDefinition - Class in adams.env

Definition for the InstanceCompare props file.

InstanceCompareDefinition() - Constructor for class adams.env.InstanceCompareDefinition

InstanceComparePanel - Class in adams.gui.visualization.instance

A tool for comparing two datasets visually.

InstanceComparePanel() - Constructor for class adams.gui.visualization.instance.InstanceComparePanel

InstanceComparePanel.DatasetIndexer - Class in adams.gui.visualization.instance

Helper class for indexing the rows of a dataset.

InstanceComparePanel.DatasetPanel - Class in adams.gui.visualization.instance

Specialized panel for loading dataset and setting various parameters.

InstanceContainer - Class in adams.gui.visualization.instance

A container class for a weka.core.Instance wrapped in a weka.core.Instance.

InstanceContainer(InstanceContainerManager, Instance) - Constructor for class adams.gui.visualization.instance.InstanceContainer

Initializes the container.

InstanceContainerDisplayIDGenerator - Class in adams.gui.visualization.instance

Class for generating display IDs for Instance objects (based on weka.core.Instance objects).

InstanceContainerDisplayIDGenerator() - Constructor for class adams.gui.visualization.instance.InstanceContainerDisplayIDGenerator

InstanceContainerList - Class in adams.gui.visualization.instance

A panel that lists Instances in a JTable.

InstanceContainerList() - Constructor for class adams.gui.visualization.instance.InstanceContainerList

InstanceContainerManager - Class in adams.gui.visualization.instance

A handler for the Instance containers.

InstanceContainerManager(ContainerListManager<InstanceContainerManager>) - Constructor for class adams.gui.visualization.instance.InstanceContainerManager

Initializes the manager.

InstanceContainerModel - Class in adams.gui.visualization.instance

A model for displaying the currently loaded Instance objects.

InstanceContainerModel(ContainerListManager<InstanceContainerManager>) - Constructor for class adams.gui.visualization.instance.InstanceContainerModel

Initializes the model.

InstanceContainerModel(InstanceContainerManager) - Constructor for class adams.gui.visualization.instance.InstanceContainerModel

Initializes the model.

InstanceContainerTableColumnNameGenerator - Class in adams.gui.visualization.instance

Abstract class for generating the column names of a table.

InstanceContainerTableColumnNameGenerator() - Constructor for class adams.gui.visualization.instance.InstanceContainerTableColumnNameGenerator

InstanceDumperVariable - Class in adams.flow.template

Generates a sub-flow that sets a variable for the adams.flow.transformer.WekaInstanceDumper transformer's outputPrefix property using a prefix based on the full flow name.

InstanceDumperVariable() - Constructor for class adams.flow.template.InstanceDumperVariable

InstanceExplorer - Class in adams.gui.menu

For displaying and filtering instances.

InstanceExplorer - Class in adams.gui.visualization.instance

A panel for exploring Instances visually.

InstanceExplorer() - Constructor for class adams.gui.menu.InstanceExplorer

Initializes the menu item with no owner.

InstanceExplorer() - Constructor for class adams.gui.visualization.instance.InstanceExplorer

InstanceExplorer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.InstanceExplorer

Initializes the menu item.

InstanceExplorerDefinition - Class in adams.env

Definition for the InstanceExplorer props file.

InstanceExplorerDefinition() - Constructor for class adams.env.InstanceExplorerDefinition

InstanceExplorerHandler - Class in adams.gui.tools.previewbrowser

Displays the following WEKA dataset types in the Instance Explorer: csv,arff,arff.gz,xrff,xrff.gz

Valid options are:

InstanceExplorerHandler() - Constructor for class adams.gui.tools.previewbrowser.InstanceExplorerHandler

InstanceGeneratorWithAdditionalFields - Interface in adams.data.instances

Generators with additional fields.

InstanceGeneratorWithFields - Interface in adams.data.instances

Generators with fields.

InstanceGrouping - Class in weka.core

Groups rows in a dataset using a regular expression on a nominal or string attribute.

InstanceGrouping(Instances, WekaAttributeIndex, BaseRegExp, String) - Constructor for class weka.core.InstanceGrouping

Initializes the object.

InstanceLinePaintlet - Class in adams.gui.visualization.instance

Paintlet for generating a line plot for Instance objects.

InstanceLinePaintlet() - Constructor for class adams.gui.visualization.instance.InstanceLinePaintlet

InstanceLinePaintlet.MarkerShape - Enum in adams.gui.visualization.instance

Enum for the marker shape to plot around the data points.

InstanceNode(int, Double) - Constructor for class weka.core.neighboursearch.NewNNSearch.InstanceNode

InstancePanel - Class in adams.gui.visualization.instance

A panel for displaying instances.

InstancePanel() - Constructor for class adams.gui.visualization.instance.InstancePanel

Initializes the panel.

InstancePanel(String) - Constructor for class adams.gui.visualization.instance.InstancePanel

Initializes the panel.

InstancePoint - Class in adams.data.instance

A 2-dimensional point (X: attribute index, Y: internal value).

InstancePoint() - Constructor for class adams.data.instance.InstancePoint

Initializes the point with no points and no ID.

InstancePoint(Integer, Double) - Constructor for class adams.data.instance.InstancePoint

Initializes the point with no ID.

InstancePointComparator - Class in adams.data.instance

A comparator for InstancePoint objects.

InstancePointComparator() - Constructor for class adams.data.instance.InstancePointComparator

The default constructor uses comparison by X in ascending manner.

InstancePointComparator(boolean, boolean) - Constructor for class adams.data.instance.InstancePointComparator

This constructor initializes the comparator either with comparison by X or by Y.

InstancePointHitDetector - Class in adams.gui.visualization.instance

Detects selections of instance points in the instance panel.

InstancePointHitDetector(InstancePanel) - Constructor for class adams.gui.visualization.instance.InstancePointHitDetector

Initializes the hit detector.

InstanceReader - Class in adams.data.io.input

Reads WEKA datasets in various formats.

InstanceReader() - Constructor for class adams.data.io.input.InstanceReader

InstanceReportFactory - Class in adams.gui.visualization.instance

A factory for GUI components for Instance-related reports.

InstanceReportFactory() - Constructor for class adams.gui.visualization.instance.InstanceReportFactory

InstanceReportFactory.Panel - Class in adams.gui.visualization.instance

A specialized panel that displays reports.

InstanceReportFactory.Table - Class in adams.gui.visualization.instance

A specialized table for displaying a Report.

INSTANCES_TO_INSTANCE - adams.flow.transformer.WekaInstanceBuffer.Operation

Instances -> Instance.

instancesActorTipText() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Returns the tip text for this property.

InstancesColumnComboBox - Class in adams.gui.visualization.instances

ComboBox that lists the attribute names of the associated Instances in alphabetical order and when the user selects one, ensures that this column is visible.

InstancesColumnComboBox(InstancesTable) - Constructor for class adams.gui.visualization.instances.InstancesColumnComboBox

Initializes the combobox.

InstancesColumnComboBox.ColumnContainer - Class in adams.gui.visualization.instances

Container for storing column name and

InstancesCrossValidationFoldGenerator - Class in adams.flow.transformer.indexedsplitsrunsgenerator

Split generator that generates folds for cross-validation for Instances objects.

InstancesCrossValidationFoldGenerator() - Constructor for class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

InstancesGroupedCrossValidationFoldGenerator - Class in adams.flow.transformer.indexedsplitsrunsgenerator

Split generator that generates folds for cross-validation for Instances objects.

InstancesGroupedCrossValidationFoldGenerator() - Constructor for class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

InstancesGroupedRandomSplitGenerator - Class in adams.flow.transformer.indexedsplitsrunsgenerator

Random split generator that works on Instances objects (groups instances).

InstancesGroupedRandomSplitGenerator() - Constructor for class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

InstancesHeaderRow - Class in adams.ml.data

Header row for an Instances object.

InstancesHeaderRow(InstancesView) - Constructor for class adams.ml.data.InstancesHeaderRow

Initializes the header row.

InstancesIndexedSplitsRunsCompatibility - Class in adams.data.indexedsplits

Performs compatibility tests between indexed splits configurations and Weka Instances objects.

InstancesIndexedSplitsRunsCompatibility() - Constructor for class adams.data.indexedsplits.InstancesIndexedSplitsRunsCompatibility

InstancesIndexedSplitsRunsEvaluation - Class in adams.flow.transformer.indexedsplitsrunsevaluation

Evaluates the specified classifier on the indexed splits runs applied to the incoming data.

InstancesIndexedSplitsRunsEvaluation() - Constructor for class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

InstancesIndexedSplitsRunsGenerator - Interface in adams.flow.transformer.indexedsplitsrunsgenerator

Indicator interface for generators that process Instances objects.

InstancesIndexedSplitsRunsPredictions - Class in adams.flow.transformer.indexedsplitsrunspredictions

Trains the referenced classifier on the training splits and generates predictions for the test splits.

InstancesIndexedSplitsRunsPredictions() - Constructor for class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

instancesIndicesTipText() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Returns the tip text for this property.

InstancesPanel - Class in adams.gui.visualization.instances

Panel displaying an Instances table.

InstancesPanel() - Constructor for class adams.gui.visualization.instances.InstancesPanel

InstancesPlot - Class in adams.gui.menu

Displays plot of Instances.

InstancesPlot() - Constructor for class adams.gui.menu.InstancesPlot

Initializes the menu item with no owner.

InstancesPlot(AbstractApplicationFrame) - Constructor for class adams.gui.menu.InstancesPlot

Initializes the menu item.

InstancesRandomSplitGenerator - Class in adams.flow.transformer.indexedsplitsrunsgenerator

Random split generator that works on Instances objects.

InstancesRandomSplitGenerator() - Constructor for class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

InstancesSortDefinitionPanel - Class in adams.gui.visualization.instances.instancestable

Represents a single sorting definition.

InstancesSortDefinitionPanel(InstancesSortPanel) - Constructor for class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

Initializes the definition panel.

InstancesSortPanel - Class in adams.gui.visualization.instances.instancestable

Panel that allows users to sort instances over an arbitrary number of columns.

InstancesSortPanel() - Constructor for class adams.gui.visualization.instances.instancestable.InstancesSortPanel

InstancesSortSetupEvent - Class in adams.gui.event

Event that gets sent when the InstancesSortPanel setup changes.

InstancesSortSetupEvent(InstancesSortPanel, InstancesSortDefinitionPanel, InstancesSortSetupEvent.EventType) - Constructor for class adams.gui.event.InstancesSortSetupEvent

Initializes the event.

InstancesSortSetupEvent.EventType - Enum in adams.gui.event

The type of event.

InstancesSortSetupListener - Interface in adams.gui.event

Interface for listeners that react to changes in a sort setup of a InstancesSortPanel.

InstancesSummaryPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab

This panel just displays relation name, number of instances, and number of attributes.

InstancesSummaryPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

Creates the instances panel with no initial instances.

InstancesTable - Class in adams.gui.visualization.instances

Table for displaying Instances objects.

InstancesTable(InstancesTableModel) - Constructor for class adams.gui.visualization.instances.InstancesTable

Initializes the table with the model.

InstancesTable(Instances) - Constructor for class adams.gui.visualization.instances.InstancesTable

Initializes the table with the data.

InstancesTableModel - Class in adams.gui.visualization.instances

The model for the Instances.

InstancesTableModel() - Constructor for class adams.gui.visualization.instances.InstancesTableModel

performs some initialization

InstancesTableModel(Instances) - Constructor for class adams.gui.visualization.instances.InstancesTableModel

initializes the model with the given data

InstancesTablePopupMenuItem - Interface in adams.gui.visualization.instances.instancestable

Ancestor for menu items of popups for the InstancesTable.

InstancesTablePopupMenuItemHelper - Class in adams.gui.visualization.instances.instancestable

Helper class for constructing popup menus for the InstancesTable.

InstancesTablePopupMenuItemHelper() - Constructor for class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper

InstancesTablePopupMenuItemHelper.TableState - Class in adams.gui.visualization.instances.instancestable

Container object for the table state used by the popup menu items.

instancesToDMatrix(Instance[]) - Method in class weka.classifiers.trees.XGBoost

Converts a WEKA dataset into a DMatrix (the input type expected by XGBoost).

InstancesView - Class in adams.ml.data

Provides a view of an Instances object.

InstancesView - Class in weka.core

Presents a view of an Instances object.

InstancesView() - Constructor for class adams.ml.data.InstancesView

Initializes the view with a dummy dataset.

InstancesView(Instances) - Constructor for class adams.ml.data.InstancesView

Initializes the view.

InstancesView(Instances, int[]) - Constructor for class weka.core.InstancesView

Initializes the dataset.

InstancesView(Instances, int, int) - Constructor for class weka.core.InstancesView

Initializes the dataset.

InstancesViewCreator - Interface in adams.data.weka

Interface for classes that generate Weka Instances views.

InstancesViewSupporter - Interface in adams.data.weka

Interface for classes that support Weka Instances views.

InstanceTab - Class in adams.gui.tools.wekainvestigator.tab

Visualizes the selected dataset like the instance explorer.

InstanceTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.InstanceTab

InstanceTable - Class in adams.gui.visualization.instance

A specialized table for displaying an Instances object.

InstanceTable(Instances) - Constructor for class adams.gui.visualization.instance.InstanceTable

Initializes the table.

InstanceTableModel - Class in adams.gui.visualization.instance

A generic table model for displaying weka.core.Instances objects.

InstanceTableModel(Instances) - Constructor for class adams.gui.visualization.instance.InstanceTableModel

Initializes the model.

instanceToRow(Instance) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor

Converts a single Instance into a JSON array (excluding class).

instanceToRow(Instance, BaseString) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Converts a single Instance into a JSON array.

InstanceUtils - Class in adams.data.instance

Utility class for instances.

InstanceUtils() - Constructor for class adams.data.instance.InstanceUtils

InstanceView - Class in adams.ml.data

Wrapper around an Instance object.

InstanceView(InstancesView, Instance) - Constructor for class adams.ml.data.InstanceView

Initializes the row view.

InstanceZoomOverviewPaintlet - Class in adams.gui.visualization.instance

Highlights the current zoom in the instance panel.

InstanceZoomOverviewPaintlet() - Constructor for class adams.gui.visualization.instance.InstanceZoomOverviewPaintlet

InstanceZoomOverviewPanel - Class in adams.gui.visualization.instance

Panel that shows the zoom in the TIC panel as overlay.

InstanceZoomOverviewPanel() - Constructor for class adams.gui.visualization.instance.InstanceZoomOverviewPanel

intArrayToString(int[]) - Method in class adams.opt.genetic.Hermione

Int array of bits to string.

INTERNAL_REPRESENTATION - weka.filters.unsupervised.attribute.NominalToNumeric.ConversionType

interpolate(double, int, double, int, double) - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns interpolated value.

interpretePosition(Instances, String) - Method in class adams.data.instances.AbstractInstanceGenerator

Interpretes the position string based on the given dataset.

InterquartileRangeSamp - Class in weka.filters.unsupervised.attribute

A sampling filter for detecting outliers and extreme values based on interquartile ranges.

InterquartileRangeSamp() - Constructor for class weka.filters.unsupervised.attribute.InterquartileRangeSamp

InterquartileRangeSamp.IQRs - Class in weka.filters.unsupervised.attribute

Container class for the IQR values.

InterQuartileRangeViewer - Class in adams.gui.tools.previewbrowser

Displays internal values of the InterquartileRange filter.

InterQuartileRangeViewer() - Constructor for class adams.gui.tools.previewbrowser.InterQuartileRangeViewer

INTERSECT - adams.data.weka.columnfinder.MultiColumnFinder.Combination

intersect/and.

INTERSECT - adams.data.weka.rowfinder.MultiRowFinder.Combination

intersect/and.

IntervalEstimatorBased - Class in adams.data.weka.evaluator

Uses a classifier that produces confidence intervals.

IntervalEstimatorBased() - Constructor for class adams.data.weka.evaluator.IntervalEstimatorBased

IntervalEstimatorBased.SortedInterval - Class in adams.data.weka.evaluator

Helper class for sorting the confidence intervals.

intervalTipText() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns the tip text for this property.

intervalTipText() - Method in class adams.flow.transformer.WekaStreamEvaluator

Returns the tip text for this property.

invalidateHashCode() - Method in class weka.core.AbstractHashableInstance

Invalidates the hash code.

invalidateName() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

Invalidates the name.

inverse(Instances) - Method in class weka.filters.unsupervised.attribute.FastWavelet

Renames the attributes when using the inverse transform.

inverseTransformTipText() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Returns the tip text for this property.

inverseTransformTipText() - Method in class weka.filters.unsupervised.attribute.FFT

Returns the tip text for this property.

Invert - Class in adams.data.weka.columnfinder

Inverts the selected columns of the provided sub-column-filter.

Invert - Class in adams.data.weka.rowfinder

Inverts the selected rows of the provided sub-row-filter.

Invert() - Constructor for class adams.data.weka.columnfinder.Invert

Invert() - Constructor for class adams.data.weka.rowfinder.Invert

INVERT - Static variable in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

INVERT - Static variable in class weka.filters.unsupervised.instance.RemoveWithLabels

INVERT_SELECTION - Static variable in class weka.filters.unsupervised.instance.KennardStone

InvertInstancesColumnFinder - Class in adams.gui.goe.popupmenu

Encloses a Instances ColumnFinder in Invert.

InvertInstancesColumnFinder() - Constructor for class adams.gui.goe.popupmenu.InvertInstancesColumnFinder

InvertInstancesRowFinder - Class in adams.gui.goe.popupmenu

Encloses a Instances RowFinder in Invert.

InvertInstancesRowFinder() - Constructor for class adams.gui.goe.popupmenu.InvertInstancesRowFinder

invertMatchingSenseTipText() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the tip text for this property.

invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.KennardStone

Returns the tip text for this property.

invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Returns the tip text for this property.

invertTipText() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Returns the tip text for this property.

invertTipText() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns the tip text for this property.

invertTipText() - Method in class adams.flow.transformer.WekaRegexToRange

Returns the tip text for this property.

invertTipText() - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

Returns the tip text for this property.

invertTipText() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Returns the tip text for this property.

invertTipText() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Returns the tip text for this property.

invertTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Returns the tip text for this property

invertTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Returns the tip text for this property

invertTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the tip text for this property.

invertTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns the tip text for this property.

InvestigatorAsNewDataset - Class in adams.gui.visualization.instances.instancestable

Allows the user to add the selected rows as new dataset in the Investigator.

InvestigatorAsNewDataset() - Constructor for class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset

InvestigatorJob - Class in adams.gui.tools.wekainvestigator.job

For running jobs in the InvestigatorPanel.

InvestigatorJob(InvestigatorPanel, String) - Constructor for class adams.gui.tools.wekainvestigator.job.InvestigatorJob

Initializes the job.

InvestigatorManagerPanel - Class in adams.gui.tools.wekainvestigator

Manages multiple sessions of the Investigator.

InvestigatorManagerPanel() - Constructor for class adams.gui.tools.wekainvestigator.InvestigatorManagerPanel

InvestigatorPanel - Class in adams.gui.tools.wekainvestigator

The main panel for the Investigator.

InvestigatorPanel() - Constructor for class adams.gui.tools.wekainvestigator.InvestigatorPanel

InvestigatorTabbedPane - Class in adams.gui.tools.wekainvestigator.tab

Tabbed pane for managing the tabs of the Investigator.

InvestigatorTabbedPane(InvestigatorPanel) - Constructor for class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane

Initializes the tabbed pane.

InvestigatorTabJob - Class in adams.gui.tools.wekainvestigator.job

For running jobs in a AbstractInvestigatorTab.

InvestigatorTabJob(AbstractInvestigatorTab, String) - Constructor for class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob

Initializes the job.

InvestigatorTabRunnableJob - Class in adams.gui.tools.wekainvestigator.job

For executing Runnable's in a AbstractInvestigatorTab.

InvestigatorTabRunnableJob(AbstractInvestigatorTab, Runnable) - Constructor for class adams.gui.tools.wekainvestigator.job.InvestigatorTabRunnableJob

Initializes the job.

InvestigatorWorkspaceHelper - Class in adams.gui.tools.wekainvestigator

Helper class for Weka Investigator workspaces.

InvestigatorWorkspaceHelper() - Constructor for class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper

InvestigatorWorkspaceList - Class in adams.gui.tools.wekainvestigator

Lists the sessions.

InvestigatorWorkspaceList() - Constructor for class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceList

IQRs(double, double, double, double) - Constructor for class weka.filters.unsupervised.attribute.InterquartileRangeSamp.IQRs

iqrTipText() - Method in class adams.data.weka.rowfinder.FilteredIQR

Returns the tip text for this property.

IR_PRECISION - adams.flow.core.EvaluationStatistic

IR_PRECISION - adams.flow.core.ExperimentStatistic

IR_RECALL - adams.flow.core.EvaluationStatistic

IR_RECALL - adams.flow.core.ExperimentStatistic

isAbstaining(Instance) - Method in class weka.classifiers.meta.ConsensusOrVote

Determines whether to abstain from the prediction.

isAntiAliasingEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns whether anti-aliasing is used.

isAntiAliasingEnabled() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Returns whether anti-aliasing is used.

isAntiAliasingEnabled() - Method in class adams.gui.visualization.instance.InstancePanel

Returns whether anti-aliasing is used.

isAntiAliasingEnabled() - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet

Returns whether anti-aliasing is used.

isAnyClassAttribute(List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Checks if any of the source attributes in the given list is a class attribute.

isAnyDateType() - Method in class adams.ml.data.DataCellView

Checks whether the cell represents a date, time or date/time value.

isAscending() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

Returns whether ascending or descending is used.

isAvailable() - Method in class adams.data.io.input.AbstractAdamsExperimentReader

Returns whether the reader is actually available.

isAvailable() - Method in class adams.data.io.output.AbstractAdamsExperimentWriter

Returns whether the writer is actually available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotColumn

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotRow

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.Binning

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.Histogram

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItem

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Returns whether the menu item is available.

isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Returns whether the menu item is available.

isBoolean() - Method in class adams.ml.data.DataCellView

Checks whether the cell represents a boolean value.

isBusy() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Returns whether the tab is busy.

isBusy() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns whether the tab is busy.

isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Returns whether the tab is busy.

isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Returns whether the tab is busy.

isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Returns whether the tab is busy.

isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Returns whether the tab is busy.

isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Returns whether the tab is busy.

isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Returns whether the tab is busy.

isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Returns whether the tab is busy.

isButtonPanelVisible() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

Returns the visibility state of the buttons panel (load/save).

isCellEditable(int, int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

Returns whether a cell is editable.

isCellEditable(int, int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.StatisticsTable

returns always false, since it's just information for the user

isCellEditable(int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel

returns true if the cell at rowindex and columnindexis editable

isClassAttribute(int) - Method in class adams.ml.data.InstancesView

Returns whether the specified column is a class attribute.

isClassAttribute(int, int) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Whether the given attribute is a class attribute.

isClassAttribute(AbstractMerge.SourceAttribute) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Checks if the given source attribute is a class attribute.

isClassAttribute(String) - Method in class adams.ml.data.InstancesView

Returns whether the specified column is a class attribute.

isClassAttributeByName(String) - Method in class adams.ml.data.InstancesView

Returns whether the specified column is a class attribute.

isClassFirst() - Method in class weka.experiment.ExtExperiment

Returns whether the class is the first attribute.

isClassIndex(int) - Method in class adams.gui.visualization.instances.InstancesTableModel

checks whether the column represents the class or not

isColumnFinderTrained() - Method in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder

Checks whether the column finder has been trained.

isColumnFinderTrained() - Method in interface adams.data.weka.columnfinder.TrainableColumnFinder

Checks whether the column finder has been trained.

isCompatible(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Checks whether the selected datasets are compatible.

isCompatible(Dataset) - Method in class adams.ml.model.classification.WekaClassificationModel

Checks whether the dataset is compatible with the model.

isCompatible(Dataset) - Method in class adams.ml.model.clustering.WekaClusteringModel

Checks whether the dataset is compatible with the model.

isCompatible(Dataset) - Method in class adams.ml.model.regression.WekaRegressionModel

Checks whether the dataset is compatible with the model.

isCompatible(Object, IndexedSplitsRuns) - Method in class adams.data.indexedsplits.InstancesIndexedSplitsRunsCompatibility

Checks whether the data is compatible with the indexed splits.

isCompatible(Instance) - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader

Checks the instance against the header, whether they are compatible.

isComplete(int[]) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Checks whether the number of rows located in the current results are complete.

isComplete(int[]) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

Checks whether the number of rows located in the current results are complete.

isContentType(int, Cell.ContentType) - Method in class adams.ml.data.InstancesView

Checks whether the given column is of the specific content type or not.

isCrossValidation() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Returns whether cross-valiation was used.

isDataLoaded() - Method in class weka.gui.explorer.ExplorerExt

Checks whether data is currently loaded.

isDate() - Method in class adams.ml.data.DataCellView

Checks whether the cell represents a date value.

isDateLenient() - Method in class adams.ml.data.InstancesView

Returns whether the parsing of dates is lenient or not.

isDateTime() - Method in class adams.ml.data.DataCellView

Checks whether the cell represents a date/time value.

isDateTimeLenient() - Method in class adams.ml.data.InstancesView

Returns whether the parsing of date/times is lenient or not.

isDateTimeMsec() - Method in class adams.ml.data.DataCellView

Checks whether the cell represents a date/time with msec value.

isDateTimeMsecLenient() - Method in class adams.ml.data.InstancesView

Returns whether the parsing of date/time msecs is lenient or not.

isDottyTree(String) - Static method in class adams.gui.tools.wekainvestigator.output.GraphHelper

Simple check whether the string represents a dotty tree.

isDottyTree(Drawable) - Static method in class adams.gui.tools.wekainvestigator.output.GraphHelper

Simple check whether the drawble generates a dotty tree.

isDouble() - Method in class adams.ml.data.DataCellView

Returns whether the content represents a double number.

isExecuting() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Returns whether an experiment is currently being executed.

isFirstDefinition(InstancesSortDefinitionPanel) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Checks whether the panel is the first one.

isFormula() - Method in class adams.ml.data.DataCellView

Returns whether the content represents a formula.

isGOEEditor() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

Returns whether the underlying editor is GenericObjectEditor.

isHit(MouseEvent) - Method in class adams.gui.visualization.instance.InstancePointHitDetector

Checks for a hit.

isHtml(Class) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator

Returns whether the generated help is HTML or plain text.

isInitialized() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns whether the scheme has been initialized.

isInlineEditingAvailable() - Method in class adams.gui.goe.WekaExperimentFileEditor

Checks whether inline editing is available.

isInlineValueValid(String) - Method in class adams.gui.goe.WekaExperimentFileEditor

Checks whether the value id valid.

isInteractive() - Method in class adams.flow.template.InstanceDumperVariable

Whether the flow generated is an interactive one.

isLastDefinition(InstancesSortDefinitionPanel) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Checks whether the panel is the last one.

isLeaf() - Method in class weka.classifiers.trees.m5.RuleNode2

Return true if this node is a leaf

isLong() - Method in class adams.ml.data.DataCellView

Returns whether the content represents a long number.

isMarkersDisabled() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Returns whether marker shapes are disabled.

isMatch(InstanceContainer, String, boolean) - Method in class adams.gui.visualization.instance.InstanceContainerManager

Returns whether the container matches the current search.

isMissing() - Method in class adams.ml.data.DataCellView

Checks whether the cell contains a missing value.

isMissing(int) - Method in class weka.core.AbstractHashableInstance

Tests if a specific value is "missing".

isMissing(Attribute) - Method in class weka.core.AbstractHashableInstance

Tests if a specific value is "missing".

isMissingAt(int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel

checks whether the value at the given position is missing

isMissingSparse(int) - Method in class weka.core.AbstractHashableInstance

Tests if a specific value is "missing" in the sparse representation.

isModified() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Checks whether the data has been modified.

isModified() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer

Checks whether the data has been modified.

isModified() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

Returns whether the setup has been modified.

isNoCleanUp() - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

Returns whether to suppress automatic clean ups.

isNonInteractive() - Method in class adams.flow.source.WekaSelectDataset

Returns whether interactiveness is enabled/disabled.

isNonInteractive() - Method in class adams.flow.transformer.WekaChooseAttributes

Returns whether interactiveness is enabled/disabled.

isNotificationEnabled() - Method in class adams.gui.visualization.instances.InstancesTableModel

returns whether the notification of changes is enabled

isNumeric() - Method in class adams.ml.data.DataCellView

Checks whether the stored string is numeric.

isNumeric(int) - Method in class adams.ml.data.InstancesView

Checks whether the given column is numeric or not.

isNumeric(int, boolean) - Method in class adams.ml.data.InstancesView

Checks whether the given column is numeric or not.

isObject() - Method in class adams.ml.data.DataCellView

Returns whether the content represents an object.

isOfficial(String) - Static method in class weka.core.WekaPackageUtils

Checks whether the package is an official one.

isOfficial(Package) - Static method in class weka.core.WekaPackageUtils

Checks whether the package is an official one.

isOnlyNominal() - Method in enum adams.flow.core.EvaluationStatistic

Returns whether the statistic applies to nominal attributes only.

isOnlyNumeric() - Method in enum adams.flow.core.EvaluationStatistic

Returns whether the statistic applies to numeric attributes only.

isOutside(Instance, int, double, double) - Static method in class weka.classifiers.RangeCheckHelper

Performs a check for the given instance, whether it exceeds the range.

isPaused() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns whether the object is currently paused.

isPaused() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns whether the object is currently paused.

isPerClass() - Method in enum adams.flow.core.EvaluationStatistic

Returns whether the statistic is a per-class one.

isPerClassLabel() - Method in enum adams.opt.genetic.Measure

Returns whether the measure is per class label.

isPLSFilter(Filter) - Method in class adams.data.conversion.SwapPLS

Checks whether the filter is an actual PLS filter.

isPreSelection() - Method in class adams.flow.transformer.WekaChooseAttributes

Returns the regular expression to pre-select attributes for the dialog.

isReadOnly() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

Returns whether the model is readonly.

isReadOnly() - Method in class adams.gui.visualization.instances.InstancesTable

returns whether the model is read-only

isReadOnly() - Method in class adams.gui.visualization.instances.InstancesTableModel

returns whether the model is read-only

isRemoveUsed() - Method in class weka.classifiers.meta.FilteredClassifierExt

Returns whether the Remove filter is used at all.

isRequired(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Checks whether the classifier/dataset combination is required.

isRowFinderTrained() - Method in class adams.data.weka.rowfinder.AbstractTrainableRowFinder

Checks whether the row finder has been trained.

isRowFinderTrained() - Method in interface adams.data.weka.rowfinder.TrainableRowFinder

Checks whether the row finder has been trained.

isRunning() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Whether the experiment is still running.

isRunning() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns whether the algorithm is still running.

isSearchMatch(SearchParameters, int) - Method in class adams.gui.visualization.instance.InstanceTableModel

Tests whether the search matches the specified row.

isSecondBetterFitness(double) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Checks whether the fitness is better (second evaluation).

isSidePanelVisible() - Method in class adams.gui.visualization.instance.InstanceExplorer

Returns whether the side panel is visible or not.

isSingleThreaded() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns whether the execution was single-threaded (after WekaCrossValidationExecution.execute()).

isSingleton() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.AppendDatasets

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.ArffViewer

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.BatchFilterDatasets

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.BayesNetEditor

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.BoundaryVisualizer

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.CostCurve

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.DatasetCompatibility

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.Experimenter

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.Explorer

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.GraphVisualizer

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.InstanceCompare

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.InstanceExplorer

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.InstancesPlot

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.MakeCompatibleDatasets

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.MarginCurve

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.MergeDatasets

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.MultiExplorer

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.PackageManager

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.PlotAttributeVsAttribute

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.ROC

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.SqlViewer

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.TreeVisualizer

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.WekaCommandToCode

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.WekaInvestigator

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.WekaMultiExperimenter

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.WekaSimpleCLI

Whether the panel can only be displayed once.

isSingleton() - Method in class adams.gui.menu.Workbench

Whether the panel can only be displayed once.

isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Whether the execution has been stopped.

isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Whether the execution has been stopped.

isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Whether the execution has been stopped.

isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Whether the execution has been stopped.

isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Whether the execution has been stopped.

isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Whether the execution has been stopped.

isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Whether the execution has been stopped.

isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup

Whether the execution has been stopped.

isStopped() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns whether the experiment has been stopped.

isStopped() - Method in class adams.multiprocess.WekaCrossValidationExecution

Returns whether the execution has been stopped.

isStopped() - Method in class weka.classifiers.evaluation.StoppableEvaluation

Whether the execution has been stopped.

isStopped() - Method in class weka.classifiers.lazy.LWLSynchro

Whether the execution has been stopped.

isStopped() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Whether the execution has been stopped.

isStopped() - Method in class weka.classifiers.meta.FilteredClassifierExt

Whether the execution has been stopped.

isStopped() - Method in class weka.classifiers.MultiLevelSplitGenerator

Whether the execution has been stopped.

isStopped() - Method in class weka.classifiers.StoppableClassifier

Whether the execution has been stopped.

isStopped() - Method in class weka.classifiers.StoppableEvaluation

Whether the execution has been stopped.

isStopped() - Method in class weka.classifiers.StoppableRandomizableClassifier

Whether the execution has been stopped.

isStopped() - Method in class weka.classifiers.StoppableSingleClassifierEnhancer

Whether the execution has been stopped.

isString() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Returns whether the sort index is nominal/string or numeric.

isString() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Returns whether the index values are nominal/string or numeric.

isTime() - Method in class adams.ml.data.DataCellView

Checks whether the cell represents a time value.

isTimeLenient() - Method in class adams.ml.data.InstancesView

Returns whether the parsing of times is lenient or not.

isTimeMsec() - Method in class adams.ml.data.DataCellView

Checks whether the cell represents a time/msec value.

isTimeMsecLenient() - Method in class adams.ml.data.InstancesView

Returns whether the parsing of times/msec is lenient or not.

isUndoEnabled() - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

Returns whether undo is enabled.

isUndoEnabled() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Returns whether undo is enabled.

isUndoEnabled() - Method in class adams.gui.visualization.instances.InstancesTable

returns whether undo support is enabled

isUndoEnabled() - Method in class adams.gui.visualization.instances.InstancesTableModel

returns whether undo support is enabled

isUndoSupported() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Returns whether an Undo manager is currently available.

isUndoSupported() - Method in class adams.gui.visualization.instance.InstancePanel

Returns whether an Undo manager is currently available.

isUniqueIDName(String) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Whether the given attribute name is the name of the unique ID attribute.

isUsingStorage() - Method in class adams.data.conversion.MapToWekaInstance

Returns whether storage items are being used.

isUsingStorage() - Method in class adams.flow.transformer.WekaFilter

Returns whether storage items are being used.

isUsingStorage() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Returns whether storage items are being used.

isUsingStorage() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns whether storage items are being used.

isUsingY() - Method in class adams.data.instance.InstancePointComparator

Returns whether Y or X number is used for ordering.

isValid() - Method in class adams.flow.container.WekaAttributeSelectionContainer

Checks whether the setup of the container is valid.

isValid() - Method in class adams.flow.container.WekaClusterEvaluationContainer

Checks whether the setup of the container is valid.

isValid() - Method in class adams.flow.container.WekaClusteringContainer

Checks whether the setup of the container is valid.

isValid() - Method in class adams.flow.container.WekaEvaluationContainer

Checks whether the setup of the container is valid.

isValid() - Method in class adams.flow.container.WekaExperimentContainer

Checks whether the setup of the container is valid.

isValid() - Method in class adams.flow.container.WekaFilterContainer

Checks whether the setup of the container is valid.

isValid() - Method in class adams.flow.container.WekaGeneticAlgorithmContainer

Checks whether the setup of the container is valid.

isValid() - Method in class adams.flow.container.WekaGeneticAlgorithmInitializationContainer

Checks whether the setup of the container is valid.

isValid() - Method in class adams.flow.container.WekaModelContainer

Checks whether the setup of the container is valid.

isValid() - Method in class adams.flow.container.WekaNearestNeighborSearchContainer

Checks whether the setup of the container is valid.

isValid() - Method in class adams.flow.container.WekaPredictionContainer

Checks whether the setup of the container is valid.

isValid() - Method in class adams.flow.container.WekaTrainTestSetContainer

Checks whether the setup of the container is valid.

isValid(String) - Method in class adams.core.base.AttributeTypeList

Checks whether the string value is a valid presentation for this class.

isValid(Instances) - Method in enum adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure

Checks whether the data can be used with this measure.

isValid(Instances, String) - Method in enum adams.opt.genetic.Measure

Checks whether the data can be used with this measure.

isValidDataIndex(BaseComboBox) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Checks whether the combobox selection index is a valid dataset index.

isValidSetup() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Checks whether the setup is valid, i.e., no name used twice, at least one sorting definition.

isVisible() - Method in class adams.gui.visualization.instance.InstanceContainer

Returns whether the instance is visible.

isVisible(int) - Method in class adams.gui.visualization.instance.InstanceContainerManager

Returns whether the container at the specified position is visible.

isZoomOverviewPanelVisible() - Method in class adams.gui.visualization.instance.InstanceExplorer

Returns whether the zoom overview panel is visible or not.

isZoomOverviewPanelVisible() - Method in class adams.gui.visualization.instance.InstancePanel

Returns whether the zoom overview panel is visible or not.

iterationsTipText() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the tip text for this property.

J

jamaToWeka(Matrix) - Static method in class adams.data.instancesanalysis.pls.MatrixHelper

Turns a Jama matrix into a Weka one.

JdbcOutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka

Stores the results in a JDBC database.

JdbcOutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel

JFreeChart - Class in adams.gui.visualization.instances.instancestable

Allows to perform a simple plot of a column or row.

JFreeChart() - Constructor for class adams.gui.visualization.instances.instancestable.JFreeChart

jobRunnerTipText() - Method in class adams.flow.transformer.WekaExperimentExecution

Returns the tip text for this property.

jobRunnerTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the tip text for this property.

JOIN - adams.data.weka.columnfinder.MultiColumnFinder.Combination

join/merge/or.

JOIN - adams.data.weka.rowfinder.MultiRowFinder.Combination

join/merge/or.

JoinAttributes - Class in weka.filters.unsupervised.attribute

A simple filter that joins several attributes into a single STRING one, with a user defined string acting as 'glue'.

JoinAttributes() - Constructor for class weka.filters.unsupervised.attribute.JoinAttributes

JoinOnID - Class in adams.flow.transformer.wekadatasetsmerge

Joins the datasets by concatenating rows that share a unique ID.

JoinOnID() - Constructor for class adams.flow.transformer.wekadatasetsmerge.JoinOnID

JoinOnID.UniqueIDEnumeration - Class in adams.flow.transformer.wekadatasetsmerge

Enumeration class that returns the rows from the source datasets joined on the unique ID attribute.

joinOptions(String[]) - Method in class adams.core.option.WekaCommandLineHandler

Turns the option array back into a commandline.

JsonAdamsExperimentReader - Class in adams.data.io.input

Reads ADAMS Experiments in JSON format.

JsonAdamsExperimentReader() - Constructor for class adams.data.io.input.JsonAdamsExperimentReader

JsonAdamsExperimentWriter - Class in adams.data.io.output

Writes ADAMS experiments in JSON format.

JsonAdamsExperimentWriter() - Constructor for class adams.data.io.output.JsonAdamsExperimentWriter

JSONSpreadSheetReader - Class in adams.data.io.input

Reads WEKA datasets in JSON format and turns them into spreadsheets.

JSONSpreadSheetReader() - Constructor for class adams.data.io.input.JSONSpreadSheetReader

JSONSpreadSheetWriter - Class in adams.data.io.output

Writes a spreadsheet in JSON file format.

JSONSpreadSheetWriter() - Constructor for class adams.data.io.output.JSONSpreadSheetWriter

K

KAPPA - adams.flow.transformer.WekaClassifierRanker.Measure

evaluation via: Kappa statistic.

KAPPA - adams.opt.genetic.Measure

Kappa.

KAPPA_STATISTIC - adams.flow.core.EvaluationStatistic

KAPPA_STATISTIC - adams.flow.core.ExperimentStatistic

KB_INFORMATION - adams.flow.core.EvaluationStatistic

KB_INFORMATION - adams.flow.core.ExperimentStatistic

KB_MEAN_INFORMATION - adams.flow.core.EvaluationStatistic

KB_MEAN_INFORMATION - adams.flow.core.ExperimentStatistic

KB_RELATIVE_INFORMATION - adams.flow.core.EvaluationStatistic

KB_RELATIVE_INFORMATION - adams.flow.core.ExperimentStatistic

keepAttributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns the tip text for this property.

keepAttributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns the tip text for this property.

keepExistingTipText() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns the tip text for this property.

keepIndices(Instances) - Method in class weka.classifiers.meta.Corr

keepIndicesBasedOnCorrelation(Instances) - Method in class weka.classifiers.meta.Corr

keepNumComponentsTipText() - Method in class adams.data.conversion.SwapPLS

Returns the tip text for this property.

keepOnlySingleUniqueIDTipText() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the tip text for this property.

KeepRange - Class in weka.filters.unsupervised.instance

Keeps only the range of rows, in the order specified.

KeepRange() - Constructor for class weka.filters.unsupervised.instance.KeepRange

keepRelationNameTipText() - Method in class adams.flow.transformer.WekaFilter

Returns the tip text for this property.

keepRelationNameTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the tip text for this property.

keepRelationNameTipText() - Method in class adams.flow.transformer.WekaStreamFilter

Returns the tip text for this property.

keepSupervisedClassTipText() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the tip-text for the keep-supervised-class option.

KennardStone - Class in weka.filters.unsupervised.instance

Applies the Kennard-Stone algorithm to the dataset.
Each row has the pre-filter (eg PLS) applied before performing the search.

KennardStone() - Constructor for class weka.filters.unsupervised.instance.KennardStone

KernelPLS - Class in adams.data.instancesanalysis.pls

KernelPLS() - Constructor for class adams.data.instancesanalysis.pls.KernelPLS

kernelTipText() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Returns the tip text for this property

kernelTipText() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Returns the tip text for this property

kernelTipText() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Returns the tip text for this property

kernelTipText() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Returns the tip text for this property

KEY - Static variable in class adams.env.InstanceCompareDefinition

the key as constant.

KEY - Static variable in class adams.env.InstanceExplorerDefinition

the key as constant.

KEY - Static variable in class adams.env.WekaInvestigatorDefinition

the key as constant.

KEY - Static variable in class adams.env.WekaInvestigatorShortcutsDefinition

the key as constant.

KEY_ACTUAL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

KEY_ADDITIONAL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

KEY_ADDITIONAL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

KEY_ADDITIONAL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

KEY_ADDITIONAL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

KEY_ADDITIONAL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

KEY_ADDITIONAL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

KEY_ADDITIONAL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

KEY_ADDITIONALATTRIBUTES - Static variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

KEY_ADDITIONALATTRIBUTES - Static variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

KEY_ADDITIONALATTRIBUTES - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

KEY_ALGORITHM - Static variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

KEY_ANTIALIASING - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

KEY_ATTRIBUTES - Static variable in class adams.gui.visualization.instances.instancestable.ArrayStatistic

KEY_ATTRIBUTES - Static variable in class adams.gui.visualization.instances.instancestable.Histogram

KEY_BATCHFILTER - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

KEY_BINNING - Static variable in class adams.gui.visualization.instances.instancestable.Binning

KEY_CLASS_INDEX - Static variable in class weka.gui.explorer.AttributeSelectionHandler

KEY_CLASS_INDEX - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_CLASS_INDEX - Static variable in class weka.gui.explorer.ClustererHandler

KEY_CLASS_INDEX - Static variable in class weka.gui.explorer.ExperimentHandler

KEY_CLASSATTRIBUTE - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper

KEY_CLASSDISTRIBUTION - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

KEY_CLASSIFIER - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

KEY_CLASSIFIER - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

KEY_CLUSTERER - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

KEY_CLUSTERER - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

KEY_COLOR - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

KEY_COLORPROVIDER - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

KEY_COLUMNS - Static variable in class adams.gui.visualization.instances.instancestable.Binning

KEY_COLUMNS - Static variable in class adams.gui.visualization.instances.instancestable.JFreeChart

KEY_COLUMNS - Static variable in class adams.gui.visualization.instances.instancestable.SimplePlot

KEY_COST_SENSITIVE_EVALUATION - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_CV_FOLDS - Static variable in class weka.gui.explorer.AttributeSelectionHandler

KEY_CV_FOLDS - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_DATA - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

KEY_DATASET - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

KEY_DATATABLE_HEIGHT - Static variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

KEY_DATATABLE_SELECTEDROWS - Static variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

KEY_DISCARDPREDICTIONS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

KEY_DISCARDPREDICTIONS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

KEY_DISCARDPREDICTIONS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

KEY_DISCARDPREDICTIONS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

KEY_DISCARDPREDICTIONS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

KEY_ERROR_PLOT_POINT_SIZE - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_EVALUATION - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

KEY_EVALUATION - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

KEY_EVALUATION - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

KEY_EVALUATION - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

KEY_EVALUATION - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

KEY_EVALUATION - Static variable in class weka.gui.explorer.ExperimentHandler

KEY_EVALUATION_METRICS - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_EVALUATION_PREFIX - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

KEY_EVALUATION_PREFIX - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

KEY_EVALUATION_PREFIX - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

KEY_EVALUATION_PREFIX - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

KEY_EVALUATION_PREFIX - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

KEY_EVALUATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

KEY_FILE - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

KEY_FILE - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

KEY_FILE - Static variable in class adams.gui.wizard.WekaSelectDatasetPage

key in the properties that contains the file name.

KEY_FILES - Static variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

key in the properties that contains the file name.

KEY_FILTER - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

KEY_FINALMODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

KEY_FINALMODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

KEY_FIRST_ATTRANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

KEY_FIRST_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

KEY_FOLD - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane

KEY_FOLD - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

KEY_FOLDS - Static variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

KEY_FOLDS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

KEY_FOLDS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

KEY_FOLDS - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

KEY_FOLDS - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

KEY_FOLDS - Static variable in class weka.gui.explorer.ExperimentHandler

KEY_GENERATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

KEY_GENERATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

KEY_GENERATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

KEY_GENERATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

KEY_GENERATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

KEY_HISTOGRAM - Static variable in class adams.gui.visualization.instances.instancestable.Histogram

KEY_HISTORY - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

KEY_HISTORY - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

KEY_HISTORY - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

KEY_HISTORY - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

KEY_HISTORY - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

KEY_ICA - Static variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

KEY_ID - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

KEY_IDS - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

KEY_IGNORED_ATTRIBUTES - Static variable in class weka.gui.explorer.ClustererHandler

KEY_JOBRUNNER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

KEY_JOBRUNNER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

KEY_JOBRUNNER - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

KEY_JOBRUNNER - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

KEY_KEEPNAME - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

KEY_LENIENT - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

KEY_LOG - Static variable in class adams.gui.tools.wekainvestigator.tab.LogTab

KEY_MARKERS - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

KEY_MAXATTRIBUTENAMES - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

KEY_MAXATTRIBUTES - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

KEY_MODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

KEY_MODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

KEY_MODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

KEY_MODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

KEY_OUTPUT_CONFUSION_MATRIX - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_OUTPUT_ENTROPY - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_OUTPUT_MODEL - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_OUTPUT_PER_CLASS - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_OUTPUT_PREDICTIONS - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_OUTPUT_SOURCE_CODE - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_OUTPUTGENERATORS - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the key for the output generators.

KEY_OUTPUTGENERATORS - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the key for the output generators.

KEY_OUTPUTGENERATORS - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the key for the output generators.

KEY_OUTPUTGENERATORS - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the key for the output generators.

KEY_OUTPUTGENERATORS - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the key for the output generators.

KEY_PERCENTAGE - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

KEY_PERCENTAGE - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

KEY_PERCENTAGE - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

KEY_PERCENTAGE_SPLIT - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_PERCENTAGE_SPLIT - Static variable in class weka.gui.explorer.ClustererHandler

KEY_PERFOLDOUTPUT - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

KEY_PLOT - Static variable in class adams.gui.visualization.instances.instancestable.JFreeChart

KEY_PLOT - Static variable in class adams.gui.visualization.instances.instancestable.SimplePlot

KEY_PREDICTED - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

KEY_PRESERVE_ORDER - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_PRESERVEORDER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

KEY_PRESERVEORDER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

KEY_PRESERVEORDER - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

KEY_PRESERVEORDER - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

KEY_QUERY - Static variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

the key for the query.

KEY_RANDOM_SEED - Static variable in class weka.gui.explorer.AttributeSelectionHandler

KEY_RANDOM_SEED - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_RANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

KEY_RANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

KEY_RANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

KEY_RANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

KEY_READER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

KEY_READER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

KEY_RELATIONNAME - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper

KEY_REPLACE - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

KEY_RUN - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

KEY_RUNS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

KEY_RUNS - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

KEY_RUNS - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

KEY_RUNS - Static variable in class weka.gui.explorer.ExperimentHandler

KEY_SCHEME - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

KEY_SCHEME_OPTIONS - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

KEY_SCHEME_VERSION_ID - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

KEY_SEARCH - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

KEY_SECOND_ATTRANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

KEY_SECOND_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

KEY_SERIALIZE - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

KEY_SERIALIZE_FILE - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

KEY_SKIPNOMINAL - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

KEY_STATISTIC - Static variable in class adams.gui.visualization.instances.instancestable.ArrayStatistic

KEY_STORE_CLUSTERS - Static variable in class weka.gui.explorer.ClustererHandler

KEY_STORE_PREDICTIONS - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_TABS - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper

KEY_TEST - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

KEY_TEST - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

KEY_TEST - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

KEY_TEST - Static variable in class weka.gui.explorer.AttributeSelectionHandler

KEY_TEST - Static variable in class weka.gui.explorer.ClassifierHandler

KEY_TEST - Static variable in class weka.gui.explorer.ClustererHandler

KEY_TESTSPLIT - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

KEY_TRAIN - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

KEY_TRAIN - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

KEY_TRAIN - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

KEY_TRAINSPLIT - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

KEY_UNDOENABLED - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper

KEY_USEVIEWS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

KEY_USEVIEWS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

KEY_USEVIEWS - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

KEY_VALIDATE - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

KEY_VARIANCE - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

KEY_WEIGHT - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

keysTipText() - Method in class adams.flow.source.WekaDatabaseReader

Returns the tip text for this property.

KEYWORD_ATTRIBUTE - Static variable in class weka.core.converters.SimpleArffLoader

KEYWORD_DATA - Static variable in class weka.core.converters.SimpleArffLoader

KEYWORD_RELATION - Static variable in class weka.core.converters.SimpleArffLoader

KMEANS_PLUS_PLUS - Static variable in class weka.clusterers.SAXKMeans

kMeansPlusPlusInit(Instances) - Method in class weka.clusterers.SAXKMeans

Initialize using the k-means++ method

kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.FilteredSearch

Returns k nearest instances in the current neighbourhood to the supplied instance.

kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.NewNNSearch

Returns k nearest instances in the current neighbourhood to the supplied instance.

kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.PCANNSearch

Returns k nearest instances in the current neighbourhood to the supplied instance.

kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.PLSNNSearch

Returns k nearest instances in the current neighbourhood to the supplied instance.

kNearestNeighboursIndices(Instance, int) - Method in class weka.core.neighboursearch.FilteredSearchWithIndices

Returns the indices of the k nearest instances in the current neighbourhood to the supplied instance.

kNearestNeighboursIndices(Instance, int) - Method in interface weka.core.neighboursearch.NearestNeighbourSearchWithIndices

Returns the indices of the k nearest instances in the current neighbourhood to the supplied instance.

kNearestNeighboursIndices(Instance, int) - Method in class weka.core.neighboursearch.NewNNSearchWithIndices

Returns the indices of the k nearest instances in the current neighbourhood to the supplied instance.

kNearestNeighboursIndices(Instance, int) - Method in class weka.core.neighboursearch.PCANNSearchWithIndices

Returns the indices of the k nearest instances in the current neighbourhood to the supplied instance.

kNearestNeighboursIndices(Instance, int) - Method in class weka.core.neighboursearch.PLSNNSearchWithIndices

Returns the indices of the k nearest instances in the current neighbourhood to the supplied instance.

KNNTipText() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns the tip text for this property.

L

LABEL - Static variable in class weka.classifiers.meta.ThresholdedBinaryClassification

LABEL - Static variable in class weka.classifiers.meta.Veto

LABEL_COUNT - adams.flow.transformer.WekaInstancesInfo.InfoType

the number of instances with the specified class label (selected attribute, only nominal).

LABEL_COUNTS - adams.flow.transformer.WekaInstancesInfo.InfoType

the counts per label (selected attribute, only nominal).

LABEL_DISTRIBUTION - adams.flow.transformer.WekaInstancesInfo.InfoType

the distribution (percentages, 0-1) per label (selected attribute, only nominal).

LABEL_FALSE - Static variable in class adams.data.instances.AbstractInstanceGenerator

the "false" label for boolean data types.

LABEL_MATCH - Static variable in class weka.filters.unsupervised.instance.DatasetLabeler

the default label for a "match".

LABEL_NONMATCH - Static variable in class weka.filters.unsupervised.instance.DatasetLabeler

the default label for a "non-match".

LABEL_REGEXP - Static variable in class weka.filters.unsupervised.instance.RemoveWithLabels

LABEL_TRUE - Static variable in class adams.data.instances.AbstractInstanceGenerator

the "true" label for boolean data types.

labelIndexTipText() - Method in class adams.flow.transformer.WekaInstancesInfo

Returns the tip text for this property.

labelIndexTipText() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the tip text for this property.

labelMatchTipText() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Returns the tip text for this property.

labelNonMatchTipText() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Returns the tip text for this property.

labelRegExpTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns the tip text for this property.

LABELS - adams.flow.transformer.WekaInstancesInfo.InfoType

the labels (selected attribute, only nominal).

labelStringTipText() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns the tip text for this property.

labelTipText() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns the tip text for this property.

labelTipText() - Method in class weka.classifiers.meta.Veto

Returns the tip text for this property.

LAMBDAMART_MAXIMISE_MAP - weka.classifiers.trees.XGBoost.Objective

LAMBDAMART_MAXIMISE_NDCG - weka.classifiers.trees.XGBoost.Objective

LAMBDAMART_PAIRWISE_RANKING - weka.classifiers.trees.XGBoost.Objective

lambdaTipText() - Method in class adams.data.instancesanalysis.pls.DIPLS

Returns the tip text for this property

lambdaTipText() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns the tip text for this property

lambdaTipText() - Method in class adams.data.instancesanalysis.pls.VCPLS

Returns the tip text for this property

lambdaTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the lambda option.

LastAttribute - Class in adams.data.weka.classattribute

Simply chooses the last attribute as class attribute.

LastAttribute() - Constructor for class adams.data.weka.classattribute.LastAttribute

lastInstance() - Method in class weka.core.InstancesView

Returns the last instance in the set.

lastUpdated() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Returns the timestamp the data was last updated.

lastUpdated() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer

Returns the timestamp the data was last updated.

LatestRecords - Class in weka.filters.unsupervised.instance

Retains the latest database records.

LatestRecords() - Constructor for class weka.filters.unsupervised.instance.LatestRecords

launch() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.AppendDatasets

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.ArffViewer

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.BatchFilterDatasets

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.BayesNetEditor

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.BoundaryVisualizer

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.CostCurve

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.DatasetCompatibility

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.Experimenter

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.Explorer

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.GraphVisualizer

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.InstanceCompare

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.InstanceExplorer

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.InstancesPlot

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.MakeCompatibleDatasets

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.MarginCurve

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.MergeDatasets

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.MultiExplorer

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.PackageManager

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.PlotAttributeVsAttribute

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.ROC

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.SqlViewer

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.TreeVisualizer

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.WekaCommandToCode

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.WekaInvestigator

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.WekaMultiExperimenter

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.WekaSimpleCLI

Launches the functionality of the menu item.

launch() - Method in class adams.gui.menu.Workbench

Launches the functionality of the menu item.

launchAssignToClusters(Instances, int[]) - Method in class weka.clusterers.SAXKMeans

Launch the tasks that assign instances to clusters

launchMoveCentroids(Instances[]) - Method in class weka.clusterers.SAXKMeans

Launch the move centroids tasks

LeanMultiScheme - Class in weka.classifiers.meta

Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data.

LeanMultiScheme() - Constructor for class weka.classifiers.meta.LeanMultiScheme

LeastMedianSq - Class in weka.classifiers.meta

Finds the base classifier with the best least median squared error.

LeastMedianSq() - Constructor for class weka.classifiers.meta.LeastMedianSq

LeaveOneOutByValueGenerator - Class in weka.classifiers

Generates train/test split pairs using the unique values from the specified attribute.

LeaveOneOutByValueGenerator() - Constructor for class weka.classifiers.LeaveOneOutByValueGenerator

Initializes the generator.

LeaveOneOutByValueGenerator(Instances, long, boolean, WekaAttributeIndex) - Constructor for class weka.classifiers.LeaveOneOutByValueGenerator

Initializes the generator.

LEFT - Static variable in class weka.classifiers.trees.m5.Rule2

leftNode() - Method in class weka.classifiers.trees.m5.RuleNode2

Get the left child of this node

LegacyClassifierErrors - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Generates classifier errors plot (legacy Weka output).

LegacyClassifierErrors() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyClassifierErrors

LegacyCostBenefitAnalysis - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Generates cost benefit analysis (legacy Weka output).

LegacyCostBenefitAnalysis() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis

LegacyCostCurve - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Generates cost curve (legacy Weka output).

LegacyCostCurve() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve

LegacyGraphVisualizer - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Displays the graph that the model generated (legacy Weka output).

LegacyGraphVisualizer() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyGraphVisualizer

LegacyMarginCurve - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Generates margin curve (legacy Weka output).

LegacyMarginCurve() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyMarginCurve

LegacyThresholdCurve - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Generates margin curve (legacy Weka output).

LegacyThresholdCurve() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

LegacyTreeVisualizer - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Displays the tree that the model generated (legacy Weka output).

LegacyTreeVisualizer - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output

Displays the tree that the model generated (legacy Weka output).

LegacyTreeVisualizer() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyTreeVisualizer

LegacyTreeVisualizer() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.LegacyTreeVisualizer

lenientTipText() - Method in class adams.data.indexedsplits.InstancesIndexedSplitsRunsCompatibility

Returns the tip text for this property.

lenientTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the tip text for this property.

LibSVMSpreadSheetReader - Class in adams.data.io.input

Reads WEKA datasets in LibSVM format and turns them into spreadsheets.

LibSVMSpreadSheetReader() - Constructor for class adams.data.io.input.LibSVMSpreadSheetReader

LibSVMSpreadSheetWriter - Class in adams.data.io.output

Writes a spreadsheet in LibSVM file format.

LibSVMSpreadSheetWriter() - Constructor for class adams.data.io.output.LibSVMSpreadSheetWriter

LIFT - adams.flow.sink.WekaThresholdCurve.AttributeName

limitTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

LINEAR_REGRESSION - weka.classifiers.trees.XGBoost.Objective

LinearRegressionAttributeEval - Class in weka.attributeSelection

Uses the coefficients of LinearRegressionJ to determine the importance of the attributes (attribute selection turned off, no elimination of collinear attributes).

LinearRegressionAttributeEval() - Constructor for class weka.attributeSelection.LinearRegressionAttributeEval

LinearRegressionJ - Class in weka.classifiers.functions

Class for using linear regression for prediction.

LinearRegressionJ() - Constructor for class weka.classifiers.functions.LinearRegressionJ

listCapabilities(Capabilities) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator

returns a comma-separated list of all the capabilities.

listOptions() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Returns an enumeration of all the available options..

listOptions() - Method in class weka.attributeSelection.LinearRegressionAttributeEval

listOptions() - Method in class weka.classifiers.functions.ClassificationViaPLS

Gets an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.FakeClassifier

Gets an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.GeneticAlgorithm

Gets an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.GPD

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.LinearRegressionJ

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.MathExpressionClassifier

Gets an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.PLSClassifierWeighted

Gets an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.PLSWeighted

Gets an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.lazy.LWLSynchro

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.AbstainAttributePercentile

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.AbstainAverage

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.AbstainingCascade

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.AbstainMinimumProbability

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.AbstainVote

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.ClassifierCascade

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.Consensus

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.ConsensusOrVote

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.Corr

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.Fallback

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.FilteredClassifierExt

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.HighLowSplit

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.InputSmearing

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.LeastMedianSq

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.MinMaxLimits

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.PartitionedStacking

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.SocketFacade

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.SubsetEnsemble

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.SuppressModelOutput

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.Veto

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.meta.VotedImbalance

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.trees.m5.M5Base2

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.trees.M5P2

Returns an enumeration describing the available options

listOptions() - Method in class weka.classifiers.trees.RandomModelTrees

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.trees.RandomRegressionForest

Returns an enumeration describing the available options.

listOptions() - Method in class weka.clusterers.SAXKMeans

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.AbstractSimpleOptionHandler

Returns an enumeration of all the available options..

listOptions() - Method in class weka.core.converters.SimpleArffLoader

Returns an enumeration of all the available options..

listOptions() - Method in class weka.core.converters.SimpleArffSaver

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.converters.SpreadSheetLoader

Lists the available options

listOptions() - Method in class weka.core.converters.SpreadSheetSaver

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.FilteredSearch

listOptions() - Method in class weka.core.neighboursearch.NewNNSearch

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.neighboursearch.PCANNSearch

listOptions() - Method in class weka.core.neighboursearch.PLSNNSearch

listOptions() - Method in class weka.core.SAXDistance

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.tokenizers.cleaners.AbstractTokenCleaner

Returns an enumeration of all the available options..

listOptions() - Method in class weka.core.tokenizers.cleaners.MultiCleaner

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.tokenizers.MultiTokenizer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns an enumeration describing the available options.

listOptions() - Method in class weka.core.WeightedEuclideanDistanceRidge

Returns an enumeration describing the available options.

listOptions() - Method in class weka.experiment.ResultMatrixMediaWiki

Returns an enumeration of all the available options..

listOptions() - Method in class weka.filters.FilteredFilter

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.FlowFilter

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.SerializedFilter

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.MultiPLS

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.PLS

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.YGradientEPO

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.YGradientGLSW

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.AnyToString

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.DownSample

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.FFT

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.LogTransform

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.PAA

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.SAX

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.SetMissingValue

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.SpellChecker

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.attribute.StringToDate

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.AlignDataset

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.KeepRange

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.KennardStone

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.LatestRecords

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

Returns an enumeration of all the available options..

listOptions() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

Gets an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.Scale

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.Sort

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.SortOnAttribute

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns an enumeration describing the available options.

listOrArray(Object) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

If the object should be a list of strings instead of an array of strings, then it gets converted accordingly.

ListPackages - Class in adams.flow.source.wekapackagemanageraction

Lists the packages.

ListPackages() - Constructor for class adams.flow.source.wekapackagemanageraction.ListPackages

ListPackages.ListType - Enum in adams.flow.source.wekapackagemanageraction

The type of list to generate.

ListPackages.OutputFormat - Enum in adams.flow.source.wekapackagemanageraction

How to output the packages.

listTypeTipText() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

Returns the tip text for this property.

load(File) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO

Loads an experiment.

load(File) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultAdamsExperimentIO

Loads an experiment.

load(File) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultWekaExperimentIO

Loads an experiment.

load(File) - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO

Loads an experiment.

load(File) - Method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter

Loads the specified file in a new panel.

load(File) - Method in class weka.gui.explorer.MultiExplorer

Loads the specified file in a new panel.

load(File[]) - Method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter

Loads the specified files in new panels.

load(File[]) - Method in class weka.gui.explorer.MultiExplorer

Loads the specified files in new panels.

loadClassifier() - Method in class weka.gui.explorer.ExplorerExt

Loads a classifier in the classify tab.

loadClusterer() - Method in class weka.gui.explorer.ExplorerExt

Loads a clusterer in the cluster tab.

loadData(Instances, List<InstanceContainer>) - Method in class adams.gui.visualization.instance.InstanceExplorer

Loads the given data into the container manager.

loadDataFromDatabase() - Method in class adams.gui.visualization.instance.InstanceExplorer

pops up SQL Viewer for SQL statement.

loadDataFromDisk() - Method in class adams.gui.visualization.instance.InstanceExplorer

pops up file dialog for loading dataset form disk.

loadDataFromDisk(File) - Method in class adams.gui.visualization.instance.InstanceExplorer

pops up file dialog for loading dataset form disk.

loadDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Loads the dataset, if possible.

loadDataset(int) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Loads the dataset.

LoadDatasetDialog - Class in adams.gui.visualization.instance

A dialog for loading datasets from disk.

LoadDatasetDialog(Dialog) - Constructor for class adams.gui.visualization.instance.LoadDatasetDialog

Creates a modal dialog.

LoadDatasetDialog(Dialog, String) - Constructor for class adams.gui.visualization.instance.LoadDatasetDialog

Creates a modal dialog.

LoadDatasetDialog(Frame) - Constructor for class adams.gui.visualization.instance.LoadDatasetDialog

Creates a modal dialog.

LoadDatasetDialog(Frame, String) - Constructor for class adams.gui.visualization.instance.LoadDatasetDialog

Creates a modal dialog.

loadFile(boolean) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Loads the file and displays the IDs.

loadFromDatabase() - Method in class weka.gui.explorer.ExplorerExt

Lets the user load data from a database.

loadFromURL() - Method in class weka.gui.explorer.ExplorerExt

Lets the user load data from a URL.

loadingsCalculationsTipText() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Returns the tip text for this property

loadModel() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Attempts to load the model and (if available) the header.

loadModel() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Attempts to load the model and (if available) the header.

loadPackageDirectory(File) - Method in class adams.core.management.WekaPackagesClassPathAugmenter

Processes a package directory.

loadParameters() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Prompts the user to select a yaml file to load the parameters for this tab from.

loadProperties() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

Loads properties from a file, prompts the user to select props file.

loadReferenceDataset() - Method in class weka.filters.unsupervised.instance.AlignDataset

Loads the reference dataset from disk or returns the manually supplied one.

loadResults() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner

Examines the supplied experiment to determine the results destination and attempts to load the results.

loadResults() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractWekaExperimentRunner

Examines the supplied experiment to determine the results destination and attempts to load the results.

loadTestSet() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Loads the test set from disk or returns the manually supplied one.

localTipText() - Method in class weka.classifiers.meta.SocketFacade

Returns the tip text for this property.

locateMethod(String) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Locates the method with the specified name (method is expected to take no parameters).

locateRows(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the rows for the classifier/dataset combination.

locationsTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the tip text for this property.

locationsTipText() - Method in class adams.flow.transformer.WekaInstancesStatistic

Returns the tip text for this property.

loClassifierTipText() - Method in class weka.classifiers.meta.HighLowSplit

log(String) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Displays the message.

log(String, Throwable) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Displays the error.

logAndShowMessage(String) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Logs the error message and shows it in the status bar.

LogClassRegressor - Class in weka.classifiers.meta

Takes log of the class attribute in the data.

LogClassRegressor() - Constructor for class weka.classifiers.meta.LogClassRegressor

logDensity(Instance, double) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Returns natural logarithm of density estimate for given value based on given instance.

logError(String, String) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Logs the error message and also displays an error dialog.

logError(String, String) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

Logs the error message and also displays an error dialog.

logError(String, Throwable) - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

Logs the exception.

logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Logs the exception and also displays an error dialog.

logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource

Logs the exception and also displays an error dialog.

logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Logs the exception and also displays an error dialog.

logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Logs the exception and also displays an error dialog.

logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Logs the exception and also displays an error dialog.

logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Logs the exception and also displays an error dialog.

logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Logs the exception and also displays an error dialog.

logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Logs the exception and also displays an error dialog.

logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Logs the exception and also displays an error dialog.

logError(String, Throwable, String) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Logs the error message and also displays an error dialog.

logError(Throwable, String) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Logs the exception and also displays an error dialog.

LOGISTIC_REGRESSION - weka.classifiers.trees.XGBoost.Objective

LOGISTIC_REGRESSION_FOR_BINARY_CLASSIFICATION - weka.classifiers.trees.XGBoost.Objective

LOGIT_RAW_REGRESSION_FOR_BINARY_CLASSIFICATION - weka.classifiers.trees.XGBoost.Objective

logMessage(String) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Logs the message.

logMessage(String) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

Logs the message.

logMessage(Throwable) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Logs the exception with no dialog.

LogPanel - Class in adams.gui.tools.wekamultiexperimenter

The log panel.

LogPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.LogPanel

LogTab - Class in adams.gui.tools.wekainvestigator.tab

Just displays the log messages.

LogTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.LogTab

LogTargetRegressor - Class in weka.classifiers.meta

Takes logs of all numeric attributes in the data.

LogTargetRegressor() - Constructor for class weka.classifiers.meta.LogTargetRegressor

LogTransform - Class in weka.filters.unsupervised.attribute

Transforms all numeric attributes in the specified range using a log-transform.
The class attribute is omitted.
If a value less or equal to zero is encountered, a missing value is output.

LogTransform() - Constructor for class weka.filters.unsupervised.attribute.LogTransform

loHipointTipText() - Method in class weka.classifiers.meta.HighLowSplit

loHipointTipText() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

LOSSGUIDE - weka.classifiers.trees.XGBoost.GrowPolicy

LowerStatistic - Enum in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated

Enumeration of lower bound statistics to compute.

lowerTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Returns the tip text for this property.

lowerTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Returns the tip text for this property.

lowerTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Returns the tip text for this property.

lowerTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the tip text for this property.

LWLContainer() - Constructor for class weka.classifiers.lazy.LWLDatasetBuilder.LWLContainer

LWLDatasetBuilder - Class in weka.classifiers.lazy

Class for building LWL-style weighted datasets.

LWLDatasetBuilder() - Constructor for class weka.classifiers.lazy.LWLDatasetBuilder

LWLDatasetBuilder.LWLContainer - Class in weka.classifiers.lazy

the container with the weighted dataset, distances, indices.

LWLIntervalEstimator - Class in weka.classifiers.lazy

Locally weighted learning.

LWLIntervalEstimator() - Constructor for class weka.classifiers.lazy.LWLIntervalEstimator

LWLSynchro - Class in weka.classifiers.lazy

Locally weighted learning.

LWLSynchro() - Constructor for class weka.classifiers.lazy.LWLSynchro

Initializes the classifier.

LWLSynchroPrefilter - Class in weka.classifiers.lazy

Locally weighted learning.

LWLSynchroPrefilter() - Constructor for class weka.classifiers.lazy.LWLSynchroPrefilter

Initializes the classifier.

LWLSynchroSplit - Class in weka.classifiers.lazy

Locally weighted learning.

LWLSynchroSplit() - Constructor for class weka.classifiers.lazy.LWLSynchroSplit

Initializes the classifier.

M

m_Aborted - Variable in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

whether the user cancelled the experiment.

m_Absolute - Variable in class weka.filters.unsupervised.attribute.CorrelationMatrix

whether to return the absolute correlations.

m_AcceptListener - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the listener waiting for the user to accept the input.

m_AccumulatdError - Variable in class adams.flow.transformer.WekaAccumulatedError

the accumulated error so far.

m_Action - Variable in class adams.flow.source.WekaPackageManagerAction

the action to execute.

m_Action - Variable in class adams.flow.standalone.WekaPackageManagerAction

the action to execute.

m_Action - Variable in class adams.flow.transformer.WekaPackageManagerAction

the action to execute.

m_ActionFileClassAttribute - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for selecting the class attribute heuristic.

m_ActionFileClear - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for clearing all datasets.

m_ActionFileClose - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for closing the investigator.

m_ActionFileOpen - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for loading a dataset.

m_ActionFileRelationName - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for selecting the relation name heuristic.

m_ActionFileStopJob - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for stopping a job.

m_Actions - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

the available actions.

m_Actions - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the available actions.

m_ActionTabCloseAllTabs - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for closing all tabs.

m_ActionTabCloseTab - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for closing a tab.

m_ActionTabCopyTab - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for copying a tab.

m_ActionTabLoadParameters - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for loading parameters for a tab.

m_ActionTabRenameTab - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for renaming a tab.

m_ActionTabSaveParameters - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for saving parmeters of a tab.

m_ActionTabUndoCloseTab - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the action for undoing closed a tab.

m_Actual - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions

the column with the actual values.

m_Actual - Variable in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure

the collected actual.

m_Actual - Variable in class weka.classifiers.functions.FromPredictions

the column with the actual values.

m_ActualAlgorithm - Variable in class adams.flow.transformer.WekaGeneticAlgorithm

the actual algorithm in use.

m_ActualAssociator - Variable in class adams.flow.transformer.WekaTrainAssociator

the actual weka associator.

m_ActualBase - Variable in class weka.classifiers.meta.Fallback

the actual base classifier.

m_ActualCapabilities - Variable in class adams.flow.condition.bool.AbstractAttributeCapabilities

the capabilities object to use.

m_ActualClass - Variable in class adams.core.discovery.genetic.GenericDoubleResolution

the actual class.

m_ActualClass - Variable in class adams.core.discovery.genetic.GenericFloatResolution

the actual class.

m_ActualClass - Variable in class adams.core.discovery.genetic.GenericInteger

the actual class.

m_ActualClass - Variable in class adams.core.discovery.genetic.GenericString

the actual class.

m_ActualClusterer - Variable in class adams.flow.transformer.WekaTrainClusterer

the weka clusterer.

m_ActualFallback - Variable in class weka.classifiers.meta.Fallback

the actual fallback classifier.

m_ActualFilter - Variable in class adams.data.spreadsheet.filter.WekaFilter

the actual filter in use.

m_ActualFilter - Variable in class adams.data.weka.rowfinder.FilteredIQR

the actual IQR filter.

m_ActualFilter - Variable in class adams.flow.transformer.WekaFilter

the actual filter used.

m_ActualFilter - Variable in class weka.classifiers.functions.PLSClassifierWeighted

the actual filter to use

m_ActualFilter - Variable in class weka.filters.SerializedFilter

the actual filter.

m_ActualFilter - Variable in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

the actual filter used internally for filtering the data.

m_ActualFolds - Variable in class adams.multiprocess.WekaCrossValidationExecution

the actual folds used.

m_ActualGenerator - Variable in class adams.flow.transformer.WekaCrossValidationSplit

the actual fold generator.

m_ActualGenerator - Variable in class adams.flow.transformer.WekaRandomSplit

the currently active generator.

m_ActualGenerator - Variable in class adams.flow.transformer.WekaSplitGenerator

the currently active generator.

m_ActualIndex - Variable in class weka.classifiers.functions.FromPredictions

the actual column index.

m_ActualJobRunner - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

JobRunner for the classifier/dataset combinations.

m_ActualJobRunner - Variable in class adams.multiprocess.WekaCrossValidationExecution

the runner in use.

m_ActualLabel - Variable in class weka.classifiers.meta.ThresholdedBinaryClassification

the index of the label to check.

m_ActualLabel - Variable in class weka.classifiers.meta.Veto

the index of the label to check.

m_ActualMax - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

the maximum to use for the actual values (pos inf = no restriction).

m_ActualMin - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

the minimum to use for the actual values (neg inf = no restriction).

m_ActualNumBalanced - Variable in class weka.classifiers.meta.VotedImbalance

the actual number of balanced datasets to generate.

m_ActualNumFolds - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator

the actual number of folds.

m_ActualNumFolds - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

the actual number of folds.

m_ActualNumFolds - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

the actual number of folds.

m_ActualNumThreads - Variable in class adams.multiprocess.WekaCrossValidationExecution

the actual number of threads to use.

m_ActualReferenceDataset - Variable in class weka.filters.unsupervised.instance.AlignDataset

the actual reference dataset in use.

m_ActualSearch - Variable in class adams.flow.transformer.WekaNearestNeighborSearch

the actual neighboorhood search in use.

m_ActualSearch - Variable in class weka.classifiers.lazy.LWLDatasetBuilder

The actual nearest neighbour search algorithm to use.

m_ActualSupport - Variable in class weka.classifiers.meta.ConsensusOrVote

the actual number of classifiers that need to support the label.

m_ActualSupport - Variable in class weka.classifiers.meta.Veto

the actual number of classifiers that need to support the label.

m_ActualTitle - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

the actual title.

m_ActualTrain - Variable in class weka.classifiers.lazy.LWLDatasetBuilder

The actual training instances used for classification.

m_AddAttributeInformation - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

whether to added attribute information to the meta-data as well.

m_AddClassification - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

whether to add the numeric classification to the output.

m_AddClassificationLabel - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

whether to add the classification label to the output (nominal classes only).

m_AddDatabaseID - Variable in class adams.data.instances.AbstractInstanceGenerator

whether to add the database ID.

m_AddDatasetInformation - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

whether to added basic dataset information to the meta-data as well.

m_AddDistribution - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

whether to add the distribution to the output (nominal classes only).

m_AddFilter - Variable in class weka.filters.unsupervised.instance.DatasetLabeler

the filter for adding the label attribute.

m_addId - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter

m_AddID - Variable in class weka.classifiers.lazy.LWLDatasetBuilder

for adding the ID to trace the instances.

m_AddIndex - Variable in class adams.flow.transformer.WekaInstancesMerge

whether to add the index to the prefix.

m_Additional - Variable in class weka.classifiers.functions.FromPredictions

the additional columns in the spreadsheet to add to the plot containers.

m_AdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

additional attributes.

m_AdditionalHandlers - Static variable in class weka.gui.explorer.WorkspaceHelper

the additional associations between Explorer.ExplorerPanel and AbstractExplorerPanelHandler.

m_AdditionalIndices - Variable in class weka.classifiers.functions.FromPredictions

the additional column indices.

m_AddLabelIndex - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer

whether to prefix the labels with a 1-based index (only nominal classes).

m_AddLabelIndex - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

whether to prefix the labels with a 1-based index (only nominal classes).

m_AddOne - Variable in class weka.filters.unsupervised.attribute.LogTransform

If true output nominal, false output numeric .

m_AdjustToVisibleData - Variable in class adams.gui.visualization.instance.InstancePanel

whether to adjust to visible data or not.

m_Aggregated - Variable in class weka.classifiers.AggregateEvaluations

the aggregated evaluation.

m_Algorithm - Variable in class adams.data.instancesanalysis.PLS

the algorithm to use.

m_Algorithm - Variable in class adams.flow.transformer.WekaGeneticAlgorithm

whether to check the header.

m_Algorithm - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

the binning algorithm.

m_Algorithm - Variable in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

the binning algorithm.

m_Algorithm - Variable in class weka.classifiers.functions.GeneticAlgorithm

the genetic algorithm.

m_Algorithm - Variable in class weka.classifiers.functions.PLSWeighted

the PLS algorithm

m_Algorithm - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

the binning algorithm.

m_Algorithm - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

the binning algorithm.

m_Algorithm - Variable in class weka.filters.supervised.attribute.MultiPLS

the PLS algorithm.

m_Algorithm - Variable in class weka.filters.supervised.attribute.PLS

the PLS algorithm.

m_Algorithm - Variable in class weka.filters.supervised.attribute.YGradientEPO

the EPO algorithm.

m_Algorithm - Variable in class weka.filters.supervised.attribute.YGradientGLSW

the GLSW algorithm.

m_Algorithm - Variable in class weka.filters.unsupervised.attribute.FastWavelet

the type of algorithm.

m_Algorithms - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

the algorithms to evaluate.

m_Alin - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

The parameters of the linear transforamtion realized by the filter on the class attribute

m_Alin - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

The parameters of the linear transformation realized by the filter on the class attribute

m_Alin - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

The parameters of the linear transforamtion realized by the filter on the class attribute

m_Alin - Variable in class weka.classifiers.functions.GPD

The parameters of the linear transforamtion realized by the filter on the class attribute

m_allEqualWeights - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

Do all instances have the same weight

m_Alpha - Variable in class weka.classifiers.trees.XGBoost

L1 regularisation term on weights.

m_Alpha - Variable in class weka.filters.supervised.attribute.YGradientEPO

Alpha parameter.

m_Alpha - Variable in class weka.filters.supervised.attribute.YGradientGLSW

Alpha parameter.

m_AlreadRegistered - Static variable in class adams.gui.goe.WekaEditorsRegistration

m_AlwaysShowMarkers - Variable in class adams.gui.visualization.instance.InstanceLinePaintlet

whether to show markers all the time.

m_AlwaysUseContainer - Variable in class adams.flow.transformer.AbstractWekaClassifierEvaluator

whether to always use a container.

m_Amount - Variable in class weka.filters.unsupervised.instance.LatestRecords

the amount to keep (less than 1: percentage, otherwise absolute number).

m_AntiAliasingEnabled - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

whether anti-aliasing is enabled.

m_AntiAliasingEnabled - Variable in class adams.gui.visualization.instance.InstanceLinePaintlet

whether anti-aliasing is enabled.

m_AntiAliasingEnabled - Variable in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet

whether anti-aliasing is enabled.

m_ArrayEditor - Variable in class adams.flow.source.WekaSelectObjects

the dialog for selecting the objects.

m_as - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

This holds the attribute stats of the current attribute on display.

m_asCache - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Cache of attribute stats info for the current data set

m_Ascending - Variable in class adams.data.instances.InstanceComparator

whether to sort ascending or descending.

m_Assignments - Variable in class weka.clusterers.SAXKMeans

Assignments obtained.

m_Associator - Variable in class adams.flow.source.WekaAssociatorSetup

the weka associator.

m_Associator - Variable in class adams.flow.transformer.WekaTrainAssociator

the name of the callable weka associator.

m_Associator - Variable in class adams.flow.transformer.WekaTrainAssociator.TrainJob

the associator to train.

m_AttIndex - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric

the attribute index.

m_AttIndices - Variable in class weka.filters.unsupervised.attribute.Detrend

the determined indices.

m_AttIndices - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

the determined indices.

m_AttIndices - Variable in class weka.filters.unsupervised.attribute.SimpleDetrend

the determined indices.

m_AttIndicesSet - Variable in class weka.filters.unsupervised.attribute.Detrend

the determined indices (as set).

m_AttIndicesSet - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

the determined indices (as set).

m_attnum - Variable in class weka.classifiers.meta.AbstainAttributePercentile

m_AttRange - Variable in class weka.filters.unsupervised.instance.KennardStone

the range of attributes to apply to.

m_AttRegExp - Variable in class weka.filters.unsupervised.attribute.Detrend

the range of attributes to work on.

m_AttRegExp - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

the range of attributes to work on.

m_attribIndex - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

This holds the index of the current attribute on display and should be set through setAttribute(int idx).

m_attribute - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

The chosen attribute

m_AttributeFilter - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Filter for removing class attribute, nominal attributes with 0 or 1 value.

m_attributeIndex - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

The index of the chosen attribute

m_AttributeIndex - Variable in class adams.data.weka.rowfinder.ByLabel

the attribute index to work on.

m_AttributeIndex - Variable in class adams.data.weka.rowfinder.ByNumericRange

the attribute index to work on.

m_AttributeIndex - Variable in class adams.data.weka.rowfinder.ByNumericValue

the attribute index to work on.

m_AttributeIndex - Variable in class adams.flow.transformer.WekaInstancesInfo

the index of the attribute to get the information for.

m_AttributeIndex - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

the attribute to index.

m_AttributeIndex - Variable in class weka.filters.unsupervised.attribute.SpellChecker

the index of the attribute to work on.

m_AttributeIndex - Variable in class weka.filters.unsupervised.instance.SortOnAttribute

the index of the attribute to sort on.

m_AttributeName - Variable in class adams.flow.transformer.WekaGetInstanceValue

the name of the attribute to get the value from the Instance.

m_AttributeName - Variable in class adams.flow.transformer.WekaInstanceEvaluator

the attribute name of the evaluation object.

m_AttributeName - Variable in class weka.filters.unsupervised.instance.DatasetLabeler

the name of the attribute name to add.

m_AttributeName - Variable in class weka.filters.unsupervised.instance.LatestRecords

the name of the attribute that holds the numeric database ID.

m_AttributeNameLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel

Displays the name of the relation

m_AttributeNames - Variable in class adams.flow.source.WekaNewInstances

the comma-separated list of attribute names.

m_AttributeNames - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

the attribute names.

m_AttributePrefix - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis

the prefix to use for the generated attributes.

m_AttributeRange - Variable in class adams.data.instancesanalysis.FastICA

the range of attributes to work.

m_AttributeRange - Variable in class adams.data.instancesanalysis.PCA

the range of attributes to work.

m_AttributeRange - Variable in class adams.data.instancesanalysis.PLS

the range of attributes to work.

m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.CorrelationMatrix

the range of attributes to work on.

m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.InputSmearing

the range of the attributes to work on.

m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.JoinAttributes

the range of the attributes to work on.

m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.LogTransform

the range of attributes to log-transform.

m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.SetMissingValue

the range of attributes to set to missing.

m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.SimpleDetrend

the range of attributes to work on.

m_AttributeRenameFindRegexs - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

The regexs to use to find attributes that require renaming.

m_AttributeRenameFormatStrings - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

The format strings specifying how to rename attributes.

m_Attributes - Variable in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

the range of attributes to plot.

m_Attributes - Variable in class weka.filters.unsupervised.attribute.EquiDistance

the indices of the identified attributes.

m_AttributeSelection - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

the attsel object.

m_AttributeSelection - Variable in class weka.classifiers.functions.LinearRegressionJ

The current attribute selection method

m_AttributeSelection - Variable in class weka.filters.unsupervised.attribute.EquiDistance

how to select the attributes.

m_AttributeStats - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

Cached stats on the attributes we've summarized so far

m_AttributesToProcess - Variable in class adams.flow.transformer.WekaMultiLabelSplitter

the indices of the class attributes still to process.

m_AttributeTypeLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel

Displays the type of attribute

m_AttributeTypes - Variable in class adams.flow.source.WekaNewInstances

the comma-separated list of attribute types.

m_AttributeX - Variable in class adams.flow.sink.WekaInstancesPlot

the attribute on the X axis.

m_AttributeX - Variable in class adams.flow.sink.WekaThresholdCurve

the attribute on the X axis.

m_AttributeX - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

the attribute on the X axis.

m_AttributeY - Variable in class adams.flow.sink.WekaInstancesPlot

the attribute on the Y axis.

m_AttributeY - Variable in class adams.flow.sink.WekaThresholdCurve

the attribute on the Y axis.

m_AttributeY - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

the attribute on the Y axis.

m_AttType - Variable in class adams.flow.transformer.WekaInstancesMerge

the attribute type of the ID attribute.

m_AttValues - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

m_Augmentations - Variable in class adams.core.management.WekaPackagesClassPathAugmenter

for storing the augmentations.

m_AutoKeyGeneration - Variable in class adams.flow.sink.WekaDatabaseWriter

whether to automatically generate a primary key.

m_Average - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

the calculated averages.

m_AverageSpacing - Variable in class weka.filters.unsupervised.attribute.EquiDistance

the average spacing.

m_AverageWidth - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval

the average width.

m_avg_target - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

The training data.

m_avg_target - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

The training data.

m_avg_target - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

The training data.

m_avg_target - Variable in class weka.classifiers.functions.GPD

The training data.

m_AxisX - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

the options for the X axis.

m_AxisY - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

the options for the Y axis.

m_B - Variable in class adams.data.instancesanalysis.pls.SIMPLS

the B matrix (used for prediction)

m_b_hat - Variable in class adams.data.instancesanalysis.pls.PLS1

the b-hat vector

m_BackupModel - Variable in class weka.classifiers.meta.SubsetEnsemble

The backup classifier, in case no ensemble could be constructed at prediction time.

m_BackupModel - Variable in class weka.classifiers.meta.VotedImbalance

The backup classifier, in case no ensemble could be constructed at prediction time.

m_barRange - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Contains the range of each bar in a histogram.

m_Base - Variable in class adams.data.instancesanalysis.pls.OPLS

the base PLS algorithm.

m_Base - Variable in class weka.classifiers.meta.Fallback

the base classifier.

m_BaseScore - Variable in class weka.classifiers.trees.XGBoost

Global bias.

m_BatchSize - Variable in class weka.classifiers.functions.PyroProxy

the batch size.

m_bestClassifier - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_bestClassifier - Variable in class weka.classifiers.meta.LeastMedianSq

m_BestClassifier - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

the best classifier.

m_bestMedian - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_bestMedian - Variable in class weka.classifiers.meta.LeastMedianSq

m_BestRange - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

stores the best range of attribtues.

m_Bias - Variable in class weka.classifiers.meta.VotedImbalance

the bias for the dataset balancing (0 = distribution in input data -- 1 = uniform distribution).

m_BinCalculation - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges

how to calculate the number of bins.

m_BinnableGroups - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

the collapsed data.

m_BinnableGroups - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

the collapsed data.

m_bins - Variable in class weka.core.SAXDistance

number of gaussian bins.

m_bins - Variable in class weka.filters.unsupervised.attribute.SAX

number of gaussian bins.

m_BinWidth - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges

the bin width - used for some calculations.

m_bits - Variable in class adams.opt.optimise.genetic.PackDataDef.DataInfo

m_bits - Variable in class adams.opt.optimise.GeneticAlgorithm

m_BitsPerGene - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the bits per gene to use.

m_BitString - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

m_Blin - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

m_Blin - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

m_Blin - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

m_Blin - Variable in class weka.classifiers.functions.GPD

m_Booster - Variable in class weka.classifiers.trees.XGBoost

The trained model.

m_BoosterType - Variable in class weka.classifiers.trees.XGBoost

The type of booster to use.

m_Border - Variable in class weka.experiment.ResultMatrixMediaWiki

the size of the border.

m_BorderTitle - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

the border title.

m_bps - Variable in class weka.filters.unsupervised.attribute.SAX

breakpoints.

m_Buffer - Variable in class adams.flow.transformer.WekaInstanceBuffer

the currently buffered data.

m_Buffer - Variable in class adams.flow.transformer.WekaInstanceDumper

the buffer.

m_BufferSize - Variable in class adams.flow.transformer.WekaInstanceDumper

the size of the buffer.

m_BuildWait - Variable in class weka.classifiers.functions.FakeClassifier

the build wait time in msec.

m_Built - Variable in class weka.classifiers.meta.AbstainingCascade

whether the models got built.

m_ButtonAction - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

the action button.

m_ButtonActivate - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

the button for activating a dataset.

m_ButtonAdd - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

the button for adding classifiers.

m_ButtonAdd - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

the button for adding files.

m_ButtonAdd - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

the button for a new sort definition.

m_ButtonAdd - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

the button for bringing up the filechooser.

m_ButtonAdd - Variable in class weka.gui.explorer.MultiExplorer

the button for adding a panel.

m_ButtonAll - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

to select all attributes

m_ButtonAnalyze - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the analyze button.

m_ButtonCancel - Variable in class adams.gui.goe.WekaExperimentFileEditor

the Cancel button.

m_ButtonCancel - Variable in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog

the Cancel button.

m_ButtonClear - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

the clear button.

m_ButtonClear - Variable in class adams.gui.tools.wekamultiexperimenter.LogPanel

the button for clearing the log.

m_ButtonClose - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the Close button.

m_ButtonCodeOutputCopy - Variable in class adams.gui.tools.WekaOptionsConversionPanel

the button for copying the code output.

m_ButtonCodeOutputPaste - Variable in class adams.gui.tools.WekaOptionsConversionPanel

the button for pasting the code output.

m_ButtonConvert - Variable in class adams.gui.tools.WekaOptionsConversionPanel

the button initiating the conversion.

m_ButtonCopy - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel

the copy button.

m_ButtonCopy - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

the copy button.

m_ButtonCopy - Variable in class weka.gui.explorer.MultiExplorer

the button for copying a panel.

m_ButtonCredentials - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel

the button for bringing up the dialog for the user credentials.

m_ButtonData - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the button for comparing the data.

m_ButtonDataGo - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the button for displaying the instances.

m_ButtonDisplay - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

the button for displaying the dataset.

m_ButtonDown - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

the down button.

m_ButtonDown - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

the button for moving classifiers down.

m_ButtonDown - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

the button for moving files down.

m_ButtonEdit - Variable in class adams.gui.goe.WekaExperimentFileEditor

the button to bring up the dialog for editing the experiment.

m_ButtonEdit - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

the button for editing a classifier.

m_ButtonEdit - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

the button for changing files.

m_ButtonEdit - Variable in class weka.gui.explorer.ExplorerExt

the edit button of the preprocess panel.

m_ButtonExecute - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

the execute button.

m_ButtonHelp - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

the help button.

m_ButtonHistory - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

the button for the history.

m_ButtonInputCopy - Variable in class adams.gui.tools.WekaOptionsConversionPanel

the button for copying the input.

m_ButtonInputPaste - Variable in class adams.gui.tools.WekaOptionsConversionPanel

the button for pasting the input.

m_ButtonInvert - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

to invert the current selection

m_ButtonLoad - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the Load button.

m_ButtonLoad - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage

the load props button.

m_ButtonLoad - Variable in class weka.gui.explorer.SqlPanel

the Load button

m_ButtonMoveDown - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

the move down button.

m_ButtonMoveDown - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

the button for moving the selected files down.

m_ButtonMoveUp - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

the move up button.

m_ButtonMoveUp - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

the button for moving the selected files up.

m_ButtonNone - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

to deselect all attributes

m_ButtonOK - Variable in class adams.gui.goe.WekaExperimentFileEditor

the OK button.

m_ButtonOK - Variable in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog

the OK button.

m_ButtonOutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the button for editing the output generators.

m_ButtonOutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the button for editing the output generators.

m_ButtonOutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the button for editing the output generators.

m_ButtonOutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the button for editing the output generators.

m_ButtonOutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the button for editing the output generators.

m_ButtonOutputGeneratorsFavorites - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the button for the output generator favorites.

m_ButtonOutputGeneratorsFavorites - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the button for the output generator favorites.

m_ButtonOutputGeneratorsFavorites - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the button for the output generator favorites.

m_ButtonOutputGeneratorsFavorites - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the button for the output generator favorites.

m_ButtonOutputGeneratorsFavorites - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the button for the output generator favorites.

m_ButtonPattern - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

for entering a regular expression for selection

m_ButtonReload - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the button for reloading an existing file.

m_ButtonRemove - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

the button for removing a dataset.

m_ButtonRemove - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

the button for removing classifiers.

m_ButtonRemove - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

the button for removing files.

m_ButtonRemove - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

the remove button.

m_ButtonRemove - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

the button for removing the selected files.

m_ButtonRemove - Variable in class weka.gui.explorer.MultiExplorer

the button for removing a panel.

m_ButtonRemoveAll - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

the button for removing all classifiers.

m_ButtonRemoveAll - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

the button for removing all files.

m_ButtonRemoveAll - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

the button for removing all files.

m_ButtonReset - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

the button for resetting the definitions.

m_ButtonSave - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

the save button.

m_ButtonSave - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

the save button.

m_ButtonSave - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel

the save button.

m_ButtonSave - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

the save button.

m_ButtonSave - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage

the save props button.

m_ButtonSelectedAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the button for copying the selected attributes range.

m_ButtonSelectedAttributesAction - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

button for removing checked attributes.

m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the start button.

m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the start button.

m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the start button.

m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the start button.

m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the start button.

m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the button to start PCA.

m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the button to start PLS.

m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the button for starting the filtering.

m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the button to start PCA.

m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the stop button.

m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the stop button.

m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the stop button.

m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the stop button.

m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the stop button.

m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the button to stop PCA.

m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the button to stop PLS.

m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the button for stop the filtering.

m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the button to stop PCA.

m_ButtonStructure - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the button for comparing the structure.

m_ButtonTextGo - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the button for displaying the instances.

m_ButtonUndo - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

the button for undoing changes.

m_ButtonUndo - Variable in class weka.gui.explorer.ExplorerExt

the undo button of the preprocess panel.

m_ButtonUp - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

the up button.

m_ButtonUp - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

the button for moving classifiers up.

m_ButtonUp - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

the button for moving files up.

m_ButtonVisualize - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the button for visualizing.

m_ButtonWorkspace - Variable in class weka.gui.explorer.MultiExplorer

the button for managing the workspaces.

m_C - Variable in class adams.data.instancesanalysis.pls.PRM

Tuning parameter.

m_C - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

The covariance matrix.

m_CallableActor - Variable in class adams.flow.source.WekaSelectDataset

the callable actor.

m_CallableActor - Variable in class adams.flow.transformer.WekaGeneticAlgorithm

the callable actor.

m_CallableName - Variable in class adams.flow.transformer.WekaGeneticAlgorithm

the callable name.

m_CanAbstain - Variable in class weka.classifiers.lazy.AbstainingLWL

whether the base classifier can abstain.

m_CanAbstain - Variable in class weka.classifiers.meta.AbstainingClassifierWrapper

whether the base classifier can abstain.

m_CanAbstain - Variable in class weka.classifiers.meta.FilteredClassifierExt

whether the base classifier can abstain.

m_CanAbstain - Variable in class weka.classifiers.meta.MinMaxLimits

whether the base classifier can abstain.

m_CanAbstain - Variable in class weka.classifiers.meta.ThreadSafeClassifierWrapper

whether the base classifier can abstain.

m_CancelListener - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the listener waiting for the user to cancel the dialog.

m_canopyClusters - Variable in class weka.clusterers.SAXKMeans

The canopy clusterer (if being used)

m_Capabilities - Variable in class adams.flow.condition.bool.AbstractAttributeCapabilities

the class index.

m_Cascade - Variable in class weka.classifiers.meta.ClassifierCascade

the cascade.

m_CellPadding - Variable in class weka.experiment.ResultMatrixMediaWiki

the cell padding.

m_CellPopupMenuCustomizer - Variable in class adams.gui.visualization.instances.InstancesTable

the customizer for the table cells popup menu.

m_CellRenderingCustomizer - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

for highlighting the cells in the table.

m_CellSpacing - Variable in class weka.experiment.ResultMatrixMediaWiki

the cell spacing.

m_centerFilter - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Filter for centering the data

m_centroidCanopyAssignments - Variable in class weka.clusterers.SAXKMeans

Canopies that each centroid falls into (determined by T1 radius)

m_CEPanel - Variable in class weka.gui.explorer.ExperimentPanel

The panel showing the current classifier selection.

m_ChangeListeners - Variable in class adams.gui.goe.WekaGenericObjectEditorPopupMenu

listeners that get notified when the user changes the setup.

m_ChangeListeners - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

the change listeners.

m_ChangeListeners - Variable in class adams.gui.visualization.instances.InstancesTable

the listeners for changes.

m_CharSet - Variable in class adams.flow.transformer.WekaTextDirectoryReader

the character set.

m_CheckBoxAntiAliasing - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

whether to use anti-aliasing.

m_CheckBoxBatchFilter - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the checkbox for batch-filtering.

m_CheckBoxCustomSplitGenerator - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

whether to use a custom split generator.

m_CheckBoxDiscardPredictions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

whether to discard the predictions.

m_CheckBoxDiscardPredictions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

whether to discard the predictions.

m_CheckBoxDiscardPredictions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

whether to discard the predictions.

m_CheckBoxDiscardPredictions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

whether to discard the predictions.

m_CheckBoxDiscardPredictions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

whether to discard the predictions.

m_CheckBoxFinalModel - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

whether to produce a final model.

m_CheckBoxIncludeDateAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

whether to include date attributes.

m_CheckBoxIncludeNominalAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

whether to include numeric nominal.

m_CheckBoxIncludeNumericAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

whether to include numeric attributes.

m_CheckBoxIncludeRelationalAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

whether to include relational attributes.

m_CheckBoxIncludeStringAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

whether to include string attributes.

m_CheckBoxKeepName - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the whether to keep the relation name.

m_CheckBoxLenient - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

whether to be lenient with checks.

m_CheckBoxMarkers - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

whether to use markers.

m_CheckBoxPerFoldOutput - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

whether to use separate evaluations per fold.

m_CheckBoxPreserveOrder - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

whether to preserve the order.

m_CheckBoxPreserveOrder - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

whether to preserve the order.

m_CheckBoxPreserveOrder - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

whether to preserve the order.

m_CheckBoxPreserveOrder - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

whether to preserve the order.

m_CheckBoxPreserveOrder - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

whether to preserve the order.

m_CheckBoxReplace - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the checkbox to replace the datasets.

m_CheckBoxSerialize - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the whether to serialize the filter to a file.

m_CheckBoxSkipNominal - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

whether to skip nominal attributes.

m_CheckBoxSwapRowsColumns - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

for swapping rows/columns.

m_CheckBoxUseViews - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

whether to use views.

m_CheckBoxUseViews - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

whether to use views.

m_CheckBoxUseViews - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

whether to use views.

m_CheckHeader - Variable in class adams.flow.transformer.WekaInstanceBuffer

whether to check the header.

m_CheckHeader - Variable in class adams.flow.transformer.WekaInstanceDumper

whether to check the header.

m_checksTurnedOff - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a numeric class.

m_checksTurnedOff - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a numeric class.

m_checksTurnedOff - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a numeric class.

m_checksTurnedOff - Variable in class weka.classifiers.functions.GPD

Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a numeric class.

m_checksTurnedOff - Variable in class weka.classifiers.functions.LinearRegressionJ

Turn off all checks and conversions?

m_ClassAttName - Variable in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

the class attribute name.

m_ClassAttribute - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

how to determine the class attribute.

m_ClassAttributeHeuristic - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the heuristic for selecting the class attribute.

m_ClassAttributeIndices - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

the class attribute indices.

m_ClassAttributes - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

the regular expression for identifying class attributes (besides an explicitly set one).

m_ClassAttributes - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

The set of class attributes for the given datasets.

m_ClassAttributes - Variable in class adams.flow.transformer.WekaMultiLabelSplitter

the indices of the class attributes.

m_ClassCombo - Variable in class weka.gui.explorer.ExperimentPanel

Lets the user select the class column.

m_ClassDetails - Variable in class adams.flow.transformer.WekaEvaluationSummary

whether to print the class details as well.

m_ClassDetails - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

whether to print the class details as well.

m_ClassDistribution - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions

the columns with the class distributions.

m_ClassDistribution - Variable in class weka.classifiers.functions.FromPredictions

the class distribution columns (if any).

m_ClassDistributionIndices - Variable in class weka.classifiers.functions.FromPredictions

the class distribution column indices.

m_ClassFilters - Variable in class weka.classifiers.meta.ClassificationViaRegressionD

The filters used to transform the class.

m_ClassFinder - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

The column finder for selecting class attributes.

m_ClassificationEntry - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

the entry to use for the numeric classification in the spreadsheet.

m_ClassificationLabelEntry - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

the entry to use for the classification label in the spreadsheet.

m_Classifier - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased

the IntervalEstimator to use.

m_Classifier - Variable in class adams.flow.source.WekaClassifierSetup

the weka classifier.

m_Classifier - Variable in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

the name of the callable weka classifier.

m_Classifier - Variable in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

the name of the callable weka classifier.

m_Classifier - Variable in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

the name of the callable weka classifier.

m_Classifier - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

the classifier to evaluate.

m_Classifier - Variable in class adams.flow.transformer.WekaStreamEvaluator

the classifier to use.

m_Classifier - Variable in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob

the classifier to evaluate.

m_Classifier - Variable in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob

the classifier to train.

m_Classifier - Variable in class adams.flow.transformer.WekaTrainClassifier

the name of the callable weka classifier.

m_Classifier - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

the classifier to train.

m_Classifier - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

the classifier.

m_Classifier - Variable in class adams.ml.model.classification.WekaClassifier

the weka classifier to use.

m_Classifier - Variable in class adams.ml.model.regression.WekaRegressor

the weka classifier to use.

m_Classifier - Variable in class adams.multiprocess.WekaCrossValidationExecution

the classifier to evaluate.

m_Classifier - Variable in class adams.multiprocess.WekaCrossValidationJob

the classifier to evaluate.

m_Classifier - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the classifier to use.

m_Classifier - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

the classifier to use if no serialized model is given.

m_Classifier - Variable in class weka.filters.supervised.instance.RemoveOutliers

the classifier to use for evaluation.

m_ClassifierEditor - Variable in class weka.gui.explorer.ExperimentPanel

Lets the user configure the classifier.

m_Classifiers - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

the classifiers to evaluate.

m_Classifiers - Variable in class adams.multiprocess.WekaCrossValidationExecution

the separate classifiers.

m_Classifiers - Variable in class weka.classifiers.meta.ClassificationViaRegressionD

The classifiers.

m_Classifiers - Variable in class weka.classifiers.meta.SubsetEnsemble

the actual classifiers in use.

m_Classifiers - Variable in class weka.classifiers.meta.VotedImbalance

the actual classifiers in use.

m_ClassifierWeights - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

m_ClassifierWeights_string - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

m_classIndex - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Contains the current class index.

m_classIndex - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

The class index from the training data

m_classIndex - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

The class index from the training data

m_classIndex - Variable in class weka.classifiers.functions.GPD

The class index from the training data

m_classIndex - Variable in class weka.classifiers.meta.Corr

m_classIndex - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

The attribute to treat as the class for purposes of cleansing.

m_classIndex - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

The attribute to treat as the class for purposes of cleansing.

m_ClassIndex - Variable in class adams.flow.sink.WekaCostBenefitAnalysis

the index of the class label.

m_ClassIndex - Variable in class adams.flow.source.WekaNewInstances

the index for the class attribute, if any.

m_ClassIndex - Variable in class adams.flow.transformer.WekaBootstrapping

the index of the class label.

m_ClassIndex - Variable in class adams.flow.transformer.WekaClassSelector

the class index.

m_ClassIndex - Variable in class adams.flow.transformer.WekaEvaluationValuePicker

the index of the class label.

m_ClassIndex - Variable in class adams.flow.transformer.WekaEvaluationValues

the range of the class labels.

m_ClassIndex - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

the index of the class label.

m_ClassIndex - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis

the index of the class label.

m_ClassIndex - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

the index of the class label.

m_ClassIndex - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the class index.

m_ClassIndex - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

the class index.

m_ClassIndex - Variable in class weka.classifiers.functions.LinearRegressionJ

The index of the class attribute

m_ClassIndex - Variable in class weka.classifiers.meta.ClassifierCascade

the class index.

m_ClassIndex - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Class index.

m_ClassLabel - Variable in class adams.flow.transformer.WekaClassifierRanker

the class label (in case of class-specific measures).

m_ClassLabel - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

the class label index.

m_ClassLabelIndex - Variable in class adams.data.conversion.WekaEvaluationToCostCurve

the class label index.

m_ClassLabelIndex - Variable in class adams.data.conversion.WekaEvaluationToThresholdCurve

the class label index.

m_ClassLabelIndex - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

the class label index.

m_ClassLabelIndex - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

the class label index for per-class stats.

m_ClassLabelIndex - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

the class label index.

m_ClassLabelIndex - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the label index.

m_ClassLabelRange - Variable in class adams.flow.sink.WekaCostCurve

the class label range.

m_ClassLabelRange - Variable in class adams.flow.sink.WekaThresholdCurve

the class label indices.

m_ClassLabelRange - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve

the class label range.

m_ClassLabelRange - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

the class label indices.

m_ClassLabels - Variable in class weka.classifiers.AggregateEvaluations

the optional class labels.

m_ClassMean - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

the class mean.

m_ClassMean - Variable in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS

the class mean.

m_ClassMean - Variable in class weka.classifiers.functions.LinearRegressionJ

The mean of the class attribute

m_classMeanForMissing - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

The class mean for missing values

m_Classname - Variable in class adams.core.discovery.genetic.GenericDoubleResolution

the class name.

m_Classname - Variable in class adams.core.discovery.genetic.GenericFloatResolution

the class name.

m_Classname - Variable in class adams.core.discovery.genetic.GenericInteger

the class name.

m_Classname - Variable in class adams.core.discovery.genetic.GenericString

the class name.

m_Classname - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode

the classname to use.

m_ClassName - Variable in class adams.flow.source.WekaNewInstances

the name for the class attribute, if any.

m_ClassName - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

The class-attribute for supervised attribute filters.

m_ClassStdDev - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

the class stddev.

m_ClassStdDev - Variable in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS

the class stddev.

m_ClassStdDev - Variable in class weka.classifiers.functions.LinearRegressionJ

The standard deviations of the class attribute

m_ClassType - Variable in class adams.gui.goe.WekaGenericObjectEditorPanel

the class type.

m_Cleaner - Variable in class weka.core.tokenizers.PreCleanedTokenizer

the cleaner to use.

m_Cleaners - Variable in class weka.core.tokenizers.cleaners.MultiCleaner

the cleaners to use.

m_cleansingClassifier - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

The classifier used to do the cleansing

m_cleansingClassifier - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

The classifier used to do the cleansing

m_ClearBuffer - Variable in class adams.flow.transformer.WekaInstanceBuffer

whether to clear the buffer once it has been forwarded.

m_ClearBufferRequired - Variable in class adams.flow.transformer.WekaInstanceBuffer

whether variable triggered clear of buffer.

m_CloseParent - Variable in class adams.gui.tools.weka.AppendDatasetsPanel

whether to close parent.

m_CloseParent - Variable in class adams.gui.tools.weka.BatchFilterDatasetsPanel

whether to close parent.

m_ClusterCentroids - Variable in class weka.clusterers.SAXKMeans

holds the cluster centroids.

m_Clusterer - Variable in class adams.flow.source.WekaClustererSetup

the weka clusterer.

m_Clusterer - Variable in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator

the name of the callable weka clusterer.

m_Clusterer - Variable in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob

the clusterer to train.

m_Clusterer - Variable in class adams.flow.transformer.WekaTrainClusterer

the name of the callable weka clusterer.

m_Clusterer - Variable in class adams.ml.model.clustering.WekaClusterer

the weka classifier to use.

m_ClusterMissingCounts - Variable in class weka.clusterers.SAXKMeans

m_ClusterNominalCounts - Variable in class weka.clusterers.SAXKMeans

For each cluster, holds the frequency counts for the values of each nominal attribute.

m_ClusterSizes - Variable in class weka.clusterers.SAXKMeans

The number of instances in each cluster.

m_ClusterStdDevs - Variable in class weka.clusterers.SAXKMeans

Holds the standard deviations of the numeric attributes in each cluster.

m_Coefficients - Variable in class weka.classifiers.functions.LinearRegressionJ

Array for storing coefficients of linear regression.

m_Coefficients - Variable in class weka.core.WeightedEuclideanDistance

Array for storing coefficients of linear regression.

m_Coefficients - Variable in class weka.core.WeightedEuclideanDistanceRidge

Array for storing coefficients of linear regression.

m_Coefficients - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay

the calculated coefficients.

m_Coefficients - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay2

the calculated coefficients.

m_coeffs - Variable in class weka.classifiers.meta.Corr

m_ColIndex - Variable in class adams.ml.data.DataCellView

the column index.

m_ColName - Variable in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

the column with the name.

m_ColName - Variable in class adams.flow.transformer.wekapackagemanageraction.Uninstall

the column with the name.

m_Color - Variable in class adams.gui.visualization.instance.InstanceContainer

the associated color.

m_colorAttrib - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

This stores and lets the user select a class attribute.

m_ColorField - Variable in class adams.gui.visualization.instance.ReportColorInstancePaintlet

the report field to get the color from.

m_colorList - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Contains discrete colours for colouring of subbars of histograms and bar plots when the class attribute is set and is nominal

m_ColorProvider - Variable in class adams.flow.sink.WekaInstanceViewer

the color provider to use.

m_ColorProvider - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

the color provider to use.

m_ColorProvider - Static variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

the color provider.

m_ColorProvider - Variable in class adams.gui.visualization.instance.InstanceContainerManager

the color provider for managing the colors.

m_Column - Variable in class adams.flow.transformer.WekaExperimentEvaluation

the column (= classifiers).

m_Column - Variable in class adams.flow.transformer.WekaGetInstancesValue

the column index.

m_Column - Variable in class adams.flow.transformer.WekaSetInstancesValue

the column to update.

m_Column - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

the column (= classifiers).

m_Column - Variable in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer

the column index.

m_ColumnComboBox - Variable in class adams.gui.visualization.instances.InstancesPanel

for listing the column names.

m_ColumnFinder - Variable in class adams.data.weka.columnfinder.AbstractFilteredColumnFinder

the ColumnFinder to apply.

m_ColumnFinder - Variable in class adams.data.weka.datasetsplitter.ColumnSplitter

Column-finder for selecting which attributes go in which dataset.

m_ColumnFinder - Variable in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

The classifier template used to do the classification.

m_ColumnFinder - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

The column-finder which selects the attributes to summarise.

m_ColumnFinderTrained - Variable in class adams.data.weka.columnfinder.RowFilteredColumnFinder

whether the column finder was trained on the subset.

m_ColumnNames - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

the column names.

m_Columns - Variable in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

num columns

m_Columns - Variable in class adams.data.weka.columnfinder.Constant

The set of columns to find.

m_Columns - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

m_ColumnSampleByLevel - Variable in class weka.classifiers.trees.XGBoost

Subsample ratio of columns for each level.

m_ColumnSampleByNode - Variable in class weka.classifiers.trees.XGBoost

Subsample ratio of columns for each node (split).

m_ColumnSampleByTree - Variable in class weka.classifiers.trees.XGBoost

Subsample ratio of columns when constructing each tree.

m_ColumnSplitter - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Column-splitter for separating attributes to be summarised.

m_ColVersion - Variable in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

the column with the version.

m_Combination - Variable in class adams.data.weka.columnfinder.MultiColumnFinder

how the indices are combined.

m_Combination - Variable in class adams.data.weka.rowfinder.MultiRowFinder

how the indices are combined.

m_Combination - Variable in class weka.classifiers.meta.ClassifierCascade

how to combine the statistics.

m_CombinationRule - Variable in class weka.classifiers.meta.AbstainVote

Combination Rule variable

m_CombinationRule - Variable in class weka.classifiers.meta.SubsetEnsemble

Combination Rule variable.

m_CombinationRule - Variable in class weka.classifiers.meta.VotedImbalance

Combination Rule variable.

m_ComboBoxClass - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

the class attribute.

m_ComboBoxClass - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the class index.

m_ComboBoxClassificationRegression - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

classification or regression.

m_ComboBoxClassModel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the class index model.

m_ComboBoxColor - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the attribute to use for color.

m_ComboBoxData - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the combobox with all the datasets.

m_ComboBoxDataActions - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the combobox with all the actions.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the datasets.

m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the datasets.

m_ComboBoxEvaluation - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

the type of evaluation.

m_ComboBoxEvaluation - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

the type of evaluation.

m_ComboBoxEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the combobox with the available evaluations.

m_ComboBoxEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the combobox with the available evaluations.

m_ComboBoxEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the combobox with the available evaluations.

m_ComboBoxEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the combobox with the available evaluations.

m_ComboBoxFirstDataset - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the first dataset.

m_ComboBoxFirstID - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the ID attribute in the first dataset to use for comparing the data.

m_ComboBoxID - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the ID.

m_ComboBoxID - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the ID index.

m_ComboBoxIDModel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the ID index model.

m_ComboBoxMetric - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the combobox with the metric to evaluate.

m_ComboBoxNames - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

the combobox with column names.

m_ComboBoxOrder - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

how to traverse.

m_ComboBoxOutput - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel

the combobox listing all the output types.

m_ComboBoxPanels - Variable in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

the combobox with all available panels.

m_ComboBoxResults - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the combobox with the results panels.

m_ComboBoxRowAttribute - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

the combobox with the attribute names.

m_ComboBoxRowAttributeModel - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

the underlying model for the comboxbox.

m_ComboBoxSecondDataset - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the second dataset.

m_ComboBoxSecondID - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the ID attribute in the second dataset to use for comparing the data.

m_ComboBoxSetups - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the combobox with the available setups.

m_ComboBoxSorting - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the sorting index.

m_ComboBoxSorting - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

the type of sorting.

m_ComboBoxSortingModel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the soriting index model.

m_ComboBoxTest - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

the test set.

m_ComboBoxTest - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

the test set.

m_ComboBoxTest - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

the test set.

m_ComboBoxTest - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

the test set.

m_ComboBoxTextActions - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the combobox with all the actions.

m_ComboBoxTextInstances - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the combobox with all the instances.

m_ComboBoxTrain - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

the train set.

m_ComboBoxTrain - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

the train set.

m_ComboBoxTrain - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

the train set.

m_ComboBoxTrain - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

the train set.

m_ComboBoxValidate - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

the validate set.

m_CommandLineHandler - Variable in class adams.flow.core.WekaPropertyValueConverter

the commandline handler to use.

m_CommandLineHandler - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

for handling commandlines.

m_Comment - Variable in class adams.flow.transformer.WekaClusterEvaluationSummary

an optional comment to output.

m_Comment - Variable in class adams.flow.transformer.WekaEvaluationSummary

an optional comment to output.

m_Communication - Variable in class weka.classifiers.functions.PyroProxy

the instance converter to use.

m_Comparator - Static variable in class adams.data.instance.Instance

the default comparator.

m_Comparator - Static variable in class adams.data.instance.InstanceUtils

comparator for finding X values.

m_Comparator - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions

the comparator to use.

m_Comparator - Variable in class weka.classifiers.AggregateEvaluations

the comparator to use.

m_ComparisonField - Variable in class adams.flow.transformer.WekaExperimentEvaluation

the comparison field.

m_ComparisonField - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

the comparison field.

m_completed - Variable in class weka.clusterers.SAXKMeans

m_Completed - Variable in class weka.classifiers.meta.SubsetEnsemble

The number of classifiers completed so far

m_Completed - Variable in class weka.classifiers.meta.VotedImbalance

The number of classifiers completed so far

m_CompleteRowsOnly - Variable in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Whether or not to skip IDs that don't exist in all source datasets.

m_ComplexityStatistics - Variable in class adams.flow.transformer.WekaEvaluationSummary

whether to print the complexity statistics as well.

m_ComplexityStatistics - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

whether to print the complexity statistics as well.

m_Component - Variable in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel

the actual component.

m_Component - Variable in class adams.gui.tools.wekainvestigator.output.TableContentPanel

the actual component.

m_Component - Variable in class adams.gui.tools.wekainvestigator.output.TextualContentPanel

the actual component.

m_ComponentRange - Variable in class weka.attributeSelection.AbstractPLSAttributeEval

for user defined range of components used.

m_Components - Variable in class adams.data.instancesanalysis.FastICA

the components.

m_ConfidenceLevel - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased

the confidence level.

m_Configured - Variable in class adams.flow.transformer.WekaGeneticAlgorithm

whether the callable actor has been configured.

m_ConfusionMatrix - Variable in class adams.flow.transformer.WekaEvaluationSummary

whether to print the confusion matrix as well.

m_ConfusionMatrix - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

whether to print the confusion matrix as well.

m_Container - Variable in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob

the model container.

m_Container - Variable in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob

the generated model container.

m_Containers - Variable in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

the generated containers.

m_Containers - Variable in class weka.classifiers.MultiLevelSplitGenerator

the list of generated containers.

m_Conversion - Variable in class weka.core.converters.SpreadSheetLoader

the conversion to use.

m_Converter - Variable in class adams.data.conversion.WekaCommandToCode

the converter to use.

m_CoordinatesPaintlet - Variable in class adams.gui.visualization.instance.InstancePanel

paintlet for drawing the X-axis.

m_Correct - Variable in class weka.filters.unsupervised.attribute.SpellChecker

the correct spelling for the labels.

m_Correction - Variable in class weka.filters.unsupervised.attribute.Detrend

the correction to use.

m_Correction - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

the correction to use.

m_Correction - Variable in class weka.filters.unsupervised.attribute.SimpleDetrend

the correction to use.

m_Correlation - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Correlation matrix for the original data.

m_CostBenefitPanel - Variable in class adams.flow.sink.WekaCostBenefitAnalysis

the panel.

m_Counter - Variable in class adams.flow.transformer.WekaInstanceDumper

the counter for the filenames.

m_Counter - Variable in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

the counter for the X value of the containers.

m_CoverVariance - Variable in class adams.flow.transformer.WekaPrincipalComponents

the variance to cover.

m_CoverVariance - Variable in class weka.core.neighboursearch.PCANNSearch

the amount of varaince to cover in the original data when retaining the best n PC's.

m_CoverVariance - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

the amount of varaince to cover in the original data when retaining the best n PC's.

m_CreateView - Variable in class adams.flow.transformer.WekaCrossValidationSplit

whether to create a view only.

m_CreateView - Variable in class adams.flow.transformer.WekaRandomSplit

whether to create a view only.

m_CrossValidation - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator

for performing cross-validation.

m_CrossValidation - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

for performing cross-validation.

m_CrossValidation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

performs the actual evaluation.

m_CrossValidation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

performs the actual evaluation.

m_CrossValidation - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment.CrossValidationExperimentJob

for executing the cross-validation.

m_CrossValidationSeed - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the cross-validation seed.

m_CrossValidationSeed - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

the cross-validation seed.

m_cs - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_Current - Variable in class adams.flow.transformer.WekaStreamEvaluator

the current counter of instances.

m_Current - Variable in class adams.gui.goe.WekaGenericArrayEditorDialog

the current object.

m_Current - Variable in class adams.gui.goe.WekaGenericArrayEditorPanel

the current value.

m_Current - Variable in class adams.gui.goe.WekaGenericObjectEditorDialog

the current object.

m_Current - Variable in class adams.gui.goe.WekaGenericObjectEditorPanel

the current object.

m_Current - Variable in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard

the current algorithm.

m_CurrentAssociator - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the current associator.

m_CurrentBoxPlot - Variable in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab

the current boxplot.

m_currentClassifier - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_currentClassifier - Variable in class weka.classifiers.meta.LeastMedianSq

m_CurrentClassifier - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator

the current classifier.

m_CurrentClassifier - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the current classifier.

m_CurrentClassifier - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the current classifier.

m_CurrentClassifier - Variable in class adams.multiprocess.WekaCrossValidationExecution

the current classifier that is being trained.

m_CurrentClassifier - Variable in class weka.classifiers.evaluation.StoppableEvaluation

the current classifier that is being evaluated.

m_CurrentClusterer - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the current clusterer.

m_CurrentEvaluation - Variable in class adams.flow.transformer.WekaTestSetEvaluator

the current evaluation.

m_CurrentEvaluation - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator

the current evaluation.

m_CurrentEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the current evaluation.

m_CurrentEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the current evaluation.

m_CurrentEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the current evaluation.

m_CurrentEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the current evaluation.

m_CurrentEvaluation - Variable in class adams.multiprocess.WekaCrossValidationExecution

the evaluation currently being run.

m_CurrentEvaluator - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the current evaluator.

m_CurrentFile - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the current file.

m_CurrentFile - Variable in class weka.gui.explorer.ExplorerExt

the current file.

m_CurrentFiles - Variable in class adams.gui.tools.DatasetCompatibilityPanel

the selected files.

m_CurrentFilter - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the current filter.

m_CurrentFold - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

the current fold.

m_CurrentFold - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator

the current fold.

m_CurrentFold - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

the current fold.

m_CurrentFold - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

the current fold.

m_CurrentFold - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

the current fold.

m_CurrentLoader - Variable in class adams.gui.tools.DatasetCompatibilityPanel

the current loader.

m_CurrentPair - Variable in class weka.classifiers.LeaveOneOutByValueGenerator

the current train/test pair to generate.

m_CurrentPanel - Variable in class adams.gui.tools.wekainvestigator.tab.DataTab

the currently displayed panel.

m_CurrentPanel - Variable in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

the currently displayed panel.

m_CurrentSearch - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the current search.

m_CurrentSetup - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the current p.

m_CustomLoader - Variable in class adams.flow.transformer.WekaFileReader

the custom loader.

m_CustomLoader - Variable in class adams.flow.transformer.WekaReorderAttributesToReference

the custom loader.

m_CustomLoader - Variable in class weka.filters.unsupervised.instance.AlignDataset

the file loader to use for loading the reference data.

m_CustomLoader - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances

the file loader to use for loading the test set.

m_CustomPaintlet - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

the custom paintlet.

m_CustomPropsFile - Variable in class adams.flow.sink.WekaDatabaseWriter

a custom properties file to use instead of default one.

m_CustomPropsFile - Variable in class adams.flow.source.WekaDatabaseReader

a custom properties file to use instead of default one.

m_CustomSaver - Variable in class adams.flow.sink.WekaFileWriter

the custom saver.

m_CustomStopMessage - Variable in class adams.flow.source.WekaSelectDataset

the custom stop message to use if flow gets stopped due to cancelation.

m_CVR - Variable in class weka.classifiers.functions.ClassificationViaPLS

the ClassificationViaRegression used internally.

m_data - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

This holds the current set of instances

m_data - Variable in class adams.opt.optimise.genetic.PackData

m_data - Variable in class weka.classifiers.functions.GPD

m_data - Variable in class weka.classifiers.trees.RandomModelTrees

m_Data - Variable in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

the data set to use for training and other bits.

m_Data - Variable in class adams.flow.source.WekaDatabaseReader

the full data.

m_Data - Variable in class adams.flow.transformer.WekaFilter.BatchFilterJob

the data to use for training.

m_Data - Variable in class adams.flow.transformer.WekaTrainAssociator.TrainJob

the data to use for training.

m_Data - Variable in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob

the data to use for training.

m_Data - Variable in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob

the data to use for training.

m_Data - Variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

the underlying data.

m_Data - Variable in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

the underlying data.

m_Data - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the data loaded.

m_Data - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

the dataset.

m_Data - Variable in class adams.gui.visualization.instance.InstanceTableModel

the underlying data.

m_Data - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

the instances that forms the basis for the sorting.

m_Data - Variable in class adams.gui.visualization.instances.InstancesTableModel

the data

m_Data - Variable in class adams.ml.data.InstancesHeaderRow

the underlying data.

m_Data - Variable in class adams.ml.data.InstancesView

the underlying data.

m_Data - Variable in class adams.ml.data.InstanceView

the underlying data.

m_Data - Variable in class adams.multiprocess.WekaCrossValidationExecution

the data to evaluate on.

m_Data - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

the data to use.

m_Data - Variable in class weka.classifiers.AbstractSplitGenerator

the original dataset.

m_Data - Variable in class weka.classifiers.meta.AbstainAttributePercentile

m_Data - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_Data - Variable in class weka.classifiers.meta.LeastMedianSq

m_Data - Variable in class weka.classifiers.meta.SubsetEnsemble

For holding the original training set temporarily.

m_Data - Variable in class weka.classifiers.meta.VotedImbalance

For holding the original training set temporarily.

m_Data - Variable in class weka.classifiers.trees.RandomRegressionForest

the original header

m_Data - Variable in class weka.core.AbstractHashableInstance

the wrapped instance.

m_Data - Variable in class weka.core.converters.SimpleArffLoader

the currently loaded data.

m_Data - Variable in class weka.core.converters.SpreadSheetLoader

the actual data.

m_Data - Variable in class weka.core.InstanceGrouping

the original data.

m_Data1 - Variable in class adams.tools.CompareDatasets

the current dataset 1.

m_Data2 - Variable in class adams.tools.CompareDatasets

the current dataset 2.

m_DatabaseConnection - Variable in class adams.data.instances.AbstractInstanceGenerator

the database connection.

m_DataGenerated - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

whether data was generated.

m_DataGenerator - Variable in class adams.flow.source.WekaDataGenerator

the filter to apply.

m_dataPointCanopyAssignments - Variable in class weka.clusterers.SAXKMeans

Canopies that each training instance falls into (determined by T1 radius)

m_DataRowType - Variable in class adams.data.conversion.WekaInstancesToSpreadSheet

the data row type to use.

m_DataSearch - Variable in class weka.classifiers.lazy.LWLSynchroSplit

the data to use for the search.

m_Dataset - Variable in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader

the header to match against.

m_Dataset - Variable in class adams.flow.transformer.WekaMultiLabelSplitter

the dataset to process.

m_Dataset - Variable in class adams.flow.transformer.WekaStoreInstance

the dataset to append to.

m_Dataset - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

the dataset in use.

m_Dataset - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

the dataset in use.

m_Dataset - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

the underlying dataset.

m_Dataset - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

the filename of the data to use for cross-validation.

m_Dataset - Variable in class weka.core.InstancesView

the underlying dataset.

m_Dataset1 - Variable in class adams.tools.CompareDatasets

the first dataset.

m_Dataset2 - Variable in class adams.tools.CompareDatasets

the second dataset.

m_DatasetFileChooser - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

the file chooser for models.

m_DatasetHeader - Variable in class adams.data.instance.Instance

a reference to the dataset the data was obtained from.

m_DatasetInfo - Variable in class adams.ml.model.classification.WekaClassificationModel

the dataset info.

m_DatasetInfo - Variable in class adams.ml.model.clustering.WekaClusteringModel

the dataset info.

m_DatasetInfo - Variable in class adams.ml.model.regression.WekaRegressionModel

the dataset info.

m_DatasetNames - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

The name of each dataset to use in attribute renaming.

m_Datasets - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

The source datasets we are merging.

m_Datasets - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

the datasets to evaluate.

m_DatasetTmpFile - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

the dataset's tmp file.

m_DatasetTmpFile - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

the dataset's tmp file.

m_DataTrain - Variable in class weka.classifiers.lazy.LWLSynchroSplit

the data to use for building the base classifier.

m_DataType - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges

the type of data to get from the Instances object (rows or columns).

m_DataType - Variable in class adams.flow.transformer.WekaInstancesStatistic

the type of data to get from the Instances object (rows or columns).

m_DateFormat - Variable in class adams.flow.transformer.WekaInstancesInfo

for formatting dates.

m_debug - Variable in class weka.classifiers.meta.AbstainAttributePercentile

m_debug - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_debug - Variable in class weka.classifiers.meta.LeastMedianSq

m_Debug - Variable in class weka.core.converters.SpreadSheetLoader

whether to print some debug information

m_Debug - Variable in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

whether to output debugging information.

m_Default - Variable in class adams.gui.goe.WekaGenericArrayEditorPanel

the default value.

m_DefaultAttributeRange - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the default range.

m_DefaultClassIndex - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the default class index.

m_DefaultColor - Variable in class adams.gui.visualization.instance.ReportColorInstancePaintlet

the default color to use if no color found in report.

m_defaultColors - Static variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

default colour list

m_DefaultDataTableHeight - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

the default data table height.

m_DefaultIDIndex - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the default ID index.

m_DefaultIncludeDateAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the default for date attributes.

m_DefaultIncludeNominalAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the default for nominal attributes.

m_DefaultIncludeNumericAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the default for numeric attributes.

m_DefaultIncludeRelationalAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the default for relational attributes.

m_DefaultIncludeStringAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the default for string attributes.

m_DefaultSortIndex - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the default sort index.

m_DeflationMode - Variable in class adams.data.instancesanalysis.pls.NIPALS

X and Y deflation Mode

m_delta - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

Gaussian Noise Value.

m_delta - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

Gaussian Noise Value.

m_delta - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

Gaussian Noise Value.

m_delta - Variable in class weka.classifiers.functions.GPD

Gaussian Noise Value.

m_deltaClass - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

Gaussian Noise Value for class.

m_deltaSquared - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

The squared noise value.

m_DerivativeOrder - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay

the order of the derivative.

m_DerivativeOrder - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay2

the order of the derivative.

m_Detector - Variable in class weka.filters.supervised.instance.RemoveOutliers

the outlier detector to use.

m_df - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Degrees of freedom, used in statistical calculations

m_Dialog - Variable in class adams.flow.source.WekaSelectObjects

the dialog for selecting the objects.

m_Dialog - Variable in class adams.gui.goe.WekaGenericArrayEditorPanel

the dialog for displaying the editor.

m_Dialog - Variable in class adams.gui.goe.WekaGenericObjectEditorPanel

the dialog for displaying the editor.

m_Dialog - Variable in class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns

the dialog for exporting.

m_DialogColorProvider - Variable in class adams.gui.visualization.instance.InstanceExplorer

the dialog for selecting the color provider.

m_DialogPaintlet - Variable in class adams.gui.visualization.instance.InstanceExplorer

the dialog for selecting the paintlet.

m_Diameter - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

the diameter of the cross.

m_Differ - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

how to handle differing values.

m_Differ - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

how to handle differing values.

m_DIPLS - Variable in class adams.data.instancesanalysis.pls.DIPLS

the actual algorithm.

m_DiscardPredictions - Variable in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

whether to discard predictions.

m_DiscardPredictions - Variable in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

whether to discard predictions.

m_DiscardPredictions - Variable in class adams.flow.transformer.WekaTestSetEvaluator

whether to discard predictions.

m_DiscardPredictions - Variable in class adams.multiprocess.WekaCrossValidationExecution

whether to discard predictions.

m_DiscardPredictions - Variable in class adams.multiprocess.WekaCrossValidationJob

whether to discard the predictions.

m_displayCurrentAttribute - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

m_displayStdDevs - Variable in class weka.clusterers.SAXKMeans

Display standard deviations for numeric atts.

m_DistanceFunction - Variable in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient

the distance function to use.

m_DistanceFunction - Variable in class weka.clusterers.SAXKMeans

the distance function used.

m_Distances - Variable in class weka.core.neighboursearch.NewNNSearch

Array holding the distances of the nearest neighbours.

m_DistinctLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel

Displays the number of distinct values

m_distMatrix - Variable in class weka.core.SAXDistance

m_DistributionFormat - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

the format to use for the distribution entries in the spreadsheet.

m_DistributionSorting - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

the type of sorting to apply to the distribution array (if applicable).

m_doneCurrentAttribute - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

m_dontReplaceMissing - Variable in class weka.clusterers.SAXKMeans

Replace missing values globally?

m_DropAbove - Variable in class weka.filters.unsupervised.instance.RemoveWithWeights

the threshold of weight above which to drop instances.

m_DropAtMost - Variable in class weka.filters.unsupervised.instance.WeightsBasedResample

the maximum percentage (0-1) of instances to drop.

m_DropBelow - Variable in class weka.filters.unsupervised.instance.RemoveWithWeights

the threshold of weight below which to drop instances.

m_DropBelow - Variable in class weka.filters.unsupervised.instance.WeightsBasedResample

the threshold of weight below which to drop instances.

m_DropNonClassYs - Variable in class weka.filters.supervised.attribute.MultiPLS

whether to keep Ys that are not the class or not.

m_Editor - Variable in class adams.gui.goe.WekaGenericArrayEditorDialog

the underlying editor.

m_Editor - Variable in class adams.gui.goe.WekaGenericObjectEditorDialog

the underlying editor.

m_Editor - Variable in class adams.gui.goe.WekaGenericObjectEditorPanel

the generic object editor.

m_Eigenvalues - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Eigenvalues for the corresponding eigenvectors.

m_Eigenvectors - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Will hold the unordered linear transformations of the (normalized) original data.

m_EliminateColinearAttributes - Variable in class weka.classifiers.functions.LinearRegressionJ

Try to eliminate correlated attributes?

m_Encoding - Variable in class adams.data.io.input.NestedAdamsExperimentReader

the encoding to use.

m_Encoding - Variable in class weka.core.converters.SimpleArffLoader

the encoding to use.

m_Encoding - Variable in class weka.core.converters.SimpleArffSaver

the encoding to use.

m_Ensemble - Variable in class weka.classifiers.meta.VotedImbalance

the vote classifier in use.

m_EnsureEqualValues - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Whether to check attributes with multiple sources for equal values among those sources.

m_ErrorCalculation - Variable in class adams.flow.transformer.WekaBootstrapping

the error calculation.

m_ErrorScaler - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator

the scaler scheme to use.

m_ErrorScaler - Variable in class adams.flow.sink.WekaClassifierErrors

The scheme for scaling the errors.

m_errPct - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_errPct - Variable in class weka.classifiers.meta.LeastMedianSq

m_Eta - Variable in class weka.classifiers.trees.XGBoost

The eta value (learning rate).

m_EvalCombo - Variable in class weka.gui.explorer.ExperimentPanel

The type of evaluation: cross-validation or random split.

m_Evaluation - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator

the underlying Evaluation object.

m_Evaluation - Variable in class adams.flow.transformer.WekaAggregateEvaluations

the current evaluation state.

m_Evaluation - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

the current evaluation.

m_Evaluation - Variable in class adams.flow.transformer.WekaStreamEvaluator

the evaluation to use.

m_Evaluation - Variable in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob

the evaluation object to use.

m_Evaluation - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

the evaluation object to use.

m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

the evaluation object.

m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

the current evaluation.

m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

the current evaluation.

m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

the current evaluation.

m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

the current evaluation.

m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

the evaluation object.

m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

the evaluation object.

m_Evaluation - Variable in class adams.multiprocess.WekaCrossValidationExecution

the (aggregated) evaluation.

m_Evaluation - Variable in class adams.multiprocess.WekaCrossValidationJob

the evaluation.

m_EvaluationError - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

for storing evaluating errors.

m_EvaluationPostProcessor - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the postprocessor for the evaluation.

m_Evaluations - Variable in class adams.multiprocess.WekaCrossValidationExecution

the separate evaluations.

m_EvaluationType - Variable in class adams.flow.sink.WekaExperimentGenerator

the type of evaluation.

m_Evaluator - Variable in class adams.flow.transformer.WekaAttributeSelection

the evaluation.

m_Evaluator - Variable in class adams.flow.transformer.WekaInstanceEvaluator

the evaluator to use.

m_Evaluator - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

the evaluation algorithm.

m_ExactMatch - Variable in class adams.data.conversion.SwapPLS

whether to use an exact match (incl options) or just the class name.

m_ExcludeClass - Variable in class weka.core.AbstractHashableInstance

whether to exclude the class from the hashcode.

m_ExcludedAttributes - Variable in class adams.flow.transformer.WekaInstancesMerge

regular expression for excluding attributes from the datasets.

m_ExcludeWeight - Variable in class weka.core.AbstractHashableInstance

whether to exclude the weight from the hashcode.

m_executionSlots - Variable in class weka.clusterers.SAXKMeans

Number of threads to run

m_executorPool - Variable in class weka.clusterers.SAXKMeans

For parallel execution mode

m_ExecutorPool - Variable in class weka.classifiers.meta.SubsetEnsemble

Pool of threads to train models with

m_ExecutorPool - Variable in class weka.classifiers.meta.VotedImbalance

Pool of threads to train models with

m_Exp - Variable in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

the copy of the experiment.

m_Experiment - Variable in class adams.flow.source.WekaNewExperiment

the experiment.

m_Experiment - Variable in class adams.flow.transformer.WekaExperimentExecution

the current experiment.

m_Experiment - Variable in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog

the current experiment.

m_Experiment - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

the experiment container.

m_Experiment - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

the experiment.

m_Experiment - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

the experiment.

m_ExperimentFile - Variable in class adams.flow.transformer.WekaExperiment

the experiment file.

m_ExperimentIO - Variable in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

the handler for loading/saving experiments.

m_ExperimentType - Variable in class adams.flow.sink.WekaExperimentGenerator

the type of experiment.

m_Explorer - Variable in class weka.gui.explorer.ExperimentPanel

the parent frame.

m_Explorer - Variable in class weka.gui.explorer.SqlPanel

the parent frame

m_Expression - Variable in class weka.classifiers.functions.MathExpressionClassifier

the expression.

m_failed - Variable in class weka.clusterers.SAXKMeans

m_Failed - Variable in class weka.classifiers.meta.SubsetEnsemble

The number of classifiers that experienced a failure of some sort during construction.

m_Failed - Variable in class weka.classifiers.meta.VotedImbalance

The number of classifiers that experienced a failure of some sort during construction.

m_Fallback - Variable in class weka.classifiers.meta.Fallback

the fallback classifier.

m_FallBack - Variable in class weka.classifiers.functions.GPD

the fallback model.

m_FastDistanceCalc - Variable in class weka.clusterers.SAXKMeans

whether to use fast calculation of distances (using a cut-off).

m_FavorZeroes - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

whether to favor 0s instead of 1s.

m_FeatureSelector - Variable in class weka.classifiers.trees.XGBoost

Feature selection and ordering method.

m_ff - Variable in class adams.opt.optimise.GeneticAlgorithm.GAJob

fitness function.

m_Fields - Variable in class adams.data.conversion.ReportToWekaInstance

the fields to turn into an instance.

m_FileChooser - Variable in class adams.gui.chooser.DatasetFileChooserPanel

the filechooser for selecting the dataset.

m_FileChooser - Variable in class adams.gui.menu.BoundaryVisualizer

filechooser for BoundaryVisualizers.

m_FileChooser - Variable in class adams.gui.menu.CostCurve

filechooser for ROCs.

m_FileChooser - Variable in class adams.gui.menu.GraphVisualizer

filechooser for GraphVisualizers.

m_FileChooser - Variable in class adams.gui.menu.InstancesPlot

filechooser for Plots.

m_FileChooser - Variable in class adams.gui.menu.MarginCurve

filechooser for ROCs.

m_FileChooser - Variable in class adams.gui.menu.ROC

filechooser for ROCs.

m_FileChooser - Variable in class adams.gui.menu.TreeVisualizer

filechooser for TreeVisualizers.

m_FileChooser - Variable in class adams.gui.tools.DatasetCompatibilityPanel

the filechooser for selecting the datasets.

m_FileChooser - Variable in class adams.gui.tools.wekainvestigator.datatable.action.Save

the file chooser for exporting.

m_FileChooser - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the filechooser for datasets.

m_FileChooser - Variable in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu

the filechooser.

m_FileChooser - Variable in class adams.gui.tools.wekainvestigator.source.SpreadSheet

the filechooser.

m_FileChooser - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel

the filechooser for saving the output.

m_FileChooser - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

the filechooser for saving the output.

m_FileChooser - Variable in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO

the filechooser for experiments.

m_FileChooser - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

the file chooser for selecting files.

m_FileChooser - Variable in class adams.gui.visualization.instance.InstancePanel

the file chooser for saving a specific sequence.

m_FileChooser - Variable in class adams.gui.visualization.instances.InstancesTable

the filechooser for exporting data.

m_FileChooser - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage

the filechooser for loading/saving properties.

m_FileChooser - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

the filechooser for selecting the files.

m_FileChooser - Variable in class weka.gui.explorer.ExplorerExt

The file chooser for selecting data files

m_FileChooserIDs - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the file saver for storing the IDs.

m_FileChooserParameters - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

the file chooser.

m_FileChooserResults - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the filechooser for loading/saving results.

m_FileChooserTitle - Variable in class adams.flow.source.WekaSelectDataset

the title of the file chooser dialog.

m_FilePanel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

for selecting the dataset file.

m_FileSerialize - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the file to serialize the trained filter to.

m_Filter - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

for centering the data

m_Filter - Variable in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS

for centering the data

m_Filter - Variable in class adams.data.spreadsheet.filter.WekaFilter

the filter to use.

m_Filter - Variable in class adams.data.weka.rowfinder.FilteredIQR

the IQR filter.

m_Filter - Variable in class adams.flow.transformer.WekaFilter.BatchFilterJob

the filter to use.

m_Filter - Variable in class adams.flow.transformer.WekaFilter

the filter to apply.

m_Filter - Variable in class adams.flow.transformer.WekaInstanceEvaluator

the filter that is used for generating the new data format.

m_Filter - Variable in class adams.flow.transformer.WekaStreamFilter

the filter to apply.

m_Filter - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

The filter used to standardize/normalize all values.

m_Filter - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

The filter used to standardize/normalize all values.

m_Filter - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

The filter used to standardize/normalize all values.

m_Filter - Variable in class weka.classifiers.functions.GPD

The filter used to standardize/normalize all values.

m_Filter - Variable in class weka.classifiers.functions.PLSClassifierWeighted

the PLS filter

m_Filter - Variable in class weka.classifiers.functions.PLSWeighted

the actual filter to use

m_Filter - Variable in class weka.core.neighboursearch.FilteredSearch

The filter

m_Filter - Variable in class weka.filters.unsupervised.attribute.FastWavelet

an optional filter for preprocessing of the data.

m_filtered - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter

m_FilteredData - Variable in class adams.flow.transformer.WekaFilter.BatchFilterJob

the filtered data.

m_Filters - Variable in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

The filters.

m_Filters - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

The filters.

m_FilterSearch - Variable in class weka.classifiers.lazy.LWLSynchroSplit

the filter to apply to the search data.

m_FilterTrain - Variable in class weka.classifiers.lazy.LWLSynchroSplit

the filter to apply to the neighborhood data before training the base classifier.

m_filterType - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

Whether to normalize/standardize/neither

m_filterType - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

Whether to normalize/standardize/neither

m_filterType - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

Whether to normalize/standardize/neither

m_filterType - Variable in class weka.classifiers.functions.GPD

Whether to normalize/standardize/neither

m_FinalModel - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator

whether to create a final model.

m_Find - Variable in class adams.flow.transformer.WekaRenameRelation

the string to find.

m_Find - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric

the regular expression to use.

m_Finders - Variable in class adams.data.weka.columnfinder.MultiColumnFinder

the column finders to use.

m_Finders - Variable in class adams.data.weka.rowfinder.MultiRowFinder

the row finders to use.

m_First - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis

the positions of the first range.

m_FirstAdd - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

whether this is the first time a dataset gets added.

m_FirstAttribute - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

the name of the first attribute.

m_FirstAttributeRange - Variable in class adams.gui.InstanceCompare

the first attribute range to use.

m_FirstAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the first set of attributes.

m_firstBatchFinished - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Have we processed the first batch (i.e.

m_firstBatchFinished - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Have we processed the first batch (i.e.

m_FirstData - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the first dataset.

m_FirstFile - Variable in class adams.gui.InstanceCompare

the first file to compare.

m_FirstRange - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis

the first range of the attributes to use.

m_FirstRowIndex - Variable in class adams.gui.InstanceCompare

the index of the first attribute to use for matching rows.

m_fitness - Variable in class adams.opt.optimise.GeneticAlgorithm.GAJob

m_Fitness - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

the fitness of the genes.

m_fitnessfn - Variable in class adams.opt.optimise.GeneticAlgorithm

m_FlowContext - Variable in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction

the flow context.

m_FlowContext - Variable in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction

the flow context.

m_FlowContext - Variable in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction

the flow context.

m_FlowContext - Variable in class adams.multiprocess.WekaCrossValidationExecution

the flow context.

m_FlowContext - Variable in class adams.multiprocess.WekaCrossValidationJob

the flow context.

m_FlowContext - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the flow context.

m_FlowContext - Variable in class weka.classifiers.functions.PyroProxy

the flow context.

m_FlowContextUpdated - Variable in class adams.flow.transformer.WekaFilter

whether the flow context has been updated.

m_FlowFile - Variable in class weka.filters.FlowFilter

the flow file to process the data with.

m_fm - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Fontmetrics used to get the font size which is required for calculating displayable area size, bar height ratio and width of strings that are displayed on top of bars indicating their count.

m_Fold - Variable in class adams.multiprocess.WekaCrossValidationJob

the fold.

m_FoldEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

the evaluation objects from the folds.

m_FoldModels - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

the fold models.

m_FoldPairs - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

the temporary pairs.

m_FoldPairs - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator

the temporary pairs.

m_FoldPairs - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

the temporary pairs.

m_FoldPairs - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

the temporary pairs.

m_FoldPairs - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

the temporary pairs.

m_Folds - Variable in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

the number of folds for cross-validation.

m_Folds - Variable in class adams.flow.sink.WekaExperimentGenerator

the number of folds to use (only cross-validation).

m_Folds - Variable in class adams.flow.transformer.WekaAttributeSelection

the number of folds.

m_Folds - Variable in class adams.flow.transformer.WekaClassifierRanker

the number of folds to use in cross-validation.

m_Folds - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

the number of folds to use.

m_Folds - Variable in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

the number of folds.

m_Folds - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator

the number of folds.

m_Folds - Variable in class adams.flow.transformer.WekaCrossValidationSplit

the number of folds to generate.

m_Folds - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

the number of folds.

m_Folds - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

the number of folds (in case of cross-validation).

m_Folds - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

the number of folds.

m_Folds - Variable in class adams.multiprocess.WekaCrossValidationExecution

the number of folds.

m_Folds - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

the cross-validation folds.

m_Folds - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the number of folds for cross-validation.

m_Folds - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

the number of folds for cross-validation.

m_FoldsPercLabel - Variable in class weka.gui.explorer.ExperimentPanel

The label for either the number of folds or the percentage for the random split.

m_FoldsPercText - Variable in class weka.gui.explorer.ExperimentPanel

Either the number of folds or the percentage for the random split.

m_ForceCompression - Variable in class weka.core.converters.SimpleArffLoader

whether to force compression.

m_Format - Variable in class weka.filters.unsupervised.attribute.StringToDate

the parse format.

m_Formatter - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the formatter for the history entries.

m_fstat - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

F-statistic for the regression

m_Full - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

the full dataset.

m_FullFilter - Variable in class adams.data.weka.rowfinder.FilteredIQR

the MultiFilter doing all the filtering.

m_FullMeansOrMediansOrModes - Variable in class weka.clusterers.SAXKMeans

Stats on the full data set for comparison purposes.

m_FullMissingCounts - Variable in class weka.clusterers.SAXKMeans

m_FullNominalCounts - Variable in class weka.clusterers.SAXKMeans

m_FullStdDevs - Variable in class weka.clusterers.SAXKMeans

m_ga - Variable in class adams.opt.optimise.GeneticAlgorithm.GAJob

ga.

m_gamma - Variable in class weka.classifiers.functions.GPD

m_Gamma - Variable in class weka.classifiers.trees.XGBoost

The gamma value (minimum split loss).

m_Generated - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

the results generated by the evaluations.

m_Generated - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

whether the split was generated.

m_Generated - Variable in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

whether the split was generated.

m_Generated - Variable in class weka.classifiers.DefaultRandomSplitGenerator

whether the split was generated.

m_Generated - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

whether the split was generated.

m_Generated - Variable in class weka.classifiers.GroupedRandomSplitGenerator

whether the split was generated.

m_GenerateLine - Variable in class adams.data.baseline.AbstractLinearRegressionBased

whether to return the line as fake data or the corrected data.

m_Generator - Variable in class adams.flow.source.AbstractWekaSetupGenerator

the underlying setup generator.

m_Generator - Variable in class adams.flow.transformer.AbstractInstanceGenerator

the generator to use.

m_Generator - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator

the fold generator.

m_Generator - Variable in class adams.flow.transformer.WekaCrossValidationSplit

the fold generator.

m_Generator - Variable in class adams.flow.transformer.WekaEnsembleGenerator

the generator to use.

m_Generator - Variable in class adams.flow.transformer.WekaRandomSplit

the split generator to use.

m_Generator - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

the fold generator.

m_Generator - Variable in class adams.flow.transformer.WekaSplitGenerator

the split generator to use.

m_Generator - Variable in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer

the generator used to load the data.

m_Generator - Variable in class adams.gui.tools.wekainvestigator.source.DataGenerator

the last filechooser.

m_Generator - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

the fold generator.

m_Generator - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

the split generator to use.

m_Generator - Variable in class adams.multiprocess.WekaCrossValidationExecution

the cross-validation fold generator.

m_Generator - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the fold generator.

m_Generator - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator

the underlying scheme for generating the folds.

m_Generator - Variable in class weka.classifiers.DefaultRandomSplitGenerator

the underlying scheme for generating the split.

m_Generator - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

the underlying scheme for generating the folds.

m_Generator - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

the underlying scheme for generating the folds.

m_Generator - Variable in class weka.classifiers.GroupedRandomSplitGenerator

the underlying scheme for generating the split.

m_Genes - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

the genes.

m_GlobalSource - Variable in class adams.flow.transformer.WekaInstanceEvaluator

the callable actor to use.

m_Glue - Variable in class weka.filters.unsupervised.attribute.JoinAttributes

the glue to use for joining the attributes.

m_GOEFinalModel - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

how to produce the final model.

m_GOEGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

the fold generator.

m_GOEGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

the fold generator.

m_GOEGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

the split generator.

m_GOEGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

the fold generator.

m_GOEGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

the split generator.

m_GOEJobRunner - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

the jobrunner.

m_GOEJobRunner - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

the jobrunner.

m_GOEJobRunner - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

the jobrunner.

m_GOEJobRunner - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

the jobrunner.

m_Grid - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

the size of the grid.

m_Group - Variable in class adams.data.binning.BinnableInstances.StringAttributeGroupExtractor

the group to extract.

m_Group - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

the group expression.

m_Group - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

the group expression.

m_Group - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

the group expression.

m_Group - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

the group expression.

m_Group - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

the group expression.

m_Group - Variable in class weka.classifiers.GroupedRandomSplitGenerator

the group expression.

m_Group - Variable in class weka.core.InstanceGrouping

the replacement string, using the groups from the regexp.

m_Group - Variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

the group expression.

m_Groups - Variable in class weka.classifiers.MultiLevelSplitGenerator

the groups to generate.

m_Groups - Variable in class weka.core.InstanceGrouping

the groups.

m_GrowPolicy - Variable in class weka.classifiers.trees.XGBoost

Controls the way new nodes are added to the tree.

m_Handler - Variable in class adams.flow.sink.WekaExperimentFileWriter

the IO handler.

m_Handler - Variable in class adams.flow.transformer.WekaExperimentFileReader

the IO handler.

m_Handlers - Variable in class adams.opt.genetic.Hermione

the handlers to use for discovery.

m_HasClass - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Data has a class set.

m_HashCode - Variable in class weka.core.AbstractHashableInstance

the current hashcode.

m_Hashed - Variable in class weka.filters.unsupervised.attribute.JoinAttributes

the hashed indices.

m_Header - Variable in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader

the header to load from disk.

m_Header - Variable in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader

the header to load from storage.

m_Header - Variable in class adams.data.conversion.ReportToWekaInstance

the header to use.

m_Header - Variable in class adams.flow.transformer.WekaInstanceDumper

the header of the dataset.

m_Header - Variable in class adams.flow.transformer.WekaInstanceEvaluator

the new header.

m_Header - Variable in class adams.flow.transformer.WekaStreamEvaluator

the current header.

m_Header - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

the header.

m_Header - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

the training header (if any).

m_Header - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

the training header (if any).

m_Header - Variable in class adams.ml.data.InstancesView

the header row.

m_Header - Variable in class weka.classifiers.functions.ClassificationViaPLS

the header of the training set.

m_Header - Variable in class weka.classifiers.meta.PeakTransformed

the header information of the transformed data.

m_Header - Variable in class weka.classifiers.meta.RangeCheck

the training header.

m_Header - Variable in class weka.classifiers.meta.SubsetEnsemble

The header of the training set.

m_Header - Variable in class weka.classifiers.meta.SumTransformed

the header information of the transformed data.

m_Header - Variable in class weka.classifiers.meta.VotedImbalance

The header of the training set.

m_Header - Variable in class weka.classifiers.trees.XGBoost

the training dataset.

m_HeaderPopupMenuCustomizer - Variable in class adams.gui.visualization.instances.InstancesTable

the customizer for the table header popup menu.

m_Helper - Variable in class adams.flow.source.WekaSelectDataset

the helper class.

m_Helper - Variable in class adams.flow.transformer.WekaClassifierRanker

the helper class.

m_Helper - Variable in class adams.flow.transformer.WekaGeneticAlgorithm

the helper class.

m_hiClassifier - Variable in class weka.classifiers.meta.HighLowSplit

m_hiLopoint - Variable in class weka.classifiers.meta.HighLowSplit

m_histBarClassCounts - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

This array holds the per class count (or per class height) of the each of the bars in a barplot or a histogram.

m_histBarCounts - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

This array holds the count (or height) for the each of the bars in a barplot or a histogram.

m_HistogramOptions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Options for the histogram

m_HistogramSetup - Variable in class adams.gui.visualization.instance.InstanceExplorer

the dialog for the histogram setup.

m_HistogramSetup - Variable in class adams.gui.visualization.instance.InstancePanel

the dialog for the histogram setup.

m_History - Variable in class adams.gui.goe.WekaGenericObjectEditorPanel

the history of used setups.

m_History - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the history.

m_History - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the history.

m_History - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the history.

m_History - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the history.

m_History - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the history.

m_History - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the history.

m_History - Variable in class weka.gui.explorer.ExperimentPanel

A panel controlling results viewing.

m_History - Variable in class weka.gui.explorer.MultiExplorer

the history panel.

m_HoldOutPercentage - Variable in class weka.classifiers.meta.ClassifierCascade

the percentage to use for validation set to determine termination criterion (0-100).

m_ICA - Variable in class adams.data.instancesanalysis.FastICA

the Fast ICA analysis to use.

m_ID - Variable in class adams.flow.sink.WekaInstanceViewer

the name of the attribute/field to use as ID.

m_ID - Variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

the ID of the container.

m_ID - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

the ID to use for the returned instances.

m_ID - Variable in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

the attribute with the IDs.

m_ID - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances

the attribute to use for identifying instances.

m_IDCounter - Static variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

the ID counter.

m_IDSplitter - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Column-splitter for separating the ID column.

m_IDTest - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances

the attribute to use for identifying instances in the test set.

m_IgnoreChanges - Variable in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

whether to ignored changes.

m_IgnoreChanges - Variable in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

whether to ignored changes.

m_IgnoreChanges - Variable in class adams.gui.visualization.instances.InstancesTableModel

whether to ignore changes, i.e.

m_IgnoreClass - Variable in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

whether to ignore the class attribute.

m_IgnoredAttributes - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

the regular expression for attributes to skip.

m_IncludeClass - Variable in class weka.filters.unsupervised.instance.RemoveDuplicates

whether to take the class into account.

m_IncludeClass - Variable in class weka.filters.unsupervised.instance.Sort

whether to take the class into account.

m_Incorrect - Variable in class weka.filters.unsupervised.attribute.SpellChecker

the (misspelled) labels of the attribute to replace.

m_IncorrectCache - Variable in class weka.filters.unsupervised.attribute.SpellChecker

the hashset with the incorret labels (for faster access).

m_Incremental - Variable in class adams.flow.source.WekaDatabaseReader

whether to output the data row-by-row.

m_IncrementalClassifier - Variable in class adams.flow.transformer.WekaTrainClassifier

the classifier to use when training incrementally.

m_IncrementalClusterer - Variable in class adams.flow.transformer.WekaTrainClusterer

the clusterer used when training incrementally.

m_Index - Variable in class adams.data.binning.BinnableInstances.StringAttributeGroupExtractor

the attribute index.

m_Index - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer

the distribution index (0-based).

m_Index - Variable in class adams.data.io.input.InstanceReader

the current index.

m_Index - Variable in class adams.data.weka.classattribute.AttributeIndex

the attribute index.

m_Index - Variable in class adams.data.weka.relationname.AttributeIndex

the attribute index.

m_Index - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

the index to use for grouping.

m_Index - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

the index to use for grouping.

m_Index - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

the index in actor's input array.

m_Index - Variable in class adams.flow.transformer.WekaExtractArray

the index of the row/column to extract.

m_Index - Variable in class adams.flow.transformer.WekaGetInstanceValue

the index of the attribute to get the value from the Instance.

m_Index - Variable in class adams.flow.transformer.WekaSetInstanceValue

the attribute index to set in the Instance.

m_Index - Variable in class adams.flow.transformer.WekaSubsets

the attribute index to split on.

m_Index - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

the current attribute index.

m_Index - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

the index.

m_Index - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

the index to use for grouping.

m_Index - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

the index to use for grouping.

m_Index - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

the index to use for grouping.

m_Index - Variable in class weka.classifiers.GroupedRandomSplitGenerator

the index to use for grouping.

m_Index - Variable in class weka.classifiers.LeaveOneOutByValueGenerator

the index to get the unique values from.

m_Index - Variable in class weka.core.InstanceGrouping

the attribute index.

m_Index - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric

the attribute to convert.

m_Index - Variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

the index to use for grouping.

m_Index - Variable in class weka.filters.unsupervised.instance.RemoveWithLabels

the attribute to remove the labels from.

m_Indexer - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

the currently loaded dataset.

m_IndexOfID - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter

m_Indices - Variable in class adams.data.instances.InstanceComparator

the column indices to use in the comparison.

m_Indices - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the selected indices.

m_Indices - Variable in class weka.classifiers.MultiLevelSplitGenerator

the attribute indices.

m_Indices - Variable in class weka.filters.unsupervised.attribute.AnyToString

the attribute indices to work on.

m_Indices - Variable in class weka.filters.unsupervised.attribute.CorrelationMatrix

the attribute indices to use.

m_Indices - Variable in class weka.filters.unsupervised.attribute.InputSmearing

the indices to work on.

m_Indices - Variable in class weka.filters.unsupervised.attribute.JoinAttributes

the indices to work on.

m_Indices - Variable in class weka.filters.unsupervised.attribute.StringToDate

the attribute indices to work on.

m_Indices1 - Variable in class adams.tools.CompareDatasets

the indices for the first dataset.

m_Indices2 - Variable in class adams.tools.CompareDatasets

the indices for the second dataset.

m_IndicesUnused - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

the indices of the unused attributes.

m_InfoPanel - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

the info panel.

m_init - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

initialised?

m_InitialDirectory - Variable in class adams.flow.source.WekaSelectDataset

the initial directory.

m_InitialFiles - Variable in class adams.flow.source.WekaSelectDataset

the initial files to use.

m_initializationMethod - Variable in class weka.clusterers.SAXKMeans

The initialization method to use

m_Initialized - Variable in class adams.data.instancesanalysis.pls.AbstractPLS

whether the scheme has been initialized.

m_Initialized - Variable in class adams.data.weka.evaluator.AbstractInstanceEvaluator

whether the evaluator got initialized.

m_Initialized - Variable in class adams.flow.transformer.WekaFilter

whether the filter has been initialized.

m_Initialized - Variable in class adams.flow.transformer.WekaStreamFilter

whether the filter has been initialized.

m_Initialized - Variable in class weka.classifiers.AbstractSplitGenerator

whether the iterator has been initialized.

m_InitializeOnce - Variable in class adams.flow.transformer.WekaFilter

whether to initialize filter only with the first batch.

m_InitializeOnce - Variable in class adams.flow.transformer.WekaReorderAttributesToReference

whether to initialize filter only with the first batch.

m_initialStartPoints - Variable in class weka.clusterers.SAXKMeans

Holds the initial start points, as supplied by the initialization method used

m_Instance - Variable in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer

the Instance the container is for.

m_InstanceClass - Variable in class adams.flow.transformer.WekaNewInstance

the class of instance to create.

m_InstancePaintlet - Variable in class adams.gui.visualization.instance.InstancePanel

paintlet for drawing the graph.

m_InstancePanel - Variable in class adams.flow.sink.WekaInstanceViewer

the panel with the instances.

m_instancepct - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_instancepct - Variable in class weka.classifiers.meta.LeastMedianSq

m_InstancePointHitDetector - Variable in class adams.gui.visualization.instance.InstancePanel

the hit detector for the tooltip.

m_Instances - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel

The instances who's attribute structure we are reporting

m_Instances - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

The instances we're playing with

m_Instances - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

The instances we're playing with

m_Instances - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

the underlying data.

m_Instances - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

the underlying data.

m_Instances - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the full dataset.

m_Instances - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the data to use for cross-validation.

m_Instances - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

the data to use for cross-validation.

m_Instances - Variable in class weka.gui.explorer.ExperimentPanel

The main set of instances we're playing with.

m_InstancesActor - Variable in class adams.flow.transformer.WekaInstanceEvaluator

the callable actor to get the Instances from in case of AbstractDatasetInstanceEvaluator.

m_InstancesHeader - Variable in class adams.ml.model.classification.WekaClassificationModel

the instances used.

m_InstancesHeader - Variable in class adams.ml.model.clustering.WekaClusteringModel

the instances used.

m_InstancesHeader - Variable in class adams.ml.model.regression.WekaRegressionModel

the instances used.

m_InstancesSortPanel - Variable in class adams.gui.visualization.instances.instancestable.DataSort

the sort panel.

m_InstancesSortSetupListeners - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

the listeners for changes in the setup.

m_intercept - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

The intercept

m_Interval - Variable in class adams.flow.transformer.WekaInstanceBuffer

the interval of when to output the Instances object.

m_Interval - Variable in class adams.flow.transformer.WekaStreamEvaluator

the interval at which to output the evaluation.

m_Intervals - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval

the intervals.

m_InverseTransform - Variable in class weka.filters.unsupervised.attribute.FastWavelet

whether to perform inverse transformation.

m_InverseTransform - Variable in class weka.filters.unsupervised.attribute.FFT

whether to perform inverse transformation (wavelet -> normal space).

m_Invert - Variable in class adams.flow.condition.bool.AbstractAttributeCapabilities

whether to invert the matching sense.

m_Invert - Variable in class adams.flow.transformer.WekaMultiLabelSplitter

whether to invert the matching sense.

m_Invert - Variable in class adams.flow.transformer.WekaRegexToRange

invert matching?

m_Invert - Variable in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

whether to invert the matching sense.

m_Invert - Variable in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Whether to invert the column indices.

m_Invert - Variable in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Whether to invert the row indices.

m_Invert - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances

whether to invert the matching.

m_Invert - Variable in class weka.filters.unsupervised.instance.RemoveWithLabels

whether to invert the matching.

m_invertMatching - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Whether to invert the match so the correctly classified instances are discarded

m_invertMatching - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Whether to invert the match so the correctly classified instances are discarded

m_InvertMatchingSense - Variable in class adams.flow.transformer.WekaInstancesMerge

whether to invert the matching sense for excluding attributes.

m_InvertSelection - Variable in class weka.filters.unsupervised.instance.KennardStone

whether to invert the selection.

m_InvertSelection - Variable in class weka.filters.unsupervised.instance.SafeRemoveRange

whether to invert the selection.

m_IQR - Variable in class adams.data.weka.rowfinder.FilteredIQR

the maximum value of the attribute.

m_IQRs - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

m_IsPercent - Variable in class weka.classifiers.meta.AbstainAverage

m_IsPercent - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

m_IsPercent - Variable in class weka.classifiers.meta.AbstainVote

m_IsString - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

whether the attribute is numeric or string/nominal.

m_Item - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane

the underlying result item.

m_Iterations - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

number of iterations.

m_Iterations - Variable in class weka.clusterers.SAXKMeans

Keep track of the number of iterations completed before convergence.

m_Iterator - Variable in class adams.flow.transformer.WekaInstanceBuffer

the iterator for broadcasting Instance objects.

m_Job - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the title of the current job.

m_JobCounter - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

the counter for finished jobs.

m_JobRunner - Variable in class adams.flow.transformer.WekaClassifierRanker

the job runner for evaluating the setups.

m_JobRunner - Variable in class adams.flow.transformer.WekaExperimentExecution

the JobRunner template.

m_JobRunner - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

the JobRunner template.

m_JobRunner - Variable in class adams.multiprocess.WekaCrossValidationExecution

the jobrunner template.

m_JobRunner - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the job runner in use.

m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaFilter

the JobRunnerInstance to use.

m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaTestSetEvaluator

the JobRunnerInstance to use.

m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaTrainAssociator

the JobRunnerInstance to use.

m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaTrainClassifier

the JobRunnerInstance to use.

m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaTrainClusterer

the JobRunnerInstance to use.

m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator

the JobRunnerInstance to use.

m_JobRunnerSetup - Variable in class adams.flow.transformer.WekaClassifierRanker

the jobrunner setup.

m_JobRunnerSetup - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator

the jobrunner setup.

m_JobRunnerSetup - Variable in class adams.flow.transformer.WekaGeneticAlgorithm

the jobrunner setup.

m_JobRunnerSetup - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

the jobrunner setup.

m_JobRunnerSetup - Variable in class adams.multiprocess.WekaCrossValidationExecution

the jobrunner setup.

m_JobRunnerSetup - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the jobrunner setup.

m_JobTotal - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

the total number of jobs.

m_k - Variable in class weka.classifiers.meta.Corr

m_KeepAttributeNames - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay

whether to keep the original attribute names.

m_KeepAttributeNames - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay2

whether to keep the original attribute names.

m_KeepExisting - Variable in class adams.flow.transformer.WekaInstanceDumper

whether to keep existing output files when actor is called for the first time, in order to allow appending to files from multiple locations in flow.

m_KeepNumComponents - Variable in class adams.data.conversion.SwapPLS

whether to migrate the number of components.

m_KeepOnlySingleUniqueID - Variable in class adams.flow.transformer.WekaInstancesMerge

whether to keep only a single instance of the unique ID attribute.

m_KeepRelationName - Variable in class adams.flow.transformer.WekaFilter

whether to keep the incoming relation name.

m_KeepRelationName - Variable in class adams.flow.transformer.WekaReorderAttributesToReference

whether to keep the incoming relation name.

m_KeepRelationName - Variable in class adams.flow.transformer.WekaStreamFilter

whether to keep the incoming relation name.

m_KeepSupervisedClass - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Whether to keep the supervised filter class or discard it.

m_Kept - Variable in class adams.data.instancesanalysis.PCA

the indices of the kept attributes.

m_kernel - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

Kernel to use *

m_kernel - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

Kernel to use *

m_kernel - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

Kernel to use

m_Kernel - Variable in class adams.data.instancesanalysis.pls.KernelPLS

the kernel to use.

m_KernelIsLinear - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

whether the kernel is a linear one

m_KernelIsLinear - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

whether the kernel is a linear one

m_KernelPLS - Variable in class adams.data.instancesanalysis.pls.KernelPLS

the actual algorithm.

m_Keys - Variable in class adams.flow.source.WekaDatabaseReader

the keys that uniquely identify a single row.

m_kNN - Variable in class weka.classifiers.lazy.LWLDatasetBuilder

The number of neighbours used to select the kernel bandwidth.

m_kNN - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

The number of neighbours used to select the kernel bandwidth.

m_L - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

(negative) covariance matrix in symmetric matrix representation

m_L - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

(negative) covariance matrix in symmetric matrix representation

m_Label - Variable in class weka.classifiers.meta.ThresholdedBinaryClassification

the label to check.

m_Label - Variable in class weka.classifiers.meta.Veto

the label to check.

m_LabelAttributeRange - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

the label for the range.

m_LabelIndex - Variable in class adams.flow.transformer.WekaInstancesInfo

the index of the label.

m_LabelIndex - Variable in class weka.classifiers.functions.ClassificationViaPLS

The label index to get the PLS matrices for.

m_LabelMapping - Variable in class weka.filters.unsupervised.instance.RemoveWithLabels

the label mapping (old -> new).

m_LabelMatch - Variable in class weka.filters.unsupervised.instance.DatasetLabeler

the label to use for a match.

m_LabelNonMatch - Variable in class weka.filters.unsupervised.instance.DatasetLabeler

the label to use for a nonmatch.

m_LabelQuery - Variable in class weka.gui.explorer.SqlPanel

displays the current query

m_LabelRegExp - Variable in class weka.filters.unsupervised.instance.RemoveWithLabels

the regular expression for matching the labels to remove.

m_LabelRowAttribute - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

the label for the attribute names.

m_LabelRows - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the label for the combobox.

m_LabelString - Variable in class weka.classifiers.functions.ClassificationViaPLS

the label string to get the PLS matrices for (overrides the label index).

m_LabelTextNumPoints - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the number of data points.

m_Lambda - Variable in class adams.data.instancesanalysis.pls.DIPLS

lambda

m_Lambda - Variable in class adams.data.instancesanalysis.pls.SparsePLS

Sparsity parameter.

m_Lambda - Variable in class adams.data.instancesanalysis.pls.VCPLS

the lambda value.

m_Lambda - Variable in class weka.classifiers.trees.XGBoost

L2 regularisation term on weights.

m_LastAttributesToVisualize - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the last indices that were visualized.

m_LastBias - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset

the last bias used.

m_LastBoxPlot - Variable in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab

the last boxplot.

m_LastError - Variable in class weka.classifiers.AggregateEvaluations

the last error.

m_LastExport - Variable in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane

the last export scheme.

m_LastLimit - Variable in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer

the last limit.

m_LastNotificationTime - Variable in class adams.opt.optimise.GeneticAlgorithm

the timestamp the last notification got sent.

m_LastPercentage - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset

the last percentage used.

m_LastReader - Variable in class adams.gui.tools.wekainvestigator.source.Clipboard

the last spreadsheet reader used.

m_LastReplacement - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset

whether replacement was used.

m_LastSeed - Variable in class adams.gui.tools.wekainvestigator.datatable.action.Randomize

the last seed.

m_LastSeed - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset

the last seed used.

m_LastSetup - Variable in class adams.gui.tools.wekainvestigator.datatable.action.Merge

the last merge setup.

m_LastSetup - Variable in class adams.gui.visualization.instances.InstancesTable

for keeping track of the setups being used (classname-{plot|process}-{column|row} - setup).

m_LastSourceID - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RemoveTestSet

the last used source ID attribute.

m_LastSplitter - Variable in class adams.gui.tools.wekainvestigator.datatable.action.Split

the last splitter.

m_LastSupervised - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset

whether supervised version was used.

m_LastTable - Variable in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer

the last setup.

m_LastTestSetID - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RemoveTestSet

the last used test set ID attribute.

m_LastUpdated - Variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

the timestamp the data was last updated.

m_Layout - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

the gridlayout in use.

m_left - Variable in class weka.classifiers.trees.m5.RuleNode2

left child node

m_Lenient - Variable in class adams.flow.transformer.WekaReorderAttributesToReference

whether to tolerate attributes that are not present in the incoming data.

m_Less - Variable in class weka.classifiers.trees.RandomRegressionForest.Node

m_Limit - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

the limit type.

m_LinearReg - Variable in class weka.classifiers.trees.RandomRegressionForest.Node

m_List - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

for listing the classifiers.

m_List - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

for listing the files.

m_ListAdditionalAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the list of additional attribute values to store in the report.

m_ListAdditionalAttributesModel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the model for the additional attributes.

m_ListCommonIDs - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the JList with the common IDs.

m_Listeners - Variable in class adams.gui.visualization.instances.InstancesTableModel

the listeners

m_ListFiles - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

the list for the file names.

m_ListIDs - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the list with instance IDs to display.

m_ListRows - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the JLiast with the rows.

m_ListRowsModel - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the model for the combobox with the rows.

m_ListType - Variable in class adams.flow.source.wekapackagemanageraction.ListPackages

the type of list to generate.

m_Loader - Variable in class adams.data.io.input.AbstractWekaSpreadSheetReader

the file loader to use.

m_Loader - Variable in class adams.gui.chooser.DatasetFileChooserPanel

the current loader.

m_Loader - Variable in class adams.gui.tools.wekainvestigator.data.FileContainer

the reader used to load the data.

m_Loader - Variable in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer

the generator used to load the data.

m_Loader - Variable in class adams.gui.tools.wekainvestigator.source.TextDirectory

the last config.

m_LoadFromDatabaseDialog - Variable in class adams.gui.visualization.instance.InstanceExplorer

the SQL viewer dialog.

m_LoadFromDiskDialog - Variable in class adams.gui.visualization.instance.InstanceExplorer

the dialog for loading datasets.

m_Loadings - Variable in class adams.data.instancesanalysis.PCA

the loadings.

m_Loadings - Variable in class adams.data.instancesanalysis.PLS

the loadings.

m_LoadingsCalculations - Variable in class weka.attributeSelection.AbstractPLSAttributeEval

for how to use the loadings.

m_Local - Variable in class weka.classifiers.meta.SocketFacade

the return address for the remote process to use.

m_Locations - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges

the array of indices/regular expressions.

m_Locations - Variable in class adams.flow.transformer.WekaInstancesStatistic

the array of indices/regular expressions.

m_locker - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Lock variable to synchronize the different threads running currently in this class.

m_loClassifier - Variable in class weka.classifiers.meta.HighLowSplit

m_loClassifier - Variable in class weka.classifiers.meta.HighLowSplitSingleClassifier

m_Log - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the log.

m_Log - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

the log.

m_Log - Variable in class weka.gui.explorer.ExperimentPanel

The destination for log/status messages.

m_Log - Variable in class weka.gui.explorer.SqlPanel

The destination for log/status messages

m_LogPanel - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

the log component.

m_LogPanel - Variable in class adams.gui.tools.wekainvestigator.tab.LogTab

the log panel.

m_loHipoint - Variable in class weka.classifiers.meta.HighLowSplit

m_loHipoint - Variable in class weka.classifiers.meta.HighLowSplitSingleClassifier

m_Lookup2 - Variable in class adams.tools.CompareDatasets

the lookup table of indices for the second dataset.

m_Lower - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

the lower value to compute.

m_Lower - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

the lower value to compute.

m_Lower - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

the lower value to compute.

m_Lower - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

the lower value to compute.

m_LR - Variable in class weka.core.WeightedEuclideanDistance

m_LR - Variable in class weka.core.WeightedEuclideanDistanceRidge

m_MainFilter - Variable in class weka.filters.FilteredFilter

The main filter to apply to the data.

m_MakeClassLast - Variable in class adams.flow.transformer.WekaMultiLabelSplitter

whether to move the class attribute to the end.

m_MakeThreadSafe - Variable in class adams.flow.transformer.WekaModelReader

whether to wrap the model in a threadsafe wrapper.

m_Manual - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

for generating class distributions.

m_ManualClassifier - Variable in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

a programmatically supplied classifier.

m_ManualClassifier - Variable in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

a programmatically supplied classifier.

m_ManualMax - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges

the manual maximum.

m_ManualMin - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges

the manual minimum.

m_Mapping - Variable in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

the mapping between fusion subset names and attribute indices.

m_Mapping - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric

the mapping between label and new value.

m_MarkerExtent - Variable in class adams.gui.visualization.instance.InstanceLinePaintlet

the maximum width/height of the shape to plot around the points (= data point marker), if there's enough space.

m_MarkersEnabled - Variable in class adams.gui.visualization.instance.InstanceLinePaintlet

indicates whether marker shapes are painted or not.

m_Matrix - Variable in class adams.flow.transformer.WekaGenericPLSMatrixAccess

the name of the matrix to extract.

m_Matrix - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel

the underlying matrix.

m_MatrixNames - Variable in class weka.filters.supervised.attribute.MultiPLS

the matrix names.

m_MatrixType - Variable in class adams.flow.transformer.WekaExtractPLSMatrix

the matrix type to extract.

m_MatrixValues - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

what values to generate.

m_max - Variable in class adams.opt.optimise.genetic.PackDataDef.DataInfo

m_max - Variable in class weka.classifiers.meta.AbstainAttributePercentile

m_max - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_max - Variable in class weka.classifiers.trees.RandomModelTrees

m_Max - Variable in class adams.flow.transformer.WekaClassifierRanker

the maximum number of top-ranked classifiers to forward.

m_Max - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

m_Max - Variable in class weka.filters.unsupervised.instance.Scale

the maximum to use.

m_MaxActual - Variable in class weka.classifiers.meta.MinMaxLimits

the actual limit to use for the upper limit.

m_MaxAttributeNames - Variable in class adams.data.instancesanalysis.PCA

the maximum number of attribute names.

m_MaxAttributeNames - Variable in class adams.flow.transformer.WekaPrincipalComponents

the maximum number of attribute names to use.

m_MaxAttributes - Variable in class adams.data.instancesanalysis.PCA

the maximum number of attributes.

m_MaxAttributes - Variable in class adams.flow.transformer.WekaPrincipalComponents

the maximum number of attributes to keep.

m_MaxAttributes - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

maximum number of attributes in the transformed data (-1 for all).

m_MaxAttributesToVisualize - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the maximum number of attributes to visualize (summary table/histogram).

m_MaxAttrsInName - Variable in class weka.core.neighboursearch.PCANNSearch

maximum number of attributes in the transformed attribute name.

m_MaxAttrsInName - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

maximum number of attributes in the transformed attribute name.

m_MaxBin - Variable in class weka.classifiers.trees.XGBoost

Maximum number of discrete bins to bucket continuous features.

m_maxCanopyCandidates - Variable in class weka.clusterers.SAXKMeans

The maximum number of candidate canopies to hold in memory at any one time (if using canopy clustering)

m_MaxClassRangePercentage - Variable in class weka.classifiers.meta.MinMaxLimits

the percentage leeway for the class range of the upper limit (0-1 = 0-100%).

m_MaxColWidth - Variable in class adams.gui.tools.wekainvestigator.tab.DataTab

the default max column width.

m_MaxColWidth - Variable in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

the default max column width.

m_MaxDecimalPlaces - Variable in class weka.core.converters.SimpleArffSaver

Max number of decimal places for numeric values

m_MaxDeltaStep - Variable in class weka.classifiers.trees.XGBoost

Maximum delta step.

m_MaxDepth - Variable in class weka.classifiers.trees.XGBoost

The maximum depth of the tree.

m_MaxDifference - Variable in class weka.classifiers.meta.AbstainAverage

m_MaxDifference - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

m_MaxDifference - Variable in class weka.classifiers.meta.AbstainVote

m_MaxDifferences - Variable in class weka.classifiers.meta.AbstainAverage

m_MaxDifferences - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

m_MaxDifferences - Variable in class weka.classifiers.meta.AbstainVote

m_MaxDifferences_string - Variable in class weka.classifiers.meta.AbstainAverage

m_MaxDifferences_string - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

m_MaxDifferences_string - Variable in class weka.classifiers.meta.AbstainVote

m_MaxDisplayItems - Variable in class adams.gui.goe.WekaGenericArrayEditorPanel

the maximum number of array items to display via toString().

m_Maxes - Variable in class weka.classifiers.meta.AbstainAverage

m_Maxes - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

m_Maxes - Variable in class weka.classifiers.meta.AbstainVote

m_MaxFactor - Variable in class weka.filters.unsupervised.instance.WeightsBasedResample

the upper limit of the multiplication factor (<= 0 is not capped).

m_MaxHandling - Variable in class weka.classifiers.meta.MinMaxLimits

how the upper limit is handled.

m_Maximum - Variable in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

the maximum.

m_Maximum - Variable in class adams.data.weka.rowfinder.ByNumericValue

the maximum value.

m_Maximum - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

the maximum value.

m_MaximumIncluded - Variable in class adams.data.weka.rowfinder.ByNumericValue

whether the maximum value is included.

m_MaximumIncluded - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

whether the maximum value is included.

m_MaxIter - Variable in class adams.data.instancesanalysis.pls.KernelPLS

Inner NIPALS loop maximum number of iterations

m_MaxIter - Variable in class adams.data.instancesanalysis.pls.NIPALS

Inner NIPALS loop maximum number of iterations

m_MaxIter - Variable in class adams.data.instancesanalysis.pls.PRM

Inner loop maximum number of iterations

m_MaxIter - Variable in class adams.data.instancesanalysis.pls.SparsePLS

Inner NIPALS loop maximum number of iterations

m_MaxIterations - Variable in class weka.clusterers.SAXKMeans

Maximum number of iterations to be executed.

m_MaxLabels - Variable in class adams.data.conversion.SpreadSheetToWekaInstances

the threshold for number of labels before an attribute gets switched to Attribute.STRING.

m_MaxLabels - Variable in class adams.data.spreadsheet.filter.WekaFilter

the threshold for number of labels before an attribute gets switched to Attribute.STRING.

m_MaxLeaves - Variable in class weka.classifiers.trees.XGBoost

Maximum number of nodes to be added.

m_MaxLevels - Variable in class weka.classifiers.meta.ClassifierCascade

the maximum number of levels in the cascade.

m_MaxManual - Variable in class weka.classifiers.meta.MinMaxLimits

the manual limit for the upper limit.

m_MaxNeighbors - Variable in class adams.flow.transformer.WekaNearestNeighborSearch

the maximum number of neighbors to return.

m_MaxSize - Variable in class adams.data.weka.predictions.RelativeNumericErrorScaler

the maximum size.

m_MaxTrainTime - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

the maximum number of seconds to train.

m_maxValue - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

This holds the max value of the current attribute.

m_MaxWidth - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased

the maximum width allowed.

m_Mean - Variable in class weka.classifiers.trees.RandomRegressionForest

the mean

m_Means - Variable in class weka.classifiers.functions.LinearRegressionJ

The attributes means

m_Means - Variable in class weka.filters.supervised.attribute.PLSFilterExtended

m_Measure - Variable in class adams.flow.transformer.WekaClassifierRanker

the measure for the evaluation.

m_Measure - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

the measure to use for ranking.

m_Measure - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

the measure to use for evaluating the fitness.

m_Measure - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the measure to use for evaluating the fitness.

m_Measure - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

the measure to use for evaluating the fitness.

m_MeasuresPrefix - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer

the optional prefix to disambiguate the measure attributes from the original ones.

m_Memory - Static variable in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter

for monitoring the Memory consumption

m_Memory - Static variable in class weka.gui.explorer.MultiExplorer

for monitoring the Memory consumption

m_MenuBar - Variable in class adams.gui.tools.DatasetCompatibilityPanel

the menu bar.

m_MenuBar - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the menu bar.

m_MenuBar - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the menu bar.

m_MenuBar - Variable in class adams.gui.visualization.instance.InstanceExplorer

the menu bar, if used.

m_MenuBar - Variable in class weka.gui.explorer.ExplorerExt

the menu bar, if used.

m_MenuFileSources - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the submenu for a sources.

m_MenuItemClearData - Variable in class adams.gui.visualization.instance.InstanceExplorer

the clear data menu item.

m_MenuItemEditData - Variable in class weka.gui.explorer.ExplorerExt

the edit data menu item.

m_MenuItemEditUndo - Variable in class weka.gui.explorer.ExplorerExt

the undo menu item.

m_MenuItemExecutionReset - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the reset menu item.

m_MenuItemExecutionStart - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the start menu item.

m_MenuItemExecutionStop - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the stop menu item.

m_MenuItemFileLoadClassifier - Variable in class weka.gui.explorer.ExplorerExt

the load classifier menu item.

m_MenuItemFileLoadClusterer - Variable in class weka.gui.explorer.ExplorerExt

the load clusterer menu item.

m_MenuItemFileLoadRecent - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the "load recent" submenu.

m_MenuItemFileSave - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the save menu item.

m_MenuItemFileSave - Variable in class weka.gui.explorer.ExplorerExt

the save menu item.

m_MenuItemFileSaveAs - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the save as menu item.

m_MenuItemFileSaveAs - Variable in class weka.gui.explorer.ExplorerExt

the save as menu item.

m_MenuItemLoadRecent - Variable in class adams.gui.visualization.instance.InstanceExplorer

the "load recent" submenu.

m_MenuItemLoadRecent - Variable in class weka.gui.explorer.ExplorerExt

the "load recent" submenu.

m_MenuItemLoadRecent1 - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the recent file menu item (first file).

m_MenuItemLoadRecent2 - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the recent file menu item (second file).

m_MenuItemOptionsCalculateModelSize - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the menu item for enabling/disabling model size calculation.

m_MenuItemOptionsSortAttributeNames - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the menu item for enabling/disabling sorting of attribute names.

m_MenuItemOptionsUndoEnabled - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the menu item for enabling/disabling undo.

m_MenuItemPrefixDatasetsWithIndex - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the prefix datasets menu item.

m_MenuItemReload - Variable in class adams.gui.tools.DatasetCompatibilityPanel

the reload menu item.

m_MenuItemReload - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the reload menu item.

m_MenuItemResultsLoadRecent - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the "load recent" submenu.

m_MenuItemResultsSave - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the save results menu item.

m_MenuItemText - Variable in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

the menu item caption.

m_MenuItemText - Variable in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

the menu item caption.

m_MenuItemUseFilename - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the use filename menu item.

m_MenuItemViewAntiAliasing - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the toggle anti-aliasing menu item.

m_MenuItemViewAntiAliasing - Variable in class adams.gui.visualization.instance.InstanceExplorer

the toggle anti-aliasing menu item.

m_MenuItemViewColorProvider - Variable in class adams.gui.visualization.instance.InstanceExplorer

the color provider menu item.

m_MenuItemViewInstanceExplorer - Variable in class weka.gui.explorer.ExplorerExt

the view instance explorer menu item.

m_MenuItemViewPaintlet - Variable in class adams.gui.visualization.instance.InstanceExplorer

the paintlet menu item.

m_MenuItemViewZoomOverview - Variable in class adams.gui.visualization.instance.InstanceExplorer

the toggle zoom overview menu item.

m_MenuTabNewTab - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the submenu for a new tab.

m_MenuView - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the menu item for view related stuff.

m_MenuView - Variable in class adams.gui.visualization.instance.InstanceExplorer

the menu item for view related stuff.

m_Merged - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

the name of the merged attribute.

m_Merged - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

the name of the merged attribute.

m_MergedDatasetName - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

The name to give the resulting dataset.

m_MergedIndex - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

the position for the merged attribute (empty = leave at default position).

m_MergedIndex - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

the position for the merged attribute (empty = leave at default position).

m_MergeMethod - Variable in class adams.flow.transformer.WekaDatasetsMerge

The method to use to perform the merge.

m_Merger - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Merger for reconstructing partial datasets.

m_Message - Variable in class adams.flow.transformer.WekaChooseAttributes

the message to display to the user.

m_MetaDataColor - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

for obtaining the color from the meta-data.

m_MetaLevelClassifier - Variable in class weka.classifiers.meta.PartitionedStacking

the meta-level classifier.

m_MetaLevelData - Variable in class weka.classifiers.meta.PartitionedStacking

the header for the meta-level data.

m_MetaLevelHeader - Variable in class weka.classifiers.meta.ClassifierCascade

the meta-level structure.

m_MetaLevelStart - Variable in class weka.classifiers.meta.ClassifierCascade

the start indices for the classifier stats in the meta-levels.

m_MethodNamePrediction - Variable in class weka.classifiers.functions.PyroProxy

the Pyro remote method for prediction.

m_MethodNameTrain - Variable in class weka.classifiers.functions.PyroProxy

the Pyro remote method for training.

m_min - Variable in class adams.opt.optimise.genetic.PackDataDef.DataInfo

m_min - Variable in class weka.classifiers.meta.AbstainAttributePercentile

m_min - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_Min - Variable in class weka.classifiers.trees.RandomRegressionForest

the minimum number of instances in subsets

m_Min - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

m_Min - Variable in class weka.filters.unsupervised.instance.Scale

the minimum to use.

m_MinActual - Variable in class weka.classifiers.meta.MinMaxLimits

the actual limit to use for the lower limit.

m_MinChildWeight - Variable in class weka.classifiers.trees.XGBoost

The minimum child weight.

m_MinClassRangePercentage - Variable in class weka.classifiers.meta.MinMaxLimits

the percentage leeway for the class range of the lower limit (0-1 = 0-100%).

m_minClusterDensity - Variable in class weka.clusterers.SAXKMeans

The minimum cluster density (according to T2 distance) allowed.

m_MinHandling - Variable in class weka.classifiers.meta.MinMaxLimits

how the lower limit is handled.

m_Minimal - Variable in class weka.attributeSelection.LinearRegressionAttributeEval

Conserve memory?

m_Minimal - Variable in class weka.classifiers.functions.LinearRegressionJ

Conserve memory?

m_MinImprovement - Variable in class weka.classifiers.meta.ClassifierCascade

the minimum improvement between levels that the statistic must improve.

m_Minimum - Variable in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

the minimum.

m_Minimum - Variable in class adams.data.weka.rowfinder.ByNumericValue

the minimum value.

m_Minimum - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

the minimum value.

m_MinimumIncluded - Variable in class adams.data.weka.rowfinder.ByNumericValue

whether the minimum value is included.

m_MinimumIncluded - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

whether the minimum value is included.

m_MinManual - Variable in class weka.classifiers.meta.MinMaxLimits

the manual limit for the lower limit.

m_minNumInstances - Variable in class weka.classifiers.trees.m5.M5Base2

The minimum number of instances to allow at a leaf node

m_MinProbability - Variable in class weka.classifiers.meta.AbstainMinimumProbability

the minimum probability that the classification must meet (0-1).

m_MinProbability - Variable in class weka.classifiers.meta.ThresholdedBinaryClassification

the minimum probability for the label.

m_Mins - Variable in class weka.classifiers.meta.AbstainAverage

m_Mins - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

m_Mins - Variable in class weka.classifiers.meta.AbstainVote

m_MinSamples - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

the minimum number of samples.

m_MinWidth - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased

the minimum width encountered.

m_MinZeroes - Variable in class weka.filters.unsupervised.instance.RemoveWithZeroes

the minimum number of zeroes that a row must have.

m_Missing - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

for replacing missing values

m_Missing - Variable in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS

for replacing missing values

m_Missing - Variable in class adams.tools.CompareDatasets

the output file for missing tests (CSV format).

m_Missing - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

The filter used to get rid of missing values.

m_Missing - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

The filter used to get rid of missing values.

m_Missing - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

The filter used to get rid of missing values.

m_Missing - Variable in class weka.classifiers.functions.GPD

The filter used to get rid of missing values.

m_MissingColor - Variable in class adams.gui.visualization.instances.AttributeValueCellRenderer

the color for missing values

m_MissingColorSelected - Variable in class adams.gui.visualization.instances.AttributeValueCellRenderer

the color for selected missing values

m_MissingFilter - Variable in class weka.classifiers.functions.LinearRegressionJ

The filter for removing missing values.

m_MissingLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel

Displays the number of missing values

m_Model - Variable in class adams.flow.condition.bool.WekaClassification

the model that was loaded from the model file.

m_Model - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

the model that was loaded from the model file.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

the table model.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

the model.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

the model that is being built.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

the fake model.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

the current model.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

the current model.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

the current model.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

the current model.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

the model.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

the current model.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

the model.

m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

The table model containing attribute names and selection status

m_Model - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

the model.

m_Model - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

the model.

m_Model - Variable in class adams.ml.model.classification.WekaClassificationModel

the underlying model.

m_Model - Variable in class adams.ml.model.clustering.WekaClusteringModel

the underlying model.

m_Model - Variable in class adams.ml.model.regression.WekaRegressionModel

the underlying model.

m_Model - Variable in class weka.attributeSelection.AbstractPLSAttributeEval

the underlying model.

m_Model - Variable in class weka.attributeSelection.LinearRegressionAttributeEval

the underlying model.

m_Model - Variable in class weka.classifiers.functions.GeneticAlgorithm

the final model.

m_ModelActor - Variable in class adams.flow.condition.bool.WekaClassification

the callable actor to get the model from.

m_ModelAttributesColor - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the color attribute model.

m_ModelAttributesID - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the attribute model.

m_ModelBuilt - Variable in class weka.classifiers.functions.LinearRegressionJ

Model already built?

m_ModelClass - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

the class attribute model.

m_ModelCommonIDs - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the model with the common IDs.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the datasets model.

m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the datasets model.

m_ModelEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the model with the available evaluations.

m_ModelEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the model with the available evaluations.

m_ModelEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the model with the available evaluations.

m_ModelEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the model with the available evaluations.

m_ModelFile - Variable in class adams.flow.condition.bool.WekaClassification

the serialized model to load.

m_ModelFileChooser - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

the file chooser for models.

m_ModelFileChooser - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

the file chooser for models.

m_ModelFileChooser - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

the file chooser for models.

m_ModelFirstDataset - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the first dataset model.

m_ModelFirstID - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the first ID attribute model.

m_ModelIDs - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the model with the IDs.

m_ModelLoader - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

the model loader.

m_ModelLoader - Variable in class adams.flow.transformer.WekaFilter

the model loader.

m_ModelMetric - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the model for the metric.

m_ModelName - Variable in class weka.classifiers.functions.PyroProxy

the model name.

m_ModelResetVariable - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

the variable to monitor for changes, triggering resets of the model.

m_ModelSecondDataset - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the second dataset model.

m_ModelSecondID - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the second ID attribute model.

m_ModelSetups - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the model with the available setups.

m_Modified - Variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

whether the data has been modified.

m_Modified - Variable in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

whether the setup has been modified.

m_ModifiedSearchMethod - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter

m_Monitor - Variable in class adams.gui.tools.wekainvestigator.data.FileContainer

the file monitor to use.

m_More - Variable in class weka.classifiers.trees.RandomRegressionForest.Node

m_Morphologies - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

the morphologies to apply.

m_Multiplier - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev

the multiplier for the standard deviation.

m_myInstances - Variable in class weka.core.neighboursearch.PCANNSearch

m_myInstances - Variable in class weka.core.neighboursearch.TransformNNSearch

Transformed instances.

m_n - Variable in class weka.core.SAXDistance

pre-sax number of attributes.

m_N - Variable in class weka.filters.supervised.attribute.YGradientEPO

Number of eigenvectors to keep.

m_name - Variable in class adams.opt.optimise.genetic.PackDataDef.DataInfo

m_Name - Variable in class adams.data.weka.classattribute.ByExactName

the string to match the attribute names against.

m_Name - Variable in class adams.data.weka.columnfinder.ByExactName

the string to match the attribute names against.

m_Name - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

the name of the item.

m_Name - Variable in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer

the column name.

m_NameLowerCase - Variable in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer

the lower case name.

m_Names - Variable in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

the names for the fusion subsets.

m_NameServer - Variable in class weka.classifiers.functions.PyroProxy

the Pyro nameserver.

m_NameServerActor - Variable in class weka.classifiers.functions.PyroProxy

the nameserver actor.

m_NameServerProxy - Variable in class weka.classifiers.functions.PyroProxy

the nameserver.

m_NameSuffix - Variable in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem

the name suffix to use (optional).

m_neighbours - Variable in class weka.core.neighboursearch.NewNNSearch

m_NestedItems - Variable in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem

nested result items.

m_NewFilter - Variable in class adams.data.conversion.SwapPLS

the new PLS filter.

m_NextInstance - Variable in class adams.flow.source.WekaDatabaseReader

the next instance to output.

m_NIPALS - Variable in class adams.data.instancesanalysis.pls.NIPALS

the actual algorithm.

m_NNSearch - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

The nearest neighbour search algorithm to use.

m_NoCheck - Variable in class adams.flow.transformer.WekaExperiment

whether not to check for experiment file to exist (e.g., when it generated on the fly).

m_NoCleanUp - Variable in class adams.gui.tools.wekainvestigator.data.DataContainerList

whether to suppress automatic cleanup.

m_node - Variable in class weka.classifiers.trees.RandomModelTrees

m_Node - Variable in class weka.classifiers.trees.RandomRegressionForest

the generated nodes

m_Nominal - Variable in class weka.classifiers.meta.ClassifierCascade

whether regression or classification.

m_NominalToBinary - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

The filter used to make attributes numeric.

m_NominalToBinary - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

The filter used to make attributes numeric.

m_NominalToBinary - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

The filter used to make attributes numeric.

m_NominalToBinary - Variable in class weka.classifiers.functions.GPD

The filter used to make attributes numeric.

m_NominalToBinaryFilter - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Filter for turning nominal values into numeric ones.

m_NonInteractive - Variable in class adams.flow.source.WekaSelectDataset

whether to automate the actor.

m_NonInteractive - Variable in class adams.flow.transformer.WekaChooseAttributes

whether to automate the actor.

m_NoReplacement - Variable in class weka.classifiers.meta.VotedImbalance

Whether to perform sampling with replacement or without.

m_norm - Variable in class weka.core.SAXDistance

suid.

m_norm - Variable in class weka.core.WeightedEuclideanDistance

m_norm - Variable in class weka.core.WeightedEuclideanDistanceRidge

m_NormaliseType - Variable in class weka.classifiers.trees.XGBoost

Type of normalisation algorithm.

m_Normalize - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges

whether to normalize the data.

m_NormalPlotOptions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

options for the normal plot

m_NormYWeights - Variable in class adams.data.instancesanalysis.pls.NIPALS

Flag to normalize Y weights

m_Notes - Variable in class adams.data.instance.Instance

the notes for the chromatogram.

m_Notes - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

the notes for the experiment.

m_NotificationEnabled - Variable in class adams.gui.visualization.instances.InstancesTableModel

whether notification is enabled

m_NoUpdate - Variable in class weka.classifiers.lazy.LWLDatasetBuilder

whether to suppress the update of the nearest-neighbor search algorithm when making predictions.

m_NoUpdate - Variable in class weka.classifiers.lazy.LWLSynchro

whether to suppress the update of the nearest-neighbor search algorithm when making predictions.

m_NoUpdate - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter

whether to suppress the update of the nearest-neighbor search algorithm when making predictions.

m_NoUpdate - Variable in class weka.classifiers.lazy.LWLSynchroSplit

whether to suppress the update of the nearest-neighbor search algorithm when making predictions.

m_NoUpdate - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

whether to suppress the update of the nearest-neighbor search algorithm when making predictions.

m_NthPoint - Variable in class weka.filters.unsupervised.attribute.DownSample

the nth point.

m_NumAttribs - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Number of attributes.

m_NumAttributes - Variable in class adams.data.instancesanalysis.PCA

the number of attributes in the data (excl class).

m_NumAttributesLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

Displays the number of attributes

m_NumBalanced - Variable in class weka.classifiers.meta.VotedImbalance

the number of balanced datasets to generate.

m_NumberInSubset - Variable in class weka.filters.unsupervised.instance.KennardStone

Number of spectra to select in subset

m_NumberOfParallelTrees - Variable in class weka.classifiers.trees.XGBoost

The number of parallel trees constructed during each iteration.

m_NumberOfRounds - Variable in class weka.classifiers.trees.XGBoost

The number of boosting rounds to perform.

m_NumberOfThreads - Variable in class weka.classifiers.trees.XGBoost

The number of threads to use.

m_NumBins - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges

the number of bins in case of manual bin calculation.

m_numbits - Variable in class adams.opt.genetic.Hermione

m_NumChrom - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

number of chromosomes.

m_NumClusters - Variable in class weka.clusterers.SAXKMeans

number of clusters to generate.

m_NumCoefficients - Variable in class adams.data.instancesanalysis.pls.SIMPLS

the number of coefficients in W to keep (0 keep all).

m_NumComponents - Variable in class adams.data.instancesanalysis.pls.AbstractPLS

the maximum number of components to generate

m_NumComponents - Variable in class weka.attributeSelection.AbstractPLSAttributeEval

the number of components parameter.

m_NumCycles - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

the number of cycles to apply.

m_NumDecimals - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges

the number of decimals to show.

m_NumDecimals - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

the number of decimals to use.

m_NumDecimals - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

the number of decimals to round to.

m_NumDecimals - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

the number of decimals to round to.

m_numericClassifyThreshold - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

The threshold for deciding when a numeric value is correctly classified

m_numericClassifyThreshold - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

The threshold for deciding when a numeric value is correctly classified

m_numericClassifyThresholdAbs - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

if Absolute error is less than this, then we're ok

m_numericClassifyThresholdAbs - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

if Absolute error is less than this, then we're ok

m_NumEvaluationBins - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

the number of evaluation bins.

m_NumExecutionSlots - Variable in class weka.classifiers.meta.SubsetEnsemble

The number of threads to have executing at any one time

m_NumExecutionSlots - Variable in class weka.classifiers.meta.VotedImbalance

The number of threads to have executing at any one time

m_NumFolds - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

the number of folds.

m_NumFolds - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

the number of folds.

m_NumFolds - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

the number of folds.

m_NumFolds - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator

the number of folds.

m_NumFolds - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

the number of folds.

m_NumFolds - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

the number of folds.

m_NumFolds - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

the number of folds.

m_NumFolds - Variable in class weka.classifiers.meta.ClassifierCascade

the number of folds for cross-validation.

m_NumFolds - Variable in class weka.filters.supervised.instance.RemoveOutliers

the number of folds to use.

m_NumGenes - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

number of genes per chromosome.

m_numInstances - Variable in class weka.classifiers.trees.m5.RuleNode2

the number of instances reaching this node

m_NumInstances - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Number of instances.

m_NumInstancesLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

Displays the number of instances

m_numIterations - Variable in class weka.classifiers.trees.RandomModelTrees

The number of iterations.

m_NumIterations - Variable in class weka.classifiers.trees.RandomRegressionForest

The number of iterations.

m_NumLabels - Variable in class weka.classifiers.meta.AbstainMinimumProbability

the number of class labels.

m_NumNumericAttributes - Variable in class weka.filters.unsupervised.instance.RemoveWithZeroes

the number of numeric attributes in the dataset.

m_numOfCleansingIterations - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

The maximum number of cleansing iterations to perform (<1 = until fully cleansed)

m_numOfCleansingIterations - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

The maximum number of cleansing iterations to perform (<1 = until fully cleansed)

m_numOfCrossValidationFolds - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

The number of cross validation folds to perform (<2 = no cross validation)

m_numOfCrossValidationFolds - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

The number of cross validation folds to perform (<2 = no cross validation)

m_numParameters - Variable in class weka.classifiers.trees.m5.RuleNode2

the number of paramters in the chosen model for this node---either the subtree model or the linear model.

m_NumPoints - Variable in class weka.filters.unsupervised.attribute.AndrewsCurves

the number of data points.

m_NumPoints - Variable in class weka.filters.unsupervised.attribute.EquiDistance

the number of points to output ("-1" uses the same amount of points as currently in the data).

m_NumPoints - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay2

the number of points to the left of a data point.

m_NumPointsLeft - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay

the number of points to the left of a data point.

m_NumPointsRight - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay

the number of points to the right of a data point.

m_NumPredictions - Variable in class adams.flow.transformer.WekaAccumulatedError

the number of overall predictions.

m_NumRandomFeatures - Variable in class weka.classifiers.meta.SubsetEnsemble

the number of random features to use (in addition to base attribute).

m_numreg - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_numreg - Variable in class weka.classifiers.meta.LeastMedianSq

m_NumRows - Variable in class adams.data.conversion.WekaCapabilitiesToInstances

the number of data rows to generate.

m_NumSimplsCoefficients - Variable in class adams.data.instancesanalysis.pls.PRM

the number of SIMPLS coefficients.

m_NumSubSamples - Variable in class adams.flow.transformer.WekaBootstrapping

the number of random sub-samples to generate.

m_NumThreads - Variable in class adams.flow.transformer.WekaClassifierRanker

the number of threads to use for parallel execution.

m_NumThreads - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator

the number of threads to use for parallel execution.

m_NumThreads - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

the number of threads to use for parallel execution.

m_NumThreads - Variable in class adams.multiprocess.WekaCrossValidationExecution

the number of threads to use for parallel execution (only used if no JobRunnerSetup/JobRunner set).

m_NumThreads - Variable in class weka.classifiers.meta.ClassifierCascade

the number of threads to use.

m_NumThreads - Variable in class weka.filters.supervised.instance.RemoveOutliers

the number of threads to use for parallel execution.

m_NumTokensAccepted - Variable in class adams.gui.visualization.instance.SimpleInstancePanelUpdater

the number of tokens accepted.

m_NumTrain - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

The number of training instances

m_NumTrain - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

The number of training instances

m_NumTrain - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

The number of training instances

m_NumTrain - Variable in class weka.classifiers.functions.GPD

The number of training instances

m_numTrials - Variable in class weka.classifiers.trees.RandomModelTrees

m_NumZeroes - Variable in class weka.filters.unsupervised.instance.RemoveWithZeroes

the number (or percentage) of zeroes that the row must contain to be removed.

m_Objective - Variable in class weka.classifiers.trees.XGBoost

The learning objective.

m_Offline - Variable in class adams.data.instances.AbstractInstanceGenerator

whether to operate in offline mode.

m_ok - Variable in class weka.classifiers.meta.AbstainAttributePercentile

m_ok - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_OldFilter - Variable in class adams.data.conversion.SwapPLS

the old PLS filter.

m_OldFilterCommandLine - Variable in class adams.data.conversion.SwapPLS

the command-line of the old filter.

m_OneDrop - Variable in class weka.classifiers.trees.XGBoost

Whether to always drop at least one tree during dropout.

m_OneMissing - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

what to do if one value is missing.

m_OneMissing - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

what to do if one value is missing.

m_OnlyFirstBatch - Variable in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Whether to only apply during first batch.

m_OnlyNominal - Variable in enum adams.flow.core.EvaluationStatistic

whether applies only to nominal classes or not.

m_OnTheFly - Variable in class adams.flow.condition.bool.WekaClassification

whether the model gets built on the fly and might not be present at the start.

m_OnTheFly - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

whether the model gets built on the fly and might not be present at the start.

m_OnTheFly - Variable in class adams.flow.transformer.WekaReorderAttributesToReference

whether the dataset gets generated on the fly and might not be available at setUp time.

m_Operation - Variable in class adams.flow.transformer.WekaInstanceBuffer

the way the buffer operates.

m_OPLS - Variable in class adams.data.instancesanalysis.pls.OPLS

the actual algorithm.

m_Optimizer - Variable in class adams.flow.transformer.WekaClassifierOptimizer

the classifier optimizer.

m_Optional - Variable in class adams.flow.transformer.WekaGeneticAlgorithm

whether the callable actor is optional.

m_original - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter

m_OriginalIndices - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

the original indices.

m_OriginalIndices - Variable in class adams.multiprocess.WekaCrossValidationExecution

the original indices.

m_OriginalIndices - Variable in class weka.classifiers.AbstractSplitGenerator

the original indicies.

m_OtherIndices - Variable in class weka.filters.supervised.attribute.MultiPLS

the indices of the other attributes.

m_OtherLabel - Variable in class weka.classifiers.meta.ThresholdedBinaryClassification

the index of the other label.

m_OtherParameters - Variable in class weka.classifiers.trees.XGBoost

Allows the user to enter arbitrary parameters.

m_Output - Variable in class adams.flow.transformer.AbstractWekaClassifierEvaluator

for generating predictions output.

m_Output - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationOutput

the output to generate.

m_Output - Variable in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob

the output to use.

m_Output - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

for collecting the output.

m_Output - Variable in class adams.multiprocess.WekaCrossValidationExecution

for generating predictions output.

m_outputAdditionalStats - Variable in class weka.attributeSelection.LinearRegressionAttributeEval

Whether to output additional statistics such as std.

m_outputAdditionalStats - Variable in class weka.classifiers.functions.LinearRegressionJ

Whether to output additional statistics such as std.

m_outputAdditionalStats - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Whether to output additional statistics such as std.

m_OutputArray - Variable in class adams.flow.source.AbstractWekaSetupGenerator

whether to output an array or a sequence of setups.

m_OutputBestSetup - Variable in class adams.flow.transformer.WekaClassifierRanker

whether to output the best setup in case of GridSearch/MultiSearch.

m_OutputBestSetup - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

whether to output the best classifier.

m_OutputBuffer - Variable in class adams.flow.transformer.AbstractWekaClassifierEvaluator

the buffer for the predictions.

m_OutputBuffer - Variable in class adams.multiprocess.WekaCrossValidationExecution

the buffer for the predictions.

m_OutputContainer - Variable in class adams.flow.transformer.WekaFilter

whether to output a container.

m_OutputDirectory - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the directory to store the generated ARFF files in.

m_OutputDirectory - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

the directory to store the generated ARFF files in.

m_OutputDistribution - Variable in class adams.flow.transformer.wekaclusterer.AddCluster

output distribution instead of cluster index.

m_OutputFile - Variable in class adams.flow.sink.WekaExperimentGenerator

the file to store the experiment in.

m_OutputFile - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

the output file.

m_OutputFile - Variable in class adams.tools.CompareDatasets

the output file (CSV format).

m_OutputFile - Variable in class weka.core.converters.SimpleArffSaver

the file to write to.

m_OutputFile - Variable in class weka.core.converters.SpreadSheetSaver

the file to write to.

m_OutputFormat - Variable in class adams.data.instancesanalysis.pls.AbstractPLS

the output format.

m_OutputFormat - Variable in class adams.flow.source.wekapackagemanageraction.ListPackages

the output format.

m_OutputFormat - Variable in class adams.flow.transformer.WekaExperimentEvaluation

the output format.

m_OutputFormat - Variable in class adams.flow.transformer.WekaInstanceDumper

the output format.

m_OutputFormat - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

the output format.

m_OutputGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem

the originating output generator.

m_OutputGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane

the output generator used.

m_OutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the output generators to use.

m_OutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the output generators to use.

m_OutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the output generators to use.

m_OutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the output generators to use.

m_OutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the output generators to use.

m_OutputHeader - Variable in class adams.data.instances.AbstractInstanceGenerator

the generated header.

m_OutputHeader - Variable in class adams.flow.transformer.WekaExperimentEvaluation

whether to output the header.

m_OutputHeader - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

whether to output the header.

m_OutputIndices - Variable in class adams.flow.transformer.WekaAttributeIterator

whether to output indices instead of the strings.

m_OutputInstance - Variable in class adams.flow.transformer.WekaClassifying

whether to output weka.core.Instance objects or PredictionContainers.

m_OutputModel - Variable in class adams.flow.transformer.WekaTestSetClustererEvaluator

whether to output the model as well.

m_OutputModel - Variable in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

whether to output the model as well.

m_OutputNominal - Variable in class weka.filters.unsupervised.attribute.SAX

If true output nominal, false output numeric .

m_OutputNumAtts - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

The number of attributes in the pc transformed data.

m_OutputOnlyModel - Variable in class adams.flow.transformer.AbstractWekaModelReader

whether to only output the model.

m_OutputPrefix - Variable in class adams.flow.transformer.WekaInstanceDumper

the output prefix.

m_OutputPrefixType - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the type of prefix to use for the output.

m_OutputRelationName - Variable in class adams.flow.transformer.WekaEvaluationSummary

whether to print the relation name of the dataset a well.

m_OutputType - Variable in class adams.flow.transformer.WekaFileReader

how to output the data.

m_OutputType - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the type of output to generate.

m_OutText - Variable in class weka.gui.explorer.ExperimentPanel

The output area for classification results.

m_Overlays - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

the overlays to use.

m_Override - Variable in class adams.flow.transformer.WekaClassSelector

whether to override any set class attribute.

m_OverrideJobRunner - Variable in class adams.flow.transformer.WekaExperimentExecution

whether to override the jobrunner in the experiment.

m_Owner - Variable in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.job.InvestigatorJob

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.source.AbstractSource

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane

the owner.

m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

the owner.

m_Owner - Variable in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel

the owner.

m_Owner - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel.HistoryPanel

the owner.

m_Owner - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

the owner.

m_Owner - Variable in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

the experimenter this runner belongs to.

m_Owner - Variable in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

the setup panel this option panel belongs to.

m_Owner - Variable in class adams.gui.visualization.instance.InstanceContainerManager

the owning panel.

m_Owner - Variable in class adams.gui.visualization.instance.InstancePointHitDetector

the owner of this detector.

m_Owner - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

the owning sort panel.

m_Owner - Variable in class adams.ml.data.DataCellView

the owning row.

m_Owner - Variable in class adams.ml.data.InstanceView

the owner.

m_P - Variable in class adams.data.instancesanalysis.pls.PLS1

the P matrix

m_packed - Variable in class adams.opt.optimise.genetic.PackDataDef

m_Padding - Variable in class weka.filters.unsupervised.attribute.FastWavelet

the type of padding.

m_PaddingType - Variable in class weka.filters.unsupervised.attribute.FFT

the type of padding to use.

m_Paintlet - Variable in class adams.flow.sink.WekaInstanceViewer

the paintlet to use.

m_Paintlet - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

the paintlet.

m_Paintlet - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

the paintlet to use.

m_Panel - Variable in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog

the setup panel.

m_Panel - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel

the currently output panel.

m_Panel - Variable in class weka.gui.explorer.ExplorerEntryPanel

the panel to display the results in.

m_PanelAnalysis - Variable in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

the current panel.

m_PanelAnalysis - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the analysis panel.

m_PanelAtt - Variable in class adams.flow.sink.WekaAttributeSummary

the visualization panel (if only one in range).

m_PanelAttSelection - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the attribute selection panel.

m_PanelAttSummary - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the attribute summary panel.

m_PanelAttVisualization - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the attribute visualization panel.

m_PanelBoth - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the panel for displaying the two instances.

m_PanelButtons - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

the panel for the buttons.

m_PanelButtons - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage

the panel for the buttons.

m_PanelButtons - Variable in class weka.gui.explorer.MultiExplorer

the panel for the buttons.

m_PanelButtons - Variable in class weka.gui.explorer.SqlPanel

the panel for the buttons

m_PanelChooser - Variable in class adams.gui.tools.weka.AbstractPanelWithFile

the chooser panel.

m_PanelClassAttribute - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

the panel for the class attribute heuristic.

m_PanelClassifiers - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

for specifying the classifiers.

m_PanelClassifiers - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

for specifying the classifiers.

m_PanelColorProvider - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the color provider.

m_PanelComboBox - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel

the panel for the combobox.

m_PanelComboBoxData - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the panel for the combobox listing the datasets.

m_PanelCompare - Variable in class adams.gui.InstanceCompare

the panel for comparing the datasets.

m_PanelComparison - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the overall panel for comparison.

m_PanelComparison - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the panel for displaying the two instances.

m_PanelComponents - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the components plot.

m_PanelCurve - Variable in class adams.gui.tools.weka.CostCurvePanel

for displaying the cost curve.

m_PanelData - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

the panel with the data.

m_PanelData - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the panel for the data.

m_PanelData - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the panel holding the table and buttons for the dataset.

m_PanelDataAction - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the panel with buttons etc.

m_PanelDataset - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

the panel for loading the file.

m_PanelDataset1 - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the panel for the first dataset.

m_PanelDataset2 - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the panel for the second dataset.

m_PanelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the panel for the datasets.

m_PanelDatasets - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

for specifying the datasets.

m_PanelDatasets - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

for specifying the datasets.

m_PanelDefinitions - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

the panel holding the defintion panels.

m_PanelDifference - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the panel with the difference.

m_PanelDifference - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the panel with the difference.

m_PanelEditor - Variable in class adams.gui.goe.WekaExperimentFileEditor

the editor panel.

m_PanelEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the panel with the evaluation.

m_PanelEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the panel with the evaluation.

m_PanelEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the panel with the evaluation.

m_PanelEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the panel with the evaluation.

m_PanelEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the panel with the evaluation.

m_PanelEvaluationSetup - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the panel for the evaluation setup to be embedded in.

m_PanelEvaluationSetup - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the panel for the evaluation setup to be embedded in.

m_PanelEvaluationSetup - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the panel for the evaluation setup to be embedded in.

m_PanelEvaluationSetup - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the panel for the evaluation setup to be embedded in.

m_PanelEvaluator - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the GOe with the evaluator.

m_PanelExecutionButtons - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the panel with the buttons.

m_PanelExecutionButtons - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the panel with the buttons.

m_PanelExecutionButtons - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the panel with the buttons.

m_PanelExecutionButtons - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the panel with the buttons.

m_PanelExecutionButtons - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the panel with the buttons.

m_PanelExplorer - Variable in class weka.gui.explorer.MultiExplorer

the actual panel for displaying the other panels.

m_PanelFile - Variable in class adams.gui.goe.WekaExperimentFileEditor

the panel for selecting the experiment file.

m_PanelFile - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

the preditions file.

m_PanelFile - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

the chooser panel for the indexed splits file.

m_PanelFile - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel

the file chooser panel.

m_PanelFile - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel

the file chooser panel.

m_PanelFile - Variable in class adams.gui.wizard.WekaSelectDatasetPage

the panel for selecting the file.

m_PanelFilter - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

the filter panel.

m_PanelGenerator - Variable in class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns

the GOE panel for the generator.

m_PanelGenerator - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

the fold generator.

m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the GOe with the associator.

m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the GOe with the classifier.

m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the GOe with the clusterer.

m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the GOe with the classifier.

m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the algorithm.

m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the GOe with the filter.

m_PanelGOE - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

the GOE for setting up classifiers.

m_PanelGOE - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel

the GOE panel.

m_PanelHistory - Variable in class weka.gui.explorer.MultiExplorer

the history panel.

m_PanelICA - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the ICA setup.

m_PanelInstance - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the plot.

m_PanelInstance - Variable in class adams.gui.visualization.instance.InstanceExplorer

the panel for displaying.

m_PanelInstSummary - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the instances summary panel.

m_PanelJobRunner - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

the JobRunner setup.

m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the panel on the left-hand side.

m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the panel on the left-hand side.

m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the panel on the left-hand side.

m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the panel on the left-hand side.

m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the panel on the left-hand side.

m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the left panel.

m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the left panel.

m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the left panel.

m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the left panel.

m_PanelLeft - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the panel on the left.

m_PanelLoadings - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the loadings plot.

m_PanelLoadings - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the loadings plot.

m_PanelLog - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the log panel.

m_PanelMain - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the panel for the preprocess panels.

m_PanelMatrix - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the GOE for the result matrix.

m_PanelModel - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

the serialized model.

m_PanelModel - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

the serialized model.

m_PanelModel - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

the serialized model.

m_PanelModel - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

the serialized model.

m_PanelOptions - Variable in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

the panel with the options.

m_PanelOutput - Variable in class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns

the chooser panel for the output file.

m_PanelOutput - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

the panel for the output type.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

the panel with the parameters.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the parameter panel.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the parameter panel.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the parameter panel.

m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the parameter panel.

m_PanelParameters - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

for listing all the options.

m_PanelParameters - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

for listing all the options.

m_PanelParametersAdvanced - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

the panel with the advanced parameters.

m_PanelQuery - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

the query panel.

m_PanelReader - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

the GOE panel for the indexed splits reader.

m_PanelResultsHandler - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

the panel for the results handler.

m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the panel on the right-hand side (displays results).

m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the panel on the right-hand side (displays results).

m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the panel on the right-hand side (displays results).

m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the panel on the right-hand side (displays results).

m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the panel on the right-hand side (displays results).

m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the right panel.

m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the right panel.

m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the right panel.

m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the right panel.

m_PanelRight - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the panel on the right.

m_Panels - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

the panels currently being displayed.

m_Panels - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

the panels currently being displayed.

m_Panels - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel

the map for panel name / panel object relation.

m_Panels - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

the list of definitions to use.

m_PanelScores - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the scores plot.

m_PanelScores - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the scores plot.

m_PanelSearch - Variable in class adams.gui.tools.wekainvestigator.output.TableContentPanel

the search panel.

m_PanelSearch - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the GOe with the search.

m_PanelSearch - Variable in class adams.gui.visualization.instances.InstancesPanel

the search panel.

m_PanelSearchID - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the search panel for the IDs.

m_PanelSetup - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the panel for the execution setup to be embedded in.

m_PanelSetup - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the current setup panel.

m_PanelSheet - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage

the parameter panel for displaying the parameters.

m_PanelSources - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the sources plot.

m_PanelsResults - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the results panels.

m_PanelStructure - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the panel for the structure.

m_PanelTester - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the GOE for the tester.

m_PanelTextAction - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the panel with buttons etc.

m_PanelTextAll - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the panel for the text tab.

m_PanelTop - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the panel for the filter and the buttons.

m_PanelWeights - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the plot of the loadings.

m_panelWidth - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel.BarCalc

m_PanelWriter - Variable in class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns

the GOE panel for the writer.

m_PanelZoomOverview - Variable in class adams.gui.visualization.instance.InstancePanel

the zoom overview panel.

m_Parameters - Variable in class adams.gui.menu.AbstractParameterHandlingWekaMenuItemDefinition

the additional parameters.

m_Params - Variable in class weka.classifiers.trees.XGBoost

the xgboost parameters.

m_ParentComponentActor - Variable in class adams.flow.source.WekaSelectDataset

the (optional) parent component to use.

m_ParentComponentActorConfigured - Variable in class adams.flow.source.WekaSelectDataset

whether the callable actor has been configured.

m_Parser - Variable in class weka.classifiers.functions.MathExpressionClassifier

the expression parser to use.

m_Password - Variable in class adams.flow.sink.WekaDatabaseWriter

the password for the user used for connecting.

m_Password - Variable in class adams.flow.source.WekaDatabaseReader

the password for the user used for connecting.

m_Password - Variable in class adams.gui.tools.wekainvestigator.data.DatabaseContainer

the password.

m_Pattern - Variable in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

the pattern in use.

m_PatternRegEx - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

The current regular expression.

m_PauseStateManager - Variable in class adams.flow.transformer.WekaGeneticAlgorithm

the pause state manager.

m_pca - Variable in class weka.core.neighboursearch.PCANNSearch

The neighbourhood of instances to find neighbours in.

m_pctile - Variable in class weka.classifiers.meta.AbstainAttributePercentile

m_pdd - Variable in class adams.opt.genetic.PackDataGeneticAlgorithm

m_pdd - Variable in class adams.opt.optimise.genetic.PackData

m_pdd - Variable in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm

m_pdd - Variable in class adams.opt.optimise.GeneticAlgorithm

m_Percent - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst

the percentage of the worst predictions to remove (0-1).

m_Percentage - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

the percentage.

m_Percentage - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

the percentage.

m_Percentage - Variable in class adams.flow.transformer.WekaBootstrapping

the size for the sub-samples (0-1).

m_Percentage - Variable in class adams.flow.transformer.WekaRandomSplit

the percentage for the split (0-1).

m_Percentage - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

the split percentage.

m_Percentage - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

the percentage.

m_Percentage - Variable in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

the percentage.

m_Percentage - Variable in class weka.classifiers.DefaultRandomSplitGenerator

the percentage.

m_Percentage - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

the percentage.

m_Percentage - Variable in class weka.classifiers.GroupedRandomSplitGenerator

the percentage.

m_Percentiles - Variable in class adams.flow.transformer.WekaBootstrapping

the percentiles to output (0-1).

m_Performance - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

the performance.

m_PerformTraining - Variable in class weka.classifiers.functions.PyroProxy

whether to perform training.

m_periodicPruningRate - Variable in class weka.clusterers.SAXKMeans

Prune low-density candidate canopies after every x instances have been seen (if using canopy clustering)

m_PlotCache - Variable in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

the cache for the plots.

m_PlotInstances - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator

the underlying data.

m_PlotName - Variable in class adams.flow.transformer.WekaAccumulatedError

the name of the plot.

m_PlotShapes - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator

for storing the plot shapes.

m_PlotSizes - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator

for storing the plot sizes.

m_PLS - Variable in class weka.classifiers.trees.RandomRegressionForest

the number of components to use in PLS

m_PLS - Variable in class weka.filters.supervised.attribute.MultiPLS

the PLS algorithms corresponding to the Y attributes.

m_plsfilter - Variable in class weka.core.neighboursearch.PLSNNSearch

The neighbourhood of instances to find neighbours in.

m_PLSFilter - Variable in class weka.classifiers.trees.RandomRegressionForest

the PLS filter used internally

m_PolynomialOrder - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay

the polynomial order.

m_PolynomialOrder - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay2

the polynomial order.

m_PopupMenu - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

the popup menu for the recent items.

m_Positions - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis

the new positions for the attributes.

m_PostProcessor - Variable in class adams.flow.transformer.WekaClustererPostProcessor

the post-processor.

m_PostProcessor - Variable in class adams.flow.transformer.WekaEvaluationPostProcessor

the post-processor to use.

m_PostProcessor - Variable in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob

the postprocessor.

m_PostProcessor - Variable in class adams.flow.transformer.WekaTrainClusterer

the post-processor.

m_PostProcessors - Variable in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor

the post-processors to apply.

m_PostProcessors - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor

the post-processors to combine.

m_PostTokenizer - Variable in class weka.core.tokenizers.PreCleanedTokenizer

the post tokenizer to use.

m_Predicted - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions

the column with the predicted values.

m_Predicted - Variable in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure

the collected predicted.

m_Predicted - Variable in class weka.classifiers.functions.FromPredictions

the column with the predicted values.

m_PredictedIndex - Variable in class weka.classifiers.functions.FromPredictions

the predicted column index.

m_PredictedMax - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

the maximum to use for the predicted values (pos inf = no restriction).

m_PredictedMin - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

the minimum to use for the predicted values (neg inf = no restriction).

m_Prediction - Variable in class adams.flow.transformer.WekaAccumulatedError.SortablePrediction

the wrapped prediction.

m_Predictions - Variable in class adams.flow.transformer.WekaAccumulatedError

the sorted predictions.

m_Predictions - Variable in class weka.classifiers.AggregateEvaluations

the collected predictions.

m_Predictions - Variable in class weka.classifiers.functions.FromPredictions

the actual predictions.

m_PredictionsFile - Variable in class weka.classifiers.functions.FromPredictions

the predictions to use.

m_PredictionType - Variable in class adams.data.instancesanalysis.pls.AbstractPLS

the prediction type to perform.

m_PredictMax - Variable in class weka.classifiers.functions.FakeClassifier

the maximum to use for the predictions.

m_PredictMin - Variable in class weka.classifiers.functions.FakeClassifier

the minimum to use for the predictions.

m_Predictor - Variable in class weka.classifiers.meta.Consensus

the index of the classifier to use for making the actual prediction.

m_Predictor - Variable in class weka.classifiers.trees.XGBoost

The type of predictor algorithm to use.

m_PredictWait - Variable in class weka.classifiers.functions.FakeClassifier

the predict wait time in msec.

m_PreferJobRunner - Variable in class adams.flow.transformer.WekaFilter

whether to offload filtering into a JobRunnerInstance.

m_PreferJobRunner - Variable in class adams.flow.transformer.WekaTestSetEvaluator

whether to offload training into a JobRunnerInstance.

m_PreferJobRunner - Variable in class adams.flow.transformer.WekaTrainAssociator

whether to offload training into a JobRunnerInstance.

m_PreferJobRunner - Variable in class adams.flow.transformer.WekaTrainClassifier

whether to offload training into a JobRunnerInstance.

m_PreferJobRunner - Variable in class adams.flow.transformer.WekaTrainClusterer

whether to offload training into a JobRunnerInstance.

m_PreferJobRunner - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator

whether to offload train/evaluate onto a JobRunnerInstance.

m_PreFilter - Variable in class adams.data.weka.rowfinder.FilteredIQR

the filter to apply to the data first.

m_PreFilter - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter

m_PreFilter - Variable in class weka.filters.FilteredFilter

The pre-filter to apply to the data.

m_PreFilter - Variable in class weka.filters.unsupervised.instance.KennardStone

Pre filter to apply before selection

m_Prefix - Variable in class adams.flow.transformer.WekaInstancesMerge

the additional prefix name to use, apart from the index.

m_Prefix - Variable in class weka.filters.unsupervised.attribute.EquiDistance

the prefix for the new attributes.

m_PrefixDatasetsWithIndex - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

whether to prefix the relation names with the index.

m_PrefixDatasetsWithIndex - Variable in class weka.experiment.ExtExperiment

whether to prefix the relation names with the index.

m_Prefixes - Variable in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

The prefixes.

m_Prefixes - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

The prefixes.

m_PrefixSeparator - Variable in class adams.flow.transformer.WekaInstancesMerge

the separator between index and actual attribute name.

m_Preparation - Variable in class weka.classifiers.meta.SocketFacade

the data preparation to use.

m_Preprocessing - Variable in class weka.core.neighboursearch.PCANNSearch

the type of preprocessing

m_Preprocessing - Variable in class weka.core.neighboursearch.PLSNNSearch

the type of preprocessing

m_PreprocessingType - Variable in class adams.data.instancesanalysis.pls.AbstractPLS

the preprocessing type to perform.

m_PreprocessingType - Variable in class weka.attributeSelection.AbstractPLSAttributeEval

the preprocessing type to perform.

m_PreSelection - Variable in class adams.flow.transformer.WekaChooseAttributes

the regular expression for pre-selecting attributes by name.

m_PreserveIDColumn - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Whether to treat the first attribute as an ID.

m_PreserveOrder - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

whether to preserve the order.

m_PreserveOrder - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

whether to preserve the order.

m_PreserveOrder - Variable in class adams.flow.transformer.WekaRandomSplit

whether to preserve the order.

m_PreserveOrder - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

whether to preserve the order.

m_PreserveOrder - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

whether to preserve the order.

m_PreserveOrder - Variable in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

whether to preserve the order.

m_PreserveOrder - Variable in class weka.classifiers.DefaultRandomSplitGenerator

whether to preserve the order.

m_PreserveOrder - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

whether to preserve the order.

m_PreserveOrder - Variable in class weka.classifiers.GroupedRandomSplitGenerator

whether to preserve the order.

m_PreserveOrder - Variable in class weka.clusterers.SAXKMeans

Preserve order of instances.

m_PreTokenizer - Variable in class weka.core.tokenizers.PreCleanedTokenizer

the pre tokenizer to use.

m_PRM - Variable in class adams.data.instancesanalysis.pls.PRM

the actual algorithm.

m_Probability - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer

the probability.

m_Processed - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator

whether the data has already been processed.

m_Processed - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

temporary filter results when determining output format to avoid duplicate processing of data.

m_Processor - Variable in class adams.flow.transformer.WekaClassifierSetupProcessor

the processor to use.

m_ProcessType - Variable in class weka.classifiers.trees.XGBoost

The type of boosting process to run.

m_Properties - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the properties.

m_Properties - Static variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the properties.

m_Properties - Static variable in class adams.gui.visualization.instance.InstanceComparePanel

the properties.

m_Properties - Static variable in class adams.gui.visualization.instance.InstanceExplorer

the properties.

m_Property - Variable in class adams.core.discovery.genetic.GenericDoubleResolution

the property name.

m_Property - Variable in class adams.core.discovery.genetic.GenericFloatResolution

the property name.

m_Property - Variable in class adams.core.discovery.genetic.GenericInteger

the property name.

m_Property - Variable in class adams.core.discovery.genetic.GenericString

the property name.

m_PropertyDescriptor - Variable in class adams.core.discovery.genetic.GenericDoubleResolution

the property descriptor.

m_PropertyDescriptor - Variable in class adams.core.discovery.genetic.GenericFloatResolution

the property descriptor.

m_PropertyDescriptor - Variable in class adams.core.discovery.genetic.GenericInteger

the property descriptor.

m_PropertyDescriptor - Variable in class adams.core.discovery.genetic.GenericString

the property descriptor.

m_Query - Variable in class adams.flow.source.WekaDatabaseReader

the query to execute.

m_Query - Variable in class adams.gui.tools.wekainvestigator.data.DatabaseContainer

the query used to load the data.

m_Queue - Variable in class adams.flow.transformer.WekaSubsets

the generated subsets.

m_r_hat - Variable in class adams.data.instancesanalysis.pls.PLS1

the regression vector "r-hat"

m_random - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_random - Variable in class weka.classifiers.meta.LeastMedianSq

m_Random - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

the random number generator.

m_Random - Variable in class weka.classifiers.functions.FakeClassifier

for generating the random numbers.

m_Random - Variable in class weka.classifiers.meta.AbstainVote

the random number generator used for breaking ties in majority voting

m_Random - Variable in class weka.filters.unsupervised.attribute.InputSmearing

the random number generator to use.

m_Randomize - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

whether to randomize the data.

m_Randomize - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

whether to randomize the data.

m_Randomize - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

whether to randomize the data.

m_Randomize - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator

whether to randomize the data.

m_Randomize - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

whether to randomize the data.

m_Randomize - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

whether to randomize the data.

m_Randomize - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

whether to randomize the data.

m_Randomize - Variable in class weka.classifiers.LeaveOneOutByValueGenerator

whether to randomize the data.

m_Randomize - Variable in class weka.filters.unsupervised.instance.RemoveDuplicates

whether to randomize the data after the removal.

m_randomseed - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_randomseed - Variable in class weka.classifiers.meta.LeastMedianSq

m_Range - Variable in class adams.data.weka.rowfinder.FilteredIQR

the attribute range to work on.

m_Range - Variable in class adams.flow.sink.WekaAttributeSummary

the attribute to visualize.

m_Range - Variable in class adams.flow.transformer.WekaAttributeIterator

the range of attributes to work on.

m_Range - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

the range of attributes to use.

m_Range - Variable in class weka.classifiers.meta.AbstainAttributePercentile

m_Range - Variable in class weka.filters.unsupervised.attribute.AnyToString

the attribute range to process.

m_Range - Variable in class weka.filters.unsupervised.attribute.EquiDistance

the attribute range to use.

m_Range - Variable in class weka.filters.unsupervised.attribute.StringToDate

the attribute range to process.

m_Range - Variable in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor

the range of attributes to work on.

m_Range - Variable in class weka.filters.unsupervised.instance.SafeRemoveRange

Range of instances requested by the user.

m_Range1 - Variable in class adams.tools.CompareDatasets

the first range of attributes.

m_Range2 - Variable in class adams.tools.CompareDatasets

the second range of attributes.

m_RangePaintlet - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

the paintlet to use for the lower/upper statistic.

m_Ranges - Variable in class adams.data.weka.rowfinder.ByNumericRange

the intervals.

m_Ranges - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange

the intervals.

m_Ranges - Variable in class weka.classifiers.meta.AbstainAttributePercentile

the ranges (attribute index <-> double[]).

m_Ranges - Variable in class weka.classifiers.meta.PartitionedStacking

the attribute ranges for the base-classifiers.

m_Ranges - Variable in class weka.classifiers.meta.RangeCheck

the ranges (attribute index <-> double[]).

m_Ranges - Variable in class weka.filters.unsupervised.attribute.detrend.RangeBased

the ranges to calculate the intercept/slope for.

m_Ranges - Variable in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased

the ranges to calculate the intercept/slope for.

m_Ranges - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

The attribute ranges.

m_Ranking - Variable in class weka.attributeSelection.AbstractPLSAttributeEval

the determined attribute ranking.

m_Ranking - Variable in class weka.attributeSelection.LinearRegressionAttributeEval

the degtermined attribute ranking.

m_RateDrop - Variable in class weka.classifiers.trees.XGBoost

Dropout rate.

m_RawColumns - Variable in class adams.data.weka.columnfinder.Constant

The raw representation of the columns to find.

m_RawRows - Variable in class adams.data.weka.rowfinder.Constant

The raw form of the rows.

m_Reader - Variable in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer

the reader used to load the data.

m_Reader - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

the spreadsheet reader to use.

m_Reader - Variable in class weka.classifiers.functions.FromPredictions

the spreadsheet reader to use.

m_Reader - Variable in class weka.core.converters.SpreadSheetLoader

the reader to use.

m_ReaderFileFilters - Static variable in class adams.gui.chooser.AdamsExperimentFileChooser

the file filters for the readers.

m_ReaderFileFilters - Static variable in class adams.gui.chooser.WekaFileChooser

the file filters for the readers.

m_ReadOnly - Variable in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

whether the model is read-only.

m_ReadOnly - Variable in class adams.gui.visualization.instances.InstancesTableModel

whether the table is read-only

m_Real - Variable in class weka.filters.unsupervised.attribute.FFT

whether to return complex or real part of the transformation.

m_RecentFilesHandler - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the recent files handler.

m_RecentFilesHandler - Variable in class adams.gui.visualization.instance.InstanceExplorer

the recent files handler.

m_RecentFilesHandler - Variable in class weka.gui.explorer.ExplorerExt

the recent files handler.

m_RecentFilesHandler1 - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the recent files handler.

m_RecentFilesHandler2 - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the recent files handler.

m_RecentFilesHandlerResults - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the recent files handler for results.

m_RecentFilesHandlerSetups - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the recent files handler for setups.

m_RecentStatementsHandler - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

the recent files handler.

m_Reference - Variable in class adams.flow.transformer.WekaReorderAttributesToReference

the reference dataset.

m_ReferenceActor - Variable in class adams.flow.transformer.WekaReorderAttributesToReference

the callable actor to get the reference data from.

m_ReferenceDataset - Variable in class weka.filters.unsupervised.instance.AlignDataset

the file containing the reference dataset.

m_ReferenceError - Variable in class adams.data.weka.predictions.NumericErrorScalerWithReference

the reference error.

m_ReferenceFile - Variable in class adams.flow.transformer.WekaReorderAttributesToReference

the reference dataset to load.

m_ReferenceSize - Variable in class adams.data.weka.predictions.NumericErrorScalerWithReference

the reference size.

m_Regex - Variable in class adams.flow.transformer.WekaRegexToRange

regular expression used to determine attribute list.

m_RegexName - Variable in class adams.flow.transformer.WekaClassSelector

the regular expression on the attribute for selecting the sub-set of attributes.

m_RegExp - Variable in class adams.data.binning.BinnableInstances.StringAttributeGroupExtractor

the regular expression.

m_RegExp - Variable in class adams.data.weka.classattribute.ByName

the regular expression to use on the name.

m_RegExp - Variable in class adams.data.weka.columnfinder.ByName

the regular expression to match the attribute names against.

m_RegExp - Variable in class adams.data.weka.rowfinder.ByLabel

the regular expression to match the labels against.

m_RegExp - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

the regular expression for the nominal/string attribute.

m_RegExp - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

the regular expression for the nominal/string attribute.

m_RegExp - Variable in class adams.flow.transformer.WekaAttributeIterator

the regular expression applied to the attribute names.

m_RegExp - Variable in class adams.flow.transformer.WekaMultiLabelSplitter

the regular expression that the class attribute names have to match.

m_RegExp - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

the regular expression for the nominal/string attribute.

m_RegExp - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

the regular expression for the nominal/string attribute.

m_RegExp - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

the regular expression for the nominal/string attribute.

m_RegExp - Variable in class weka.classifiers.GroupedRandomSplitGenerator

the regular expression for the nominal/string attribute.

m_RegExp - Variable in class weka.core.InstanceGrouping

the regular expression.

m_RegExp - Variable in class weka.filters.unsupervised.attribute.EquiDistance

the regular expression to use.

m_RegExp - Variable in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

The prefixes.

m_RegExp - Variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

the regular expression for the nominal/string attribute.

m_RegExps - Variable in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

the regular expressions to identify fusion subsets.

m_RegExps - Variable in class weka.classifiers.MultiLevelSplitGenerator

the regular expressions to apply to determine the grouping.

m_Registered - Static variable in class adams.gui.goe.WekaEditorsRegistration

whether registration already occurred.

m_regressionTree - Variable in class weka.classifiers.trees.m5.M5Base2

Make a regression tree/rule instead of a model tree/rule

m_RelationName - Variable in class adams.flow.source.WekaNewInstances

the name for the relation, if any.

m_RelationName - Variable in class adams.flow.transformer.WekaCrossValidationSplit

the format of the relation names of the generated datasets.

m_RelationName - Variable in class weka.classifiers.AggregateEvaluations

dataset name.

m_RelationName - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

the template for the relation name.

m_RelationName - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator

the template for the relation name.

m_RelationName - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

the template for the relation name.

m_RelationName - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

the template for the relation name.

m_RelationName - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

the template for the relation name.

m_RelationName - Variable in class weka.classifiers.LeaveOneOutByValueGenerator

the template for the relation name.

m_RelationNameHeuristic - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the heuristic for updating the relation name.

m_RelationNameLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

Displays the name of the relation

m_RelativeWidths - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased

whether to divide the calculated widths by the class value.

m_RelativeWidths - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval

whether the widths are relative.

m_Remote - Variable in class weka.classifiers.meta.SocketFacade

the address of the remote process.

m_RemoteObject - Variable in class weka.classifiers.functions.PyroProxy

the remote object.

m_RemoteObjectName - Variable in class weka.classifiers.functions.PyroProxy

the Pyro remote object.

m_remove - Variable in class weka.classifiers.meta.Corr

m_Remove - Variable in class adams.flow.transformer.WekaChooseAttributes

the Remove filter in use.

m_Remove - Variable in class adams.flow.transformer.WekaInstancesMerge

whether to remove when not all present.

m_Remove - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

the remove filter for trimming the range of attributes to return.

m_Remove - Variable in class weka.classifiers.meta.FilteredClassifierExt

The additional remove filter.

m_Remove - Variable in class weka.classifiers.meta.PartitionedStacking

the filters for removing the unwanted attributes for the base classifiers.

m_Remove - Variable in class weka.filters.unsupervised.attribute.DatasetCleaner

the remove filter to use.

m_RemoveChars - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

the characters to remove from the merged name (start/end).

m_RemoveChars - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

the characters to remove from the merged name (start/end).

m_removetrain - Variable in class weka.classifiers.meta.AbstainAttributePercentile

m_RemoveUnused - Variable in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Whether unused attributes are left out of the output.

m_RemoveUnused - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Whether unused attributes are left out of the output.

m_Renderer - Variable in class adams.gui.visualization.instances.InstancesTable

the renderer to use.

m_Reorder - Variable in class adams.flow.transformer.WekaReorderAttributesToReference

the reorder filter to use.

m_Replace - Variable in class adams.flow.transformer.WekaRenameRelation

the string to replace with.

m_Replace - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric

the replacement string.

m_ReplaceMissing - Variable in class adams.data.instancesanalysis.pls.AbstractPLS

whether to replace missing values

m_ReplaceMissing - Variable in class weka.attributeSelection.AbstractPLSAttributeEval

the replace missing values parameter.

m_ReplaceMissingFilter - Variable in class weka.clusterers.SAXKMeans

replace missing values in training instances.

m_ReplaceMissingFilter - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Filters for replacing missing values.

m_Report - Variable in class adams.data.instance.Instance

the automatically generated report.

m_Reports - Variable in class adams.gui.visualization.instance.InstanceExplorer

the reports.

m_ReportTable - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the table with the report.

m_ReportTable - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the table with the report.

m_ResetModel - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

whether we need to reset the model.

m_ResetResults - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

whether to reset the results before starting the experiment.

m_Residuals - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_Residuals - Variable in class weka.classifiers.meta.LeastMedianSq

m_Result - Variable in class adams.gui.goe.WekaGenericArrayEditorDialog

whether the dialog was cancelled or ok'ed.

m_Result - Variable in class adams.gui.goe.WekaGenericObjectEditorDialog

whether the dialog was cancelled or ok'ed.

m_ResultFile - Variable in class adams.flow.sink.WekaExperimentGenerator

the file to store the result in.

m_ResultFormat - Variable in class adams.flow.sink.WekaExperimentGenerator

the result format.

m_Results - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

the raw results from the experiment.

m_Results - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

the generated results.

m_Results - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

the generated results.

m_ResultsFileChooser - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

the file chooser for the results.

m_ResultsHandler - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

the handler for the results.

m_Reverse - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions

whether to reverse the sorting.

m_Reverse - Variable in class weka.classifiers.AggregateEvaluations

whether to reverse the sorting.

m_ridge - Variable in class weka.classifiers.trees.RandomModelTrees

m_Ridge - Variable in class adams.data.baseline.AbstractLinearRegressionBased

the ridge.

m_Ridge - Variable in class weka.attributeSelection.LinearRegressionAttributeEval

The ridge parameter

m_Ridge - Variable in class weka.classifiers.functions.LinearRegressionJ

The ridge parameter

m_Ridge - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_Ridge - Variable in class weka.classifiers.meta.LeastMedianSq

m_Ridge - Variable in class weka.core.WeightedEuclideanDistanceRidge

m_right - Variable in class weka.classifiers.trees.m5.RuleNode2

right child node

m_Row - Variable in class adams.flow.transformer.WekaExperimentEvaluation

the row (= datasets).

m_Row - Variable in class adams.flow.transformer.WekaGetInstancesValue

the index of the row.

m_Row - Variable in class adams.flow.transformer.WekaSetInstancesValue

the index of the row.

m_Row - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

the row (= datasets).

m_RowAttribute1 - Variable in class adams.tools.CompareDatasets

the optional attribute for matching up rows (dataset 1).

m_RowAttribute2 - Variable in class adams.tools.CompareDatasets

the optional attribute for matching up rows (dataset 2).

m_RowAttributeIsString - Variable in class adams.tools.CompareDatasets

whether the row attribute is a string/nominal attribute or not.

m_RowFinder - Variable in class adams.data.weka.columnfinder.RowFilteredColumnFinder

the RowFinder to use first.

m_RowFinder - Variable in class adams.data.weka.datasetsplitter.RowSplitter

The selector for splitting rows between the two datasets.

m_RowFinder - Variable in class adams.data.weka.rowfinder.AbstractFilteredRowFinder

the RowFinder to apply.

m_RowFinder - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

The row-finder which separates training data from actual data.

m_RowFinder - Variable in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

The classifier template used to do the classification.

m_RowFinder - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

the row finder to use if enabled.

m_RowFinderEnabled - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

whether to use the row finder.

m_RowIndex - Variable in class adams.gui.visualization.instance.InstanceComparePanel

the internal index.

m_RowRange - Variable in class weka.filters.unsupervised.instance.KeepRange

the index of the attribute to sort on.

m_Rows - Variable in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

num rows

m_Rows - Variable in class adams.data.weka.rowfinder.Constant

The constant set of rows to find.

m_Rows - Variable in class adams.gui.event.WekaInvestigatorDataEvent

the affected rows, null for all.

m_Rows - Variable in class weka.core.InstancesView

the rows to use.

m_Rows - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

m_RowSelection - Variable in class weka.filters.unsupervised.instance.MultiRowProcessor

the row selection scheme.

m_RowSplitter - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Row-splitter for splitting training and actual data.

m_rsquared - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

R^2 value for the regression

m_rsquaredAdj - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Adjusted R^2 value for the regression

m_ruleSet - Variable in class weka.classifiers.trees.m5.M5Base2

the rule set

m_run - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter

m_Run - Variable in class adams.gui.tools.wekainvestigator.job.InvestigatorTabRunnableJob

the runnable to execute.

m_Run - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

the run.

m_RunEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

the evaluation objects from the runs.

m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

the run information.

m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics

whether to print the run information as well.

m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

the run information.

m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

whether to print the run information as well.

m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

the run information.

m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics

whether to print the run information as well.

m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

the run information.

m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

whether to print the run information as well.

m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

the run information.

m_RunModels - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

the run models.

m_Runner - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the runner thread.

m_Running - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

whether the experiment is running.

m_Running - Variable in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

whether the experiment is still running.

m_Running - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

whether the algorithm is still running.

m_RunOriginalIndices - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

the original indices (runs).

m_Runs - Variable in class adams.flow.sink.WekaExperimentGenerator

the number of runs to perform.

m_Runs - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

the number of runs to perform.

m_Runs - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

the number of runs.

m_RunsSpinner - Variable in class weka.gui.explorer.ExperimentPanel

The spinner for the number of runs.

m_RunThread - Variable in class weka.gui.explorer.ExperimentPanel

A thread that classification runs in.

m_SamplePercentage - Variable in class weka.classifiers.meta.VotedImbalance

the sample percentage to use (0-100).

m_SampleSize - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

the sample size to use.

m_SampleType - Variable in class weka.classifiers.trees.XGBoost

Type of sampling algorithm.

m_saveInstances - Variable in class weka.classifiers.trees.m5.M5Base2

Save instances at each node in an M5 tree for visualization purposes.

m_SaveOut - Variable in class weka.gui.explorer.ExperimentPanel

The buffer saving object for saving output.

m_Saver - Variable in class adams.data.io.output.AbstractWekaSpreadSheetWriter

the file loader to use.

m_Saver - Variable in class adams.flow.sink.WekaDatabaseWriter

the database saver.

m_Saver - Variable in class adams.gui.chooser.DatasetFileChooserPanel

the current saver.

m_scale - Variable in class adams.opt.optimise.genetic.PackDataDef.DataInfo

m_scalefactor - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_scalefactor - Variable in class weka.classifiers.meta.LeastMedianSq

m_ScalePositiveWeights - Variable in class weka.classifiers.trees.XGBoost

Scales the weights of positive instances by this factor.

m_Scaler - Variable in class adams.data.weka.predictions.AutoScaler

the scaler to use for numeric classes.

m_Scores - Variable in class adams.data.instancesanalysis.PCA

the scores.

m_Scores - Variable in class adams.data.instancesanalysis.PLS

the scores.

m_Search - Variable in class adams.flow.transformer.WekaAttributeSelection

the search method.

m_Search - Variable in class adams.flow.transformer.WekaNearestNeighborSearch

the neighboorhood search to use.

m_Search - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

the search algorithm.

m_Search - Variable in class weka.classifiers.lazy.LWLDatasetBuilder

The nearest neighbour search algorithm to use.

m_SearchPanel - Variable in class adams.gui.visualization.instance.InstanceExplorer

for searching the fields in the reports.

m_SearchPanel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the search panel.

m_Second - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis

the positions of the second range.

m_SecondAttribute - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

the name of the second attribute.

m_SecondAttributeRange - Variable in class adams.gui.InstanceCompare

the second attribute range to use.

m_SecondAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the second set of attributes.

m_SecondBestFitness - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

the best fitness so far (second evaluation).

m_SecondBestSetup - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

the best setup so far (second evaluation).

m_SecondBestWeights - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

the best weights/bits so far (second evaluation).

m_SecondCrossValidationSeed - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

the cross-validation seed (second evaluation).

m_SecondData - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the second dataset.

m_SecondFile - Variable in class adams.gui.InstanceCompare

the second file to compare.

m_SecondFitness - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob

the current fitness (second evaluation).

m_SecondFolds - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob

the cross-validation folds (second evaluation).

m_SecondFolds - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

the number of folds for cross-validation (second evaluation).

m_SecondRange - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis

the second range of the attributes to use.

m_SecondRowIndex - Variable in class adams.gui.InstanceCompare

the index of the second attribute to use for matching rows.

m_SecondSeed - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob

the cross-validation seed (second evaluation).

m_SecondStoredResults - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

the cache for results (second evaluation).

m_Seed - Variable in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

the random seed for cross-valiation.

m_Seed - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

the seed value.

m_Seed - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

the seed value.

m_Seed - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

the seed value.

m_Seed - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

the seed value.

m_Seed - Variable in class adams.flow.transformer.WekaAttributeSelection

the seed value.

m_Seed - Variable in class adams.flow.transformer.WekaBootstrapping

the random number seed.

m_Seed - Variable in class adams.flow.transformer.WekaClassifierRanker

the random seed to use.

m_Seed - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

the seed value to use.

m_Seed - Variable in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

the seed value.

m_Seed - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator

the seed value.

m_Seed - Variable in class adams.flow.transformer.WekaCrossValidationSplit

the seed value.

m_Seed - Variable in class adams.flow.transformer.WekaRandomSplit

the seed value.

m_Seed - Variable in class adams.multiprocess.WekaCrossValidationExecution

the seed value.

m_Seed - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

the cross-validation seed.

m_Seed - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

the seed value.

m_Seed - Variable in class weka.classifiers.AbstractSplitGenerator

the seed value.

m_Seed - Variable in class weka.classifiers.functions.FakeClassifier

the seed.

m_Seed - Variable in class weka.classifiers.trees.XGBoost

The random number seed.

m_Seed - Variable in class weka.filters.supervised.instance.RemoveOutliers

the seed value.

m_Seed - Variable in class weka.filters.unsupervised.attribute.InputSmearing

The random number seed.

m_Seed - Variable in class weka.filters.unsupervised.instance.RemoveDuplicates

the seed value for the randomization.

m_Seed - Variable in class weka.filters.unsupervised.instance.WeightsBasedResample

the seed for randomizing the final dataset.

m_seIntercept - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

standard error of the intercept

m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

the additional attributes to store.

m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

the additional attributes to store.

m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

the additional attributes to store.

m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

the additional attributes to store.

m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

the additional attributes to store.

m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

the additional attributes to store.

m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

the additional attributes to store.

m_SelectColumns - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the dataset keys.

m_SelectComparisonBase - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the comparison base.

m_SelectedAttributes - Variable in class weka.classifiers.functions.LinearRegressionJ

Which attributes are relevant?

m_SelectionListeners - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

the listeners for changes in the selection.

m_SelectionProcessor - Variable in class weka.filters.unsupervised.instance.MultiRowProcessor

the row processing scheme.

m_SelectRows - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the resultset keys.

m_Self - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the dialog itself.

m_SeparateFolds - Variable in class adams.multiprocess.WekaCrossValidationExecution

whether to separate folds.

m_Serialized - Variable in class weka.filters.SerializedFilter

the flow file to process the data with.

m_Server - Variable in class weka.classifiers.meta.SocketFacade

the server socket for receiving the replies.

m_seSlope - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

standard error of the slope

m_Setup - Variable in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

the property for the genetic algorithm setup.

m_Setups - Variable in class adams.flow.source.AbstractWekaSetupGenerator

all the setups.

m_SetupUpload - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

for uploading the setups.

m_SharedStringsTable - Variable in class adams.ml.data.InstancesView

the shared string table.

m_ShortcutProperties - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the shortcut properties.

m_ShowAttributeIndex - Variable in class adams.gui.visualization.instances.InstancesTableModel

whether to display the attribute index in the table header.

m_ShowAttributeWeights - Variable in class adams.gui.visualization.instances.InstancesTableModel

whether to show attribute weights.

m_ShowDistribution - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer

whether to output the class distribution (only nominal classes).

m_ShowDistribution - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

whether to output the class distribution (only nominal classes).

m_ShowError - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer

whether to add an error colunm.

m_ShowError - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

whether to add an error colunm.

m_ShowProbability - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer

whether to output the probability of the prediction (only nominal classes).

m_ShowProbability - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

whether to output the probability of the prediction (only nominal classes).

m_ShowWeight - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer

whether to output the weight as well.

m_ShowWeight - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

whether to output the weight as well.

m_ShowWeightsColumn - Variable in class adams.gui.visualization.instances.InstancesTableModel

whether to show a weights column.

m_showZeroInstancesAsUnknown - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

Whether to display 0 or ? for the number of instances in cases where a dataset has only structure.

m_Significance - Variable in class adams.flow.transformer.WekaExperimentEvaluation

the significance.

m_Significance - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

the significance.

m_Silent - Variable in class weka.classifiers.MultiLevelSplitGenerator

whether to suppress error output.

m_SimpleAttributeNames - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

whether to just number the attributes rather than compiling them from other attribute names.

m_SIMPLS_MATRIX_LOCAL - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilter

m_SIMPLS_MATRIX_LOCAL - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

m_Size - Variable in class adams.data.weka.predictions.FixedSizeErrorScaler

the size.

m_SizeLimit - Variable in class weka.filters.unsupervised.instance.WeightsBasedResample

the maximum size of the dataset to generate (<= 0 is off, <= 10 is percentage, > 10 is absolute).

m_SkipBuild - Variable in class adams.flow.transformer.WekaTrainClassifier

whether to skip the buildClassifier call for incremental classifiers.

m_SkipDrop - Variable in class weka.classifiers.trees.XGBoost

Probability of skipping the dropout procedure during the boosting operation.

m_SkipHistory - Variable in class weka.gui.explorer.AbstractExplorerPanelHandler

whether to skip the history panels.

m_SkipIdentical - Variable in class weka.core.neighboursearch.NewNNSearch

Whether to skip instances from the neighbours that are identical to the query instance.

m_SkipNominal - Variable in class adams.data.instancesanalysis.PCA

whether to skip nominal attributes (and not apply NominalToBinary).

m_SkipTrain - Variable in class weka.classifiers.meta.SocketFacade

whether to skip training.

m_slope - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

The slope

m_sort_packed - Variable in class adams.opt.optimise.genetic.PackDataDef

m_SortAttributes - Variable in class adams.gui.tools.wekainvestigator.datatable.DataTable

whether to sort the attributes alphabetically.

m_SortDefinitionPanel - Variable in class adams.gui.event.InstancesSortSetupEvent

the definition panel that was added/removed.

m_SortedEigens - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Sorted eigenvalues.

m_SortLabels - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions

whether to sort the labels.

m_SortLabels - Variable in class weka.classifiers.AggregateEvaluations

whether to sort the labels.

m_Source - Variable in class adams.data.io.input.InstanceReader

the data source for reading.

m_Source - Variable in class adams.flow.source.WekaDatabaseReader

the actual loader for loading the data.

m_Source - Variable in class adams.flow.transformer.WekaFileReader

the actual loader for loading the data.

m_Source - Variable in class adams.gui.tools.wekainvestigator.data.FileContainer

the source.

m_Source - Variable in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer

the source.

m_SourceCodeClass - Variable in class adams.flow.transformer.WekaClassifierInfo

the name of the source code class.

m_sourceFile - Variable in class weka.core.converters.SpreadSheetLoader

Holds the source of the data set.

m_SourceLookup - Variable in class adams.data.weka.datasetsplitter.ColumnSplitter

Mapping from the split attributes to their source in the original dataset.

m_Sources - Variable in class adams.data.instancesanalysis.FastICA

the sources.

m_SparseFormat - Variable in class adams.flow.source.WekaDatabaseReader

whether to output data in sparse format.

m_SparsePLS - Variable in class adams.data.instancesanalysis.pls.SparsePLS

the actual algorithm.

m_speedUpDistanceCompWithCanopies - Variable in class weka.clusterers.SAXKMeans

Whether to reducet the number of distance calcs done by k-means with canopies

m_SpinnerFolds - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

the number of folds.

m_SpinnerFolds - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

the number of folds.

m_SpinnerFolds - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

the number of folds.

m_SpinnerFolds - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

the number of folds.

m_SpinnerFolds - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

the number of folds.

m_SpinnerRuns - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

the number of runs.

m_SpinnerRuns - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

the number of runs.

m_SpinnerRuns - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

the number of runs.

m_SplitIndex - Variable in class weka.classifiers.trees.RandomRegressionForest.Node

m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

the split pane.

m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the split pane for left/right panels.

m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the split pane for left/right panels.

m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the split pane for left/right panels.

m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the split pane for left/right panels.

m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the split pane for left/right panels.

m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the split pane.

m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the split pane.

m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the split pane.

m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the split pane.

m_SplitPane - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the split pane.

m_SplitPane - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

the split pane.

m_SplitPane - Variable in class weka.gui.explorer.MultiExplorer

the split pane for the components.

m_SplitPercentage - Variable in class adams.flow.sink.WekaExperimentGenerator

the split-percentage to use (only train/test splits).

m_splitpoint - Variable in class weka.classifiers.meta.HighLowSplit

m_splitpoint - Variable in class weka.classifiers.meta.HighLowSplitSingleClassifier

m_Splits - Variable in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

the number of splits.

m_Splits - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

m_Splitter - Variable in class adams.flow.transformer.WekaDatasetSplit

The splitter to use.

m_SplitValue - Variable in class weka.classifiers.trees.RandomRegressionForest.Node

m_SpreadSheetType - Variable in class adams.data.conversion.WekaInstancesToSpreadSheet

the type of spreadsheet to use.

m_squaredErrors - Variable in class weka.clusterers.SAXKMeans

Holds the squared errors for all clusters.

m_SSR - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_SSR - Variable in class weka.classifiers.meta.LeastMedianSq

m_standardizeFilter - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Filter for standardizing the data

m_start - Variable in class adams.opt.genetic.Hermione

m_StartBut - Variable in class weka.gui.explorer.ExperimentPanel

Click to start running the experiment.

m_Statistic - Variable in class adams.flow.transformer.WekaInstancesStatistic

the statistic to generate.

m_Statistic - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

the statistic to generate.

m_Statistic - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

the statistic to generate.

m_Statistic - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

the statistic to generate.

m_Statistic - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

the statistic to generate.

m_Statistic - Variable in class weka.classifiers.meta.ClassifierCascade

the statistic to use for termination.

m_Statistics - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

the statistics to output.

m_Statistics - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

the statistics to output.

m_StatisticValue - Variable in class adams.flow.transformer.WekaEvaluationValuePicker

the comparison field.

m_StatisticValues - Variable in class adams.flow.transformer.WekaBootstrapping

the comparison fields.

m_StatisticValues - Variable in class adams.flow.transformer.WekaEvaluationValues

the comparison fields.

m_StatsTable - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

the statistics table.

m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the status bar.

m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab

the status bar.

m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

the status bar.

m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

the status bar.

m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab

the status bar.

m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

the status bar.

m_StatusBar - Variable in class adams.gui.visualization.instance.InstanceComparePanel

for displaying error messages.

m_StatusBar - Variable in class adams.gui.visualization.instance.InstanceExplorer

the status bar.

m_StatusBarDateFormat - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

for timestamps in the statusbar.

m_StatusMessageHandler - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

for notifications.

m_StatusMessageHandler - Variable in class adams.multiprocess.WekaCrossValidationExecution

for outputting notifications.

m_StatusMessageHandler - Variable in class adams.multiprocess.WekaCrossValidationJob

for outputting notifications.

m_StdDev - Variable in class weka.classifiers.meta.InputSmearing

the standard deviation multiplier to use.

m_StdDev - Variable in class weka.filters.unsupervised.attribute.InputSmearing

the standard deviation multiplier to use.

m_StdDevs - Variable in class weka.classifiers.functions.LinearRegressionJ

The attribute standard deviations

m_StdDevs - Variable in class weka.filters.supervised.attribute.PLSFilterExtended

m_StdDevs - Variable in class weka.filters.unsupervised.attribute.InputSmearing

the std devs to use.

m_StopBut - Variable in class weka.gui.explorer.ExperimentPanel

Click to stop a running experiment.

m_StopFlowIfCanceled - Variable in class adams.flow.source.WekaSelectDataset

whether to stop the flow if canceled.

m_StopMode - Variable in class adams.flow.source.WekaSelectDataset

how to perform the stop.

m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

whether the build was stopped.

m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

whether the build was stopped.

m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

whether the build was stopped.

m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

whether the build was stopped.

m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

whether the build was stopped.

m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup

whether the experiment got stopped.

m_Stopped - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

whether the experiment was stopped.

m_Stopped - Variable in class adams.multiprocess.WekaCrossValidationExecution

whether the execution has been stopped.

m_Stopped - Variable in class weka.classifiers.evaluation.StoppableEvaluation

whether the execution was stopped.

m_Stopped - Variable in class weka.classifiers.lazy.LWLSynchro

whether the classifier was stopped.

m_Stopped - Variable in class weka.classifiers.lazy.LWLSynchroSplit

whether the classifier was stopped.

m_Stopped - Variable in class weka.classifiers.meta.FilteredClassifierExt

whether the classifier was stopped.

m_Stopped - Variable in class weka.classifiers.MultiLevelSplitGenerator

whether the generation got stopped.

m_Stopped - Variable in class weka.classifiers.StoppableClassifier

whether the classifier was stopped.

m_Stopped - Variable in class weka.classifiers.StoppableRandomizableClassifier

whether the classifier was stopped.

m_Stopped - Variable in class weka.classifiers.StoppableSingleClassifierEnhancer

whether the classifier was stopped.

m_Stopping - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

whether the execution is in the process of stopping.

m_Stopping - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

whether the execution is in the process of stopping.

m_Storage - Variable in class adams.flow.transformer.WekaNearestNeighborSearch

the storage item.

m_StorageName - Variable in class adams.data.conversion.MapToWekaInstance

the name of the stored value.

m_StorageName - Variable in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

the name of the datasets in the internal storage.

m_StoredResults - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the cache for results.

m_StoredResults - Variable in class adams.opt.optimise.GeneticAlgorithm

the cache for results.

m_StoreFilename - Variable in class adams.flow.transformer.WekaTextDirectoryReader

whether to store the filename as extra attribute.

m_Stratify - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

whether to stratify the data (in case of nominal class).

m_Stratify - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

whether to stratify the data (in case of nominal class).

m_Stratify - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

whether to stratify the data (in case of nominal class).

m_Stratify - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator

whether to stratify the data (in case of nominal class).

m_Stratify - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

whether to stratify the data (in case of nominal class).

m_Stratify - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator

whether to stratify the data (in case of nominal class).

m_Strict - Variable in class adams.flow.transformer.WekaInstancesMerge

whether to fail if IDs not unique.

m_structure - Variable in class weka.core.converters.SpreadSheetLoader

Holds the determined structure (header) of the data set.

m_Structure - Variable in class adams.data.io.input.InstanceReader

the current data structure.

m_Structure - Variable in class adams.flow.source.WekaDatabaseReader

the structure.

m_Structure - Variable in class adams.flow.transformer.WekaFileReader

the structure.

m_SubProcess - Variable in class weka.filters.FlowFilter

the flow for processing the data.

m_Subsample - Variable in class weka.classifiers.trees.XGBoost

Subsample ratio of the training instances.

m_SubSample - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_SubSample - Variable in class weka.classifiers.meta.LeastMedianSq

m_subset - Variable in class weka.classifiers.meta.Corr

m_SummaryFilter - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

The filter which performs attribute summarising.

m_SumOfEigenValues - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

sum of the eigenvalues.

m_sumOfWeightsLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

Displays the sum of instance weights

m_SupervisedClassSplitter - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Column-splitter for removing the supervised filter class.

m_SupplementaryData - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

supplementary data.

m_SupplementaryName - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

the supplementary name.

m_SuppliedPrefix - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the supplied prefix.

m_SuppliedReferenceDataset - Variable in class weka.filters.unsupervised.instance.AlignDataset

the supplied test set, when using programmatically.

m_SuppliedTestSet - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances

the supplied test set, when using programmatically.

m_Support - Variable in class weka.classifiers.meta.ConsensusOrVote

the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.

m_Support - Variable in class weka.classifiers.meta.Veto

the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.

m_Support - Variable in class weka.gui.explorer.SqlPanel

Manages sending notifications to people when we change the set of working instances.

m_Supported - Variable in class adams.data.instancesanalysis.PCA

the supported attributes.

m_suppressErrorMessage - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

If true, suppress error message if no useful attribute was found

m_SuppressModelOutput - Variable in class weka.classifiers.meta.AbstainingCascade

whether to suppress the model output.

m_SuppressModelOutput - Variable in class weka.classifiers.meta.ConsensusOrVote

whether to suppress the model output.

m_SuppressModelOutput - Variable in class weka.classifiers.meta.SuppressModelOutput

whether to suppress the model output.

m_SuppressModelOutput - Variable in class weka.classifiers.meta.ThresholdedBinaryClassification

whether to suppress the model output.

m_SuppressModelOutput - Variable in class weka.classifiers.meta.Veto

whether to suppress the model output.

m_SuppressModelOutput - Variable in class weka.classifiers.meta.VotedImbalance

whether to suppress the model output.

m_SwapAxes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

whether to swap the axes.

m_SwapRowsAndColumns - Variable in class adams.flow.transformer.WekaExperimentEvaluation

whether to swap rows and columns.

m_SwapRowsAndColumns - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

whether to swap rows and columns.

m_t - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive

The vector of target values.

m_t - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights

The vector of target values.

m_t - Variable in class weka.classifiers.functions.GaussianProcessesWeighted

The vector of target values.

m_t - Variable in class weka.classifiers.functions.GPD

The vector of target values.

m_t1 - Variable in class weka.clusterers.SAXKMeans

The t1 radius to pass through to Canopy

m_t2 - Variable in class weka.clusterers.SAXKMeans

The t2 radius to pass through to Canopy

m_TabbedPane - Variable in class adams.flow.sink.WekaAttributeSummary

the tabbed pane with the attribute visualizations (if more than one in range).

m_TabbedPane - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the tabbed pane for the tabs.

m_TabbedPane - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

the tabbed pane with the generated output.

m_TabbedPane - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

the tabbed pane in case multiple panels get displayed.

m_TabbedPane - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

the tabbed pane in case multiple panels get displayed.

m_TabbedPane - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the tabbed pane.

m_TabbedPane - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

the tabbed pane for datasets and classifiers.

m_TabbedPane - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

the tabbed pane for datasets and classifiers.

m_TabbedPane - Variable in class adams.gui.visualization.instance.InstanceExplorer

the tabbed pane for the data to display.

m_TabbedPane - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the tabbed pane.

m_TabbedPane - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the tabbed pane for displaying the data.

m_TabbedPaneData - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the tabbed pane for the data.

m_TabbedPanePlots - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the tabbed pane for the plots.

m_TabbedPanePlots - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the tabbed pane for the plots.

m_TabbedPanePlots - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the tabbed pane for the plots.

m_Table - Variable in class adams.flow.sink.WekaInstancesDisplay

the table with the instances.

m_Table - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

the table.

m_Table - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

The table displaying attribute names and selection status

m_Table - Variable in class adams.gui.visualization.instances.InstancesColumnComboBox

the associated table.

m_Table - Variable in class adams.gui.visualization.instances.InstancesPanel

the table.

m_TableCache - Variable in class adams.gui.tools.wekainvestigator.tab.DataTab

the cache for the tables.

m_TableData - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the table for displaying the instances.

m_TableData - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

the table with the dataset.

m_TableName - Variable in class adams.flow.sink.WekaDatabaseWriter

protected the name of the table to store the data in.

m_TableResult - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

the generated spreadsheet.

m_TableResults - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

the table with the statistics.

m_Target - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage

the current target.

m_Template - Variable in class adams.data.conversion.MapToWekaInstance

the template.

m_Template - Variable in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels

the vote template.

m_Template - Variable in class adams.flow.transformer.wekaensemblegenerator.VotedModels

the vote template.

m_Template - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

the template.

m_Template - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds

the vote template.

m_Template - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

the template.

m_Template - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

the template.

m_Template - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

the template.

m_Test - Variable in class adams.flow.transformer.WekaClassifierRanker

the callable actor to obtain the test dataset for train/test evaluation from.

m_Test - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

the test data to evaluate with (if folds less than 2).

m_Test - Variable in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob

the data to use for testing.

m_Test - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

the data to use for testing.

m_Test - Variable in class adams.multiprocess.WekaCrossValidationJob

the test set.

m_TestAttributes - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer

the additional attributes from the test data to add to the output.

m_TestBase - Variable in class adams.flow.transformer.WekaExperimentEvaluation

the test base.

m_TestBase - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

the test base.

m_TestData - Variable in class adams.flow.transformer.WekaGeneticAlgorithm

the storage name of the test data.

m_TestData - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

the test data to use (can be null).

m_Tester - Variable in class adams.flow.transformer.WekaExperimentEvaluation

the tester class to use.

m_Tester - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

the tester class to use.

m_TestInstances - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the data to use for evaluation (if null, cross-validation is used).

m_TestLoader - Variable in class weka.gui.explorer.ExperimentPanel

The loader used to load the user-supplied test set (if any).

m_Testset - Variable in class adams.flow.transformer.WekaTestSetClustererEvaluator

the name of the callable trainset provider.

m_Testset - Variable in class adams.flow.transformer.WekaTestSetEvaluator

the name of the callable trainset provider.

m_TestSet - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances

the file containing the test set.

m_TestSplitName - Variable in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

the split to use for testing.

m_TestSplitName - Variable in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

the split to use for testing.

m_TextActual - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

the text with the actual column index.

m_TextAdditional - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

the columns with the additional data to store.

m_TextAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the additional attribute range.

m_TextAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the additional attribute range.

m_TextAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the additional attribute range.

m_TextArea - Variable in class adams.gui.tools.DatasetCompatibilityPanel

the text area to output the results in.

m_TextArea - Variable in class adams.gui.tools.wekamultiexperimenter.LogPanel

the text area for outputting the log.

m_TextAreaCodeOutput - Variable in class adams.gui.tools.WekaOptionsConversionPanel

the text area for the output.

m_TextAreaInput - Variable in class adams.gui.tools.WekaOptionsConversionPanel

the text area for the input.

m_TextAreaKey - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

for displaying the results.

m_TextAreaResults - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel

for displaying the results.

m_TextAttributeRange - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

the attribute range.

m_TextAttributeRange - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab

the attribute range.

m_TextAttributeRange - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

the attribute range.

m_TextAttributeRange - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the attribute range.

m_TextAttributeRange - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

the edit field for the range.

m_TextAttributeRange - Variable in class adams.gui.visualization.instance.LoadDatasetDialog

the text field for the attribute range.

m_TextClassDistribution - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

the columns with the class distribution columns range.

m_TextCommon - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the IDs present in both datasets.

m_TextEvaluation - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

the evaluation parameter.

m_TextEvaluation - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

the evaluation parameter.

m_TextFirstRange - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the text field for the first attribute range.

m_TextMaxAttributeNames - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the maximum number of attribute names.

m_TextMaxAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the maximum number of attributes.

m_TextNotes - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

the notes.

m_TextOnlyFirst - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the IDs only present in the first dataset.

m_TextOnlySecond - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the IDs only present in the second dataset.

m_TextPassword - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel

the password.

m_TextPercentage - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

the split percentage.

m_TextPercentage - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

the split percentage.

m_TextPercentage - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

the split percentage.

m_TextPredicted - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

the text with the predicted column index.

m_TextRepetitions - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

the number of repetitions.

m_TextRepetitions - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

the number of repetitions.

m_TextSecondRange - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the text field for the second attribute range.

m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

the seed value.

m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

the seed value.

m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

the seed value.

m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

the seed value.

m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

the seed value.

m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

the seed value.

m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

the seed value.

m_TextSelectedAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

the currently selected attributes.

m_TextSignificance - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

the significance.

m_TextStructure - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab

the text area with the structure output.

m_TextTestSplitName - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

the text with the name for the test split.

m_TextTrainSplitName - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

the text with the name for the train split.

m_TextURL - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel

the JDBC URL.

m_TextUser - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel

the user name.

m_TextVariance - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

the variance.

m_TextWeight - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

the text with the weight column index.

m_threadRun - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

True if the thread m_hc above is running.

m_Threshold - Variable in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

the percentage to the threshold.

m_Threshold - Variable in class adams.tools.CompareDatasets

the threshold for listing correlations.

m_Threshold - Variable in class weka.classifiers.meta.ClassifierCascade

the threshold for the statistic for termination.

m_ThresholdCheck - Variable in class weka.classifiers.meta.ClassifierCascade

whether to go below or above the threshold.

m_Thresholds - Variable in class weka.classifiers.meta.VotedImbalance

the thresholds to use (pair: probability minority class = num balanced).

m_Timeout - Variable in class weka.classifiers.meta.SocketFacade

the timeout for the socket.

m_Timestamp - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

the timestamp.

m_TimestampCache - Variable in class adams.gui.tools.wekainvestigator.tab.DataTab

the cache for the last update cache.

m_TimestampCache - Variable in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

the cache for the last update cache.

m_Title - Variable in class adams.gui.tools.wekainvestigator.job.InvestigatorJob

the title of the job.

m_Title - Variable in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob

the title of the job.

m_Title - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary

the title.

m_Title - Variable in class weka.gui.explorer.ExplorerEntryPanel

the parent's default title.

m_TitleClassDetails - Variable in class adams.flow.transformer.WekaEvaluationSummary

the title to use for the summary.

m_TitleGenerator - Variable in class weka.gui.explorer.ExplorerExt

for generating the title.

m_TitleMatrix - Variable in class adams.flow.transformer.WekaEvaluationSummary

the title to use for the matrix.

m_TitleNameColumn - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

the title of the name column.

m_TitleSummary - Variable in class adams.flow.transformer.WekaEvaluationSummary

the title to use for the summary.

m_TitleValueColumn - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

the title of the value column.

m_Tokenizers - Variable in class weka.core.tokenizers.MultiTokenizer

the tokenizers to use.

m_Tokens - Variable in class weka.core.tokenizers.MultiTokenizer

the collected tokens.

m_Tol - Variable in class adams.data.instancesanalysis.pls.KernelPLS

Inner NIPALS loop improvement tolerance

m_Tol - Variable in class adams.data.instancesanalysis.pls.NIPALS

Inner NIPALS loop improvement tolerance

m_Tol - Variable in class adams.data.instancesanalysis.pls.PRM

Inner loop improvement tolerance

m_Tol - Variable in class adams.data.instancesanalysis.pls.SparsePLS

Inner NIPALS loop improvement tolerance

m_TolerateHeaderChanges - Variable in class adams.data.instances.AbstractInstanceGenerator

whether to tolerate header changes.

m_ToolTipMaxColumns - Variable in class adams.gui.visualization.instance.InstancePanel

the maximum number of columns for the tooltip.

m_ToolTipMaxRows - Variable in class adams.gui.visualization.instance.InstancePanel

the maximum number of rows for the tooltip.

m_TopK - Variable in class weka.classifiers.trees.XGBoost

The number of top features to select.

m_topOfTree - Variable in class weka.classifiers.trees.m5.Rule2

the top of the m5 tree for this rule

m_Train - Variable in class adams.flow.transformer.WekaClassifierRanker

the callable actor to obtain the training dataset from.

m_Train - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob

the train data to evaluate with.

m_Train - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

the data to use for training.

m_Train - Variable in class adams.multiprocess.WekaCrossValidationJob

the training set.

m_Train - Variable in class weka.classifiers.lazy.LWLDatasetBuilder

The training instances used for classification.

m_TrainCopy - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Keep a copy for the class attribute (if set).

m_Trained - Variable in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder

whether the column finder was trained already.

m_Trained - Variable in class adams.data.weka.rowfinder.AbstractTrainableRowFinder

whether the row finder was trained already.

m_TrainInstances - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

The data to transform analyse/transform.

m_TrainSplitName - Variable in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

the split to use for training.

m_TrainSplitName - Variable in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

the split to use for training.

m_TrainStart - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

the time when training commenced.

m_TransformedData - Variable in class weka.classifiers.functions.LinearRegressionJ

Variable for storing transformed training data.

m_TransformedFormat - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

The header for the transformed data format.

m_TransformFilter - Variable in class weka.classifiers.functions.LinearRegressionJ

The filter storing the transformation from nominal to binary attributes.

m_TreeMethod - Variable in class weka.classifiers.trees.XGBoost

The tree construction algorithm.

m_tstatIntercept - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

t-statistic of the intercept

m_tstatSlope - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

t-statistic of the slope

m_TurnOffAbstaining - Variable in class weka.classifiers.meta.AbstainingClassifierWrapper

whether to turn off abstaining.

m_TweedieVariancePower - Variable in class weka.classifiers.trees.XGBoost

Parameter that controls the variance of the Tweedie distribution.

m_Type - Variable in class adams.flow.transformer.WekaClassifierInfo

the type of information to generate.

m_Type - Variable in class adams.flow.transformer.WekaClustererInfo

the type of information to generate.

m_Type - Variable in class adams.flow.transformer.WekaEvaluationInfo

the type of information to generate.

m_Type - Variable in class adams.flow.transformer.WekaExtractArray

the type of extraction.

m_Type - Variable in class adams.flow.transformer.WekaInstancesInfo

the type of information to generate.

m_Type - Variable in class adams.gui.event.InstancesSortSetupEvent

what type of event occurred.

m_Type - Variable in class adams.gui.event.WekaInvestigatorDataEvent

the event type.

m_Type - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric

the type of conversion to perform.

m_Types - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis

the types of the attributes.

m_Undo - Variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

the undo manager.

m_Undo - Variable in class adams.gui.visualization.instance.InstancePanel

the undo manager.

m_UndoEnabled - Variable in class adams.gui.tools.wekainvestigator.data.DataContainerList

whether undo is enabled.

m_UndoEnabled - Variable in class adams.gui.visualization.instances.InstancesTableModel

whether undo is active

m_UndoHandler - Variable in class adams.gui.visualization.instances.InstancesTableModel

optional undo handler.

m_UndoList - Variable in class adams.gui.visualization.instances.InstancesTableModel

the undo list (contains temp.

m_UniqueID - Variable in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

The name of the attribute to use as the merge key.

m_UniqueID - Variable in class adams.flow.transformer.WekaInstancesMerge

the string or numeric attribute to use as unique identifier for rows.

m_UniqueIDAtts - Variable in class adams.flow.transformer.WekaInstancesMerge

the unique ID attributes.

m_UniqueLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel

Displays the number of unique values

m_UniqueValues - Variable in class weka.classifiers.LeaveOneOutByValueGenerator

the unique values.

m_Unset - Variable in class adams.flow.transformer.WekaClassSelector

whether to unset the class index.

m_Unsupported - Variable in class adams.data.instancesanalysis.PCA

the unsupported attributes.

m_UpdateContainerColor - Variable in class adams.gui.visualization.instance.ReportColorInstancePaintlet

whether to update the color of the container.

m_UpdateHeader - Variable in class weka.filters.unsupervised.instance.RemoveWithLabels

whether to update the header.

m_UpdateInterval - Variable in class adams.gui.visualization.instance.SimpleInstancePanelUpdater

the interval of tokens processed after which to update the display.

m_Updater - Variable in class adams.flow.sink.WekaInstanceViewer

the updater to use.

m_Updater - Variable in class weka.classifiers.trees.XGBoost

Choice of algorithm to fit linear model.

m_UpdateRelationName - Variable in class adams.flow.transformer.WekaMultiLabelSplitter

whether to use the class attribute name as new relation name.

m_UpdateWait - Variable in class weka.classifiers.functions.FakeClassifier

the update wait time in msec.

m_Upper - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

the upper value to compute.

m_Upper - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

the upper value to compute.

m_Upper - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

the upper value to compute.

m_Upper - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

the upper value to compute.

m_URL - Variable in class adams.flow.sink.WekaDatabaseWriter

the database URL to query.

m_URL - Variable in class adams.flow.source.WekaDatabaseReader

the database URL to query.

m_URL - Variable in class adams.gui.tools.wekainvestigator.data.DatabaseContainer

the database URL.

m_UseAbsoluteError - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer

whether to use absolute errors.

m_UseAbsoluteError - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

whether to use absolute errors.

m_UseAllK - Variable in class weka.classifiers.lazy.LWLDatasetBuilder

True if m_kNN should be set to all instances.

m_UseColumnNamesAsClassLabels - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions

whether to use the column name as class labels.

m_UseCustomLoader - Variable in class adams.flow.transformer.WekaFileReader

whether to use a custom converter.

m_UseCustomLoader - Variable in class adams.flow.transformer.WekaReorderAttributesToReference

whether to use a custom converter.

m_UseCustomLoader - Variable in class weka.filters.unsupervised.instance.AlignDataset

whether to use a custom loader for the reference data.

m_UseCustomLoader - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances

whether to use a custom loader for the test set.

m_UseCustomPaintlet - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

whether to use a custom paintlet.

m_UseCustomSaver - Variable in class adams.flow.sink.WekaFileWriter

whether to use a custom converter.

m_UseError - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

whether to use the error for the cross-size.

m_UseFilename - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

whether to use the filename (w/o path) instead of relationname.

m_UseFilename - Variable in class weka.experiment.ExtExperiment

whether to use the filename (w/o path) instead of relationname.

m_UseFixedMinMax - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges

whether to use fixed min/max for manual bin calculation.

m_UseMedian - Variable in class adams.flow.transformer.wekaclusterer.ClusterCenters

compute median instead of mean.

m_UseModelResetVariable - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

whether to use a variable to monitor for changes, triggering resets of the model.

m_UseOriginalIndices - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer

whether to align output with original dataset (if possible).

m_UseOuterWindow - Variable in class adams.flow.source.WekaSelectDataset

whether to use the outer window as parent.

m_UsePrefix - Variable in class adams.flow.transformer.WekaInstancesMerge

whether to prefix the attribute names of each dataset with an index.

m_UseProbabilities - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

whether to use the probabilities rather 0 and 1.

m_User - Variable in class adams.flow.sink.WekaDatabaseWriter

the database user to use for connecting.

m_User - Variable in class adams.flow.source.WekaDatabaseReader

the database user to use for connecting.

m_User - Variable in class adams.gui.tools.wekainvestigator.data.DatabaseContainer

the user.

m_UseRelationNameAsFilename - Variable in class adams.flow.sink.WekaFileWriter

whether to use the relation name as filename.

m_UseRelationNameAsFilename - Variable in class adams.flow.transformer.WekaInstanceDumper

whether to use the relation name as filename.

m_UseRelationNameAsTable - Variable in class adams.flow.sink.WekaDatabaseWriter

whether to use the relation as table name.

m_UseRowAttribute - Variable in class adams.tools.CompareDatasets

whether to use the row attribute or not.

m_UseSecondEvaluation - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob

whether to use second evaluation.

m_UseSecondEvaluation - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

whether to use second evaluation with different seed.

m_useUnpruned - Variable in class weka.classifiers.trees.m5.M5Base2

Do not prune tree/rules

m_UseViews - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator

whether to use views.

m_UseViews - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

whether to use views.

m_UseViews - Variable in class adams.multiprocess.WekaCrossValidationExecution

whether to use views.

m_UseViews - Variable in class weka.classifiers.AbstractSplitGenerator

whether to use views.

m_UseWekaEditors - Static variable in class adams.gui.goe.WekaEditorsRegistration

whether to use the Weka editors.

m_UseY - Variable in class adams.data.instance.InstancePointComparator

whether to compare Y or X.

m_Value - Variable in class adams.flow.transformer.WekaSetInstancesValue

the value to set.

m_Value - Variable in class adams.flow.transformer.WekaSetInstanceValue

the value to set.

m_VariableName - Variable in class adams.flow.template.InstanceDumperVariable

the variable to update.

m_VariableName - Variable in class adams.flow.transformer.WekaInstanceBuffer

the variable to listen to.

m_VariableName - Variable in class adams.flow.transformer.WekaNearestNeighborSearch

the variable to listen to.

m_variance - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_Variance - Variable in class adams.data.instancesanalysis.PCA

the variance to cover.

m_VCPLS - Variable in class adams.data.instancesanalysis.pls.VCPLS

the actual algorithm.

m_Verbosity - Variable in class weka.classifiers.trees.XGBoost

Verbosity of printing messages.

m_VersusFitOptions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Options for the vs fit

m_VersusOrderOptions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Options for the vs order

m_ViewDialogs - Variable in class adams.gui.visualization.instance.InstancePanel

the dialog for displaying a sequence.

m_Viewer - Variable in class weka.gui.explorer.SqlPanel

the SQL panel

m_Visible - Variable in class adams.gui.visualization.instance.InstanceContainer

whether the instance is visible.

m_VisualizePanel - Variable in class adams.flow.sink.WekaClassifierErrors

the Weka plot panel.

m_VisualizePanel - Variable in class adams.flow.sink.WekaCostCurve

the panel.

m_VisualizePanel - Variable in class adams.flow.sink.WekaInstancesPlot

the text area.

m_VisualizePanel - Variable in class adams.flow.sink.WekaMarginCurve

the panel.

m_VisualizePanel - Variable in class adams.flow.sink.WekaThresholdCurve

the text area.

m_Vote - Variable in class weka.classifiers.meta.ConsensusOrVote

the ensemble.

m_Vote - Variable in class weka.classifiers.meta.Veto

the ensemble.

m_VotingType - Variable in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs

the type of voting to perform .

m_W - Variable in class adams.data.instancesanalysis.pls.PLS1

the W matrix

m_W - Variable in class adams.data.instancesanalysis.pls.SIMPLS

the W matrix

m_WaitForJobs - Variable in class adams.multiprocess.WekaCrossValidationExecution

whether to wait for jobs to finish when stopping.

m_WaveNo - Variable in class weka.filters.unsupervised.attribute.Detrend

the extracted wave numbers.

m_WaveNo - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

the extracted wave numbers.

m_WaveNo - Variable in class weka.filters.unsupervised.attribute.SimpleDetrend

the fake wave numbers.

m_WaveNoRegExp - Variable in class weka.filters.unsupervised.attribute.Detrend

the regexp for extracting the wavenumbers from the attribute name.

m_WaveNoRegExp - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

the regexp for extracting the wavenumbers from the attribute name.

m_weight - Variable in class weka.classifiers.meta.AbstainLeastMedianSq

m_weight - Variable in class weka.classifiers.meta.LeastMedianSq

m_Weight - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions

the (optional) column with the instance weights.

m_Weight - Variable in class weka.classifiers.functions.FromPredictions

the column with the error values (optional).

m_WeightIndex - Variable in class weka.classifiers.functions.FromPredictions

the weight column index.

m_WeightKernel - Variable in class weka.classifiers.lazy.LWLDatasetBuilder

The weighting kernel method currently selected.

m_WeightKernel - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

The weighting kernel method currently selected.

m_weights - Variable in class adams.opt.optimise.GeneticAlgorithm.GAJob

weights.

m_Weights - Variable in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

the property for the weights (optional).

m_windows - Variable in class weka.filters.unsupervised.attribute.PAA

number of windows.

m_windows - Variable in class weka.filters.unsupervised.attribute.SAX

number of windows.

m_WithReplacement - Variable in class adams.flow.transformer.WekaBootstrapping

whether to use with replacement or not.

m_Wizard - Variable in class adams.gui.tools.weka.AppendDatasetsPanel

the wizard pane.

m_Wizard - Variable in class adams.gui.tools.weka.BatchFilterDatasetsPanel

the wizard pane.

m_Worker - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

for executing operations (loading files etc).

m_Worker - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

whether the evaluation is currently running.

m_Worker - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

whether the evaluation is currently running.

m_WorkspaceFileChooser - Variable in class weka.gui.explorer.MultiExplorer

the file chooser for the workspaces.

m_Writer - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

the spreadsheet writer to use.

m_Writer - Variable in class weka.core.converters.SpreadSheetSaver

the spreadsheet writer to use.

m_WriterFileFilters - Static variable in class adams.gui.chooser.AdamsExperimentFileChooser

the file filters for the writers.

m_WriterFileFilters - Static variable in class adams.gui.chooser.WekaFileChooser

the file filters for the writers.

m_Writing - Variable in class adams.flow.transformer.WekaInstanceDumper

whether currently writing to disk.

m_X - Variable in class adams.data.instance.InstancePoint

the X value.

m_XIndices - Variable in class weka.filters.supervised.attribute.MultiPLS

the indices of the X attributes.

m_XRegExp - Variable in class weka.filters.supervised.attribute.MultiPLS

the regular expression for the X columns.

m_Y - Variable in class adams.data.instance.InstancePoint

the Y value.

m_YIndices - Variable in class weka.filters.supervised.attribute.MultiPLS

the indices of the Y attributes.

m_YRegExp - Variable in class weka.filters.supervised.attribute.MultiPLS

the regular expression for the Y columns.

m_zerocount - Variable in class adams.opt.optimise.GeneticAlgorithm

m_ZoomOverview - Variable in class adams.flow.sink.WekaInstanceViewer

whether to display the zoom overview.

M5Base2 - Class in weka.classifiers.trees.m5

M5Base.

M5Base2() - Constructor for class weka.classifiers.trees.m5.M5Base2

Constructor

M5P2 - Class in weka.classifiers.trees

M5Base.

M5P2() - Constructor for class weka.classifiers.trees.M5P2

Creates a new M5P instance.

MAE - adams.flow.transformer.WekaClassifierRanker.Measure

evaluation via: Mean absolute error.

MAE - adams.opt.genetic.Measure

Mean absolute error.

MAE - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure

evaluation via: Mean absolute error.

main(String[]) - Static method in class adams.data.io.input.ArffSpreadSheetReader

Runs the reader from the command-line.

main(String[]) - Static method in class adams.data.io.input.JSONSpreadSheetReader

Runs the reader from the command-line.

main(String[]) - Static method in class adams.data.io.input.LibSVMSpreadSheetReader

Runs the reader from the command-line.

main(String[]) - Static method in class adams.data.io.input.MatlabSpreadSheetReader

Runs the reader from the command-line.

main(String[]) - Static method in class adams.data.io.input.SVMLightSpreadSheetReader

Runs the reader from the command-line.

main(String[]) - Static method in class adams.data.io.input.XrffSpreadSheetReader

Runs the reader from the command-line.

main(String[]) - Static method in class adams.gui.goe.WekaGenericArrayEditorDialog

For testing only.

main(String[]) - Static method in class adams.gui.goe.WekaGenericObjectEditorDialog

For testing only.

main(String[]) - Static method in class adams.gui.InstanceCompare

Starts the frame.

main(String[]) - Static method in class adams.gui.tools.wekainvestigator.InvestigatorManagerPanel

Just for testing.

main(String[]) - Static method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

Tests out the attribute summary panel from the command line.

main(String[]) - Static method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

Tests out the instance summary panel from the command line.

main(String[]) - Static method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter

Starts the experimenter environment.

main(String[]) - Static method in class adams.gui.wizard.WekaPropertySheetPanelPage

For testing only.

main(String[]) - Static method in class adams.opt.optimise.GeneticAlgorithm

main(String[]) - Static method in class weka.attributeSelection.LinearRegressionAttributeEval

Main method for running this class from commandline.

main(String[]) - Static method in class weka.attributeSelection.PLS1AttributeEval

Main method for running this class from commandline.

main(String[]) - Static method in class weka.attributeSelection.SIMPLSAttributeEval

Main method for running this class from commandline.

main(String[]) - Static method in class weka.classifiers.functions.ClassificationViaPLS

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.functions.FakeClassifier

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.functions.GaussianProcessesAdaptive

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.functions.GaussianProcessesNoWeights

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.functions.GaussianProcessesWeighted

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.functions.GeneticAlgorithm

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.functions.GPD

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.functions.LinearRegressionJ

Generates a linear regression function predictor.

main(String[]) - Static method in class weka.classifiers.functions.MathExpressionClassifier

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.functions.PLSClassifierWeighted

Main method for running this classifier from commandline.

main(String[]) - Static method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings

Main method for running this classifier from commandline.

main(String[]) - Static method in class weka.classifiers.functions.PLSWeighted

Main method for running this classifier from commandline.

main(String[]) - Static method in class weka.classifiers.functions.PyroProxy

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.functions.SimpleLinearRegressionIntervalEstimator

Generates a linear regression function predictor.

main(String[]) - Static method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Main method for testing this class

main(String[]) - Static method in class weka.classifiers.lazy.LWLIntervalEstimator

Main method for executing this classifier.

main(String[]) - Static method in class weka.classifiers.lazy.LWLSynchro

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.lazy.LWLSynchroPrefilter

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.lazy.LWLSynchroSplit

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.AbstainAttributePercentile

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.AbstainAverage

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.AbstainingClassifierWrapper

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.AbstainLeastMedianSq

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.AbstainVote

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.ClassificationViaRegressionD

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.ClassifierCascade

Main method for executing the class.

main(String[]) - Static method in class weka.classifiers.meta.Corr

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.FilteredClassifierExt

Main method for running this classifier.

main(String[]) - Static method in class weka.classifiers.meta.HighLowSplit

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.HighLowSplitSingleClassifier

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.InputSmearing

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.meta.LeastMedianSq

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.LogClassRegressor

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.LogTargetRegressor

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.MinMaxLimits

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.PartitionedStacking

Main method for running this classifier.

main(String[]) - Static method in class weka.classifiers.meta.PeakTransformed

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.SubsetEnsemble

Main method for running this class from commandline.

main(String[]) - Static method in class weka.classifiers.meta.SumTransformed

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.ThreadSafeClassifierWrapper

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.meta.VotedImbalance

Main method for running this class from commandline.

main(String[]) - Static method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper

Main method for running this class.

main(String[]) - Static method in class weka.classifiers.trees.M5P2

Main method by which this class can be tested

main(String[]) - Static method in class weka.classifiers.trees.RandomModelTrees

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.trees.RandomRegressionForest

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.trees.XGBoost

Main method for running this class.

main(String[]) - Static method in class weka.clusterers.SAXKMeans

Main method for executing this class.

main(String[]) - Static method in class weka.core.converters.SimpleArffLoader

Main method.

main(String[]) - Static method in class weka.core.converters.SimpleArffSaver

Main method.

main(String[]) - Static method in class weka.core.converters.SpreadSheetLoader

Main method.

main(String[]) - Static method in class weka.core.converters.SpreadSheetSaver

Main method.

main(String[]) - Static method in class weka.experiment.ResultMatrixAdamsCSV

for testing only.

main(String[]) - Static method in class weka.experiment.ResultMatrixMediaWiki

for testing only.

main(String[]) - Static method in class weka.filters.FilteredFilter

Main method for running this filter.

main(String[]) - Static method in class weka.filters.SerializedFilter

Main method for running this filter.

main(String[]) - Static method in class weka.filters.supervised.attribute.MultiPLS

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.supervised.attribute.PLS

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.supervised.attribute.PLSFilterWithLoadings

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.supervised.attribute.YGradientEPO

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.supervised.attribute.YGradientGLSW

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.AndrewsCurves

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.AnyToString

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.CorrelationMatrix

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.Detrend

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.DownSample

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.EquiDistance

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.FastWavelet

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.FFT

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.InputSmearing

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.JoinAttributes

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.LogTransform

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.MergeManyAttributes

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

runs the filter with the given arguments.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Main method for executing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.NominalToNumeric

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.NormalizeAdaptive

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.PAA

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Main method for executing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.RowSum

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.SAX

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.SetMissingValue

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.SimpleDetrend

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.SpellChecker

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.attribute.StringToDate

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.AlignDataset

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.KeepRange

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.instance.LatestRecords

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.instance.MultiRowProcessor

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveDuplicates

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveTestInstances

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveWithLabels

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveWithWeights

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.RowNorm

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.SafeRemoveRange

Main method for running this filter from command-line.

main(String[]) - Static method in class weka.filters.unsupervised.instance.Scale

Main method for testing this class.

main(String[]) - Static method in class weka.filters.unsupervised.instance.Sort

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.instance.SortOnAttribute

Main method for running this filter.

main(String[]) - Static method in class weka.filters.unsupervised.instance.WeightsBasedResample

Main method for testing this class.

main(String[]) - Static method in class weka.gui.explorer.ExperimentPanel

Tests out the Experiment panel from the command line.

main(String[]) - Static method in class weka.gui.explorer.ExplorerExt

Starts the explorer environment.

main(String[]) - Static method in class weka.gui.explorer.MultiExplorer

Starts the explorer environment.

main(String[]) - Static method in class weka.gui.explorer.SqlPanel

For testing only.

mainFilterTipText() - Method in class weka.filters.FilteredFilter

Returns the tip text for this property.

MAJORITY_VOTING_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType

MAJORITY_VOTING_RULE - Static variable in class weka.classifiers.meta.AbstainVote

combination rule: Majority Voting (only nominal classes)

makeClassLastTipText() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns the tip text for this property.

MakeCompatibleDatasets - Class in adams.gui.menu

For making compatible ARFF datasets.

MakeCompatibleDatasets() - Constructor for class adams.gui.menu.MakeCompatibleDatasets

Initializes the menu item with no owner.

MakeCompatibleDatasets(AbstractApplicationFrame) - Constructor for class adams.gui.menu.MakeCompatibleDatasets

Initializes the menu item.

makeThreadSafeTipText() - Method in class adams.flow.transformer.WekaModelReader

Returns the tip text for this property.

MANUAL - weka.classifiers.meta.MinMaxLimits.LimitHandling

manually supplied value for limit.

manualMaxTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the tip text for this property.

manualMinTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the tip text for this property.

MapToWekaInstance - Class in adams.data.conversion

Converts a map into a Weka Instance, using the provided storage object (Instances) as template.

MapToWekaInstance() - Constructor for class adams.data.conversion.MapToWekaInstance

MarginCurve - Class in adams.gui.menu

Displays a margin curve.

MarginCurve() - Constructor for class adams.gui.menu.MarginCurve

Initializes the menu item with no owner.

MarginCurve(AbstractApplicationFrame) - Constructor for class adams.gui.menu.MarginCurve

Initializes the menu item.

markerExtentTipText() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Returns the tip text for this property.

markersDisabledTipText() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Returns the tip text for this property.

match(String) - Method in class adams.flow.transformer.WekaRegexToRange

Return match, given invert status.

match(List<Struct2<Instances, Instances>>, List<Struct2<Instances, Instances>>, int) - Method in class weka.classifiers.MultiLevelSplitGenerator

Combines train and test splits as long as there are matches.

match(Instance) - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader

Matches the input instance against the header.

MatchWekaInstanceAgainstFileHeader - Class in adams.data.conversion

Matches an Instance against a dataset header loaded from a file, i.e., it automatically converts STRING attributes into NOMINAL ones and vice versa.
The file can be any format that WEKA recognizes.

MatchWekaInstanceAgainstFileHeader() - Constructor for class adams.data.conversion.MatchWekaInstanceAgainstFileHeader

MatchWekaInstanceAgainstStorageHeader - Class in adams.data.conversion

Matches an Instance against a dataset header from storage, i.e., it automatically converts STRING attributes into NOMINAL ones and vice versa.

MatchWekaInstanceAgainstStorageHeader() - Constructor for class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader

MathExpressionClassifier - Class in weka.classifiers.functions

Simple classifier that uses a pre-defined formula that can make use of attribute values using their names.
Grammar:
expr_list ::= '=' expr_list expr_part | expr_part ;
expr_part ::= expr ;

expr ::= ( expr )

# data types
| number
| string
| boolean
| date

# constants
| true
| false
| pi
| e
| now()
| today()

# negating numeric value
| -expr

# comparisons
| expr < expr
| expr <= expr
| expr > expr
| expr >= expr
| expr = expr
| expr != expr (or: expr <> expr)

# boolean operations
| ! expr (or: not expr)
| expr & expr (or: expr and expr)
| expr | expr (or: expr or expr)
| if[else] ( expr , expr (if true) , expr (if false) )
| ifmissing ( variable , expr (default value if variable is missing) )
| isNaN ( expr )

# arithmetics
| expr + expr
| expr - expr
| expr * expr
| expr / expr
| expr ^ expr (power of)
| expr % expr (modulo)
;

# numeric functions
| abs ( expr )
| sqrt ( expr )
| cbrt ( expr )
| log ( expr )
| log10 ( expr )
| exp ( expr )
| sin ( expr )
| sinh ( expr )
| cos ( expr )
| cosh ( expr )
| tan ( expr )
| tanh ( expr )
| atan ( expr )
| atan2 ( exprY , exprX )
| hypot ( exprX , exprY )
| signum ( expr )
| rint ( expr )
| floor ( expr )
| pow[er] ( expr , expr )
| ceil ( expr )
| min ( expr1 , expr2 )
| max ( expr1 , expr2 )
| year ( expr )
| month ( expr )
| day ( expr )
| hour ( expr )
| minute ( expr )
| second ( expr )
| weekday ( expr )
| weeknum ( expr )

# string functions
| substr ( expr , start [, end] )
| left ( expr , len )
| mid ( expr , start , len )
| right ( expr , len )
| rept ( expr , count )
| concatenate ( expr1 , expr2 [, expr3-5] )
| lower[case] ( expr )
| upper[case] ( expr )
| trim ( expr )
| matches ( expr , regexp )
| trim ( expr )
| len[gth] ( str )
| find ( search , expr [, pos] )
| replace ( str , pos , len , newstr )
| substitute ( str , find , replace [, occurrences] )
;

Notes:
- Variables are either all upper case letters (e.g., "ABC") or any character apart from "]" enclosed by "[" and "]" (e.g., "[Hello World]").
- 'start' and 'end' for function 'substr' are indices that start at 1.
- Index 'end' for function 'substr' is excluded (like Java's 'String.substring(int,int)' method)
- Line comments start with '#'.
- Semi-colons (';') or commas (',') can be used as separator in the formulas,
e.g., 'pow(2,2)' is equivalent to 'pow(2;2)'
- dates have to be of format 'yyyy-MM-dd' or 'yyyy-MM-dd HH:mm:ss'
- times have to be of format 'HH:mm:ss' or 'yyyy-MM-dd HH:mm:ss'
- the characters in square brackets in function names are optional:
e.g.

MathExpressionClassifier() - Constructor for class weka.classifiers.functions.MathExpressionClassifier

Constructor.

MatlabSpreadSheetReader - Class in adams.data.io.input

Reads WEKA datasets in ARFF format and turns them into spreadsheets.

MatlabSpreadSheetReader() - Constructor for class adams.data.io.input.MatlabSpreadSheetReader

MatlabSpreadSheetWriter - Class in adams.data.io.output

Writes a spreadsheet in ARFF file format.

MatlabSpreadSheetWriter() - Constructor for class adams.data.io.output.MatlabSpreadSheetWriter

matrixAlgoToWeka(Matrix) - Static method in class adams.data.instancesanalysis.pls.MatrixHelper

Turns a matrix-algorithm matrix into a Weka one.

MatrixHelper - Class in adams.data.instancesanalysis.pls

Helper class for the matrix-algorithm library.

MatrixHelper - Class in weka.core.matrix

Some matrix operations.

MatrixHelper() - Constructor for class adams.data.instancesanalysis.pls.MatrixHelper

MatrixHelper() - Constructor for class weka.core.matrix.MatrixHelper

MatrixTab - Class in adams.gui.tools.wekainvestigator.tab

Visualizes the selected dataset as matrix plot.

MatrixTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.MatrixTab

matrixTipText() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess

Returns the tip text for this property.

matrixToBits(Matrix, double, double, int, int, int, int) - Static method in class adams.core.discovery.genetic.WekaGeneticHelper

Convert weka Matrix into bit string

matrixToSpreadSheet(Matrix, String) - Static method in class adams.data.instancesanalysis.pls.MatrixHelper

Turns the matrix into a spreadsheet.

matrixTypeTipText() - Method in class adams.flow.transformer.WekaExtractPLSMatrix

Returns the tip text for this property.

matrixValuesTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Returns the tip text for this property.

MATTHEWS_CORRELATION_COEFFICIENT - adams.flow.core.EvaluationStatistic

MATTHEWS_CORRELATION_COEFFICIENT - adams.flow.core.ExperimentStatistic

MAX - adams.flow.transformer.WekaInstancesInfo.InfoType

the maximum value (selected attribute, only numeric).

MAX - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.UpperStatistic

MAX - Static variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

MAX_COLUMN_WIDTH - Static variable in class adams.gui.tools.wekainvestigator.datatable.DataTable

the maximum column width.

MAX_DATA_POINTS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

the maximum number of data points before turning off anti-aliasing.

MAX_DECIMAL - Static variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

the maximum number of decimals after the decimal point to use.

MAX_HTML_LENGTH - Static variable in class adams.gui.tools.wekainvestigator.output.RunInformationHelper

the maximum length for HTML cells.

MAX_LEVELS - Static variable in class weka.classifiers.meta.ClassifierCascade

MAX_POINTS - Static variable in class adams.gui.visualization.instances.instancestable.JFreeChart

the maximum of data points to plot.

MAX_POINTS - Static variable in class adams.gui.visualization.instances.instancestable.SimplePlot

the maximum of data points to plot.

MAX_RELATIONNAME_LENGTH - Static variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

the maximum length for the relationname when assembling the name.

MAX_ROWS - Static variable in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer

MAX_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType

MAX_RULE - Static variable in class weka.classifiers.meta.AbstainVote

combination rule: Maximum Probability

maxAttributeNamesTipText() - Method in class adams.data.instancesanalysis.PCA

Returns the tip text for this property.

maxAttributesTipText() - Method in class adams.data.instancesanalysis.PCA

Returns the tip text for this property.

maxBinTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the maxBin option.

maxClassRangePercentageTipText() - Method in class weka.classifiers.meta.MinMaxLimits

Returns the tip text for this property.

maxDecimalPlacesTipText() - Method in class weka.core.converters.SimpleArffSaver

Returns the tip text for this property.

maxDepthTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the maxDepth option.

maxDifferenceTipText() - Method in class weka.classifiers.meta.AbstainAverage

Returns the tip text for this property

maxDifferenceTipText() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Returns the tip text for this property

maxDifferenceTipText() - Method in class weka.classifiers.meta.AbstainVote

Returns the tip text for this property

maxFactorTipText() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns the tip text for this property.

maxHandlingTipText() - Method in class weka.classifiers.meta.MinMaxLimits

Returns the tip text for this property.

maximumAttributeNamesTipText() - Method in class adams.flow.transformer.WekaPrincipalComponents

Returns the tip text for this property.

maximumAttributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Returns the tip text for this property.

maximumAttributesTipText() - Method in class adams.flow.transformer.WekaPrincipalComponents

Returns the tip text for this property.

maximumAttributesTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Returns the tip text for this property.

maximumDeltaStepTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the maximumDeltaStep option.

maximumIncludedTipText() - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns the tip text for this property.

maximumIncludedTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Returns the tip text for this property.

maximumTipText() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the tip text for this property.

maximumTipText() - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns the tip text for this property.

maximumTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Returns the tip text for this property.

maxIterationsTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

maxIterationsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Returns the tip text for this property

maxIterationsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Returns the tip text for this property

maxIterTipText() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Returns the tip text for this property

maxIterTipText() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns the tip text for this property

maxIterTipText() - Method in class adams.data.instancesanalysis.pls.PRM

Returns the tip text for this property

maxIterTipText() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns the tip text for this property

maxLabelsTipText() - Method in class adams.data.conversion.SpreadSheetToWekaInstances

Returns the tip text for this property.

maxLabelsTipText() - Method in class adams.data.spreadsheet.filter.WekaFilter

Returns the tip text for this property.

maxLeavesTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the maxLeaves option.

maxLevelsTipText() - Method in class weka.classifiers.meta.ClassifierCascade

Returns the tip text for this property.

maxManualTipText() - Method in class weka.classifiers.meta.MinMaxLimits

Returns the tip text for this property.

maxNeighborsTipText() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns the tip text for this property.

maxNumRows() - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic

Returns the maximum number of rows that the plugin requires.

maxNumRows() - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights

Returns the maximum number of rows that the plugin requires.

maxNumRows() - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset

Returns the maximum number of rows that the plugin requires.

maxNumRows() - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Returns the maximum number of rows that the plugin requires.

maxNumRows() - Method in interface adams.gui.visualization.instances.instancestable.PlotSelectedRows

Returns the maximum number of rows that the plugin requires.

maxNumRows() - Method in interface adams.gui.visualization.instances.instancestable.ProcessSelectedRows

Returns the maximum number of rows that the plugin requires.

maxNumRows() - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Returns the maximum number of rows that the plugin requires.

maxSizeTipText() - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler

Returns the tip text for this property.

maxTipText() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the tip text for this property.

maxTipText() - Method in class weka.classifiers.trees.RandomModelTrees

Returns the tip text for this property.

maxTipText() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

maxTipText() - Method in class weka.filters.unsupervised.instance.Scale

Returns the tip text for this property.

maxTrainTimeTipText() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the tip text for this property.

maxval - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp.IQRs

mayRemoveInstanceAfterFirstBatchDone() - Method in class weka.filters.FilteredFilter

Derived filters may removed rows.

mayRemoveInstanceAfterFirstBatchDone() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Derived filters may removed rows.

mayRemoveInstances() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Method that returns whether the filter may remove instances after the first batch has been done.

mayRemoveInstances() - Method in class weka.filters.unsupervised.instance.DatasetCleaner

Method that returns whether the filter may remove instances after the first batch has been done.

mayRemoveInstances() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Method that returns whether the filter may remove instances after the first batch has been done.

Mean - Class in weka.filters.unsupervised.attribute.detrend

Performs the correction using simply the mean.

Mean() - Constructor for class weka.filters.unsupervised.attribute.detrend.Mean

MEAN - adams.flow.transformer.WekaInstancesInfo.InfoType

the mean (selected attribute, only numeric).

MEAN - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.CenterStatistic

MEAN_ABSOLUTE_ERROR - adams.flow.core.EvaluationStatistic

MEAN_ABSOLUTE_ERROR - adams.flow.core.ExperimentStatistic

means() - Method in class weka.filters.supervised.attribute.PLSFilterExtended

the mean of all the attributes

means(Instances) - Method in class weka.classifiers.meta.Corr

Measure - Enum in adams.opt.genetic

The measure to use for evaluating.

measureNumRules() - Method in class weka.classifiers.trees.m5.M5Base2

return the number of rules

measuresPrefixTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the tip text for this property.

measureTipText() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the tip text for this property.

measureTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

measureTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the tip text for this property.

median - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp.IQRs

MEDIAN - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.CenterStatistic

MEDIAN - weka.classifiers.meta.ClassifierCascade.Combination

use the median of the probabilities/classifications.

MEDIAN_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType

MEDIAN_RULE - Static variable in class weka.classifiers.meta.AbstainVote

combination rule: Median Probability (only numeric class)

MemoryContainer - Class in adams.gui.tools.wekainvestigator.data

Dataset exists only in memory.

MemoryContainer(Instances) - Constructor for class adams.gui.tools.wekainvestigator.data.MemoryContainer

Uses the specified data.

MenuItemComparator - Class in adams.gui.tools.wekainvestigator.history

Comparator for sorting the menu items for the history panel.

MenuItemComparator - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold

Comparator for sorting the menu items for the per-fold pane.

MenuItemComparator() - Constructor for class adams.gui.tools.wekainvestigator.history.MenuItemComparator

MenuItemComparator() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.MenuItemComparator

menuItemTextTipText() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

Returns the tip text for this property.

menuItemTextTipText() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

Returns the tip text for this property.

merge(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Merges the datasets.

merge(Instances[], Instances[], HashSet) - Method in class adams.flow.transformer.WekaInstancesMerge

Merges the datasets based on the collected IDs.

Merge - Class in adams.gui.tools.wekainvestigator.datatable.action

Merges the selected datasets (side-by-side).

Merge() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Merge

Instantiates the action.

MergeDatasets - Class in adams.gui.menu

For merging datasets (side-by-side) into single dataset.

MergeDatasets() - Constructor for class adams.gui.menu.MergeDatasets

Initializes the menu item with no owner.

MergeDatasets(AbstractApplicationFrame) - Constructor for class adams.gui.menu.MergeDatasets

Initializes the menu item.

mergedIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Returns the tip text for this property.

mergedIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Returns the tip text for this property.

mergeInstance(Instance) - Method in class weka.core.AbstractHashableInstance

Merges this instance with the given instance and returns the result.

MergeManyAttributes - Class in weka.filters.unsupervised.attribute

Merges two or more attributes, offers various strategies if values differ or not present.
Uses the common subsequence (either from start or end) of the attributes as name of the merged attribute, otherwise the concatenation of them (separated by '-').

MergeManyAttributes() - Constructor for class weka.filters.unsupervised.attribute.MergeManyAttributes

mergeMethodTipText() - Method in class adams.flow.transformer.WekaDatasetsMerge

Gets the tip-text for the merge method option.

MergeTwoAttributes - Class in weka.filters.unsupervised.attribute

Merges two attributes, offers various strategies if values differ or not present.
Uses the common subsequence (either from start or end) of the two attributes as name of the merged attribute, otherwise the concatenation of the both (separated by '-').

MergeTwoAttributes() - Constructor for class weka.filters.unsupervised.attribute.MergeTwoAttributes

mergeWith(Row) - Method in class adams.ml.data.InstancesHeaderRow

Merges its own data with the one provided by the specified row.

mergeWith(Row) - Method in class adams.ml.data.InstanceView

Merges its own data with the one provided by the specified row.

mergeWith(SpreadSheet) - Method in class adams.ml.data.InstancesView

Puts the content of the provided spreadsheet on the right.

messageTipText() - Method in class adams.flow.transformer.WekaChooseAttributes

Returns the tip text for this property.

metaDataColorTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

metaLevelClassifierTipText() - Method in class weka.classifiers.meta.PartitionedStacking

Returns the tip text for this property.

MetaPartitionedMultiFilter - Class in weka.filters.unsupervised.attribute

With each specified filter, a regular expression is associated that defines the range of attributes to apply the filter to.

MetaPartitionedMultiFilter() - Constructor for class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

methodNamePredictionTipText() - Method in class weka.classifiers.functions.PyroProxy

Returns the tip text for this property.

methodNameTrainTipText() - Method in class weka.classifiers.functions.PyroProxy

Returns the tip text for this property.

MIN - adams.flow.transformer.WekaInstancesInfo.InfoType

the minimum value (selected attribute, only numeric).

MIN - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.LowerStatistic

MIN - Static variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

MIN_GLIBC_VERSION - Static variable in class weka.classifiers.trees.XGBoost

MIN_IMPROVEMENT - Static variable in class weka.classifiers.meta.ClassifierCascade

MIN_PROBABILITY - Static variable in class weka.classifiers.meta.AbstainMinimumProbability

MIN_PROBABILITY - Static variable in class weka.classifiers.meta.ThresholdedBinaryClassification

MIN_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType

MIN_RULE - Static variable in class weka.classifiers.meta.AbstainVote

combination rule: Minimum Probability

MIN_SAMPLES - Static variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

minChildWeightTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the minChildWeight option.

minClassRangePercentageTipText() - Method in class weka.classifiers.meta.MinMaxLimits

Returns the tip text for this property.

minHandlingTipText() - Method in class weka.classifiers.meta.MinMaxLimits

Returns the tip text for this property.

minimalTipText() - Method in class weka.classifiers.functions.LinearRegressionJ

Returns the tip text for this property.

minImprovementTipText() - Method in class weka.classifiers.meta.ClassifierCascade

Returns the tip text for this property.

minimumIncludedTipText() - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns the tip text for this property.

minimumIncludedTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Returns the tip text for this property.

minimumTipText() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the tip text for this property.

minimumTipText() - Method in class adams.data.weka.rowfinder.ByNumericValue

Returns the tip text for this property.

minimumTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Returns the tip text for this property.

minManualTipText() - Method in class weka.classifiers.meta.MinMaxLimits

Returns the tip text for this property.

MinMaxLimits - Class in weka.classifiers.meta

Allows to influence the handling of lower/upper limits of the built classifier when making predictions.
The following types of handling are available: AS_IS, MANUAL, CLASS_RANGE
Details on the types:
- AS_IS: prediction does not get changed
- MANUAL: applies the manual limit, ie at most this limit is output
- CLASS_RANGE: applies the percentage leeway to the class attribute range of the training set to determine the actual limit value.

MinMaxLimits() - Constructor for class weka.classifiers.meta.MinMaxLimits

MinMaxLimits.LimitHandling - Enum in weka.classifiers.meta

Determines the type of handling for the limit

minNumInstancesTipText() - Method in class weka.classifiers.trees.m5.M5Base2

Returns the tip text for this property

minNumRows() - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic

Returns the minimum number of rows that the plugin requires.

minNumRows() - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights

Returns the minimum number of rows that the plugin requires.

minNumRows() - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset

Returns the minimum number of rows that the plugin requires.

minNumRows() - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Returns the minimum number of rows that the plugin requires.

minNumRows() - Method in interface adams.gui.visualization.instances.instancestable.PlotSelectedRows

Returns the minimum number of rows that the plugin requires.

minNumRows() - Method in interface adams.gui.visualization.instances.instancestable.ProcessSelectedRows

Returns the minimum number of rows that the plugin requires.

minNumRows() - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Returns the minimum number of rows that the plugin requires.

minProbabilityTipText() - Method in class weka.classifiers.meta.AbstainMinimumProbability

Returns the tip text for this property

minProbabilityTipText() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns the tip text for this property.

minSamplesTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Returns the tip text for this property.

minTipText() - Method in class weka.classifiers.trees.RandomRegressionForest

Returns the tip text for this property

minTipText() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

minTipText() - Method in class weka.filters.unsupervised.instance.Scale

Returns the tip text for this property.

MISSING_CLASS_VALUES - adams.flow.core.Capability

can handle missing values in class attribute.

MISSING_VALUES - adams.flow.core.Capability

can handle missing values in attributes.

missingTipText() - Method in class adams.tools.CompareDatasets

Returns the tip text for this property.

mNumComponents - Variable in class weka.core.neighboursearch.PLSNNSearch

MODEL - adams.flow.transformer.WekaClassifierInfo.InfoType

model.

MODEL - adams.flow.transformer.WekaClustererInfo.InfoType

model.

modelActorTipText() - Method in class adams.flow.condition.bool.WekaClassification

Returns the tip text for this property.

modelActorTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the tip text for this property.

modelActorTipText() - Method in class adams.flow.transformer.WekaFilter

Returns the tip text for this property.

modelFileTipText() - Method in class adams.flow.condition.bool.WekaClassification

Returns the tip text for this property.

modelFileTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the tip text for this property.

modelFileTipText() - Method in class adams.flow.transformer.WekaFilter

Returns the tip text for this property.

modelLoadingTypeTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the tip text for this property.

modelLoadingTypeTipText() - Method in class adams.flow.transformer.WekaFilter

Returns the tip text for this property.

modelNameTipText() - Method in class weka.classifiers.functions.PyroProxy

Returns the tip text for this property.

ModelOutput - Class in adams.gui.tools.wekainvestigator.tab.associatetab.output

Outputs the model if available.

ModelOutput - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Outputs the model if available.

ModelOutput - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output

Outputs the model if available.

ModelOutput() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.output.ModelOutput

ModelOutput() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.ModelOutput

ModelOutput() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.ModelOutput

ModelOutputHandler - Interface in weka.core

Interface for classes that allow user to decide whether to output a model in string representation or not.

modelResetVariableTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the tip text for this property.

modelStorageTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the tip text for this property.

modelStorageTipText() - Method in class adams.flow.transformer.WekaFilter

Returns the tip text for this property.

modelToSpreadSheet() - Method in class adams.gui.visualization.instances.InstancesTable

Returns the underlying sheet.

ModificationActionListener() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationActionListener

ModificationChangeListener() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationChangeListener

ModificationDocumentListener() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationDocumentListener

modified() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

Sets the modified flag in the owner.

MODIFIED - adams.gui.event.InstancesSortSetupEvent.EventType

the setup was modified.

MonitoringDataContainer - Interface in adams.gui.tools.wekainvestigator.data

Interface for data containers that monitor their source for changes.

morphologiesTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Returns the tip text for this property.

moveCentroid(int, Instances, boolean, boolean) - Method in class weka.clusterers.SAXKMeans

Move the centroid to it's new coordinates.

MOVED - adams.gui.event.InstancesSortSetupEvent.EventType

the setup was moved.

moveDefinition(boolean) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

Moves itself around in the list of sorting panels.

moveDefinition(InstancesSortDefinitionPanel, boolean) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Moves the panel up/down.

MSLE - Class in weka.classifiers.evaluation

Computes the mean squared log error (MSLE) for regression models.

MSLE - adams.flow.core.EvaluationStatistic

MSLE - adams.flow.core.ExperimentStatistic

MSLE - adams.opt.genetic.Measure

Mean squared logarithmic error.

MSLE() - Constructor for class weka.classifiers.evaluation.MSLE

msq(Instances) - Method in class weka.classifiers.meta.Corr

MultiAttributeSummaryPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab

Can display one or more instances of AttributeSummaryPanel class.

MultiAttributeSummaryPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

MultiAttributeVisualizationPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab

Can display one or more instances of AttributeVisualizationPanel class.

MultiAttributeVisualizationPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

MultiClassifiersCombinerModels - Class in adams.flow.transformer.wekaensemblegenerator

Generates a MultipleClassifiersCombiner meta-classifier from the incoming pre-built classifier models.

MultiClassifiersCombinerModels() - Constructor for class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels

MultiCleaner - Class in weka.core.tokenizers.cleaners

Combines multiple cleaners, applies them sequentially.

MultiCleaner() - Constructor for class weka.core.tokenizers.cleaners.MultiCleaner

MultiClustererPostProcessor - Class in adams.flow.transformer.wekaclusterer

Applies the specified post-processors sequentially.

MultiClustererPostProcessor() - Constructor for class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor

MultiColumnFinder - Class in adams.data.weka.columnfinder

Applies multiple column finding algorithms to the data.
The indices can be either joined or intersected.

MultiColumnFinder() - Constructor for class adams.data.weka.columnfinder.MultiColumnFinder

MultiColumnFinder.Combination - Enum in adams.data.weka.columnfinder

How combine the indices.

MultiExperimenter - Class in adams.gui.tools.wekamultiexperimenter

Extended interface for the WEKA Experimenter, allowing for an arbitrary number of Experimenter panels.

MultiExperimenter() - Constructor for class adams.gui.tools.wekamultiexperimenter.MultiExperimenter

MultiExplorer - Class in adams.gui.menu

Opens the (multi-version of the) WEKA Explorer.

MultiExplorer - Class in weka.gui.explorer

Extended interface for the WEKA Explorer, allowing for an arbitrary number of Explorer panels.

MultiExplorer() - Constructor for class adams.gui.menu.MultiExplorer

Initializes the menu item with no owner.

MultiExplorer() - Constructor for class weka.gui.explorer.MultiExplorer

MultiExplorer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.MultiExplorer

Initializes the menu item.

MultiLevelSplitGenerator - Class in weka.classifiers

Generates splits based on groups extracted via regular expressions.

MultiLevelSplitGenerator() - Constructor for class weka.classifiers.MultiLevelSplitGenerator

MultiplicativeScatterCorrection - Class in weka.filters.unsupervised.attribute

Performs Multiplicative Scatter Correction, using the specified correction scheme.

MultiplicativeScatterCorrection() - Constructor for class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

multiplierTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev

Returns the tip text for this property.

MultiPLS - Class in weka.filters.supervised.attribute

For each Y that gets identified by the regular expression for Y attributes, the specified PLS (partial least squares) algorithm gets applied to the X attributes identified by the corresponding regular expression.

MultiPLS() - Constructor for class weka.filters.supervised.attribute.MultiPLS

MultiPostProcessor - Class in adams.flow.transformer.wekaevaluationpostprocessor

Applies the specified post-processors sequentially to the input data and combines their output.

MultiPostProcessor() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor

MultiRowFinder - Class in adams.data.weka.rowfinder

Applies multiple row finding algorithms to the data.
The indices can be either joined or intersected.

MultiRowFinder() - Constructor for class adams.data.weka.rowfinder.MultiRowFinder

MultiRowFinder.Combination - Enum in adams.data.weka.rowfinder

How combine the indices.

MultiRowProcessor - Class in weka.filters.unsupervised.instance

Uses the specified row selection scheme to identify groups of rows in the data coming through and then applies the selected row processor to these subsets.

MultiRowProcessor() - Constructor for class weka.filters.unsupervised.instance.MultiRowProcessor

MultiTokenizer - Class in weka.core.tokenizers

Combines the tokens of several tokenizers, skipping duplicate tokens.

MultiTokenizer() - Constructor for class weka.core.tokenizers.MultiTokenizer

N

NAME - Static variable in class weka.classifiers.evaluation.Bias

NAME - Static variable in class weka.classifiers.evaluation.Dice

NAME - Static variable in class weka.classifiers.evaluation.MSLE

NAME - Static variable in class weka.classifiers.evaluation.RPD

NAME - Static variable in class weka.classifiers.evaluation.RSquared

NAME - Static variable in class weka.classifiers.evaluation.SDR

names() - Method in class adams.flow.container.WekaAssociatorContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaAttributeSelectionContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaClusterEvaluationContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaClusteringContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaEvaluationContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaExperimentContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaFilterContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaGeneticAlgorithmContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaGeneticAlgorithmInitializationContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaModelContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaNearestNeighborSearchContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaPredictionContainer

Returns all value names that can be used (theoretically).

names() - Method in class adams.flow.container.WekaTrainTestSetContainer

Returns all value names that can be used (theoretically).

nameServerTipText() - Method in class weka.classifiers.functions.PyroProxy

Returns the tip text for this property.

nameServerTipText() - Method in interface weka.core.PyroProxyObject

Returns the tip text for this property.

namesTipText() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Returns the tip text for this property.

nameTipText() - Method in class adams.data.weka.classattribute.ByExactName

Returns the tip text for this property.

nameTipText() - Method in class adams.data.weka.columnfinder.ByExactName

Returns the tip text for this property.

NAN - Static variable in class adams.data.weka.rowfinder.ByNumericValue

the placeholder for NaN.

NAN - Static variable in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

the placeholder for NaN.

nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.NewNNSearch

Returns the nearest instance in the current neighbourhood to the supplied instance.

nearestNeighbourSearchAlgorithmTipText() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns the tip text for this property.

NearestNeighbourSearchWithIndices - Interface in weka.core.neighboursearch

Interface for neighborhood search algorithms that can return the indices of the neighbors.

NestedAdamsExperimentReader - Class in adams.data.io.input

Reads ADAMS Experiments in nested format.

NestedAdamsExperimentReader() - Constructor for class adams.data.io.input.NestedAdamsExperimentReader

NestedAdamsExperimentWriter - Class in adams.data.io.output

Writes ADAMS experiments in nested format.

NestedAdamsExperimentWriter() - Constructor for class adams.data.io.output.NestedAdamsExperimentWriter

nestedItemNames() - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem

Returns the names of the nested items.

newBest(double, OptData) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection

Callback for best measure so far

newCell() - Method in class adams.ml.data.InstancesView

Creates a new cell.

newCell(Row) - Method in class adams.ml.data.InstancesHeaderRow

Creates a new instance of a cell.

newCell(Row) - Method in class adams.ml.data.InstanceView

Creates a new instance of a cell.

newChooserPanel() - Method in class adams.flow.source.valuedefinition.WekaGOEValueDefinition

Instantiates the new chooser panel.

newComparator() - Method in class adams.data.instance.Instance

Returns the comparator in use.

newContainer(Comparable) - Method in class adams.gui.visualization.instance.InstanceContainerManager

Returns a new container containing the given payload.

newContainer(String, WekaEvaluationContainer, TIntList) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor

Creates a new evaluation container from the specified subset of predictions.

newContainerManager() - Method in class adams.gui.visualization.instance.InstancePanel

Returns the container manager to use.

newEvaluation(String, Evaluation, TIntList) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor

Creates a new evaluation from the specified subset of predictions.

newExperiment() - Static method in class adams.gui.goe.WekaExperimentFileEditor

Generates a new (simple) experiment.

newFileChooser() - Static method in class weka.gui.explorer.WorkspaceHelper

Creates a filechooser for loading/saving workspaces.

newFilterTipText() - Method in class adams.data.conversion.SwapPLS

Returns the tip text for this property.

newInstance() - Method in class adams.ml.data.InstancesView

Returns a new instance.

newInstanceForDataset(Instances) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter

Creates a new empty instance suited to the given dataset

newInstanceForDataset(Instances) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Creates a new dense instance of the size expected by the given dataset.

newJob(int, int[], Instances, Instances) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Creates a new Job instance.

newJob(int, int[], Instances, Instances) - Method in class adams.opt.genetic.DarkLord

Creates a new Job instance.

newJob(int, int[], Instances, Instances) - Method in class adams.opt.genetic.Hermione

Creates a new Job instance.

newLoader() - Method in class adams.data.io.input.AbstractWekaSpreadSheetReader

Returns an instance of the file loader.

newLoader() - Method in class adams.data.io.input.ArffSpreadSheetReader

Returns an instance of the file loader.

newLoader() - Method in class adams.data.io.input.JSONSpreadSheetReader

Returns an instance of the file loader.

newLoader() - Method in class adams.data.io.input.LibSVMSpreadSheetReader

Returns an instance of the file loader.

newLoader() - Method in class adams.data.io.input.MatlabSpreadSheetReader

Returns an instance of the file loader.

newLoader() - Method in class adams.data.io.input.SVMLightSpreadSheetReader

Returns an instance of the file loader.

newLoader() - Method in class adams.data.io.input.XrffSpreadSheetReader

Returns an instance of the file loader.

newModel() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Creates a new instance of a PLS algorrithm.

newModel() - Method in class weka.attributeSelection.PLS1AttributeEval

Creates a new instance of a PLS algorrithm.

newModel() - Method in class weka.attributeSelection.SIMPLSAttributeEval

Creates a new instance of a PLS algorrithm.

newModelLoader() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Instantiates the model loader to use.

newModelLoader() - Method in class adams.flow.transformer.WekaClassifying

Instantiates the model loader to use.

newModelLoader() - Method in class adams.flow.transformer.WekaClustering

Instantiates the model loader to use.

newMultiPagePane(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.AbstractOutputGenerator

Generates a new MultiPagePane instance.

NewNNSearch - Class in weka.core.neighboursearch

Class implementing the brute force search algorithm for nearest neighbour search.

NewNNSearch() - Constructor for class weka.core.neighboursearch.NewNNSearch

Constructor.

NewNNSearch(Instances) - Constructor for class weka.core.neighboursearch.NewNNSearch

Constructor that uses the supplied set of instances.

NewNNSearch.InstanceNode - Class in weka.core.neighboursearch

NewNNSearchWithIndices - Class in weka.core.neighboursearch

NewNNSearch with index support.

NewNNSearchWithIndices() - Constructor for class weka.core.neighboursearch.NewNNSearchWithIndices

newPanel() - Method in class adams.flow.sink.WekaAttributeSummary

Creates the panel to display in the dialog.

newPanel() - Method in class adams.flow.sink.WekaClassifierErrors

Creates the panel to display in the dialog.

newPanel() - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Creates the panel to display in the dialog.

newPanel() - Method in class adams.flow.sink.WekaCostCurve

Creates the panel to display in the dialog.

newPanel() - Method in class adams.flow.sink.WekaGraphVisualizer

Creates the panel to display in the dialog.

newPanel() - Method in class adams.flow.sink.WekaInstancesDisplay

Creates the panel to display in the dialog.

newPanel() - Method in class adams.flow.sink.WekaInstancesPlot

Creates the panel to display in the dialog.

newPanel() - Method in class adams.flow.sink.WekaInstanceViewer

Creates the panel to display in the dialog.

newPanel() - Method in class adams.flow.sink.WekaMarginCurve

Creates the panel to display in the dialog.

newPanel() - Method in class adams.flow.sink.WekaThresholdCurve

Creates the panel to display in the dialog.

newPanel() - Method in class adams.flow.sink.WekaTreeVisualizer

Creates the panel to display in the dialog.

newPoint() - Method in class adams.data.instance.Instance

Returns a new instance of a sequence point.

newReport() - Method in class adams.data.instance.Instance

Creates an empty report.

newReportPanel() - Method in class adams.gui.visualization.instance.InstanceExplorer

Creates a new tabbed pane for the reports.

newSaver() - Method in class adams.data.io.output.AbstractWekaSpreadSheetWriter

Returns an instance of the file loader.

newSaver() - Method in class adams.data.io.output.ArffSpreadSheetWriter

Returns an instance of the file loader.

newSaver() - Method in class adams.data.io.output.JSONSpreadSheetWriter

Returns an instance of the file loader.

newSaver() - Method in class adams.data.io.output.LibSVMSpreadSheetWriter

Returns an instance of the file loader.

newSaver() - Method in class adams.data.io.output.MatlabSpreadSheetWriter

Returns an instance of the file loader.

newSaver() - Method in class adams.data.io.output.SVMLightSpreadSheetWriter

Returns an instance of the file loader.

newSaver() - Method in class adams.data.io.output.XrffSpreadSheetWriter

Returns an instance of the file loader.

newSetup(Class) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Sets the new setup panel.

newTab(String, JComponent) - Method in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane

Adds the component as tab to the result item.

newTable(ReportFactory.Model) - Method in class adams.gui.visualization.instance.InstanceReportFactory.Panel

Returns a new table instance.

newWindow() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Displays a new preview window/frame.

newWorkspace(boolean) - Method in class adams.gui.tools.wekainvestigator.InvestigatorManagerPanel

Returns a new workspace instance.

newWorkspace(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter

Returns a new workspace instance.

newWorkspaceHelper() - Method in class adams.gui.tools.wekainvestigator.InvestigatorManagerPanel

Returns a new instance of the workspace helper to use.

newWorkspaceList() - Method in class adams.gui.tools.wekainvestigator.InvestigatorManagerPanel

Instantiates a new panel for workspaces.

newWorkspaceList() - Method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter

Instantiates a new panel for workspaces.

newZoomPaintlet() - Method in class adams.gui.visualization.instance.InstanceZoomOverviewPanel

Creates a new zoom paintlet.

next() - Method in class weka.classifiers.AbstractSplitGenerator

Returns the next element in the iteration.

next() - Method in interface weka.classifiers.SplitGenerator

Returns the next element in the iteration.

next(int) - Method in class adams.tools.CompareDatasets

Returns the next row pair to compare.

nextByIndex(int) - Method in class adams.tools.CompareDatasets

Returns the next pair by simple index.

nextByRowAttribute(int) - Method in class adams.tools.CompareDatasets

Returns the next pair by using the value of the row attribute.

nextElement() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID.UniqueIDEnumeration

nextElement() - Method in class adams.flow.transformer.wekadatasetsmerge.Simple.SimpleRowSetIterator

nextElement() - Method in class weka.core.tokenizers.MultiTokenizer

Returns the next element of this enumeration if this enumeration object has at least one more element to provide.

nextElement() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns the next element of this enumeration if this enumeration object has at least one more element to provide.

nextID() - Static method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Returns the next container ID.

nextIteration() - Method in class weka.experiment.ExtExperiment

Carries out the next iteration of the experiment.

nextPowerOf2(int) - Static method in class weka.filters.unsupervised.attribute.FastWavelet

returns the next bigger number that's a power of 2.

NIPALS - Class in adams.data.instancesanalysis.pls

NIPALS() - Constructor for class adams.data.instancesanalysis.pls.NIPALS

NO_CLASS - adams.flow.core.Capability

can handle data without class attribute, eg clusterers.

NO_CLASS - Static variable in class adams.gui.visualization.instance.LoadDatasetDialog

the "no class" constant.

NO_ID - Static variable in class adams.gui.visualization.instance.LoadDatasetDialog

the "no id" constant.

NO_NEXT_SELECTED_INDEX - Static variable in class adams.data.weka.datasetsplitter.RowSplitter

Sentinel for when there's no more selected rows.

NO_SORTING - Static variable in class adams.gui.visualization.instance.LoadDatasetDialog

the "no sorting" constant.

NO_SOURCE - Static variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel

Message shown when no instances have been loaded and no attribute set

NO_SOURCE - Static variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

Message shown when no instances have been loaded

noAdditionalFieldsPrefixTipText() - Method in interface adams.data.instances.InstanceGeneratorWithAdditionalFields

Returns the tip text for this property.

NoChange - Class in adams.data.weka.relationname

Simply returns the current relation name.

NoChange() - Constructor for class adams.data.weka.relationname.NoChange

noCheckTipText() - Method in class adams.flow.transformer.WekaExperiment

Returns the tip text for this property.

NoClassAttribute - Class in adams.data.weka.classattribute

Never returns a class attribute.

NoClassAttribute() - Constructor for class adams.data.weka.classattribute.NoClassAttribute

Node(Instances, Random, int) - Constructor for class weka.classifiers.trees.RandomRegressionForest.Node

the constructor

nodeToString() - Method in class weka.classifiers.trees.m5.RuleNode2

Returns a description of this node (debugging purposes)

noiseTipText() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Returns the tip text for this property

noiseTipText() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Returns the tip text for this property

noiseTipText() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Returns the tip text for this property

noiseTipText() - Method in class weka.classifiers.functions.GPD

Returns the tip text for this property.

NOMINAL_ATTRIBUTES - adams.flow.core.Capability

can handle nominal attributes.

NOMINAL_CLASS - adams.flow.core.Capability

can handle nominal classes.

nominalTipText() - Method in class weka.filters.unsupervised.attribute.SAX

Returns the tip text for this property.

NominalToNumeric - Class in weka.filters.unsupervised.attribute

Converts a nominal attribute into a numeric one.

NominalToNumeric() - Constructor for class weka.filters.unsupervised.attribute.NominalToNumeric

NominalToNumeric.ConversionType - Enum in weka.filters.unsupervised.attribute

Enumeration of conversion types.

NONE - adams.data.conversion.WekaPredictionContainerToSpreadSheet.Sorting

no sorting.

NONE - adams.data.instancesanalysis.pls.PredictionType

no prediction at all.

NONE - adams.data.instancesanalysis.pls.PreprocessingType

NONE - adams.gui.visualization.instance.InstanceLinePaintlet.MarkerShape

nothing.

NONE - adams.opt.genetic.OutputPrefixType

no prefix.

NONE - adams.opt.genetic.OutputType

no output.

nonInteractiveTipText() - Method in class adams.flow.source.WekaSelectDataset

Returns the tip text for this property.

nonInteractiveTipText() - Method in class adams.flow.transformer.WekaChooseAttributes

Returns the tip text for this property.

noReplacementTipText() - Method in class weka.classifiers.meta.VotedImbalance

Returns the tip text for this property.

normaliseTypeTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the normaliseType option.

NormalizeAdaptive - Class in weka.filters.unsupervised.attribute

Normalizes all numeric values in the given dataset (apart from the class attribute, if set).

NormalizeAdaptive() - Constructor for class weka.filters.unsupervised.attribute.NormalizeAdaptive

NormalizeDuplicateChars - Class in weka.core.tokenizers.cleaners

Replaces all duplicate characters with a single one.

NormalizeDuplicateChars() - Constructor for class weka.core.tokenizers.cleaners.NormalizeDuplicateChars

normalizeTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the tip text for this property.

normalizeVector(Matrix) - Static method in class weka.core.matrix.MatrixHelper

normalizes the given vector (inplace)

normalPlotOptionsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

tip text for the normalplot options property.

normYWeightsTipText() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns the tip text for this property

NOT_RUNNING - Static variable in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

The message displayed when no experiment is running

notCoveredInstances() - Method in class weka.classifiers.trees.m5.Rule2

Get the instances not covered by this rule

notesTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the tip text for this property.

notifyChangeListeners() - Method in class adams.gui.goe.WekaGenericObjectEditorPopupMenu

Notifies all change listeners that the user modified the setup.

notifyChangeListeners() - Method in class adams.gui.visualization.instances.InstancesTable

Notifies all the change listeners.

notifyChangeListeners(ChangeEvent) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Sends the event to all change listeners.

notifyInstancesSortSetupListeners(InstancesSortSetupEvent) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Notifies all listeners with the specified event.

notifyListener(TableModelEvent) - Method in class adams.gui.visualization.instances.InstancesTableModel

notfies all listener of the change of the model

notifySelectionListeners(ListSelectionEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Notifies all listeners that the selection has changed.

noUpdateTipText() - Method in class weka.classifiers.lazy.LWLSynchro

Returns the tip text for this property.

noUpdateTipText() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

Returns the tip text for this property.

noUpdateTipText() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Returns the tip text for this property.

noUpdateTipText() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns the tip text for this property.

nPointTipText() - Method in class weka.core.SAXDistance

Returns the tip text for this property.

nthPointTipText() - Method in class weka.filters.unsupervised.attribute.DownSample

Returns the tip text for this property.

NTipText() - Method in class weka.filters.supervised.attribute.YGradientEPO

Returns the tip text for this property

Null - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel

Does not generate a final model.

Null() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.Null

NullCommunicationProcessor - Class in adams.data.wekapyroproxy

Dummy, does nothing.

NullCommunicationProcessor() - Constructor for class adams.data.wekapyroproxy.NullCommunicationProcessor

NullFinder - Class in adams.data.weka.columnfinder

Dummy finder, does not find any columns.

NullFinder - Class in adams.data.weka.rowfinder

Dummy finder, does not find any rows.

NullFinder() - Constructor for class adams.data.weka.columnfinder.NullFinder

NullFinder() - Constructor for class adams.data.weka.rowfinder.NullFinder

NUM_ATTRIBUTES - adams.flow.transformer.WekaInstancesInfo.InfoType

the number of attributes.

NUM_CLASS_LABELS - adams.flow.transformer.WekaInstancesInfo.InfoType

the number of class labels.

NUM_CLUSTERS - adams.flow.transformer.WekaClustererInfo.InfoType

number of clusters.

NUM_CONTAINERS_THRESHOLD - Static variable in class adams.gui.tools.wekainvestigator.datatable.action.Split

the threshold for number of generated containers.

NUM_DISTINCT_VALUES - adams.flow.transformer.WekaInstancesInfo.InfoType

the number of distinct values (selected attribute).

NUM_FALSE_NEGATIVES - adams.flow.core.EvaluationStatistic

NUM_FALSE_NEGATIVES - adams.flow.core.ExperimentStatistic

NUM_FALSE_POSITIVES - adams.flow.core.EvaluationStatistic

NUM_FALSE_POSITIVES - adams.flow.core.ExperimentStatistic

NUM_FOLDS - Static variable in class weka.classifiers.meta.ClassifierCascade

NUM_FOLDS - Static variable in class weka.filters.supervised.instance.RemoveOutliers

NUM_INSTANCES - adams.flow.transformer.WekaInstancesInfo.InfoType

the number of instances.

NUM_LABELS - adams.flow.transformer.WekaInstancesInfo.InfoType

the number of labels (selected attribute, only nominal).

NUM_MISSING_VALUES - adams.flow.transformer.WekaInstancesInfo.InfoType

the number of missing values (selected attribute, only nominal).

NUM_PLOTS_HORIZONTAL - Static variable in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab

the number of plots side-by-side.

NUM_POINTS - Static variable in class weka.filters.unsupervised.attribute.EquiDistance

the option for the number of points.

NUM_PREDICTIONS - adams.flow.transformer.WekaEvaluationInfo.InfoType

NUM_THREADS - Static variable in class weka.classifiers.meta.ClassifierCascade

NUM_THREADS - Static variable in class weka.filters.supervised.instance.RemoveOutliers

NUM_TRUE_NEGATIVES - adams.flow.core.EvaluationStatistic

NUM_TRUE_NEGATIVES - adams.flow.core.ExperimentStatistic

NUM_TRUE_POSITIVES - adams.flow.core.EvaluationStatistic

NUM_TRUE_POSITIVES - adams.flow.core.ExperimentStatistic

NUM_UNIQUE_VALUES - adams.flow.transformer.WekaInstancesInfo.InfoType

the number of unique values (selected attribute).

numAttributes() - Method in class weka.core.AbstractHashableInstance

Returns the number of attributes.

numattrsTipText() - Method in class weka.classifiers.meta.Corr

Returns the tip text for this property.

numBalancedTipText() - Method in class weka.classifiers.meta.VotedImbalance

Returns the tip text for this property.

NUMBER_CORRECT - adams.flow.core.EvaluationStatistic

NUMBER_CORRECT - adams.flow.core.ExperimentStatistic

NUMBER_IN_SUBSET - Static variable in class weka.filters.unsupervised.instance.KennardStone

NUMBER_INCORRECT - adams.flow.core.EvaluationStatistic

NUMBER_INCORRECT - adams.flow.core.ExperimentStatistic

NUMBER_OF_TESTING_INSTANCES - adams.flow.core.ExperimentStatistic

NUMBER_OF_TRAINING_INSTANCES - adams.flow.core.ExperimentStatistic

NUMBER_UNCLASSIFIED - adams.flow.core.EvaluationStatistic

NUMBER_UNCLASSIFIED - adams.flow.core.ExperimentStatistic

numberInSubsetTipText() - Method in class weka.filters.unsupervised.instance.KennardStone

Returns the tip text for this property.

numberOfClusters() - Method in class weka.clusterers.SAXKMeans

Returns the number of clusters.

numberOfLinearModels() - Method in class weka.classifiers.trees.m5.RuleNode2

Get the number of linear models in the tree

numberOfParallelTreesTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the numberOfParallelTrees option.

numberOfRequiredDMatrixColumns(Instances) - Method in class weka.classifiers.trees.XGBoost

Calculates the number of columns required to represent the attributes of the given dataset when converted to a DMatrix.

numberOfRoundsTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the number of rounds option.

numBinsTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the tip text for this property.

numChromTipText() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the tip text for this property.

numClasses() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Returns the number of classes in the test set.

numClasses() - Method in class weka.core.AbstractHashableInstance

Returns the number of class labels.

numClasses() - Method in class weka.core.InstancesView

Returns the number of class labels.

numClustersTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

numCoefficientsTipText() - Method in class adams.data.instancesanalysis.pls.SIMPLS

Returns the tip text for this property

numComponentsTipText() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the tip text for this property

numComponentsTipText() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Returns the tip text for this property

numCyclesTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Returns the tip text for this property.

numDecimalsTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the tip text for this property.

numDecimalsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Returns the tip text for this property.

numDecimalsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Returns the tip text for this property.

numDecimalsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Returns the tip text for this property.

NUMERIC_ATTRIBUTES - adams.flow.core.Capability

can handle numeric attributes.

NUMERIC_CLASS - adams.flow.core.Capability

can handle numeric classes.

NumericClassGroupExtractor() - Constructor for class adams.data.binning.BinnableInstances.NumericClassGroupExtractor

NumericErrorScalerWithReference - Class in adams.data.weka.predictions

Scales the errors for numeric class attributes, using an user-specified error as reference point for a specified size.

NumericErrorScalerWithReference() - Constructor for class adams.data.weka.predictions.NumericErrorScalerWithReference

numEvaluationBinsTipText() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

numExecutionSlotsTipText() - Method in class weka.classifiers.meta.SubsetEnsemble

Returns the tip text for this property.

numExecutionSlotsTipText() - Method in class weka.classifiers.meta.VotedImbalance

Returns the tip text for this property.

numExecutionSlotsTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property

numFoldsTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Returns the tip text for this property.

numFoldsTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the tip text for this property.

numFoldsTipText() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

numFoldsTipText() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns the tip text for this property.

numFoldsTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

numFoldsTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the tip text for this property.

numFoldsTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns the tip text for this property.

numFoldsTipText() - Method in class weka.classifiers.meta.ClassifierCascade

Returns the tip text for this property.

numFoldsTipText() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the tip text for this property.

numFoldsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Returns the tip text for this property

numFoldsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Returns the tip text for this property

numInstances() - Method in class weka.core.InstancesView

Returns the number of instances in the dataset.

numIterationsTipText() - Method in class weka.classifiers.trees.RandomModelTrees

Returns the tip text for this property.

numIterationsTipText() - Method in class weka.classifiers.trees.RandomRegressionForest

Returns the tip text for this property

numLeaves(int) - Method in class weka.classifiers.trees.m5.RuleNode2

Sets the leaves' numbers

numParameters() - Method in class weka.classifiers.functions.LinearRegressionJ

Get the number of coefficients used in the model

numPointsLeftTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns the tip text for this property.

numPointsRightTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns the tip text for this property.

numPointsTipText() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

Returns the tip text for this property.

numPointsTipText() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the tip text for this property.

numPointsTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns the tip text for this property.

numRandomFeaturesTipText() - Method in class weka.classifiers.meta.SubsetEnsemble

Returns the tip text for this property.

numRegressionsTipText() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Returns the tip text for this property

numRegressionsTipText() - Method in class weka.classifiers.meta.LeastMedianSq

Returns the tip text for this property

numRowsTipText() - Method in class adams.data.conversion.WekaCapabilitiesToInstances

Returns the tip text for this property.

numSimplsCoefficientsTipText() - Method in class adams.data.instancesanalysis.pls.PRM

Returns the tip text for this property

numSubSamplesTipText() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the tip text for this property.

numThreadsTipText() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the tip text for this property.

numThreadsTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the tip text for this property.

numThreadsTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the tip text for this property.

numThreadsTipText() - Method in class weka.classifiers.meta.ClassifierCascade

Returns the tip text for this property.

numThreadsTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the numThreads option.

numThreadsTipText() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the tip text for this property.

numValues() - Method in class weka.core.AbstractHashableInstance

Returns the number of values present in a sparse representation.

numZeroesTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Returns the tip text for this property.

O

objectiveTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the objective option.

offlineTipText() - Method in class adams.data.instances.AbstractInstanceGenerator

Returns the tip text for this property.

oldFilterTipText() - Method in class adams.data.conversion.SwapPLS

Returns the tip text for this property.

oneDropTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the oneDrop option.

ONEMISSING_MISSING - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

what to do if one is missing: missing.

ONEMISSING_MISSING - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

what to do if one is missing: missing.

ONEMISSING_USE_FIRST_PRESENT - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

what to do if one is missing: use first present value.

ONEMISSING_USE_PRESENT - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

what to do if one is missing: use present value.

oneMissingTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Returns the tip text for this property.

oneMissingTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Returns the tip text for this property.

ONLY_MULTIINSTANCE - adams.flow.core.Capability

can handle multi-instance data.

onlyFirstBatchTipText() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Returns the tip text for this property.

onTheFlyTipText() - Method in class adams.flow.condition.bool.WekaClassification

Returns the tip text for this property.

onTheFlyTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the tip text for this property.

onTheFlyTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the tip text for this property.

open() - Method in class adams.gui.tools.DatasetCompatibilityPanel

Brings up dialog for selecting files.

open() - Method in class weka.gui.explorer.ExplorerExt

Lets the user choose a file.

open(File) - Method in class weka.gui.explorer.ExplorerExt

For opening an external file.

open(File[]) - Method in class adams.gui.tools.DatasetCompatibilityPanel

Opens the specified files, determines the loader automatically.

open(File[], AbstractFileLoader) - Method in class adams.gui.tools.DatasetCompatibilityPanel

Opens the specified files with the given loader.

openFile() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Lets user select a dataset.

openFile(File) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Lets user select a dataset.

openRecent(RecentItemEvent<JMenu, RecentFilesHandlerWithCommandline.Setup>) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

For opening a recently used file.

openRecent(RecentItemEvent<JMenu, File>) - Method in class weka.gui.explorer.ExplorerExt

For opening a recently used file.

openRecentResults(RecentItemEvent<JMenu, RecentFilesHandlerWithCommandline.Setup>) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

For opening a recently used results file.

openRecentSetup(RecentItemEvent<JMenu, File>) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

For opening a recently used experiment file.

openResults() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Loads the results from a file.

openResults(File, AbstractFileLoader) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Loads the results from the file.

openResultsDB() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Loads the results from a database.

openSetup() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Lets the user choose an experiment file.

openSetup(File) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

For opening an experiment file.

openWorkspace() - Method in class weka.gui.explorer.MultiExplorer

Opens a workspace.

operationTipText() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns the tip text for this property.

OPLS - Class in adams.data.instancesanalysis.pls

OPLS() - Constructor for class adams.data.instancesanalysis.pls.OPLS

optimise(OptData, FitnessFunction) - Method in class adams.opt.optimise.GeneticAlgorithm

optimizerTipText() - Method in class adams.flow.transformer.WekaClassifierOptimizer

Returns the tip text for this property.

optionalTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns the tip text for this property.

originalIndices - Variable in class weka.classifiers.lazy.LWLDatasetBuilder.LWLContainer

the indices (from the training dataset).

otherParametersTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the otherParameters option.

OuterProductAnalysis - Class in weka.filters.unsupervised.attribute

Performs Outer Product Analysis (OPA).

For more information, see:
Fabricio S.Terra, Raphael A.Viscarra Rossel, Jose A.M.Dematte (2019).

OuterProductAnalysis() - Constructor for class weka.filters.unsupervised.attribute.OuterProductAnalysis

output() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Returns the generated token.

output() - Method in class adams.flow.source.WekaDatabaseReader

Returns the generated token.

output() - Method in class adams.flow.transformer.WekaAccumulatedError

Returns the generated token.

output() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the generated token.

output() - Method in class adams.flow.transformer.WekaFileReader

Returns the generated token.

output() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns the generated token.

output() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Returns the generated token.

output() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns the generated token.

output() - Method in class adams.flow.transformer.WekaSubsets

Returns the generated token.

outputAdditionalStatsTipText() - Method in class weka.classifiers.functions.LinearRegressionJ

Returns the tip text for this property.

outputAdditionalStatsTipText() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns the tip text for this property.

outputArrayTipText() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Returns the tip text for this property.

outputArrayTipText() - Method in class adams.flow.source.WekaSelectDataset

Returns the tip text for this property.

outputArrayTipText() - Method in class adams.flow.source.WekaSelectObjects

Returns the tip text for this property.

outputArrayTipText() - Method in class adams.flow.transformer.WekaAttributeIterator

Returns the tip text for this property.

outputArrayTipText() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor

Returns the tip text for this property.

outputArrayTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns the tip text for this property.

outputArrayTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the tip text for this property.

outputArrayTipText() - Method in class adams.flow.transformer.WekaInstancesInfo

Returns the tip text for this property.

outputArrayTipText() - Method in class adams.flow.transformer.WekaRandomSplit

Returns the tip text for this property.

outputArrayTipText() - Method in class adams.flow.transformer.WekaSplitGenerator

Returns the tip text for this property.

outputBestSetupTipText() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the tip text for this property.

outputContainerTipText() - Method in class adams.flow.transformer.WekaFilter

Returns the tip text for this property.

outputDataset(double, Instances) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Saves the instances to a file.

outputDirectoryTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

outputDirectoryTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Returns the tip text for this property.

outputDistributionTipText() - Method in class adams.flow.transformer.wekaclusterer.AddCluster

Returns the tip text for this property.

outputFileTipText() - Method in class adams.flow.sink.AbstractWekaModelWriter

Returns the tip text for this property.

outputFileTipText() - Method in class adams.flow.sink.WekaExperimentFileWriter

Returns the tip text for this property.

outputFileTipText() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the tip text for this property.

outputFileTipText() - Method in class adams.flow.sink.WekaFileWriter

Returns the tip text for this property.

outputFileTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Returns the tip text for this property.

outputFileTipText() - Method in class adams.tools.CompareDatasets

Returns the tip text for this property.

outputFormatTipText() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

Returns the tip text for this property.

outputFormatTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the tip text for this property.

outputFormatTipText() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns the tip text for this property.

outputFormatTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the tip text for this property.

outputHeaderTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the tip text for this property.

outputHeaderTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the tip text for this property.

outputIndicesTipText() - Method in class adams.flow.transformer.WekaAttributeIterator

Returns the tip text for this property.

outputInstanceTipText() - Method in class adams.flow.transformer.WekaClassifying

Returns the tip text for this property.

outputModelTipText() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Returns the tip text for this property.

outputModelTipText() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

Returns the tip text for this property.

outputNameTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Gets the tip-text for the output name option.

outputOnlyModelTipText() - Method in class adams.flow.transformer.AbstractWekaModelReader

Returns the tip text for this property.

OutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka

Allows the user to select the output type, e.g., ARFF file or JDBC database.

OutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel

outputPrefixTipText() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns the tip text for this property.

OutputPrefixType - Enum in adams.opt.genetic

Defines what kind of prefix to use for outputting data and setups.

outputPrefixTypeTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

outputRelationNameTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the tip text for this property.

outputSetup(double, Instances, Classifier, int, int[]) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Saves the setup to a props file.

OutputTabbedPane - Class in adams.gui.tools.wekainvestigator.output

Tabbed pane for the output.

OutputTabbedPane() - Constructor for class adams.gui.tools.wekainvestigator.output.OutputTabbedPane

outputTipText() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Returns the tip text for this property.

outputTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the tip text for this property.

outputTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the tip text for this property.

outputTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput

Returns the tip text for this property.

OutputType - Enum in adams.opt.genetic

Defines what to output during a genetic algorithm run.

outputTypeTipText() - Method in class adams.flow.transformer.WekaFileReader

Returns the tip text for this property.

outputTypeTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

overlaysTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

overrideJobRunnerTipText() - Method in class adams.flow.transformer.WekaExperimentExecution

Returns the tip text for this property.

overrideTipText() - Method in class adams.flow.transformer.WekaClassSelector

Returns the tip text for this property.

ownerChanged() - Method in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel

Gets called when the owner changes.

ownerChanged() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

Gets called when the owner changes.

ownerChanged() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

Gets called when the owner changes.

ownerChanged() - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

Gets called when the owner changes.

P

PAA - Class in weka.filters.unsupervised.attribute

Valid options are:

PAA() - Constructor for class weka.filters.unsupervised.attribute.PAA

PACKAGE - adams.flow.source.wekapackagemanageraction.ListPackages.OutputFormat

PackageManager - Class in adams.gui.menu

Opens the WEKA PackageManager.

PackageManager() - Constructor for class adams.gui.menu.PackageManager

Initializes the menu item with no owner.

PackageManager(AbstractApplicationFrame) - Constructor for class adams.gui.menu.PackageManager

Initializes the menu item.

PackData - Class in adams.opt.optimise.genetic

???

PackData(PackDataDef) - Constructor for class adams.opt.optimise.genetic.PackData

PackDataDef - Class in adams.opt.optimise.genetic

???

PackDataDef() - Constructor for class adams.opt.optimise.genetic.PackDataDef

PackDataDef.DataInfo - Class in adams.opt.optimise.genetic

PackDataGeneticAlgorithm - Class in adams.opt.genetic

???

PackDataGeneticAlgorithm - Class in adams.opt.optimise.genetic

???

PackDataGeneticAlgorithm() - Constructor for class adams.opt.genetic.PackDataGeneticAlgorithm

PackDataGeneticAlgorithm() - Constructor for class adams.opt.optimise.genetic.PackDataGeneticAlgorithm

PackDataInitialSetupsProvider<T extends PackDataGeneticAlgorithm> - Class in adams.opt.genetic.initialsetups

PackDataInitialSetupsProvider() - Constructor for class adams.opt.genetic.initialsetups.PackDataInitialSetupsProvider

pad(Instances) - Method in class weka.filters.unsupervised.attribute.FastWavelet

pads the data to conform to the necessary number of attributes.

PADDING_ZERO - Static variable in class weka.filters.unsupervised.attribute.FastWavelet

the type of padding: Zero padding.

paddingTipText() - Method in class weka.filters.unsupervised.attribute.FastWavelet

Returns the tip text for this property.

paintComponent(Graphics) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Paints this component

paintletTipText() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the tip text for this property.

paintletTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Returns the tip text for this property.

paintletTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the tip text for this property.

paintValue(Graphics, Rectangle) - Method in class adams.gui.goe.WekaExperimentFileEditor

Paints a representation of the current Object.

Panel() - Constructor for class adams.gui.visualization.instance.HistogramFactory.Panel

Panel() - Constructor for class adams.gui.visualization.instance.InstanceReportFactory.Panel

Initializes the tabbed pane with not reports.

PARAM_CLASSVALUES - Static variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

PARAM_CLASSVALUES - Static variable in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS

PARAMETERS - adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption

parametersTipText() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Returns the tip text for this property.

paramValue() - Method in enum weka.classifiers.trees.XGBoost.Objective

paramValue() - Method in interface weka.classifiers.trees.XGBoost.ParamValueProvider

Provides a proxy object suitable for the XGBoost parameter system in place of this object.

paramValue() - Method in enum weka.classifiers.trees.XGBoost.Predictor

paramValue() - Method in enum weka.classifiers.trees.XGBoost.Verbosity

parentComponentActorTipText() - Method in class adams.flow.source.WekaSelectDataset

Returns the tip text for this property.

parentNode() - Method in class weka.classifiers.trees.m5.RuleNode2

Get the parent of this node

parse(String) - Method in class adams.data.instance.InstancePoint

Parses a string and instantiates a sequence point of it.

parse(String) - Method in enum adams.flow.core.EvaluationStatistic

Parses the given string and returns the associated enum.

parse(String) - Method in enum adams.flow.core.ExperimentStatistic

Parses the given string and returns the associated enum.

parse(String) - Method in enum adams.flow.sink.WekaThresholdCurve.AttributeName

Parses the given string and returns the associated enum.

parse(String) - Method in enum adams.flow.transformer.WekaClassifierRanker.Measure

Parses the given string and returns the associated enum.

parse(String) - Method in class adams.gui.goe.WekaAttributeIndexEditor

Parses the given string and returns the generated object.

parse(String) - Method in class adams.gui.goe.WekaAttributeRangeEditor

Parses the given string and returns the generated object.

parse(String) - Method in class adams.gui.goe.WekaLabelIndexEditor

Parses the given string and returns the generated object.

parse(String) - Method in class adams.gui.goe.WekaLabelRangeEditor

Parses the given string and returns the generated object.

parse(String) - Method in class adams.gui.goe.WekaUnorderedAttributeRangeEditor

Parses the given string and returns the generated object.

parse(String[], char) - Static method in class weka.core.WekaOptionUtils

Parses an array option, returns all the occurrences of the option as a string array.

parse(String[], char, double) - Static method in class weka.core.WekaOptionUtils

Parses a double option, uses default if option is missing.

parse(String[], char, float) - Static method in class weka.core.WekaOptionUtils

Parses a float option, uses default if option is missing.

parse(String[], char, int) - Static method in class weka.core.WekaOptionUtils

Parses an int option, uses default if option is missing.

parse(String[], char, long) - Static method in class weka.core.WekaOptionUtils

Parses an long option, uses default if option is missing.

parse(String[], char, BaseObject) - Static method in class weka.core.WekaOptionUtils

Parses a BaseObject option, uses default if option is missing.

parse(String[], char, BaseObject[]) - Static method in class weka.core.WekaOptionUtils

Parses a BaseObject option, uses default if option is missing.

parse(String[], char, Index) - Static method in class weka.core.WekaOptionUtils

Parses an Index option, uses default if option is missing.

parse(String[], char, Index[]) - Static method in class weka.core.WekaOptionUtils

Parses an Index option, uses default if option is missing.

parse(String[], char, OptionHandler) - Static method in class weka.core.WekaOptionUtils

Parses an adams.core.option.OptionHandler option, uses default if option is missing.

parse(String[], char, OptionHandler[], Class) - Static method in class weka.core.WekaOptionUtils

Parses an adams.core.option.OptionHandler array option, uses default if option is missing.

parse(String[], char, Range) - Static method in class weka.core.WekaOptionUtils

Parses a Range option, uses default if option is missing.

parse(String[], char, Range[]) - Static method in class weka.core.WekaOptionUtils

Parses a Range option, uses default if option is missing.

parse(String[], char, File) - Static method in class weka.core.WekaOptionUtils

Parses a File option, uses default if option is missing.

parse(String[], char, Class<T>) - Static method in class weka.core.WekaOptionUtils

Parses an array option, returns all the occurrences of the option as a string array.

parse(String[], char, Enum) - Static method in class weka.core.WekaOptionUtils

Parses an enum option, uses default if option is missing.

parse(String[], char, String) - Static method in class weka.core.WekaOptionUtils

Parses a String option, uses default if option is missing.

parse(String[], char, OptionHandler) - Static method in class weka.core.WekaOptionUtils

Parses an OptionHandler option, uses default if option is missing.

parse(String[], char, OptionHandler[], Class) - Static method in class weka.core.WekaOptionUtils

Parses an OptionHandler array option, uses default if option is missing.

parse(String[], String) - Static method in class weka.core.WekaOptionUtils

Parses an array option, returns all the occurrences of the option as a string array.

parse(String[], String, double) - Static method in class weka.core.WekaOptionUtils

Parses a double option, uses default if option is missing.

parse(String[], String, float) - Static method in class weka.core.WekaOptionUtils

Parses a float option, uses default if option is missing.

parse(String[], String, int) - Static method in class weka.core.WekaOptionUtils

Parses an int option, uses default if option is missing.

parse(String[], String, long) - Static method in class weka.core.WekaOptionUtils

Parses a long option, uses default if option is missing.

parse(String[], String, BaseObject) - Static method in class weka.core.WekaOptionUtils

Parses a BaseObject option, uses default if option is missing.

parse(String[], String, BaseObject[]) - Static method in class weka.core.WekaOptionUtils

Parses a BaseObject option, uses default if option is missing.

parse(String[], String, Index) - Static method in class weka.core.WekaOptionUtils

Parses a Index option, uses default if option is missing.

parse(String[], String, Index[]) - Static method in class weka.core.WekaOptionUtils

Parses a Index option, uses default if option is missing.

parse(String[], String, PlaceholderDirectory) - Static method in class weka.core.WekaOptionUtils

Parses a PlaceholderDirectory option, uses default if option is missing.

parse(String[], String, PlaceholderFile) - Static method in class weka.core.WekaOptionUtils

Parses a PlaceholderFile option, uses default if option is missing.

parse(String[], String, OptionHandler) - Static method in class weka.core.WekaOptionUtils

Parses an adams.core.option.OptionHandler option, uses default if option is missing.

parse(String[], String, OptionHandler[], Class) - Static method in class weka.core.WekaOptionUtils

Parses an adams.core.option.OptionHandler array option, uses default if option is missing.

parse(String[], String, Range) - Static method in class weka.core.WekaOptionUtils

Parses a Range option, uses default if option is missing.

parse(String[], String, Range[]) - Static method in class weka.core.WekaOptionUtils

Parses a Range option, uses default if option is missing.

parse(String[], String, File) - Static method in class weka.core.WekaOptionUtils

Parses a File option, uses default if option is missing.

parse(String[], String, Class<T>) - Static method in class weka.core.WekaOptionUtils

Parses an array option, returns all the occurrences of the option as a string array.

parse(String[], String, Enum) - Static method in class weka.core.WekaOptionUtils

Parses an enum option, uses default if option is missing.

parse(String[], String, Object, Class) - Static method in class weka.core.WekaOptionUtils

Parses an array option, uses default if option is missing.

parse(String[], String, String) - Static method in class weka.core.WekaOptionUtils

Parses a String option, uses default if option is missing.

parse(String[], String, OptionHandler) - Static method in class weka.core.WekaOptionUtils

Parses an OptionHandler option, uses default if option is missing.

parse(String[], String, OptionHandler[], Class) - Static method in class weka.core.WekaOptionUtils

Parses an OptionHandler array option, uses default if option is missing.

parseAttribute(String) - Method in class weka.core.converters.SimpleArffLoader

Extracts the attribute name, type and date format from the line.

parseClassify(byte[]) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation

Parses the data received from the process, to be returned by the Classifier.classifyInstance(Instance) method.

parseClassify(byte[]) - Method in class weka.classifiers.meta.socketfacade.Simple

Parses the data received from the process, to be returned by the Classifier.classifyInstance(Instance) method.

parseContent(String) - Method in class adams.ml.data.DataCellView

Attempts to determine the data type of the string.

parseContent(String, Cell.ContentType) - Method in class adams.ml.data.DataCellView

Parses the content of the cell using the specified type.

parseDense(Instances, String) - Method in class weka.core.converters.SimpleArffLoader

Parses a dense instance.

parseDistribution(byte[], int) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation

Parses the data received from the process, to be returned by the Classifier.distributionForInstance(Instance) method.

parseDistribution(byte[], int) - Method in class weka.classifiers.meta.socketfacade.Simple

Parses the data received from the process, to be returned by the Classifier.distributionForInstance(Instance) method.

parsePrediction(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Parses the prediction.

parsePredictions(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Parses the predictions.

parseSparse(Instances, String) - Method in class weka.core.converters.SimpleArffLoader

Parses a data row in sparse format.

parseString(String) - Method in class weka.classifiers.meta.AbstainAverage

Expect ; separated entries with min,max,difference e.g.

parseString(String) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Expect ; separated entries with min,max,difference e.g.

parseString(String) - Method in class weka.classifiers.meta.AbstainVote

Expect ; separated entries with min,max,difference e.g.

parseSubRange(String) - Method in class adams.data.weka.WekaUnorderedAttributeRange

Parses the subrange.

parseTrain(byte[]) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation

Parses the data received from the process from the training process.

parseTrain(byte[]) - Method in class weka.classifiers.meta.socketfacade.Simple

Parses the data received from the process from the training process.

parseWeights(String) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Expect "1,1,1,1"

PartialLeastSquaresTab - Class in adams.gui.tools.wekainvestigator.tab

Visualizes the PLS loadings and PLS space calculated from the selected dataset.

PartialLeastSquaresTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

PartitionedMultiFilter2 - Class in weka.filters.unsupervised.attribute

A filter that applies filters on subsets of attributes and assembles the output into a new dataset.

PartitionedMultiFilter2() - Constructor for class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

PartitionedStacking - Class in weka.classifiers.meta

Builds the base-classifiers on subsets of the data defined by ranges that correspond to the base-classifiers.

PartitionedStacking() - Constructor for class weka.classifiers.meta.PartitionedStacking

PassThrough - Class in adams.data.weka.evaluator

A dummy evaluator that OKs all data.

PassThrough - Class in adams.flow.transformer.wekaclassifiersetupprocessor

Simply returns the same setups.

PassThrough - Class in adams.flow.transformer.wekaclusterer

Dummy post-processor that just returns the model container as it is.

PassThrough - Class in adams.flow.transformer.wekaevaluationpostprocessor

Does nothing, just passes through the input data.

PassThrough - Class in weka.core.tokenizers.cleaners

Dummy, never removes a token.

PassThrough - Class in weka.filters.unsupervised.instance.multirowprocessor.processor

Just passes through the data.

PassThrough() - Constructor for class adams.data.weka.evaluator.PassThrough

PassThrough() - Constructor for class adams.flow.transformer.wekaclassifiersetupprocessor.PassThrough

PassThrough() - Constructor for class adams.flow.transformer.wekaclusterer.PassThrough

PassThrough() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.PassThrough

PassThrough() - Constructor for class weka.core.tokenizers.cleaners.PassThrough

PassThrough() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.processor.PassThrough

passwordTipText() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the tip text for this property.

passwordTipText() - Method in class adams.flow.source.WekaDatabaseReader

Returns the tip text for this property.

PATTERN - Static variable in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

the pattern to use.

pauseExecution() - Method in class adams.flow.transformer.WekaClassifierRanker

Pauses the execution.

pauseExecution() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Pauses the execution.

PCA - Class in adams.data.instancesanalysis

Performs principal components analysis and allows access to loadings and scores.

PCA() - Constructor for class adams.data.instancesanalysis.PCA

PCANNSearch - Class in weka.core.neighboursearch

Class implementing the brute force search algorithm for nearest neighbour search, filtered using PLS.

PCANNSearch() - Constructor for class weka.core.neighboursearch.PCANNSearch

Constructor.

PCANNSearch(Instances) - Constructor for class weka.core.neighboursearch.PCANNSearch

Constructor that uses the supplied set of instances.

PCANNSearchWithIndices - Class in weka.core.neighboursearch

PCANNSearch with index support.

PCANNSearchWithIndices() - Constructor for class weka.core.neighboursearch.PCANNSearchWithIndices

pctTipText() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

pctTipText() - Method in class weka.classifiers.meta.LeastMedianSq

PeakTransformed - Class in weka.classifiers.meta

Uses the maximum peak in the instances.

PeakTransformed() - Constructor for class weka.classifiers.meta.PeakTransformed

PERCENT_CORRECT - adams.flow.core.EvaluationStatistic

PERCENT_CORRECT - adams.flow.core.ExperimentStatistic

PERCENT_CORRECT - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

PERCENT_INCORRECT - adams.flow.core.EvaluationStatistic

PERCENT_INCORRECT - adams.flow.core.ExperimentStatistic

PERCENT_UNCLASSIFIED - adams.flow.core.EvaluationStatistic

PERCENT_UNCLASSIFIED - adams.flow.core.ExperimentStatistic

percentageTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns the tip text for this property.

percentageTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Returns the tip text for this property.

percentageTipText() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the tip text for this property.

percentageTipText() - Method in class adams.flow.transformer.WekaRandomSplit

Returns the tip text for this property.

percentageTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Returns the tip text for this property.

percentageTipText() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

percentageTipText() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

percentageTipText() - Method in class weka.classifiers.DefaultRandomSplitGenerator

Returns the tip text for this property.

percentageTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

percentageTipText() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns the tip text for this property.

percentilesTipText() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the tip text for this property.

percentileTipText() - Method in class weka.classifiers.meta.AbstainAttributePercentile

percentTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst

Returns the tip text for this property.

PerFoldMultiPagePane - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold

Specialized multi-page pane for managing per-fold data.

PerFoldMultiPagePane(AbstractOutputGenerator, ResultItem, Class) - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane

Initializes the pane.

PerformancePlot(String, AbstractClassifierBasedGeneticAlgorithm) - Constructor for class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot

Initializes plot.

performComparison() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Performs the comparison between the rows from the two datasets.

performFlush() - Method in class adams.flow.transformer.WekaInstanceDumper

Performs the flush.

performInitialization(AbstractGeneticAlgorithm, PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix

Gets called for performing the initialization.

performSetUpChecks(boolean) - Method in class adams.flow.sink.WekaFileWriter

Hook for performing setup checks -- used in setUp() and preExecute().

performSwap(PropertyPath.Path, PropertyDescriptor, Object, Object) - Method in class adams.data.conversion.SwapPLS

Performs the swap.

performTrainingTipText() - Method in class weka.classifiers.functions.PyroProxy

Returns the tip text for this property.

PLACEHOLDER_CURRENTFOLD - Static variable in class weka.classifiers.CrossValidationHelper

the placeholder for the current fold number.

PLACEHOLDER_CURRENTVALUE - Static variable in class weka.classifiers.LeaveOneOutByValueGenerator

the placeholder for the current value in the test set.

PLACEHOLDER_INDEX - Static variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

the placeholder for the class index in the distribution format.

PLACEHOLDER_LABEL - Static variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

the placeholder for the class label in the distribution format.

PLACEHOLDER_ORIGINAL - Static variable in class weka.classifiers.CrossValidationHelper

the placeholder for the (original) relation name.

PLACEHOLDER_ORIGINAL - Static variable in class weka.classifiers.LeaveOneOutByValueGenerator

the placeholder for the (original) relation name.

PLACEHOLDER_TYPE - Static variable in class weka.classifiers.CrossValidationHelper

the placeholder for "train" or "test" type.

PLACEHOLDER_TYPE - Static variable in class weka.classifiers.LeaveOneOutByValueGenerator

the placeholder for "train" or "test" type.

PlainTextResultsPanel - Class in adams.gui.tools.wekamultiexperimenter.analysis

Displays the results in plain text.

PlainTextResultsPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel

plot(InstancesTablePopupMenuItemHelper.TableState, boolean) - Method in class adams.gui.visualization.instances.instancestable.Binning

Allows the user to generate a plot from either a row or a column.

plot(InstancesTablePopupMenuItemHelper.TableState, boolean) - Method in class adams.gui.visualization.instances.instancestable.Histogram

Allows the user to generate a plot from either a row or a column.

plot(InstancesTablePopupMenuItemHelper.TableState, boolean, int, int[]) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Allows the user to generate a plot from either a row or a column.

plot(InstancesTablePopupMenuItemHelper.TableState, boolean, int, int[]) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Allows the user to generate a plot from either a row or a column.

PLOT_SIZE - Static variable in class weka.gui.visualize.plugins.FixedClassifierErrors

fixed plot size.

PlotAttributeVsAttribute - Class in adams.gui.menu

Allows the user to select a dataset and plot attribute vs attribute (selected by user).

PlotAttributeVsAttribute() - Constructor for class adams.gui.menu.PlotAttributeVsAttribute

Initializes the menu item with no owner.

PlotAttributeVsAttribute(AbstractApplicationFrame) - Constructor for class adams.gui.menu.PlotAttributeVsAttribute

Initializes the menu item.

plotColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotColumn

Plots the specified column.

plotColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.Binning

Plots the specified column.

plotColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.Histogram

Plots the specified column.

plotColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Plots the specified column.

plotColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.PlotColumn

Plots the specified column.

plotColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Plots the specified column.

PlotColumn - Interface in adams.gui.visualization.instances.instancestable

Interface for plugins that plot a column.

plotNameTipText() - Method in class adams.flow.transformer.WekaAccumulatedError

Returns the tip text for this property.

plotRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotRow

Plots the specified row.

plotRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.Binning

Plots the specified row.

plotRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.Histogram

Plots the specified row.

plotRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Plots the specified row.

plotRow(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.PlotRow

Plots the specified row.

plotRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Plots the specified row.

PlotRow - Interface in adams.gui.visualization.instances.instancestable

Interface for plugins that plot a row.

plotSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Plots the specified row.

plotSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.PlotSelectedRows

Plots the specified row.

plotSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Plots the specified row.

PlotSelectedRows - Interface in adams.gui.visualization.instances.instancestable

Interface for plugins that plot selected rows.

PLS - Class in adams.data.instancesanalysis

Performs partial least squares analysis and allows access to loadings and scores.

PLS - Class in weka.filters.supervised.attribute

Applies the specified partial least squares (PLS) algorithm to the data.

PLS() - Constructor for class adams.data.instancesanalysis.PLS

PLS() - Constructor for class weka.filters.supervised.attribute.PLS

PLS1 - Class in adams.data.instancesanalysis.pls

Implementation of PLS1 algorithm.

For more information see:

Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002).

PLS1() - Constructor for class adams.data.instancesanalysis.pls.PLS1

PLS1_B_HAT - adams.flow.transformer.WekaExtractPLSMatrix.MatrixType

the b-hat vector for PLS1

PLS1_P - adams.flow.transformer.WekaExtractPLSMatrix.MatrixType

the P matrix for PLS1

PLS1_REGVECTOR - adams.flow.transformer.WekaExtractPLSMatrix.MatrixType

the regression vector "r-hat" for PLS1

PLS1_W - adams.flow.transformer.WekaExtractPLSMatrix.MatrixType

the W matrix for PLS1

PLS1AttributeEval - Class in weka.attributeSelection

Uses the first component of PLS1 to determine the importance of the attributes (defaults: no preprocessing, missing values not replaced, and 20 components)

PLS1AttributeEval() - Constructor for class weka.attributeSelection.PLS1AttributeEval

PLSClassifierWeighted - Class in weka.classifiers.functions

A wrapper classifier for the PLSFilter, utilizing the PLSFilter's ability to perform predictions.

PLSClassifierWeighted() - Constructor for class weka.classifiers.functions.PLSClassifierWeighted

PLSClassifierWeightedWithLoadings - Class in weka.classifiers.functions

A wrapper classifier for the PLSFilter, utilizing the PLSFilter's ability to perform predictions.

Allows access to the PLS matrices in case the filter is a PLSFilterWithLoadings instance.

PLSClassifierWeightedWithLoadings() - Constructor for class weka.classifiers.functions.PLSClassifierWeightedWithLoadings

PLSFilterExtended - Class in weka.filters.supervised.attribute

Class contains changes to the Weka's PLSFilter in order to have simpls work with multiple y attributes.

PLSFilterExtended() - Constructor for class weka.filters.supervised.attribute.PLSFilterExtended

PLSFilterNumComponents - Class in adams.core.discovery.genetic

SavitzkyGolay numPoints handler.

PLSFilterNumComponents() - Constructor for class adams.core.discovery.genetic.PLSFilterNumComponents

PLSFilterWithLoadings - Class in weka.filters.supervised.attribute

Runs Partial Least Square Regression over the given instances and computes the resulting beta matrix for prediction.
By default it replaces missing values and centers the data.

Allows access to the internal matrices.

For more information see:

Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002).

PLSFilterWithLoadings() - Constructor for class weka.filters.supervised.attribute.PLSFilterWithLoadings

PLSMatrixAccess - Interface in weka.core

For classes that allow access to PLS matrices.

PLSNNSearch - Class in weka.core.neighboursearch

Class implementing the brute force search algorithm for nearest neighbour search, filtered using PLS.

PLSNNSearch() - Constructor for class weka.core.neighboursearch.PLSNNSearch

Constructor.

PLSNNSearch(Instances) - Constructor for class weka.core.neighboursearch.PLSNNSearch

Constructor that uses the supplied set of instances.

PLSNNSearchWithIndices - Class in weka.core.neighboursearch

PLSNNSearch with index support.

PLSNNSearchWithIndices() - Constructor for class weka.core.neighboursearch.PLSNNSearchWithIndices

PLSTipText() - Method in class weka.classifiers.trees.RandomRegressionForest

Returns the tip text for this property

PLSWeighted - Class in weka.classifiers.functions

A wrapper classifier for the PLS filter, utilizing the filter's ability to perform predictions.

PLSWeighted() - Constructor for class weka.classifiers.functions.PLSWeighted

POISSON_REGRESSION_FOR_COUNT_DATA - weka.classifiers.trees.XGBoost.Objective

polynomialOrderTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Returns the tip text for this property.

polynomialOrderTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Returns the tip text for this property.

POST_TOKENIZER - Static variable in class weka.core.tokenizers.PreCleanedTokenizer

postExecute(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Hook method just after the experiment was run.

postExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup

Hook method for after executing the experiment, e.g., cleaning up temp files.

postExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Hook method for after executing the experiment, e.g., cleaning up temp files.

postExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Hook method for after executing the experiment, e.g., cleaning up temp files.

postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Hook method that gets called after finishing a job.

postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Hook method that gets called after finishing a job.

postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Hook method that gets called after finishing a job.

postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Hook method that gets called after finishing a job.

postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Hook method that gets called after finishing a job.

postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Hook method that gets called after finishing a job.

postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Hook method that gets called after finishing a job.

postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Hook method that gets called after stopping a job.

postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Hook method that gets called after finishing a job.

postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Hook method that gets called after finishing a job.

postGenerate(Object, IndexedSplitsRuns, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

For post-processing successfully generated splits.

postProcess(WekaEvaluationContainer) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor

Post-processes the evaluation container.

postProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor

Post-processes the model container.

postProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor

Post-processes the evaluation.

postProcess(Evaluation) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Post-processes the Evaluation if necessary.

postProcessCheck() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Checks whether all post-conditions have been met.

postProcessCheck() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob

Checks whether all post-conditions have been met.

postProcessCheck() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob

Checks whether all post-conditions have been met.

postProcessCheck() - Method in class adams.flow.transformer.WekaTrainAssociator.TrainJob

Checks whether all post-conditions have been met.

postProcessCheck() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob

Checks whether all post-conditions have been met.

postProcessCheck() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob

Checks whether all post-conditions have been met.

postProcessCheck() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

Checks whether all post-conditions have been met.

postProcessCheck() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

Checks whether all post-conditions have been met.

postProcessCheck() - Method in class adams.multiprocess.WekaCrossValidationJob

Checks whether all post-conditions have been met.

postProcessCheck() - Method in class adams.opt.optimise.GeneticAlgorithm.GAJob

postProcessDistances(double[]) - Method in class weka.core.SAXDistance

Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).

postProcessDistances(double[]) - Method in class weka.core.WeightedEuclideanDistance

Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).

postProcessDistances(double[]) - Method in class weka.core.WeightedEuclideanDistanceRidge

Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).

postProcessHeader(T) - Method in class adams.data.instances.AbstractInstanceGenerator

Adds IDs, notes, additional fields to header.

postProcessorsTipText() - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor

Returns the tip text for this property.

postProcessorsTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor

Returns the tip text for this property.

postProcessorTipText() - Method in class adams.flow.transformer.WekaClustererPostProcessor

Returns the tip text for this property.

postProcessorTipText() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor

Returns the tip text for this property.

postProcessorTipText() - Method in class adams.flow.transformer.WekaTrainClusterer

Returns the tip text for this property.

postProcessOutput(T, Instance) - Method in class adams.data.instances.AbstractInstanceGenerator

For adding IDs, notes, additional fields to the data.

postRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob

Gets called after execution.

postRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob

Gets called after execution.

postRun() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Further clean-ups in derived classes.

postRun(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner

Hook method that gets executed after the experiment has finished (successfully or not).

postRun(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Hook method that gets executed after the experiment has finished (successfully or not).

postRun(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractWekaExperimentRunner

Hook method that gets executed after the experiment has finished (successfully or not).

postRun(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.runner.DefaultWekaExperimentRunner

Hook method that gets executed after the experiment has finished (successfully or not).

postRun(String) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Further clean-ups in derived classes.

postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Hook method that gets called after successfully starting a job.

postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Hook method that gets called after successfully starting a job.

postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Hook method that gets called after successfully starting a job.

postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Hook method that gets called after successfully starting a job.

postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Hook method that gets called after successfully starting a job.

postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Hook method that gets called after successfully starting a job.

postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Hook method that gets called after successfully starting a job.

postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Hook method that gets called after successfully starting a job.

postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Hook method that gets called after successfully starting a job.

postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Hook method that gets called after successfully starting a job.

postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Hook method that gets called after stopping a job.

postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Hook method that gets called after stopping a job.

postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Hook method that gets called after stopping a job.

postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Hook method that gets called after stopping a job.

postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Hook method that gets called after stopping a job.

postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Hook method that gets called after stopping a job.

postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Hook method that gets called after stopping a job.

postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Hook method that gets called after stopping a job.

postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Hook method that gets called after stopping a job.

postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Hook method that gets called after stopping a job.

postTokenizerTipText() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns the tip text for this property.

postTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

Postprocesses the data.

postTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Postprocesses the data.

postTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS

Postprocesses the data.

postUpdate() - Method in class adams.gui.visualization.instance.InstancePanel

Hook method, called after the update was performed.

PRE_FILTER - Static variable in class weka.filters.unsupervised.instance.KennardStone

PRE_TOKENIZER - Static variable in class weka.core.tokenizers.PreCleanedTokenizer

PRECISION - adams.flow.sink.WekaThresholdCurve.AttributeName

PRECISION - adams.opt.genetic.Measure

precision.

PreCleanedTokenizer - Class in weka.core.tokenizers

Allows the cleaning of tokens before actual tokenization.

PreCleanedTokenizer() - Constructor for class weka.core.tokenizers.PreCleanedTokenizer

predict(Instances) - Method in class adams.data.instancesanalysis.pls.PLS1

Performs predictions on the data.

PREDICTED_CLUSTER - Static variable in class adams.flow.transformer.wekaclusterer.AddCluster

PREDICTED_DISTRIBUTION - Static variable in class adams.flow.transformer.wekaclusterer.AddCluster

PREDICTED_MINUS_ACTUAL - adams.flow.transformer.WekaBootstrapping.ErrorCalculation

predictedMaxTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

predictedMinTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

predictedTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the tip text for this property.

predictedTipText() - Method in class weka.classifiers.functions.FromPredictions

Returns the tip text for this property.

predictIntervals(Instance, double) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Predicts a confidence interval for the given instance and confidence level.

predictIntervals(Instance, double) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Computes a prediction interval for the given instance and confidence level.

predictIntervals(Instance, double) - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Predicts a confidence interval for the given instance and confidence level.

predictIntervals(Instance, double) - Method in class weka.classifiers.functions.SimpleLinearRegressionIntervalEstimator

Returns an N * 2 array, where N is the number of prediction intervals.

predictIntervals(Instance, double) - Method in class weka.classifiers.lazy.LWLIntervalEstimator

Returns an N * 2 array, where N is the number of prediction intervals.

predictIntervals(Instance, double) - Method in class weka.classifiers.meta.FilteredClassifierExt

Returns an N * 2 array, where N is the number of prediction intervals.

PredictionEccentricity - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Generates classifier prediction eccentricity.

PredictionEccentricity() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

predictionForInstance(Instance, boolean) - Method in class weka.classifiers.meta.ClassifierCascade

Returns the prediction for the instance.

PredictionHelper - Class in adams.gui.tools.wekainvestigator.tab.classifytab

Helper class for dealing with predictions from result items.

PredictionHelper() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.PredictionHelper

Predictions - Class in adams.flow.transformer.wekarepeatedcrossvalidationoutput

Generates statistics for predictions from repeated cross-validation runs.

Predictions - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Displays the predictions.

Predictions - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated

Generates statistics for predictions from repeated cross-validation runs.

Predictions() - Constructor for class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Predictions() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Predictions() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

PREDICTIONS_RECORDED - adams.flow.transformer.WekaEvaluationInfo.InfoType

predictionsFileTipText() - Method in class weka.classifiers.functions.FromPredictions

Returns the tip text for this property.

PredictionTrend - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Generates a 'prediction trend' for classifier errors: sorts the predictions on the actual value and plots actual and predicted side-by-side.

PredictionTrend() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

PredictionType - Enum in adams.data.instancesanalysis.pls

The type of prediction to perform.

predictionTypeTipText() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the tip text for this property

PredictionUtils - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated

Helper class for predictions from repeated cross-validation runs.

PredictionUtils() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.PredictionUtils

predictMaxTipText() - Method in class weka.classifiers.functions.FakeClassifier

Returns the tip text for this property.

predictMinTipText() - Method in class weka.classifiers.functions.FakeClassifier

Returns the tip text for this property.

predictorTipText() - Method in class weka.classifiers.meta.Consensus

Returns the tip text for this property.

predictorTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the predictor option.

predictWaitTipText() - Method in class weka.classifiers.functions.FakeClassifier

Returns the tip text for this property.

preExecute() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Hook method just before the experiment is run (after initialization).

preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaFilter

Returns the tip text for this property.

preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Returns the tip text for this property.

preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaTrainAssociator

Returns the tip text for this property.

preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaTrainClassifier

Returns the tip text for this property.

preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaTrainClusterer

Returns the tip text for this property.

preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator

Returns the tip text for this property.

preFilterTipText() - Method in class adams.data.weka.rowfinder.FilteredIQR

Returns the tip text for this property.

preFilterTipText() - Method in class weka.filters.FilteredFilter

Returns the tip text for this property.

preFilterTipText() - Method in class weka.filters.unsupervised.instance.KennardStone

Returns the tip text for this property.

prefix(int, StringBuffer) - Method in class weka.classifiers.trees.RandomRegressionForest.Node

generates the tree structure prefix

PREFIX - Static variable in class weka.filters.unsupervised.attribute.EquiDistance

the option for the prefix of the new attribute names.

PREFIX_ADDITIONALFIELDS - Static variable in class adams.data.weka.ArffUtils

the prefix for additional fields.

PREFIX_DATASET_ATTRIBUTE - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator

PREFIX_NOTE - Static variable in class adams.data.weka.ArffUtils

the prefix for notes.

prefixAttributes(Instances, int) - Method in class adams.flow.transformer.WekaInstancesMerge

Prefixes the attributes.

prefixDatasetsWithIndexTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the tip text for this property.

prefixesTipText() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Returns the tip text for this property.

prefixesTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Returns the tip text for this property.

prefixSeparatorTipText() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the tip text for this property.

prefixTipText() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the tip text for this property.

prefixTipText() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the tip text for this property.

preparationTipText() - Method in class weka.classifiers.meta.SocketFacade

Returns the tip text for this property.

prepareClassify(Instance, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation

Prepares the instance for the Classifier.classifyInstance(Instance) method.

prepareClassify(Instance, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.Simple

Prepares the instance for the Classifier.classifyInstance(Instance) method.

prepareData(Instances, int) - Method in class adams.flow.transformer.WekaInstancesMerge

Prepares the data, prefixing attributes, removing columns, etc, before merging it.

prepareDistribution(Instance, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation

Prepares the instance for the Classifier.distributionForInstance(Instance) method.

prepareDistribution(Instance, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.Simple

Prepares the instance for the Classifier.distributionForInstance(Instance) method.

prepareTrain(Instances, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation

Prepares the data for training.

prepareTrain(Instances, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.Simple

Prepares the data for training.

prepareUpdate() - Method in class adams.gui.visualization.instance.InstancePanel

Updates the axes with the min/max of the new data.

preProcessCheck() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Checks whether all pre-conditions have been met.

preProcessCheck() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob

Checks whether all pre-conditions have been met.

preProcessCheck() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob

Checks whether all pre-conditions have been met.

preProcessCheck() - Method in class adams.flow.transformer.WekaTrainAssociator.TrainJob

Checks whether all pre-conditions have been met.

preProcessCheck() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob

Checks whether all pre-conditions have been met.

preProcessCheck() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob

Checks whether all pre-conditions have been met.

preProcessCheck() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

Checks whether all pre-conditions have been met.

preProcessCheck() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

Checks whether all pre-conditions have been met.

preProcessCheck() - Method in class adams.multiprocess.WekaCrossValidationJob

preProcessCheck() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob

Checks whether all pre-conditions have been met.

preProcessCheck() - Method in class adams.opt.optimise.GeneticAlgorithm.GAJob

PreprocessHandler - Class in weka.gui.explorer

Manages the PreprocessPanel.

PreprocessHandler() - Constructor for class weka.gui.explorer.PreprocessHandler

PreprocessingType - Enum in adams.data.instancesanalysis.pls

The preprocessing type.

preprocessingTypeTipText() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the tip text for this property

preprocessingTypeTipText() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Returns the tip text for this property

PreprocessTab - Class in adams.gui.tools.wekainvestigator.tab

Preprocessing tab.

PreprocessTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.PreprocessTab

preRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob

Gets called before the execution.

preRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob

Gets called before the execution.

preRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Hook method that gets executed before the experiment gets initialized.

preRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.RemoteWekaExperimentRunner

Hook method that gets executed before the experiment gets initialized.

preRun() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Some more initializations.

preRun() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Further initializations in derived classes.

preRun() - Method in class adams.opt.genetic.DarkLord

Some more initializations.

preRun() - Method in class adams.opt.genetic.Hermione

Some more initializations.

preRun() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Further initializations in derived classes.

preRun() - Method in class adams.opt.optimise.GeneticAlgorithm

Some more initializations.

preRun() - Method in class adams.tools.CompareDatasets

Before the actual run is executed.

preSelectionTipText() - Method in class adams.flow.transformer.WekaChooseAttributes

Returns the tip text for this property.

preserveIDColumnTipText() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the tip-text for the preserve-id-column option.

preserveInstancesOrderTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

preserveOrderTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns the tip text for this property.

preserveOrderTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Returns the tip text for this property.

preserveOrderTipText() - Method in class adams.flow.transformer.WekaRandomSplit

Returns the tip text for this property.

preserveOrderTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Returns the tip text for this property.

preserveOrderTipText() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

preserveOrderTipText() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

preserveOrderTipText() - Method in class weka.classifiers.DefaultRandomSplitGenerator

Returns the tip text for this property.

preserveOrderTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

preserveOrderTipText() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns the tip text for this property.

preTokenizerTipText() - Method in class weka.core.tokenizers.PreCleanedTokenizer

Returns the tip text for this property.

preTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

Preprocesses the data.

preTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Preprocesses the data.

preTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS

Preprocesses the data.

PrincipalComponentsJ - Class in weka.filters.unsupervised.attribute

* Performs a principal components analysis and transformation of the data.
* Dimensionality reduction is accomplished by choosing enough eigenvectors to account for some percentage of the variance in the original data -- default 0.95 (95%).
* Based on code of the attribute selection scheme 'PrincipalComponents' by Mark Hall and Gabi Schmidberger.

PrincipalComponentsJ() - Constructor for class weka.filters.unsupervised.attribute.PrincipalComponentsJ

PrincipalComponentsTab - Class in adams.gui.tools.wekainvestigator.tab

Visualizes the PCA loadings and PCA space calculated from the selected dataset.

PrincipalComponentsTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

print(double[]) - Method in class adams.opt.genetic.PackDataGeneticAlgorithm

Outputs the bits with the logger - logging needs to be enabled.

print(double[]) - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm

printAllModels() - Method in class weka.classifiers.trees.m5.RuleNode2

Print all the linear models at the learf (debugging purposes)

printBits(int[]) - Method in class adams.opt.genetic.PackDataGeneticAlgorithm

Outputs the bits with the logger - logging needs to be enabled.

printBits(int[]) - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm

printLeafModels() - Method in class weka.classifiers.trees.m5.RuleNode2

print all leaf models

printNodeLinearModel() - Method in class weka.classifiers.trees.m5.RuleNode2

print the linear model at this node

PRM - Class in adams.data.instancesanalysis.pls

PRM() - Constructor for class adams.data.instancesanalysis.pls.PRM

process() - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator

Processes the data if necessary.

process() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Does the actual execution of the job.

process() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob

Does the actual execution of the job.

process() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob

Does the actual execution of the job.

process() - Method in class adams.flow.transformer.WekaTrainAssociator.TrainJob

Does the actual execution of the job.

process() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob

Does the actual execution of the job.

process() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob

Does the actual execution of the job.

process() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

Does the actual execution of the job.

process() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

Does the actual execution of the job.

process() - Method in class adams.multiprocess.WekaCrossValidationJob

Does the actual execution of the job.

process() - Method in class adams.opt.optimise.GeneticAlgorithm.GAJob

Does the actual execution of the job.

process() - Method in class weka.core.InstanceGrouping

Performs the grouping.

process(Classifier[]) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.AbstractClassifierSetupProcessor

Processes the classifier array.

process(Instance) - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.AnyToString

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.DownSample

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.FFT

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.LogTransform

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.PAA

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.RowSum

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.SAX

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.SetMissingValue

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.SpellChecker

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.attribute.StringToDate

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.instance.RowNorm

processes the given instance (may change the provided instance) and returns the modified version.

process(Instance) - Method in class weka.filters.unsupervised.instance.Scale

processes the given instance (may change the provided instance) and returns the modified version.

process(Instances) - Method in class weka.filters.FilteredFilter

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.FlowFilter

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.SerializedFilter

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.supervised.attribute.MultiPLS

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.supervised.attribute.PLS

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.supervised.attribute.PLSFilterExtended

Override in order to have the destandardized predictions for multiple y added.

process(Instances) - Method in class weka.filters.supervised.attribute.YGradientEPO

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.supervised.attribute.YGradientGLSW

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.supervised.instance.RemoveOutliers

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.Detrend

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.EquiDistance

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.FastWavelet

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.InputSmearing

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.AlignDataset

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.KeepRange

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.KennardStone

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.LatestRecords

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.Sort

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.SortOnAttribute

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Processes the given data (may change the provided dataset) and returns the modified version.

process(Instances, Instance) - Method in class weka.filters.unsupervised.attribute.EquiDistance

processes the given instance (may change the provided instance) and returns the modified version.

processCell(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell

Processes the specified column.

processCell(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.ProcessCell

Processes the specified cell.

ProcessCell - Interface in adams.gui.visualization.instances.instancestable

Interface for plugins that process a cell.

processColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn

Processes the specified column.

processColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.ProcessColumn

Processes the specified column.

ProcessColumn - Interface in adams.gui.visualization.instances.instancestable

Interface for plugins that process a column.

processData(T) - Method in class adams.data.baseline.AbstractLinearRegressionBased

Performs the actual correcting.

processData(Instances) - Method in class weka.filters.unsupervised.attribute.FastWavelet

processes the instances using the HAAR/JSci algorithm.

processDatasetWithClusterer(Instances, Clusterer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor

Performs some form of processing on the full dataset.

processDatasetWithClusterer(Instances, Clusterer) - Method in class adams.flow.transformer.wekaclusterer.AddCluster

Performs some form of processing on the full dataset.

processDatasetWithClusterer(Instances, Clusterer) - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters

Performs some form of processing on the full dataset.

processDatasetWithClusterer(Instances, Clusterer) - Method in class adams.flow.transformer.wekaclusterer.ClusterCounts

Performs some form of processing on the full dataset.

processDatasetWithClusterer(Instances, Clusterer) - Method in class adams.flow.transformer.wekaclusterer.ClusterStatistics

Performs some form of processing on the full dataset.

processHit(MouseEvent, List<InstancePoint>) - Method in class adams.gui.visualization.instance.InstancePointHitDetector

Performs the action when a hit is detected.

processInstance(Instance) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Processes the instance and generates the output token.

processInstance(Instance) - Method in class adams.flow.transformer.WekaClassifying

Processes the instance and generates the output token.

processInstance(Instance) - Method in class adams.flow.transformer.WekaClustering

Processes the instance and generates the output token.

processorTipText() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor

Returns the tip text for this property.

processRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow

Processes the specified row.

processRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic

Processes the specified row.

processRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights

Processes the specified row.

processRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset

Processes the specified row.

processRow(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.ProcessRow

Processes the specified row.

ProcessRow - Interface in adams.gui.visualization.instances.instancestable

Interface for plugins that process a row.

processRows(List<Instance>) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractSelectionProcessor

Returns the list of row indices generated from the data.

processSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

Plots the specified rows.

processSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

Processes the specified rows.

processSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.ProcessSelectedRows

Processes the specified row.

ProcessSelectedRows - Interface in adams.gui.visualization.instances.instancestable

Interface for plugins that processes selected rows.

processSIMPLS(Instances) - Method in class weka.filters.supervised.attribute.PLSFilterExtended

Extended superclass method for increasing dimensions and/of changing handling of the Matrices C,W,P,Q to deal with multiple Y variables.

processSIMPLS(Instances) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter

processSIMPLS(Instances) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

processTipText(PlotPanel, Point, String) - Method in class adams.gui.visualization.instance.InstancePanel

Processes the given tip text.

processTypeTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the processType option.

PRODUCT_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType

PRODUCT_RULE - Static variable in class weka.classifiers.meta.AbstainVote

combination rule: Product of Probabilities (only nominal classes)

PROMPT - Static variable in class adams.gui.menu.PackageManager

promptHistogramSetup() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.CompareModels

Prompts the user for a histogram setup.

promptParameters(InstancesTable) - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic

Prompts the user for parameters.

promptParameters(InstancesTablePopupMenuItemHelper.TableState, boolean) - Method in class adams.gui.visualization.instances.instancestable.Binning

Prompts the user to configure the parameters.

promptParameters(InstancesTablePopupMenuItemHelper.TableState, boolean) - Method in class adams.gui.visualization.instances.instancestable.Histogram

Prompts the user to configure the parameters.

promptParameters(InstancesTablePopupMenuItemHelper.TableState, boolean) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart

Prompts the user to configure the parameters.

promptParameters(InstancesTable, boolean) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot

Prompts the user to configure the parameters.

PROPERTY_CMDLINE - Static variable in class adams.gui.wizard.WekaPropertySheetPanelPage

the identifier for the commandline of the object.

PROPERTY_WEKAEDITORS - Static variable in class adams.gui.goe.WekaEditorsRegistration

property indicating whether to use the Weka editors instead of the Adams ones.

propertyTipText() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Returns the tip text for this property.

propertyTipText() - Method in class adams.core.discovery.genetic.GenericFloatResolution

Returns the tip text for this property.

propertyTipText() - Method in class adams.core.discovery.genetic.GenericInteger

Returns the tip text for this property.

propertyTipText() - Method in class adams.core.discovery.genetic.GenericString

Returns the tip text for this property.

PROPS_FILTER - Static variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the key for a filter setup in the setup properties.

PROPS_FILTER - Static variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

the key for a filter setup in the setup properties.

PROPS_MASK - Static variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the key for the mask in the setup properties.

PROPS_MASK - Static variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

the key for the mask in the setup properties.

PROPS_RELATION - Static variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

the key for the relation name in the generated properties file.

PROPS_RELATION - Static variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

the key for the relation name in the generated properties file.

prune() - Method in class weka.classifiers.trees.m5.RuleNode2

Recursively prune the tree

pruneBackup() - Method in class adams.flow.sink.WekaDatabaseWriter

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaAccumulatedError

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaAggregateEvaluations

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaFileReader

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaFilter

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaInstanceBuffer

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaInstanceDumper

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaStreamEvaluator

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaTrainClassifier

Removes entries from the backup.

pruneBackup() - Method in class adams.flow.transformer.WekaTrainClusterer

Removes entries from the backup.

PublicPrincipalComponents - Class in weka.filters.unsupervised.attribute

Class that is identical to the Principal components class except it contains a public method to get the coefficients from the principal components model

PublicPrincipalComponents() - Constructor for class weka.filters.unsupervised.attribute.PublicPrincipalComponents

PullUpClassifier - Class in adams.gui.goe.popupmenu

For pulling up classifiers from SingleClassifierEnhancer wrappers.

PullUpClassifier() - Constructor for class adams.gui.goe.popupmenu.PullUpClassifier

PullUpClusterer - Class in adams.gui.goe.popupmenu

For pulling up clusterers from SingleClustererEnhancer wrappers.

PullUpClusterer() - Constructor for class adams.gui.goe.popupmenu.PullUpClusterer

PullUpInstancesColumnFinder - Class in adams.gui.goe.popupmenu

Pulls up the base Instances ColumnFinder from a filtered ColumnFinder.

PullUpInstancesColumnFinder() - Constructor for class adams.gui.goe.popupmenu.PullUpInstancesColumnFinder

PullUpInstancesRowFinder - Class in adams.gui.goe.popupmenu

Pulls up the base Instances RowFinder from a filtered RowFinder.

PullUpInstancesRowFinder() - Constructor for class adams.gui.goe.popupmenu.PullUpInstancesRowFinder

putBits(int[]) - Method in class adams.opt.optimise.genetic.PackData

PyroProxy - Class in weka.classifiers.functions

Proxy for a python model using Pyro4 for communication.

PyroProxy() - Constructor for class weka.classifiers.functions.PyroProxy

PyroProxyObject - Interface in weka.core

Interface for classes that make use of Pyro4.

Q

quartile1 - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp.IQRs

QUARTILE25 - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.LowerStatistic

quartile3 - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp.IQRs

QUARTILE75 - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.UpperStatistic

queryTipText() - Method in class adams.flow.source.WekaDatabaseReader

Returns the tip text for this property.

queryUser(PerFoldMultiPagePane, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation

Queries the user for the range.

queryUser(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation

Queries the user for the range.

R

RAE - adams.flow.transformer.WekaClassifierRanker.Measure

evaluation via: Relative absolute error.

RAE - adams.opt.genetic.Measure

Relative absolute error.

RAE - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure

evaluation via: Relative absolute error.

RANDOM - weka.classifiers.trees.XGBoost.FeatureSelector

RANDOM - Static variable in class weka.clusterers.SAXKMeans

randomize(TIntList, Random) - Method in class weka.classifiers.AbstractSplitGenerator

Randomizes the indices using the given random number generator.

Randomize - Class in adams.gui.tools.wekainvestigator.datatable.action

Randomizes the selected dataset.

Randomize() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Randomize

Instantiates the action.

randomizeTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Returns the tip text for this property.

randomizeTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the tip text for this property.

randomizeTipText() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

randomizeTipText() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns the tip text for this property.

randomizeTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

randomizeTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the tip text for this property.

randomizeTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns the tip text for this property.

randomizeTipText() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Returns the tip text for this property.

randomizeTipText() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns the tip text for this property.

RandomModelTrees - Class in weka.classifiers.trees

RandomModelTrees() - Constructor for class weka.classifiers.trees.RandomModelTrees

RandomRegressionForest - Class in weka.classifiers.trees

RandomRegressionForest: subtract mean and pls, then grow completely random trees (leaf: min ..

RandomRegressionForest() - Constructor for class weka.classifiers.trees.RandomRegressionForest

RandomRegressionForest.Node - Class in weka.classifiers.trees

TODO: description of class

randomSeedTipText() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Returns the tip text for this property

randomSeedTipText() - Method in class weka.classifiers.meta.LeastMedianSq

Returns the tip text for this property

RandomSplitGenerator - Interface in weka.classifiers

Interface for generators of random splits of datasets.

RandomSubset - Class in adams.gui.tools.wekainvestigator.datatable.action

Creates a random subset from a dataset and inserts it as a new dataset.

RandomSubset() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset

Instantiates the action.

range - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState

the row range.

RANGE - weka.filters.unsupervised.attribute.EquiDistance.AttributeSelection

RANGE - Static variable in class weka.filters.unsupervised.attribute.EquiDistance

the option for the attribute range.

RANGE - Static variable in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor

range1TipText() - Method in class adams.tools.CompareDatasets

Returns the tip text for this property.

range2TipText() - Method in class adams.tools.CompareDatasets

Returns the tip text for this property.

RangeBased - Class in weka.filters.unsupervised.attribute.detrend

Performs the correction using slopes/intercepts calculated for the defined ranges.

RangeBased - Class in weka.filters.unsupervised.attribute.multiplicativescattercorrection

Performs the correction using slopes/intercepts calculated for the defined ranges.

RangeBased() - Constructor for class weka.filters.unsupervised.attribute.detrend.RangeBased

RangeBased() - Constructor for class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased

RangeCheck - Class in weka.classifiers.meta

Keeps track of the ranges in case of numeric attributes.

RangeCheck() - Constructor for class weka.classifiers.meta.RangeCheck

RangeCheckClassifier - Interface in weka.classifiers

Interface for classifiers that allow checks whether data is outside the training range of the classifier.

RangeCheckHelper - Class in weka.classifiers

Helper class for generating range checks.

RangeCheckHelper() - Constructor for class weka.classifiers.RangeCheckHelper

rangePaintletTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the tip text for this property.

rangesTipText() - Method in class adams.data.weka.rowfinder.ByNumericRange

Returns the tip text for this property.

rangesTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange

Returns the tip text for this property.

rangesTipText() - Method in class weka.classifiers.meta.PartitionedStacking

Returns the tip text for this property.

rangesTipText() - Method in class weka.filters.unsupervised.attribute.detrend.RangeBased

Returns the tip text for this property.

rangesTipText() - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased

Returns the tip text for this property.

rangesTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Returns the tip text for this property.

rangeTipText() - Method in class adams.flow.sink.WekaAttributeSummary

Returns the tip text for this property.

rangeTipText() - Method in class adams.flow.transformer.WekaAttributeIterator

Returns the tip text for this property.

rangeTipText() - Method in class weka.filters.unsupervised.attribute.AnyToString

Returns the tip text for this property.

rangeTipText() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the tip text for this property.

rangeTipText() - Method in class weka.filters.unsupervised.attribute.StringToDate

Returns the tip text for this property.

rangeTipText() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor

Returns the tip text for this property.

RankingJob(Classifier, int, Instances, Instances, long, int, WekaClassifierRanker.Measure, WekaLabelIndex, boolean) - Constructor for class adams.flow.transformer.WekaClassifierRanker.RankingJob

Initializes the job.

rateDropTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the rateDrop option.

rbfKernel(double[], double[], double) - Method in class weka.classifiers.functions.GPD

Computes the RBF kernel.

read() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractResultsHandler

Loads the results (if possible).

read() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Loads the results (if possible).

read(PlaceholderFile) - Method in class adams.data.io.input.AbstractAdamsExperimentReader

Reads the experiment file.

read(BufferedReader) - Method in class weka.core.converters.SimpleArffLoader

Performs the actual reading.

read(File, MultiExplorer) - Static method in class weka.gui.explorer.WorkspaceHelper

Reads the explorer session and initializes the explorer object.

readData() - Method in class adams.data.io.input.InstanceReader

Uses the named setup to read the data.

readerForFile(File) - Static method in class adams.gui.chooser.AdamsExperimentFileChooser

Returns the reader for the specified file.

readerForFile(File) - Static method in class adams.gui.chooser.WekaFileChooser

Returns the reader for the specified file.

readerTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Returns the tip text for this property.

readerTipText() - Method in class weka.classifiers.functions.FromPredictions

Returns the tip text for this property.

readerTipText() - Method in class weka.core.converters.SpreadSheetLoader

The tip text for this property.

realTipText() - Method in class weka.filters.unsupervised.attribute.FFT

Returns the tip text for this property.

RECALL - adams.flow.sink.WekaThresholdCurve.AttributeName

RECALL - adams.opt.genetic.Measure

recall.

receive() - Method in class weka.classifiers.meta.SocketFacade

Receives the response data.

recordClassAttributes() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Scans the datasets for attributes that should be considered classes, and keeps a record of them.

redo() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Performs a redo if possible.

ReducedData - Class in adams.gui.tools.wekainvestigator.tab.attseltab.output

Generates the reduced dataset.

ReducedData() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.output.ReducedData

reduceNumberOfDistanceCalcsViaCanopiesTipText() - Method in class weka.clusterers.SAXKMeans

Returns the tip text for this property.

ReevaluateModel - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation

Re-evaluates a serialized model.

ReevaluateModel - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation

Re-evaluates a serialized model.

ReevaluateModel() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

ReevaluateModel() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

REFERENCE_SIZE - Static variable in class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors

the error size of the reference error (mid-class range).

referenceActorTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the tip text for this property.

referenceErrorTipText() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference

Returns the tip text for this property.

referenceFileTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the tip text for this property.

referenceSizeTipText() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference

Returns the tip text for this property.

RefreshCache - Class in adams.flow.standalone.wekapackagemanageraction

Refreshes the package cache.

RefreshCache() - Constructor for class adams.flow.standalone.wekapackagemanageraction.RefreshCache

regenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Regenerates the output.

regenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Regenerates the output.

regenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Regenerates the output.

regenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Regenerates the output.

regenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Regenerates the output.

regexNameTipText() - Method in class adams.flow.transformer.WekaClassSelector

Returns the tip text for this property.

REGEXP - weka.filters.unsupervised.attribute.EquiDistance.AttributeSelection

REGEXP - Static variable in class weka.filters.unsupervised.attribute.EquiDistance

the option for the attribute regexp.

REGEXP - Static variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

regExpsTipText() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Returns the tip text for this property.

regExpsTipText() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns the tip text for this property.

regExpTipText() - Method in class adams.data.weka.classattribute.ByName

Returns the tip text for this property.

regExpTipText() - Method in class adams.data.weka.columnfinder.ByName

Returns the tip text for this property.

regExpTipText() - Method in class adams.data.weka.rowfinder.ByLabel

Returns the tip text for this property.

regExpTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the tip text for this property.

regExpTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns the tip text for this property.

regExpTipText() - Method in class adams.flow.transformer.WekaAttributeIterator

Returns the tip text for this property.

regExpTipText() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns the tip text for this property.

regExpTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

regExpTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns the tip text for this property.

regExpTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the tip text for this property.

regExpTipText() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns the tip text for this property.

regExpTipText() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Returns the tip text for this property.

regExpTipText() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Returns the tip text for this property.

regExpTipText() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Returns the tip text for this property.

regexTipText() - Method in class adams.flow.transformer.WekaRegexToRange

Returns the tip text for this property.

registerAdditionalHandler(Class, AbstractExplorerPanelHandler) - Static method in class weka.gui.explorer.WorkspaceHelper

Registers an additional handler for an Explorer.ExplorerPanel.

registerEditors(Map<String, Map<String, String>>) - Method in class adams.gui.goe.WekaEditorsRegistration

Reregisters class hierarchies with ADAMS object editors.

registerEditors(Properties) - Method in class adams.gui.goe.WekaEditorsRegistration

Reregisters class hierarchies with ADAMS object editors.

registerHierarchies(Map<String, Map<String, String>>) - Method in class adams.gui.goe.WekaEditorsRegistration

Registers the class hierarchies with ADAMS.

registerHierarchies(Properties) - Method in class adams.gui.goe.WekaEditorsRegistration

Registers the class hierarchies with ADAMS.

REGRESSION - adams.flow.sink.WekaExperimentGenerator.ExperimentType

regression.

regressionPrediction(Instance, boolean[], double[]) - Method in class weka.classifiers.functions.LinearRegressionJ

Calculate the dependent value for a given instance for a given regression model.

RELATION - adams.opt.genetic.OutputPrefixType

the relation name.

RELATION_NAME - adams.flow.transformer.WekaEvaluationInfo.InfoType

RELATION_NAME - adams.flow.transformer.WekaInstancesInfo.InfoType

the name of the dataset.

RELATIONAL_ATTRIBUTES - adams.flow.core.Capability

can handle relational attributes.

RELATIONAL_CLASS - adams.flow.core.Capability

can handle relational classes.

relationalValue(int) - Method in class weka.core.AbstractHashableInstance

Returns the relational value of a relational attribute.

relationalValue(Attribute) - Method in class weka.core.AbstractHashableInstance

Returns the relational value of a relational attribute.

relationNameTemplateTipText() - Static method in class weka.classifiers.CrossValidationHelper

Returns the tiptext for the relation name template.

relationNameTipText() - Method in class adams.flow.source.WekaNewInstances

Returns the tip text for this property.

relationNameTipText() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the tip text for this property.

relationNameTipText() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

relationNameTipText() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns the tip text for this property.

relationNameTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

relationNameTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the tip text for this property.

relationNameTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns the tip text for this property.

relationNameTipText() - Static method in class weka.classifiers.LeaveOneOutByValueGenerator

Returns the tiptext for the relation name template.

RELATIVE_ABSOLUTE_ERROR - adams.flow.core.EvaluationStatistic

RELATIVE_ABSOLUTE_ERROR - adams.flow.core.ExperimentStatistic

RelativeNumericErrorScaler - Class in adams.data.weka.predictions

Scales the errors for numeric class attributes.

RelativeNumericErrorScaler() - Constructor for class adams.data.weka.predictions.RelativeNumericErrorScaler

relativeWidthsTipText() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Returns the tip text for this property.

reload() - Method in class adams.gui.tools.DatasetCompatibilityPanel

Re-compares the currently loaded files.

reload() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Reloads the data.

reload() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer

Reloads the data.

reload() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Reloads the currently loaded dataset.

reload() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Reloads the datasets.

remoteObjectNameTipText() - Method in class weka.classifiers.functions.PyroProxy

Returns the tip text for this property.

remoteObjectNameTipText() - Method in interface weka.core.PyroProxyObject

Returns the tip text for this property.

remoteTipText() - Method in class weka.classifiers.meta.SocketFacade

Returns the tip text for this property.

RemoteWekaExperimentIO - Class in adams.gui.tools.wekamultiexperimenter.io

IO handler for remote experiments.

RemoteWekaExperimentIO() - Constructor for class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO

RemoteWekaExperimentRunner - Class in adams.gui.tools.wekamultiexperimenter.runner

A class that handles running a copy of the experiment in a separate thread.

RemoteWekaExperimentRunner(ExperimenterPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.runner.RemoteWekaExperimentRunner

Initializes the thread.

remove() - Method in class weka.classifiers.AbstractSplitGenerator

Unsupported.

remove() - Method in interface weka.classifiers.SplitGenerator

Unsupported.

remove(int) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

remove(int) - Method in class adams.gui.visualization.instance.InstanceContainerManager

Removes the container at the specified position.

remove(int) - Method in class weka.core.InstancesView

Removes the instance at the given position.

remove(Object) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

Remove - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction

Removes the selected attributes.

Remove() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.Remove

Instantiates the action.

REMOVE - adams.gui.event.InstancesSortSetupEvent.EventType

a definition was removed.

removeAccessoryLabel(Container) - Static method in class weka.gui.AdamsHelper

Removes the label in the accessory component, to make space for the bookmarks.

removeAll(Collection<?>) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

removeAttributeIndicesTipText() - Method in class weka.classifiers.meta.FilteredClassifierExt

Returns the tip text for this property.

removeAttributeType(String) - Method in class weka.core.converters.SimpleArffLoader

Removes the attribute type.

removeCell(int) - Method in class adams.ml.data.InstancesHeaderRow

Removes the cell at the specified index.

removeCell(int) - Method in class adams.ml.data.InstanceView

Removes the cell at the specified index.

removeCell(String) - Method in class adams.ml.data.InstancesHeaderRow

Removes the cell at the specified index.

removeCell(String) - Method in class adams.ml.data.InstanceView

Removes the cell at the specified index.

removeChangeListener(ChangeListener) - Method in class adams.gui.goe.WekaGenericObjectEditorPopupMenu

Removes the listener from the internal list of listeners that get notified when the user changes the setup.

removeChangeListener(ChangeListener) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Removes the change listener from the internal list.

removeChangeListener(ChangeListener) - Method in class adams.gui.visualization.instances.InstancesTable

Removes the listener from the pool of listeners that get notified when the data changes.

removeCharsTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Returns the tip text for this property.

removeCharsTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Returns the tip text for this property.

removeClassAttribute(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Removes the class attribute from the dataset (if present).

removeClassAttributes() - Method in class adams.ml.data.InstancesView

Removes all set class attributes.

removeColumn(int) - Method in class adams.ml.data.InstancesView

Removes the specified column.

removeColumn(String) - Method in class adams.ml.data.InstancesView

Removes the specified column.

removeData(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Removes the selected rows, removes all if rows are null.

removeDefinition() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

Removes itself from the list of sorting panels.

removeDefinition(InstancesSortDefinitionPanel) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Removes the panel from the list of sort definitions.

RemoveDuplicateIDs - Class in weka.filters.unsupervised.instance

Removes rows with IDs that occur multiple times.
Also skips rows with missing ID.

RemoveDuplicateIDs() - Constructor for class weka.filters.unsupervised.instance.RemoveDuplicateIDs

RemoveDuplicates - Class in weka.filters.unsupervised.instance

Removes all duplicate instances.

RemoveDuplicates() - Constructor for class weka.filters.unsupervised.instance.RemoveDuplicates

removeEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Removes the specified entry.

removeEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Removes the specified entry.

removeEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Removes the specified entry.

removeEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Removes the specified entry.

removeEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Removes the specified entry.

removeEntry(String) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel.HistoryPanel

Removes the specified entry.

removeIf(Predicate<? super DataContainer>) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

removeIncomplete(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Removes the incomplete rows of the classifier/dataset combination.

removeInstancesSortSetupListener(InstancesSortSetupListener) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Removes the specified listener.

RemoveInstancesWithMissingValue - Class in weka.filters.unsupervised.instance

Removes all instances that contain missing values.

RemoveInstancesWithMissingValue() - Constructor for class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

RemoveMisclassifiedAbs - Class in weka.filters.unsupervised.instance

A filter that removes instances which are incorrectly classified.

RemoveMisclassifiedAbs() - Constructor for class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

RemoveMisclassifiedRel - Class in weka.filters.unsupervised.instance

A filter that removes instances which are incorrectly classified.

RemoveMisclassifiedRel() - Constructor for class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

removeMissing() - Method in class adams.ml.data.InstancesHeaderRow

Removes all cells marked "missing".

removeMissing() - Method in class adams.ml.data.InstancesView

Removes all cells marked "missing".

removeMissing() - Method in class adams.ml.data.InstanceView

Removes all cells marked "missing".

RemoveNonWordCharTokens - Class in weka.core.tokenizers.cleaners

Removes tokens that contain non-word characters.

RemoveNonWordCharTokens() - Constructor for class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

RemoveOutliers - Class in weka.filters.supervised.instance

Cross-validates the specified classifier on the incoming data and applies the outlier detector to the actual vs predicted data to remove the outliers.
NB: only works on full dataset, not instance by instance.

RemoveOutliers() - Constructor for class weka.filters.supervised.instance.RemoveOutliers

removePanel(int) - Method in class weka.gui.explorer.MultiExplorer

Removes the panel at the specified index.

removePanel(String) - Method in class weka.gui.explorer.MultiExplorer

Removes the panel with the given name.

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.SqlPanel

Removes a PropertyChangeListener.

removeRange(int, int) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

removeRow(int) - Method in class adams.ml.data.InstancesView

Removes the specified row.

removeRow(String) - Method in class adams.ml.data.InstancesView

Removes the specified row.

removeSelectionListener(ListSelectionListener) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Remove a listener from the list that's notified each time a change to the selection occurs.

removeTabAt(int) - Method in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane

Removes the tab.

removeTableModelListener(TableModelListener) - Method in class adams.gui.visualization.instances.InstancesTableModel

removes a listener from the list that is notified each time a change to the data model occurs

RemoveTestInstances - Class in weka.filters.unsupervised.instance

Removes all instances of the provided test set from the data passing through.
Requires an attribute in the data that uniquely identifies instances across datasets.

RemoveTestInstances() - Constructor for class weka.filters.unsupervised.instance.RemoveTestInstances

RemoveTestSet - Class in adams.gui.tools.wekainvestigator.datatable.action

Removes the test instances from one dataset in another.

RemoveTestSet() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.RemoveTestSet

Instantiates the action.

removeTipText() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the tip text for this property.

removeTrainTipText() - Method in class weka.classifiers.meta.AbstainAttributePercentile

removeUnusedTipText() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Returns the tip text for this property.

removeUnusedTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Returns the tip text for this property.

removeUpdate(DocumentEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationDocumentListener

RemoveWithLabels - Class in weka.filters.unsupervised.instance

Allows the user to remove nominal labels via a regular expression.

RemoveWithLabels() - Constructor for class weka.filters.unsupervised.instance.RemoveWithLabels

RemoveWithWeights - Class in weka.filters.unsupervised.instance

Removes instances with weights outside the defined limits.

RemoveWithWeights() - Constructor for class weka.filters.unsupervised.instance.RemoveWithWeights

RemoveWithZeroes - Class in weka.filters.unsupervised.instance

Removes all instances that contain at least the specified number (or percentage) of zeroes in numeric attributes.

RemoveWithZeroes() - Constructor for class weka.filters.unsupervised.instance.RemoveWithZeroes

RemoveWorst - Class in adams.flow.transformer.wekaevaluationpostprocessor

Removes the worst predictions, which are considered outliers that detract from the actual model performance.

RemoveWorst() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst

RemoveWorstStdDev - Class in adams.flow.transformer.wekaevaluationpostprocessor

Removes the worst predictions, which are considered outliers that detract from the actual model performance.

RemoveWorstStdDev() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev

Rename - Class in adams.gui.tools.wekainvestigator.datatable.action

Renames the selected dataset.

Rename - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction

Renames the selected attribute.

Rename() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Rename

Instantiates the action.

Rename() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.Rename

Instantiates the action.

renameAttribute(int, String) - Method in class weka.core.InstancesView

Renames an attribute.

renameAttributeAt(int, String) - Method in class adams.gui.visualization.instances.InstancesTableModel

renames the attribute at the given col index

renameAttributes(Instances, String) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

renames all the attributes in the dataset (excluding the class if present) by adding the prefix to the name.

renameAttributeValue(int, int, String) - Method in class weka.core.InstancesView

Renames the value of a nominal (or string) attribute value.

renameData(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Renames the selected row, does nothing if 0 or more than 1 selected.

renameTabAt(int) - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane

Prompts the user to enter a new name for the tab.

ReorderAttributes - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction

Allows the user to reorder the attributes.

ReorderAttributes() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ReorderAttributes

Instantiates the action.

RepeatedCrossValidation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation

Performs repeated cross-validation.

RepeatedCrossValidation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

REPLACE - Static variable in class weka.filters.unsupervised.attribute.NominalToNumeric

replaceAttributeAt(Attribute, int) - Method in class weka.core.InstancesView

Replaces the attribute at the given position (0 to numAttributes()) with the given attribute and sets all its values to be missing.

replaceMissingTipText() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Returns the tip text for this property

replaceMissingTipText() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Returns the tip text for this property

replaceMissingValues(double[]) - Method in class weka.core.AbstractHashableInstance

Replaces all missing values in the instance with the values contained in the given array.

ReplaceMissingValuesWithZero - Class in weka.filters.unsupervised.attribute

Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means from the training data.

ReplaceMissingValuesWithZero() - Constructor for class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero

replaceTipText() - Method in class adams.flow.transformer.WekaRenameRelation

Returns the tip text for this property.

replaceTipText() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the tip text for this property.

REPORT_ADDITIONAL_PREFIX - Static variable in class adams.data.instance.Instance

the key prefix in the report for the additional attributes.

REPORT_CLASS - Static variable in class adams.data.instance.Instance

the key in the report for the class.

REPORT_DATASET - Static variable in class adams.data.instance.Instance

the key in the report for the dataset name.

REPORT_DB_ID - Static variable in class adams.data.instance.Instance

the key in the report for the database ID.

REPORT_DISPLAY_ID - Static variable in class adams.data.instance.Instance

the key in the report for the display ID.

REPORT_ID - Static variable in class adams.data.instance.Instance

the key in the report for the ID.

REPORT_ROW - Static variable in class adams.data.instance.Instance

the key in the report for the row in the dataset.

ReportColorInstancePaintlet - Class in adams.gui.visualization.instance

Paintlet for generating a line plot using the color stored in the report.

ReportColorInstancePaintlet() - Constructor for class adams.gui.visualization.instance.ReportColorInstancePaintlet

ReportToWekaInstance - Class in adams.data.conversion

Converts a report into a weka.core.Instance objects.

ReportToWekaInstance() - Constructor for class adams.data.conversion.ReportToWekaInstance

requiresFlowContext() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns whether flow context is actually required.

requiresFlowContext() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Returns whether flow context is actually required.

requiresInitialization() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix

Returns whether the handler requires an initialization.

requiresWrapper() - Method in class adams.gui.application.WekaExperimenterPreferencesPanel

Returns whether the panel requires a wrapper scrollpane/panel for display.

requiresWrapper() - Method in class adams.gui.application.WekaExplorerPreferencesPanel

Returns whether the panel requires a wrapper scrollpane/panel for display.

requiresWrapper() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel

Returns whether the panel requires a wrapper scrollpane/panel for display.

reset() - Method in class adams.core.discovery.genetic.GenericDoubleResolution

reset() - Method in class adams.core.discovery.genetic.GenericFloatResolution

reset() - Method in class adams.core.discovery.genetic.GenericInteger

reset() - Method in class adams.core.discovery.genetic.GenericString

reset() - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader

Resets the converter.

reset() - Method in class adams.data.conversion.ReportToWekaInstance

Resets the scheme.

reset() - Method in class adams.data.conversion.SwapPLS

Resets the scheme.

reset() - Method in class adams.data.instances.AbstractInstanceGenerator

Resets the generator (but does not clear the input data!).

reset() - Method in class adams.data.instancesanalysis.FastICA

Resets the scheme.

reset() - Method in class adams.data.instancesanalysis.PCA

Resets the scheme.

reset() - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

Resets the scheme.

reset() - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Resets the scheme.

reset() - Method in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS

Resets the scheme.

reset() - Method in class adams.data.instancesanalysis.pls.PLS1

Resets the scheme.

reset() - Method in class adams.data.instancesanalysis.PLS

Resets the scheme.

reset() - Method in class adams.data.instancesanalysis.pls.SIMPLS

Resets the scheme.

reset() - Method in class adams.data.io.input.InstanceReader

Resets the filter.

reset() - Method in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder

Resets the object, including the trained state.

reset() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

Resets the scheme.

reset() - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Resets the scheme.

reset() - Method in class adams.data.weka.rowfinder.AbstractTrainableRowFinder

Resets the object, including the trained state.

reset() - Method in class adams.data.weka.rowfinder.FilteredIQR

Resets the object.

reset() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Resets the scheme.

reset() - Method in class adams.flow.sink.WekaDatabaseWriter

Resets the actor.

reset() - Method in class adams.flow.source.WekaDatabaseReader

Resets the scheme.

reset() - Method in class adams.flow.source.WekaSelectDataset

Resets the scheme.

reset() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Resets the scheme.

reset() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaAccumulatedError

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaAggregateEvaluations

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaFileReader

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaFilter

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaInstanceBuffer

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaInstanceDumper

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Resets the actor.

reset() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Resets the actor.

reset() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaRandomSplit

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Resets the actor.

reset() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Resets the actor.

reset() - Method in class adams.flow.transformer.WekaSplitGenerator

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaStreamEvaluator

Initializes the members.

reset() - Method in class adams.flow.transformer.WekaStreamFilter

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaTrainClassifier

Resets the scheme.

reset() - Method in class adams.flow.transformer.WekaTrainClusterer

Resets the scheme.

reset() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel

Resets the settings to their default.

reset() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Invalidates the indexer.

reset() - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater

Resets the object.

reset() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Removes all sort definition panels.

reset() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Resets the genetic algorihtm.

reset() - Method in class adams.opt.optimise.GeneticAlgorithm

Resets the genetic algorihtm.

reset() - Method in class weka.classifiers.AbstractSplitGenerator

Resets the generator.

reset() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Resets the generator.

reset() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Resets the generator.

reset() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Resets the generator.

reset() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Resets the generator.

reset() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Resets the generator.

reset() - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Resets the scheme.

reset() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Resets the generator.

reset() - Method in class weka.classifiers.MultiLevelSplitGenerator

Resets the scheme.

reset() - Method in class weka.core.converters.SimpleArffLoader

Resets the loader.

reset() - Method in class weka.core.converters.SpreadSheetLoader

Resets the loader ready to read a new data set

reset() - Method in class weka.core.tokenizers.cleaners.AbstractTokenCleaner

Resets the cleaner.

reset() - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

Resets the cleaner.

reset() - Method in class weka.filters.FlowFilter

Resets the filter.

reset() - Method in class weka.filters.SerializedFilter

Resets the filter.

reset() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

Resets the cleaner.

reset() - Method in class weka.filters.unsupervised.attribute.AnyToString

resets the filter, i.e., m_NewBatch to true and m_FirstBatchDone to false.

reset() - Method in class weka.filters.unsupervised.attribute.Detrend

Resets the filter.

reset() - Method in class weka.filters.unsupervised.attribute.EquiDistance

Resets the filter.

reset() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

resets the filter.

reset() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Resets the filter.

reset() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Resets the cleaner.

reset() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Resets the filter.

reset() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Resets the filter.

reset() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Resets the filter.

reset() - Method in class weka.filters.unsupervised.attribute.SpellChecker

resets the filter.

reset() - Method in class weka.filters.unsupervised.attribute.StringToDate

resets the filter, i.e., m_NewBatch to true and m_FirstBatchDone to false.

reset() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

Resets the scheme.

reset() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Resets the filter.

RESET - adams.gui.event.InstancesSortSetupEvent.EventType

the setup was reset.

resetColorProvider() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Resets the color provider to the default one.

resetDefinitions() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Resets the definitions.

resetInternalState(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Resets the internal state of the merge method when new datasets are supplied.

resetMinMax(double, double) - Method in class adams.opt.optimise.genetic.PackDataDef.DataInfo

resetOptions() - Method in class weka.core.converters.SimpleArffSaver

resetOptions() - Method in class weka.core.converters.SpreadSheetSaver

resetResultsTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the tip text for this property.

ResettableExperiment - Interface in adams.gui.tools.wekamultiexperimenter.experiment

Interface for experiments that can clear any prior results.

ResidualsVsFitted - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Plots the residuals vs the fitted values (= predictions).

ResidualsVsFitted() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsFitted

ResidualsVsPredictor - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Plots the residuals vs the predictor.

ResidualsVsPredictor() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsPredictor

restoreGOE(Map, String, Object, GenericObjectEditor) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Restores the value of the GenericObjectEditor.

restoreSelectedIndex(Map, String, Integer, JComboBox) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Restores the selected index of the BaseComboBox.

restoreSelectedIndices(Map, String, int[], JList) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Restores the selected indices of the JList.

restoreSelectedState(Map, String, Boolean, JCheckBox) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Sets the selected state of the checkbox.

restoreSelectedState(JCheckBox, Boolean) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Sets the selected state of the checkbox.

restoreSelection(DataContainer[]) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Tries to restore the selection using the provided containers.

restoreSpinner(Map, String, Integer, JSpinner) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Restores the integer value of the JSpinner.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.sink.WekaDatabaseWriter

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaAccumulatedError

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaAggregateEvaluations

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaCrossValidationSplit

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaFileReader

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaFilter

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaInstanceBuffer

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaInstanceDumper

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaStreamEvaluator

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaStreamFilter

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaTrainClassifier

Restores the state of the actor before the variables got updated.

restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaTrainClusterer

Restores the state of the actor before the variables got updated.

restoreText(Map, String, String, JTextComponent) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Restores the text of the text component, e.g., a BaseTextField.

resultFileTipText() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the tip text for this property.

resultFormatTipText() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the tip text for this property.

ResultItem - Class in adams.gui.tools.wekainvestigator.tab.associatetab

Container for an evaluation, model, training set header.

ResultItem - Class in adams.gui.tools.wekainvestigator.tab.attseltab

Container for an attribute selection, evaluator and search method.

ResultItem - Class in adams.gui.tools.wekainvestigator.tab.classifytab

Container for an evaluation, model, training set header.

ResultItem - Class in adams.gui.tools.wekainvestigator.tab.clustertab

Container for an evaluation, model, training set header.

ResultItem - Class in adams.gui.tools.wekainvestigator.tab.experimenttab

Container for an experiment run.

ResultItem(Associator, Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

Initializes the item.

ResultItem(ASEvaluation, ASSearch, Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Initializes the item.

ResultItem(Classifier, Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Initializes the item.

ResultItem(Classifier, Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

Initializes the item.

ResultItem(Clusterer, Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Initializes the item.

ResultMatrixAdamsCSV - Class in weka.experiment

Generates the matrix in ADAMS CSV ('comma-separated values') format.

ResultMatrixAdamsCSV() - Constructor for class weka.experiment.ResultMatrixAdamsCSV

initializes the matrix as 1x1 matrix.

ResultMatrixAdamsCSV(int, int) - Constructor for class weka.experiment.ResultMatrixAdamsCSV

initializes the matrix with the given dimensions.

ResultMatrixAdamsCSV(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixAdamsCSV

initializes the matrix with the values from the given matrix.

ResultMatrixMediaWiki - Class in weka.experiment

Generates table output in MediaWiki format.

ResultMatrixMediaWiki() - Constructor for class weka.experiment.ResultMatrixMediaWiki

initializes the matrix as 1x1 matrix.

ResultMatrixMediaWiki(int, int) - Constructor for class weka.experiment.ResultMatrixMediaWiki

initializes the matrix with the given dimensions.

ResultMatrixMediaWiki(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixMediaWiki

initializes the matrix with the values from the given matrix.

resultsHandlerTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the tip text for this property.

resumeExecution() - Method in class adams.flow.transformer.WekaClassifierRanker

Resumes the execution.

resumeExecution() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Resumes the execution.

retrieveFile() - Method in class weka.core.converters.SimpleArffLoader

Return the current source file/ destination file

returnLeaves(FastVector[]) - Method in class weka.classifiers.trees.m5.RuleNode2

Return a list containing all the leaves in the tree

reverseTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the tip text for this property.

Revert - Class in adams.gui.tools.wekainvestigator.datatable.action

Reverts the selected dataset (if possible).

Revert() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Revert

Instantiates the action.

ridgeTipText() - Method in class adams.data.baseline.AbstractLinearRegressionBased

Returns the tip text for this property.

ridgeTipText() - Method in class weka.attributeSelection.LinearRegressionAttributeEval

Returns the tip text for this property

ridgeTipText() - Method in class weka.classifiers.functions.LinearRegressionJ

Returns the tip text for this property

ridgeTipText() - Method in class weka.classifiers.trees.RandomModelTrees

Returns the tip text for this property.

ridgeTipText() - Method in class weka.core.WeightedEuclideanDistanceRidge

Returns the tip text for this property

RIGHT - Static variable in class weka.classifiers.trees.m5.Rule2

rightNode() - Method in class weka.classifiers.trees.m5.RuleNode2

Get the right child of this node

RMSE - adams.flow.transformer.WekaClassifierRanker.Measure

evaluation via: Root mean squared error.

RMSE - adams.opt.genetic.Measure

Root mean squared error.

RMSE - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure

evaluation via: Root mean squared error.

ROC - Class in adams.gui.menu

Displays ROC curve data.

ROC() - Constructor for class adams.gui.menu.ROC

Initializes the menu item with no owner.

ROC(AbstractApplicationFrame) - Constructor for class adams.gui.menu.ROC

Initializes the menu item.

ROOT_MEAN_SQUARED_ERROR - adams.flow.core.EvaluationStatistic

ROOT_MEAN_SQUARED_ERROR - adams.flow.core.ExperimentStatistic

ROOT_RELATIVE_SQUARED_ERROR - adams.flow.core.EvaluationStatistic

ROOT_RELATIVE_SQUARED_ERROR - adams.flow.core.ExperimentStatistic

rootMeanSquaredError() - Method in class weka.classifiers.trees.m5.RuleNode2

Get the root mean squared error at this node

RoundErrorScaler - Class in adams.data.weka.predictions

Performs no scaling at all, just rounds the error to the next integer.

RoundErrorScaler() - Constructor for class adams.data.weka.predictions.RoundErrorScaler

ROW - adams.flow.transformer.WekaExtractArray.ExtractionType

row.

ROW_ACTIVATED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent

row got activated.

ROW_BY_INDEX - adams.flow.transformer.WekaInstancesStatisticDataType

obtains rows.

ROW_MISSING - Static variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

The constant value for datasets that do not have an input row for this output row.

ROW_SELECTION - Static variable in class weka.filters.unsupervised.instance.MultiRowProcessor

rowAttribute1TipText() - Method in class adams.tools.CompareDatasets

Returns the tip text for this property.

rowAttribute2TipText() - Method in class adams.tools.CompareDatasets

Returns the tip text for this property.

RowFilteredColumnFinder - Class in adams.data.weka.columnfinder

This column finder first filters the rows before finding any columns on the subset of rows.

RowFilteredColumnFinder() - Constructor for class adams.data.weka.columnfinder.RowFilteredColumnFinder

RowFinder - Interface in adams.data.weka.rowfinder

Interface for classes that "find" rows of interest in datasets.

rowFinderEnabledTipText() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns the tip text for this property.

rowFinderTipText() - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder

Returns the tip text for this property.

rowFinderTipText() - Method in class adams.data.weka.datasetsplitter.RowSplitter

Gets the tip-text for the rowFinder option.

rowFinderTipText() - Method in class adams.data.weka.rowfinder.AbstractFilteredRowFinder

Returns the tip text for this property.

rowFinderTipText() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the tip-text for the row-finder option.

rowFinderTipText() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Returns the tip text for this property.

rowFinderTipText() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns the tip text for this property.

rowFinderTipText() - Method in class weka.filters.unsupervised.instance.DatasetCleaner

Returns the tip text for this property.

rowFinderTipText() - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Returns the tip text for this property.

rowKeys() - Method in class adams.ml.data.InstancesView

Returns a collection of all row keys.

rowKeyToIndex(String) - Method in class adams.ml.data.InstancesView

Turns the rowKey into a row index.

RowNorm - Class in weka.filters.unsupervised.instance

Row wise normalization.

RowNorm() - Constructor for class weka.filters.unsupervised.instance.RowNorm

rowRangeTipText() - Method in class weka.filters.unsupervised.instance.KeepRange

Returns the tip text for this property.

rows() - Method in class adams.ml.data.InstancesView

Returns all rows.

ROWS - Static variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

ROWS_ADDED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent

rows got added.

ROWS_DELETED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent

rows got deleted.

ROWS_MODIFIED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent

rows got modified.

rowSelectionTipText() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Returns the tip text for this property.

RowSplitter - Class in adams.data.weka.datasetsplitter

Splits a dataset in two based on the rows selected by the row-finder.

RowSplitter() - Constructor for class adams.data.weka.datasetsplitter.RowSplitter

RowStatistic - Class in adams.gui.visualization.instances.instancestable

Allows the calculation of row statistics.

RowStatistic() - Constructor for class adams.gui.visualization.instances.instancestable.RowStatistic

rowsTipText() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the tip text for this property.

rowsTipText() - Method in class adams.data.weka.rowfinder.Constant

Gets the tip-text for the rows option.

rowsTipText() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

RowSum - Class in weka.filters.unsupervised.attribute

Sums up all numeric values in a row and replaces them with it.

RowSum() - Constructor for class weka.filters.unsupervised.attribute.RowSum

rowTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the tip text for this property.

rowTipText() - Method in class adams.flow.transformer.WekaGetInstancesValue

Returns the tip text for this property.

rowTipText() - Method in class adams.flow.transformer.WekaSetInstancesValue

Returns the tip text for this property.

rowTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the tip text for this property.

RPD - Class in weka.classifiers.evaluation

Computes the RPD (Ratio of Performance to Deviation) for regression models: RPD = SD / RMSE
https://www.academia.edu/4303409/Why_you_dont_need_to_use_RPD

RPD - adams.flow.core.EvaluationStatistic

RPD - adams.flow.core.ExperimentStatistic

RPD() - Constructor for class weka.classifiers.evaluation.RPD

RRSE - adams.flow.transformer.WekaClassifierRanker.Measure

evaluation via: Root relative squared error.

RRSE - adams.opt.genetic.Measure

Root relative squared error.

RRSE - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure

evaluation via: Root relative squared error.

RSquared - Class in weka.classifiers.evaluation

Computes the R^2 for regression models.

RSquared() - Constructor for class weka.classifiers.evaluation.RSquared

RSQUARED - adams.flow.core.EvaluationStatistic

RSQUARED - adams.flow.core.ExperimentStatistic

RSQUARED - adams.opt.genetic.Measure

R^2.

Rule2 - Class in weka.classifiers.trees.m5

Generates a single m5 tree or rule

Rule2() - Constructor for class weka.classifiers.trees.m5.Rule2

Constructor declaration

RuleNode2 - Class in weka.classifiers.trees.m5

Constructs a node for use in an m5 tree or rule

RuleNode2(double, double, RuleNode2) - Constructor for class weka.classifiers.trees.m5.RuleNode2

Creates a new RuleNode instance.

Rules - Class in adams.gui.tools.wekainvestigator.tab.associatetab.output

Outputs the rules if available AssociationRulesProducer.

Rules() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.output.Rules

run() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob

Executes the job.

run() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob

Executes the job.

run() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel.BarCalc

run() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel.HistCalc

run() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Starts running the experiment.

run() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Runs the genetic algorithm.

runClassifier(Classifier, String[]) - Static method in class weka.classifiers.simple.AbstractSimpleClassifier

runs the classifier instance with the given options.

runExperimenter(String[]) - Static method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter

Runs an experimenter instance.

runExplorer(String[]) - Static method in class weka.gui.explorer.ExplorerExt

Runs an explorer instance.

runExplorer(String[]) - Static method in class weka.gui.explorer.MultiExplorer

Runs an explorer instance.

runGeneticAlgorithm(Class, Class, String[]) - Static method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Runs the genetic algorithm with the given options.

RunInformation - Class in adams.gui.tools.wekainvestigator.tab.associatetab.output

Generates run information.

RunInformation - Class in adams.gui.tools.wekainvestigator.tab.attseltab.output

Generates run information.

RunInformation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Generates run information.

RunInformation - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output

Generates run information.

RunInformation - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.output

Generates run information.

RunInformation() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.output.RunInformation

RunInformation() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.output.RunInformation

RunInformation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.RunInformation

RunInformation() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.RunInformation

RunInformation() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.output.RunInformation

RunInformationHelper - Class in adams.gui.tools.wekainvestigator.output

Helper class for run information.

RunInformationHelper() - Constructor for class adams.gui.tools.wekainvestigator.output.RunInformationHelper

runInformationTipText() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics

Returns the tip text for this property.

runInformationTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Returns the tip text for this property.

runInformationTipText() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics

Returns the tip text for this property.

runInformationTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the tip text for this property.

runsTipText() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the tip text for this property.

runsTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the tip text for this property.

runsTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the tip text for this property.

S

SafeRemoveRange - Class in weka.filters.unsupervised.instance

A filter that removes a given range of instances of a dataset.
Works just like weka.filters.unsupervised.instance.RemoveRange, but has a more robust handling of instance ranges.

SafeRemoveRange() - Constructor for class weka.filters.unsupervised.instance.SafeRemoveRange

SAMPLE_SIZE - adams.flow.sink.WekaThresholdCurve.AttributeName

SAMPLE_SIZE - Static variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

sampleCorrs(Instances) - Method in class weka.classifiers.meta.Corr

sampleDevs(Instances, double[]) - Method in class weka.classifiers.meta.Corr

SamplePlot - Class in adams.flow.transformer.wekarepeatedcrossvalidationoutput

Generates plot containers with statistics derived for each sample across the cross-validation runs.

SamplePlot - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated

Generates a plot with statistics derived for each sample across the cross-validation runs.

SamplePlot() - Constructor for class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

SamplePlot() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

sampleSizeTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Returns the tip text for this property.

sampleTypeTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the sampleType option.

save() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu

Pops up the filechooser.

save() - Method in class weka.gui.explorer.ExplorerExt

Allows the user to save the file.

save(AbstractExperiment, File) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultAdamsExperimentIO

Saves an experiment.

save(File) - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu

Saves the content to the specified file.

save(File) - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel

Saves the content to the specified file.

save(File) - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel

Saves the content to the specified file.

save(File) - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel

Saves the content to the specified file.

save(T, File) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO

Saves an experiment.

save(Experiment, File) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultWekaExperimentIO

Saves an experiment.

save(RemoteExperiment, File) - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO

Saves an experiment.

Save - Class in adams.gui.tools.wekainvestigator.datatable.action

Saves the selected data.

Save() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Save

Instantiates the action.

saveAs() - Method in class weka.gui.explorer.ExplorerExt

Allows the user to save the file.

saveAs(TableRowRange) - Method in class adams.gui.visualization.instances.InstancesTable

Exports the data.

SaveAs - Class in adams.gui.visualization.instance.containerlistpopup

Allows the saving of an instance container.

SaveAs() - Constructor for class adams.gui.visualization.instance.containerlistpopup.SaveAs

saveBuffer(String) - Method in class weka.gui.explorer.ExperimentPanel

Save the currently selected experiment output to a file.

saveDataset() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Saves the result as a new dataset.

saveExperimentData(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Saves the results to a file.

SaveGraph - Class in weka.gui.visualize.plugins

Allows user to save graph (eg generated by BayesNet) as file.

SaveGraph() - Constructor for class weka.gui.visualize.plugins.SaveGraph

SaveIndexedSplitsRuns - Class in adams.gui.tools.wekainvestigator.datatable.action

Saves the indexed splits runs generated from the selected data.

SaveIndexedSplitsRuns() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns

Instantiates the action.

saveInstance(InstanceContainer) - Method in class adams.gui.visualization.instance.InstancePanel

Saves the specified instance as spreadsheet file.

saveInstancesTipText() - Method in class weka.classifiers.trees.M5P2

Returns the tip text for this property

saveModel(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Saves the model to a file.

saveModel(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Saves the model to a file.

saveModel(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Saves the model to a file.

saveObject(Object) - Method in class weka.classifiers.meta.Corr

saveParameters() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Prompts the user to select a yaml file to store the parameters of the tab under.

saveProperties() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

Saves properties to a file, prompts the user to select props file.

saveReducedData(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Saves the reduced data to a file.

saveResults() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Saves the results to a file.

saveResults(File) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Saves the results to the file.

saveResults(File, AbstractFileSaver) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Saves the results to the file.

saveSetup() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Allows the user to save the file.

saveSetup(File) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Saves the experiment to the specified file.

saveSetupAs() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Allows the user to save the file.

SaveTree - Class in weka.gui.visualize.plugins

Saves a tree in dotty notation as file.

SaveTree() - Constructor for class weka.gui.visualize.plugins.SaveTree

SaveVisible - Class in adams.gui.visualization.instance.plotpopup

Allows the user to save the visible containers as ARFF.

SaveVisible() - Constructor for class adams.gui.visualization.instance.plotpopup.SaveVisible

saveWorkspace() - Method in class weka.gui.explorer.MultiExplorer

Saves the current workspace.

SavitzkyGolay - Class in weka.filters.unsupervised.attribute

A filter that applies Savitzky-Golay smoothing.
If a class attribute is present this will not be touched and moved to the end.

For more information see:

A.

SavitzkyGolay() - Constructor for class weka.filters.unsupervised.attribute.SavitzkyGolay

SavitzkyGolay2 - Class in weka.filters.unsupervised.attribute

A filter that applies Savitzky-Golay smoothing.
If a class attribute is present this will not be touched and moved to the end.

For more information see:

A.

SavitzkyGolay2() - Constructor for class weka.filters.unsupervised.attribute.SavitzkyGolay2

SavitzkyGolay2NumPoints - Class in adams.core.discovery.genetic

SavitzkyGolay numPoints handler.

SavitzkyGolay2NumPoints() - Constructor for class adams.core.discovery.genetic.SavitzkyGolay2NumPoints

SAX - Class in weka.filters.unsupervised.attribute

A simple filter that retains only every nth attribute.

SAX() - Constructor for class weka.filters.unsupervised.attribute.SAX

SAXDistance - Class in weka.core

Implementing Euclidean distance (or similarity) function.

One object defines not one distance but the data model in which the distances between objects of that data model can be computed.

Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.

For more information, see:

Wikipedia.

SAXDistance() - Constructor for class weka.core.SAXDistance

Constructs an Euclidean Distance object, Instances must be still set.

SAXDistance(Instances) - Constructor for class weka.core.SAXDistance

Constructs an Euclidean Distance object and automatically initializes the ranges.

SAXKMeans - Class in weka.clusterers

SimpleKMeans adapted for SAX.

SAXKMeans() - Constructor for class weka.clusterers.SAXKMeans

the default constructor.

scale(ArrayList) - Method in class adams.data.weka.predictions.AbstractErrorScaler

Scales the errors.

scale(ArrayList) - Method in class adams.data.weka.predictions.AutoScaler

Scales the errors.

scale(ArrayList) - Method in class adams.data.weka.predictions.FixedSizeErrorScaler

Scales the errors.

scale(ArrayList) - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference

Scales the errors.

scale(ArrayList) - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler

Scales the errors.

scale(ArrayList) - Method in class adams.data.weka.predictions.RoundErrorScaler

Scales the errors.

Scale - Class in weka.filters.unsupervised.instance

Scales all numeric attributes between the specified min/max.

Scale() - Constructor for class weka.filters.unsupervised.instance.Scale

scalePositiveWeightsTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the scalePositiveWeights option.

scalerTipText() - Method in class adams.data.weka.predictions.AutoScaler

Returns the tip text for this property.

ScatterPlotTab - Class in adams.gui.tools.wekainvestigator.tab

For plotting attributes against each other.

ScatterPlotTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

SDR - Class in weka.classifiers.evaluation

Computes the SDR (Standard Deviation of Residuals) for regression models.

SDR - adams.flow.core.EvaluationStatistic

SDR - adams.flow.core.ExperimentStatistic

SDR() - Constructor for class weka.classifiers.evaluation.SDR

search() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Searches the panel with the filter.

search() - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Performs a search in the fields.

searchTipText() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns the tip text for this property.

searchTipText() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns the tip text for this property.

secondAttributeRangeTipText() - Method in class adams.gui.InstanceCompare

Returns the tip text for this property.

secondAttributeTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Returns the tip text for this property.

secondCrossValidationSeedTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Returns the tip text for this property.

secondDatasetTipText() - Method in class adams.gui.InstanceCompare

Returns the tip text for this property.

secondFoldsTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Returns the tip text for this property.

secondRangeTipText() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Returns the tip text for this property.

secondRowIndexTipText() - Method in class adams.gui.InstanceCompare

Returns the tip text for this property.

seedTipText() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

Returns the tip text for this property.

seedTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Returns the tip text for this property.

seedTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the tip text for this property.

seedTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Returns the tip text for this property.

seedTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Returns the tip text for this property.

seedTipText() - Method in class adams.flow.transformer.WekaAttributeSelection

Returns the tip text for this property.

seedTipText() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the tip text for this property.

seedTipText() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the tip text for this property.

seedTipText() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Returns the tip text for this property.

seedTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the tip text for this property.

seedTipText() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Returns the tip text for this property.

seedTipText() - Method in class adams.flow.transformer.WekaRandomSplit

Returns the tip text for this property.

seedTipText() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Returns the tip text for this property.

seedTipText() - Method in class weka.classifiers.AbstractSplitGenerator

Returns the tip text for this property.

seedTipText() - Method in class weka.classifiers.functions.FakeClassifier

Returns the tip text for this property.

seedTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the seed option.

seedTipText() - Method in class weka.filters.supervised.instance.RemoveOutliers

Returns the tip text for this property.

seedTipText() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Returns the tip text for this property

seedTipText() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Returns the tip text for this property.

seedTipText() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns the tip text for this property.

selCol - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState

the selected column.

selectAttributes(Instances, List<Integer>) - Method in class adams.flow.transformer.WekaChooseAttributes

Prompts the user to select attributes.

selectColorProvider() - Method in class adams.gui.visualization.instance.InstanceExplorer

Lets the user select a new color provider.

SELECTION_GREEDY - Static variable in class weka.classifiers.functions.LinearRegressionJ

Attribute selection method: Greedy method

SELECTION_M5 - Static variable in class weka.classifiers.functions.LinearRegressionJ

Attribute selection method: M5 method

SELECTION_NONE - Static variable in class weka.classifiers.functions.LinearRegressionJ

Attribute selection method: No attribute selection

SELECTION_PROCESSOR - Static variable in class weka.filters.unsupervised.instance.MultiRowProcessor

selectionProcessorTipText() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Returns the tip text for this property.

selectionRowToModelRow(int) - Method in class adams.gui.visualization.instances.InstancesTable

Determines the actual row index.

selectPaintlet() - Method in class adams.gui.visualization.instance.InstanceExplorer

Lets the user select a new paintlet.

selectRows(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.AbstractRowSelection

Returns the list of row indices generated from the data.

selectSubSample(Instances, Random) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Produces a random sample from m_Data in m_SubSample.

selectSubSample(Instances, Random) - Method in class weka.classifiers.meta.LeastMedianSq

Produces a random sample from m_Data in m_SubSample.

selRow - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState

the selected row.

selRows - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState

the selected rows.

send(byte[]) - Method in class weka.classifiers.meta.SocketFacade

Sends the data to the remote host.

serialize(InvestigatorPanel) - Method in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper

Generates a view of the panel that can be serialized.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Generates a view of the tab that can be serialized.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Returns the objects for serialization.

serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Returns the objects for serialization.

serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Generates a view of the explorer panel that can be serialized.

serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AssociationsHandler

Generates a view of the explorer panel that can be serialized.

serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AttributeSelectionHandler

Generates a view of the explorer panel that can be serialized.

serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ClassifierHandler

Generates a view of the explorer panel that can be serialized.

serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ClustererHandler

Generates a view of the explorer panel that can be serialized.

serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.DefaultHandler

Generates a view of the explorer panel that can be serialized.

serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ExperimentHandler

Generates a view of the explorer panel that can be serialized.

serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.PreprocessHandler

Generates a view of the explorer panel that can be serialized.

serialize(ExplorerExt, String, ObjectOutputStream, boolean) - Static method in class weka.gui.explorer.WorkspaceHelper

Serializes the explorer instance to the output stream.

serialize(GenericObjectEditor) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Serializes the content of a GenericObjectEditor.

serialize(ResultHistoryPanel) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Serializes a ResultHistoryPanel.

SERIALIZED_MODEL_SIZE - adams.flow.core.ExperimentStatistic

SERIALIZED_TEST_SET_SIZE - adams.flow.core.ExperimentStatistic

SERIALIZED_TRAIN_SET_SIZE - adams.flow.core.ExperimentStatistic

SerializedAdamsExperimentReader - Class in adams.data.io.input

Reads serialized ADAMS Experiments.

SerializedAdamsExperimentReader() - Constructor for class adams.data.io.input.SerializedAdamsExperimentReader

SerializedAdamsExperimentWriter - Class in adams.data.io.output

Writes serialized ADAMS experiments.

SerializedAdamsExperimentWriter() - Constructor for class adams.data.io.output.SerializedAdamsExperimentWriter

SerializedFilter - Class in weka.filters

Processes the data with a the (trained) filter deserialized from the specified file.

SerializedFilter() - Constructor for class weka.filters.SerializedFilter

serializedTipText() - Method in class weka.filters.SerializedFilter

Returns the tip text for this property.

SESSION_FILE - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel

the file to store the recent files in.

SESSION_FILE - Static variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

the file to store the recent files in.

SESSION_FILE - Static variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

the file to store the recent files in.

SESSION_FILE - Static variable in class adams.gui.visualization.instance.InstanceExplorer

the file to store the recent files in.

SESSION_FILE - Static variable in class weka.gui.explorer.ExplorerExt

the file to store the recent files in.

SESSION_FILE_1 - Static variable in class adams.gui.visualization.instance.InstanceComparePanel

the file to store the recent files in (first file).

SESSION_FILE_2 - Static variable in class adams.gui.visualization.instance.InstanceComparePanel

the file to store the recent files in (second file).

set(int, DataContainer) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

set(int, InstanceContainer) - Method in class adams.gui.visualization.instance.InstanceContainerManager

Replaces the container at the given position.

set(int, Instance) - Method in class weka.core.InstancesView

Replaces the instance at the given position.

set(String, double) - Method in class adams.opt.optimise.genetic.PackData

set(Instance) - Method in class adams.data.instance.Instance

Clears the container and adds the data from the weka.core.Instance (internal values).

set(Instance, int, int[], Range, HashSet<Integer>) - Method in class adams.data.instance.Instance

Clears the container and adds the data from the weka.core.Instance (internal values).

setAbsErr(double) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Sets the threshold for the max error when predicting a numeric class.

setAbsErr(double) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Sets the threshold for the max error when predicting a numeric class.

setAbsolute(boolean) - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Sets whether to return the absolute values of the coefficients.

setAcceptListener(ChangeListener) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Sets the listener for the event that the user accepts the input.

setAction(AbstractWekaPackageManagerAction) - Method in class adams.flow.source.WekaPackageManagerAction

Sets the action to use.

setAction(AbstractWekaPackageManagerAction) - Method in class adams.flow.standalone.WekaPackageManagerAction

Sets the action to use.

setAction(AbstractWekaPackageManagerAction) - Method in class adams.flow.transformer.WekaPackageManagerAction

Sets the action to use.

setActual(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Sets the column with the actual values.

setActual(SpreadSheetColumnIndex) - Method in class weka.classifiers.functions.FromPredictions

Sets the column with the actual values.

setActualMax(double) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets the upper limit in use for the actual values.

setActualMin(double) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets the lower limit in use for the actual values.

setActualTitle(String) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Sets the actual title to use.

setAddAttributeInformation(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

Sets whether to add attribute information to the metadata.

setAddClassification(boolean) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Sets whether to add the numeric classification (label index for nominal classes).

setAddClassificationLabel(boolean) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Sets whether to add the classification label (only for nominal classes).

setAddDatabaseID(boolean) - Method in class adams.data.instances.AbstractInstanceGenerator

Sets whether the database ID is added to the data or not.

setAddDatasetInformation(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator

Sets whether to add dataset information to the metadata.

setAddDistribution(boolean) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Sets whether to add the class distribution (only for nominal classes).

setAddIndex(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge

Sets whether to add the dataset index number to the prefix.

setAdditional(SpreadSheetColumnRange) - Method in class weka.classifiers.functions.FromPredictions

Sets the additional columns to add to the plot containers.

setAdditionalAttributes(SpreadSheet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Sets the additional attributes data.

setAdditionalFields(Field[]) - Method in interface adams.data.instances.InstanceGeneratorWithAdditionalFields

Sets the additional fields to add.

setAdditionalParameters(String[]) - Method in class adams.gui.menu.AbstractParameterHandlingWekaMenuItemDefinition

Sets the additional parameters.

setAddLabelIndex(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Sets whether to prefix the labels with the index.

setAddLabelIndex(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Sets whether to prefix the labels with the index.

setAddOne(boolean) - Method in class weka.filters.unsupervised.attribute.LogTransform

Sets whether to add '1' to the values before log-transform.

setAdjustToVisibleData(boolean) - Method in class adams.gui.visualization.instance.InstancePanel

Sets whether the display is adjusted to only the visible data or everything currently loaded.

setAlgorithm(BinningAlgorithm) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Sets the binning algorithm.

setAlgorithm(BinningAlgorithm) - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Sets the binning algorithm.

setAlgorithm(BinningAlgorithm) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Sets the binning algorithm.

setAlgorithm(BinningAlgorithm) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Sets the binning algorithm.

setAlgorithm(AbstractPLS) - Method in class adams.data.instancesanalysis.PLS

Sets the algorithm to use.

setAlgorithm(AbstractPLS) - Method in class weka.classifiers.functions.PLSWeighted

Set the PLS algorithm (only used for setup).

setAlgorithm(AbstractPLS) - Method in class weka.filters.supervised.attribute.MultiPLS

Sets the PLS algorithm to use.

setAlgorithm(AbstractPLS) - Method in class weka.filters.supervised.attribute.PLS

Sets the PLS algorithm to use.

setAlgorithm(AbstractClassifierBasedGeneticAlgorithm) - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Sets the genetic algorithm to apply to the dataset.

setAlgorithm(AbstractClassifierBasedGeneticAlgorithm) - Method in class weka.classifiers.functions.GeneticAlgorithm

Sets the genetic algorithm to use.

setAlgorithm(SelectedTag) - Method in class weka.filters.unsupervised.attribute.FastWavelet

Sets the type of algorithm to use.

setAlgorithms(BinningAlgorithm[]) - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Sets the binning algorithms to choose from.

setAlpha(double) - Method in class weka.filters.supervised.attribute.YGradientEPO

Set the alpha parameter.

setAlpha(double) - Method in class weka.filters.supervised.attribute.YGradientGLSW

Set the alpha parameter.

setAlpha(float) - Method in class weka.classifiers.trees.XGBoost

Sets the L1 regularisation term on weights.

setAlwaysShowMarkers(boolean) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Sets whether to always draw markers.

setAlwaysUseContainer(boolean) - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Sets whether to always use an evaluation container as output.

setAmount(double) - Method in class weka.filters.unsupervised.instance.LatestRecords

Sets the amount of records to keep (0,1]=percentage, (1,+inf)=absolute number.

setAntiAliasingEnabled(boolean) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Sets whether to use anti-aliasing.

setAntiAliasingEnabled(boolean) - Method in class adams.gui.visualization.instance.InstancePanel

Sets whether to use anti-aliasing.

setAntiAliasingEnabled(boolean) - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet

Sets whether to use anti-aliasing.

setAntiAliasingEnabled(AutoOnOff) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets whether to use anti-aliasing.

setAssociator(CallableActorReference) - Method in class adams.flow.transformer.WekaTrainAssociator

Sets the name of the callable associator to use.

setAssociator(Associator) - Method in class adams.flow.source.WekaAssociatorSetup

Sets the associator to use.

setAttRange(Range) - Method in class weka.filters.unsupervised.instance.KennardStone

Sets the attribute range to use for distance calculation (after applying pre-filter).

setAttRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.Detrend

Sets the regular expression used for identifying the attributes to process.

setAttRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Sets the regular expression used for identifying the attributes to process.

setAttribute(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

Sets the attribute that statistics will be displayed for.

setAttribute(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Tells the panel which attribute to visualize.

setAttribute(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

Displays a single attribute.

setAttribute(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

Displays a single attribute.

setAttribute(String) - Method in class weka.classifiers.meta.AbstainAttributePercentile

setAttributeIndex(Index) - Method in class adams.data.weka.rowfinder.ByLabel

Sets the index of the attribute to perform the matching on.

setAttributeIndex(WekaAttributeIndex) - Method in class adams.data.weka.rowfinder.ByNumericRange

Sets the index of the column to perform the matching on.

setAttributeIndex(WekaAttributeIndex) - Method in class adams.data.weka.rowfinder.ByNumericValue

Sets the index of the column to perform the matching on.

setAttributeIndex(WekaAttributeIndex) - Method in class adams.flow.transformer.WekaInstancesInfo

Sets the attribute index to use for attribute-specific information.

setAttributeIndex(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Sets the index of the attribute to use for indexing.

setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.SpellChecker

Sets the attribute index (1-based) of the attribute to process.

setAttributeIndex(String) - Method in class weka.filters.unsupervised.instance.SortOnAttribute

Sets the attribute index (1-based) of the attribute to sort on.

setAttributeName(String) - Method in class adams.flow.transformer.WekaGetInstanceValue

Sets the name of the attribute to get the value for.

setAttributeName(String) - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Set the new attribute's name.

setAttributeName(String) - Method in class weka.filters.unsupervised.instance.LatestRecords

Sets the name of the attribute containing the numeric database ID.

setAttributeNames(BaseList) - Method in class adams.flow.source.WekaNewInstances

Sets the list of attribute names.

setAttributeNames(BaseString[]) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Sets the names of the attributes.

setAttributePrefix(String) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Sets the second attribute range to use (regular expression on attribute names).

setAttributeRange(Range) - Method in class adams.data.weka.rowfinder.FilteredIQR

Sets the attribute range to work on.

setAttributeRange(Range) - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Sets the range of attributes to detrend.

setAttributeRange(WekaAttributeRange) - Method in class adams.data.instancesanalysis.FastICA

Sets the attribute range parameter.

setAttributeRange(WekaAttributeRange) - Method in class adams.data.instancesanalysis.PCA

Sets the attribute range parameter.

setAttributeRange(WekaAttributeRange) - Method in class adams.data.instancesanalysis.PLS

Sets the attribute range parameter.

setAttributeRange(WekaAttributeRange) - Method in class weka.filters.unsupervised.attribute.InputSmearing

Sets the range (1-based) of the attributes to work on.

setAttributeRange(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Sets the range of attributes.

setAttributeRange(String) - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Sets the range of attributes to compute the matrix for.

setAttributeRange(String) - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Sets the range (1-based) of the attributes to combine.

setAttributeRange(String) - Method in class weka.filters.unsupervised.attribute.LogTransform

Sets the range of attributes to process.

setAttributeRange(String) - Method in class weka.filters.unsupervised.attribute.SetMissingValue

Sets the range of attributes to compute the matrix for.

setAttributeRenamesExp(BaseRegExp[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Sets the array of attribute rename expressions.

setAttributeRenamesFormat(BaseString[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Sets the array of format strings used for attribute renaming.

setAttributes(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

Displays multiple attributes.

setAttributes(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

Displays multiple attributes.

setAttributes(Range) - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator

Sets the range of attributes to create plot containers for.

setAttributeSelection(EquiDistance.AttributeSelection) - Method in class weka.filters.unsupervised.attribute.EquiDistance

Sets how the attributes get selected.

setAttributeSelectionMethod(SelectedTag) - Method in class weka.classifiers.functions.LinearRegressionJ

Sets the method used to select attributes for use in the linear regression.

setAttributeTypes(AttributeTypeList) - Method in class adams.flow.source.WekaNewInstances

Sets the list of attribute types.

setAttributeX(WekaAttributeIndex) - Method in class adams.flow.sink.WekaInstancesPlot

Sets the attribute to show on the X axis.

setAttributeX(WekaThresholdCurve.AttributeName) - Method in class adams.flow.sink.WekaThresholdCurve

Sets the attribute to show on the X axis.

setAttributeX(WekaThresholdCurve.AttributeName) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Sets the attribute to show on the X axis.

setAttributeY(WekaAttributeIndex) - Method in class adams.flow.sink.WekaInstancesPlot

Sets the attribute to show on the Y axis.

setAttributeY(WekaThresholdCurve.AttributeName) - Method in class adams.flow.sink.WekaThresholdCurve

Sets the attribute to show on the Y axis.

setAttributeY(WekaThresholdCurve.AttributeName) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Sets the attribute to show on the Y axis.

setAutoKeyGeneration(boolean) - Method in class adams.flow.sink.WekaDatabaseWriter

Sets whether to automatically generate a primary key.

setAxisX(AxisPanelOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Sets the setup for the X axis.

setAxisY(AxisPanelOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Sets the setup for the Y axis.

setBase(AbstractPLS) - Method in class adams.data.instancesanalysis.pls.OPLS

Sets the base PLS algorithm to use.

setBase(Classifier) - Method in class weka.classifiers.meta.Fallback

Sets the base classifier.

setBaseScore(float) - Method in class weka.classifiers.trees.XGBoost

Sets the initial prediction score of all instances (global bias).

setBatchSize(String) - Method in class weka.classifiers.functions.PyroProxy

Set the batch size to use.

setBestRange(Range) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Sets the best range of attributes.

setBestRange(String) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Sets the best range of attributes.

setBias(double) - Method in class weka.classifiers.meta.VotedImbalance

Sets the bias towards a uniform class.

setBinCalculation(ArrayHistogram.BinCalculation) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Sets how the number of bins is calculated.

setBins(int) - Method in class weka.core.SAXDistance

Sets the nth point setting.

setBins(int) - Method in class weka.filters.unsupervised.attribute.SAX

Sets the nth point setting.

setBinWidth(double) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Sets the bin width to use (for some calculations).

setBits(int) - Method in class adams.opt.optimise.GeneticAlgorithm

Bits per gene.

setBitsForPosition(int, int[], List<Integer>, List<Integer>, int, int[]) - Method in class adams.opt.genetic.Hermione

Updates the bits.

setBitsPerGene(int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the bits per gene to use.

setBitstring(String) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

setBooster(XGBoost.BoosterType) - Method in class weka.classifiers.trees.XGBoost

Sets the type of booster to use.

setBorder(int) - Method in class weka.experiment.ResultMatrixMediaWiki

Sets the thickness of the border.

setBorderTitle(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Sets the title of the border.

setBufferSize(int) - Method in class adams.flow.transformer.WekaInstanceDumper

Sets the number of instances to buffer before writing them to disk.

setBuildRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.M5Base2

Set the value of regressionTree.

setBuildWait(int) - Method in class weka.classifiers.functions.FakeClassifier

Sets the time in msec to wait when calling buildClassifier.

setButtonPanelVisible(boolean) - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

Sets the visibility state of the buttons panel (load/save).

setC(double) - Method in class adams.data.instancesanalysis.pls.PRM

Tuning parameter.

setCallableName(CallableActorReference) - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Sets the name of the callable sink to use.

setCancelListener(ChangeListener) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Sets the listener for the event that the user discarded the input.

setCanChangeClassInDialog(PropertyEditor, boolean) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler

Sets whether the class can be changed in the dialog.

setCanopyMaxNumCanopiesToHoldInMemory(int) - Method in class weka.clusterers.SAXKMeans

Set the maximum number of candidate canopies to retain in memory during training.

setCanopyMinimumCanopyDensity(double) - Method in class weka.clusterers.SAXKMeans

Set the minimum T2-based density below which a canopy will be pruned during periodic pruning.

setCanopyPeriodicPruningRate(int) - Method in class weka.clusterers.SAXKMeans

Set the how often to prune low density canopies during training (if using canopy clustering)

setCanopyT1(double) - Method in class weka.clusterers.SAXKMeans

Set the t1 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs

setCanopyT2(double) - Method in class weka.clusterers.SAXKMeans

Set the t2 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs

setCapabilities(Capability[]) - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Sets the capabilities.

setCellPadding(int) - Method in class weka.experiment.ResultMatrixMediaWiki

Sets the cell padding for the table.

setCellPopupMenuCustomizer(PopupMenuCustomizer) - Method in class adams.gui.visualization.instances.InstancesTable

Sets the popup menu customizer to use (for the cells).

setCellRenderingCustomizer(CellRenderingCustomizer) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Sets the cell rendering customizer.

setCellSpacing(int) - Method in class weka.experiment.ResultMatrixMediaWiki

Sets the cell spacing for the table.

setCenterData(boolean) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Set whether to center (rather than standardize) the data.

setCharSet(String) - Method in class adams.flow.transformer.WekaTextDirectoryReader

Sets the character set to use.

setCheckHeader(boolean) - Method in class adams.flow.transformer.WekaInstanceBuffer

Sets whether to check the header or not.

setCheckHeader(boolean) - Method in class adams.flow.transformer.WekaInstanceDumper

Sets whether to check the header or not.

setClassAttribute(int, boolean) - Method in class adams.ml.data.InstancesView

Sets the class attribute status for a column.

setClassAttribute(AbstractClassAttributeHeuristic) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets the heuristic for determining the class attribute (if not explicitly set).

setClassAttribute(String, boolean) - Method in class adams.ml.data.InstancesView

Sets the class attribute status for a column.

setClassAttributeByName(String, boolean) - Method in class adams.ml.data.InstancesView

Sets the class attribute status for a column.

setClassAttributeHeuristic(AbstractClassAttributeHeuristic) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Sets the class attribute heuristic.

setClassAttributes(BaseRegExp) - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS

Sets the regular expression for identifying the class attributes (besides an explicitly set one).

setClassDetails(boolean) - Method in class adams.flow.transformer.WekaEvaluationSummary

Sets whether the class details are output as well.

setClassDetails(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Sets whether the class details are output as well.

setClassDistribution(SpreadSheetUnorderedColumnRange) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Sets the columns with the class distribution (nominal class).

setClassDistribution(SpreadSheetUnorderedColumnRange) - Method in class weka.classifiers.functions.FromPredictions

Sets the class distribution columns.

setClassFinder(ColumnFinder) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Sets the finder to use for finding class attributes in the source datasets.

setClassificationEntry(String) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Sets the value for the 'Name' column for the numeric classification.

setClassificationLabelEntry(String) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Sets the value for the 'Name' column for the classification label.

setClassifier(CallableActorReference) - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

Sets the name of the callable classifier to use.

setClassifier(CallableActorReference) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Sets the name of the callable classifier to use.

setClassifier(CallableActorReference) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Sets the name of the callable classifier to use.

setClassifier(CallableActorReference) - Method in class adams.flow.transformer.WekaTrainClassifier

Sets the name of the callable classifier to use.

setClassifier(Classifier) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Sets the classifier to use, must implement weka.classifiers.IntervalEstimator.

setClassifier(Classifier) - Method in class adams.flow.source.WekaClassifierSetup

Sets the classifier to use.

setClassifier(Classifier) - Method in class adams.ml.model.classification.WekaClassifier

Sets the classifier to use.

setClassifier(Classifier) - Method in class adams.ml.model.regression.WekaRegressor

Sets the classifier to use.

setClassifier(Classifier) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets the classifier to use.

setClassifier(Classifier) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the classifier to use.

setClassifier(Classifier) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Sets the classifier to use (if no serialized model is used).

setClassifier(Classifier) - Method in class weka.classifiers.lazy.LWLIntervalEstimator

Set the base learner, which must implement IntervalEstimator.

setClassifier(Classifier) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Set the base learner.

setClassifier(Classifier) - Method in class weka.classifiers.meta.VotedImbalance

setClassifier(Classifier) - Method in class weka.filters.supervised.instance.RemoveOutliers

Sets the classifier.

setClassifier(Classifier) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Sets the classifier to classify instances with.

setClassifier(Classifier) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Sets the classifier to classify instances with.

setClassifiers(Classifier[]) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets the classifiers to use.

setClassifiers(Classifier[]) - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

Sets the classifiers to use.

setClassifierWeights(String) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

setClassIndex(int) - Method in class weka.classifiers.meta.ClassifierCascade

the class index.

setClassIndex(int) - Method in class weka.core.InstancesView

Sets the class index of the set.

setClassIndex(int) - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive

setClassIndex(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Sets the attribute on which misclassifications are based.

setClassIndex(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Sets the attribute on which misclassifications are based.

setClassIndex(Index) - Method in class adams.flow.transformer.WekaClassSelector

Sets the class index.

setClassIndex(WekaAttributeIndex) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the class index.

setClassIndex(WekaLabelIndex) - Method in class adams.flow.sink.WekaCostBenefitAnalysis

Sets the index of class label (1-based).

setClassIndex(WekaLabelIndex) - Method in class adams.flow.transformer.WekaBootstrapping

Sets the index of class label index (1-based).

setClassIndex(WekaLabelIndex) - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Sets the class label index (1-based).

setClassIndex(WekaLabelIndex) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Sets the index of class label index (1-based).

setClassIndex(WekaLabelIndex) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis

Sets the index of class label (1-based).

setClassIndex(WekaLabelIndex) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Sets the index of class label index (1-based).

setClassIndex(WekaLabelRange) - Method in class adams.flow.transformer.WekaEvaluationValues

Sets the range of class labels indices (1-based).

setClassIndex(String) - Method in class adams.flow.source.WekaNewInstances

Sets the index of the class attribute.

setClassIndex(String) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Sets the class index.

setClassLabel(WekaLabelIndex) - Method in class adams.flow.transformer.WekaClassifierRanker

Sets the class label index to use for class-specific measures.

setClassLabelIndex(Index) - Method in class adams.data.conversion.WekaEvaluationToCostCurve

Sets the class label index (1-based index).

setClassLabelIndex(Index) - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve

Sets the class label index (1-based index).

setClassLabelIndex(Index) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets the index of the class label to use when generating per-class statistics.

setClassLabelIndex(WekaLabelIndex) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the index of the class label to use for statistics that work on a per-label-basis.

setClassLabelRange(WekaLabelRange) - Method in class adams.flow.sink.WekaCostCurve

Sets the class label indices.

setClassLabelRange(WekaLabelRange) - Method in class adams.flow.sink.WekaThresholdCurve

Sets the class label indices.

setClassLabelRange(WekaLabelRange) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve

Sets the class label indices.

setClassLabelRange(WekaLabelRange) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve

Sets the class label indices.

setClassLabels(List<String>) - Method in class weka.classifiers.AggregateEvaluations

Sets the class labels to use.

setClassMissing() - Method in class weka.core.AbstractHashableInstance

Sets the class value of an instance to be "missing".

setClassname(BaseClassname) - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Sets the classname to be the handler for.

setClassname(BaseClassname) - Method in class adams.core.discovery.genetic.GenericFloatResolution

Sets the classname to be the handler for.

setClassname(BaseClassname) - Method in class adams.core.discovery.genetic.GenericInteger

Sets the classname to be the handler for.

setClassname(BaseClassname) - Method in class adams.core.discovery.genetic.GenericString

Sets the classname to be the handler for.

setClassname(String) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode

Sets the classname to use.

setClassName(BaseString) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Sets the name of the attribute to use as the class attribute for supervised summary filters.

setClassName(String) - Method in class adams.flow.source.WekaNewInstances

Sets the name of the class attribute.

setClassNoise(double) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Set the level of Gaussian Noise for the class.

setClassType(PropertyEditor, Class) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler

Sets the class type to use.

setClassValue(double) - Method in class weka.core.AbstractHashableInstance

Sets the class value of an instance to the given value (internal floating-point format).

setClassValue(String) - Method in class weka.core.AbstractHashableInstance

Sets the class value of an instance to the given value.

setCleaner(TokenCleaner) - Method in class weka.core.tokenizers.PreCleanedTokenizer

Sets the cleaner to use for cleaning the tokens from the initial tokenization.

setCleaners(TokenCleaner[]) - Method in class weka.core.tokenizers.cleaners.MultiCleaner

Sets the cleaners to use.

setClearBuffer(boolean) - Method in class adams.flow.transformer.WekaInstanceBuffer

Sets whether to clear the buffer once the dataset has been forwarded.

setClusterer(CallableActorReference) - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator

Sets the name of the callable clusterer to use.

setClusterer(CallableActorReference) - Method in class adams.flow.transformer.WekaTrainClusterer

Sets the clusterer to use.

setClusterer(Clusterer) - Method in class adams.flow.source.WekaClustererSetup

Sets the clusterer to use.

setClusterer(Clusterer) - Method in class adams.ml.model.clustering.WekaClusterer

Sets the clusterer to use.

setColName(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

Sets the spreadsheet column with the name.

setColName(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall

Sets the spreadsheet column with the name.

setColor(Color) - Method in class adams.gui.visualization.instance.InstanceContainer

Sets the color to use.

setColorField(Field) - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Sets the report field that contains the color.

setColoringIndex(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Set the coloring (class) index for the plot

setColorProvider(ColorProvider) - Method in class adams.flow.sink.WekaInstanceViewer

Sets the color provider to use.

setColorProvider(ColorProvider) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Sets the color provider for the plots.

setColorProvider(ColorProvider) - Method in class adams.gui.visualization.instance.InstanceContainerManager

Sets the color provider to use.

setColumn(BaseString[]) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Sets list of fields that identify a column.

setColumn(BaseString[]) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Sets list of fields that identify a column.

setColumn(WekaAttributeIndex) - Method in class adams.flow.transformer.WekaGetInstancesValue

Sets the column.

setColumn(WekaAttributeIndex) - Method in class adams.flow.transformer.WekaSetInstancesValue

Sets the column index.

setColumnFinder(ColumnFinder) - Method in class adams.data.weka.columnfinder.AbstractFilteredColumnFinder

Sets the column finder to use.

setColumnFinder(ColumnFinder) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter

Sets the column finder.

setColumnFinder(ColumnFinder) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Sets the column finder to use.

setColumnFinder(ColumnFinder) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Sets the column finder which selects the attributes for summarisation.

setColumns(int) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Sets the size of array.

setColumns(int) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

setColumns(BaseInteger[]) - Method in class adams.data.weka.columnfinder.Constant

Sets the constant set of columns to find.

setColumnSampleByLevel(float) - Method in class weka.classifiers.trees.XGBoost

Sets the sub-sample ratio of columns for each level.

setColumnSampleByNode(float) - Method in class weka.classifiers.trees.XGBoost

Sets the sub-sample ratio of columns for each node (split).

setColumnSampleByTree(float) - Method in class weka.classifiers.trees.XGBoost

Sets the sub-sample ratio of columns when constructing each tree.

setColVersion(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial

Sets the (optional) spreadsheet column with the version.

setCombination(MultiColumnFinder.Combination) - Method in class adams.data.weka.columnfinder.MultiColumnFinder

Sets how the indices are combined.

setCombination(MultiRowFinder.Combination) - Method in class adams.data.weka.rowfinder.MultiRowFinder

Sets how the indices are combined.

setCombination(ClassifierCascade.Combination) - Method in class weka.classifiers.meta.ClassifierCascade

how to combine the statistics.

setCombinationRule(SelectedTag) - Method in class weka.classifiers.meta.AbstainVote

Sets the combination rule to use.

setCombinationRule(SelectedTag) - Method in class weka.classifiers.meta.SubsetEnsemble

Sets the combination rule to use.

setCombinationRule(SelectedTag) - Method in class weka.classifiers.meta.VotedImbalance

Sets the combination rule to use.

setComment(BaseText) - Method in class adams.flow.transformer.WekaClusterEvaluationSummary

Sets the comment to output in the summary.

setComment(BaseText) - Method in class adams.flow.transformer.WekaEvaluationSummary

Sets the comment to output in the summary.

setCommunication(AbstractCommunicationProcessor) - Method in class weka.classifiers.functions.PyroProxy

Sets the model proxy to use for communication.

setCommunication(AbstractCommunicationProcessor) - Method in interface weka.core.PyroProxyObject

Sets the handler for the communication.

setComparator(Comparator) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Sets the comparator to use.

setComparator(Comparator) - Method in class weka.classifiers.AggregateEvaluations

Sets the comparator to use.

setComparisonField(ExperimentStatistic) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Sets the comparison field.

setComparisonField(ExperimentStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Sets the comparison field.

setCompleteRowsOnly(boolean) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Sets whether incomplete rows should be skipped.

setComplexityStatistics(boolean) - Method in class adams.flow.transformer.WekaEvaluationSummary

Sets whether to output complexity stats as well.

setComplexityStatistics(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Sets whether to output complexity stats as well.

setComponentRange(Range) - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Sets the range of components to be used.

setConfidenceLevel(double) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Sets the confidence level.

setConfusionMatrix(boolean) - Method in class adams.flow.transformer.WekaEvaluationSummary

Sets whether to output the confusion matrix as well.

setConfusionMatrix(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Sets whether to output the confusion matrix as well.

setContainerManager(InstanceContainerManager) - Method in class adams.gui.visualization.instance.InstanceExplorer

Sets the manager for handling the containers.

setContent(DateTime) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContent(DateTimeMsec) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContent(Time) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContent(TimeMsec) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContent(Boolean) - Method in class adams.ml.data.DataCellView

Ignored.

setContent(Byte) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContent(Double) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContent(Float) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContent(Integer) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContent(Long) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContent(Short) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContent(String) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContent(Date) - Method in class adams.ml.data.DataCellView

Sets the content of the cell.

setContentAs(String, Cell.ContentType) - Method in class adams.ml.data.DataCellView

Sets the content of the cell, trying to parse the content using the specified content type.

setContentAsString(String) - Method in class adams.ml.data.DataCellView

Sets the string content of the cell.

setConversion(Conversion) - Method in class weka.core.converters.SpreadSheetLoader

Sets the conversion to use for converting the spreadsheet into an Instances object.

setConverter(Converter) - Method in class adams.data.conversion.WekaCommandToCode

Sets the converter to use.

setCorrect(String) - Method in class weka.filters.unsupervised.attribute.SpellChecker

Sets the correct label.

setCorrection(AbstractDetrend) - Method in class weka.filters.unsupervised.attribute.Detrend

Sets the correction scheme to apply.

setCorrection(AbstractDetrend) - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Sets the correction scheme to apply.

setCorrection(AbstractMultiplicativeScatterCorrection) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Sets the correction scheme to apply.

setCreateView(boolean) - Method in interface adams.data.weka.InstancesViewCreator

Sets whether to create a view only.

setCreateView(boolean) - Method in class adams.flow.transformer.WekaCrossValidationSplit

Sets whether to create a view only.

setCreateView(boolean) - Method in class adams.flow.transformer.WekaRandomSplit

Sets whether to create a view only.

setCrossValidationSeed(int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the seed value to use for cross-validation.

setCrossValidationSeed(int) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Sets the seed value to use for cross-validation.

setCurrent(File) - Method in class adams.gui.chooser.DatasetFileChooserPanel

Sets the current value.

setCurrent(File) - Method in class adams.gui.tools.weka.AbstractPanelWithFile

Sets the current file to use.

setCurrent(File) - Method in class adams.gui.tools.weka.CostCurvePanel

Sets the current file to use.

setCurrent(File) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Sets the current file.

setCurrent(File) - Method in class adams.gui.wizard.WekaSelectDatasetPage

Sets the current file.

setCurrent(File[]) - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

Sets the current files.

setCurrent(Object) - Method in class adams.gui.goe.WekaGenericArrayEditorDialog

Sets the current object.

setCurrent(Object) - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Sets the current value.

setCurrent(Object) - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

Sets the current object.

setCurrent(Object) - Method in class adams.gui.goe.WekaGenericObjectEditorPanel

Sets the current value.

setCurrentDirectory(File) - Method in class adams.gui.chooser.DatasetFileChooserPanel

Sets the current directory to use for the file chooser.

setCurrentDirectory(File) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Sets the current directory to use for the file chooser.

setCurrentDirectory(File) - Method in class adams.gui.wizard.WekaSelectDatasetPage

Sets the current directory to use for the file chooser.

setCurrentDirectory(File) - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

Sets the current directory to use for the file chooser.

setCurrentFile(File) - Method in class weka.gui.explorer.ExplorerExt

Only updates the current file member, does not load it.

setCustomLoader(AbstractFileLoader) - Method in class adams.flow.transformer.WekaFileReader

Sets the custom loader to use.

setCustomLoader(AbstractFileLoader) - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Sets the custom loader to use.

setCustomLoader(AbstractFileLoader) - Method in class weka.filters.unsupervised.instance.AlignDataset

Sets the custom loader to use (if enabled).

setCustomLoader(AbstractFileLoader) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Sets the custom loader to use (if enabled).

setCustomPaintlet(XYSequencePaintlet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets the custom paintlet.

setCustomPropsFile(PlaceholderFile) - Method in class adams.flow.sink.WekaDatabaseWriter

Sets the custom properties file to use for initializing the database setup instead of WEKA's default one.

setCustomPropsFile(PlaceholderFile) - Method in class adams.flow.source.WekaDatabaseReader

Sets the custom properties file to use for initializing the database setup instead of WEKA's default one.

setCustomSaver(AbstractFileSaver) - Method in class adams.flow.sink.WekaFileWriter

Sets the custom saver to use.

setCustomStopMessage(String) - Method in class adams.flow.source.WekaSelectDataset

Sets the custom message to use when stopping the flow.

setData(Instance) - Method in class adams.gui.visualization.instance.InstanceContainer

Sets the instance.

setData(List<DataContainer>) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

Sets the underlying data and notifies listeners of change.

setData(List<DataContainer>, boolean) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

Sets the underlying data.

setData(Instances) - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

Sets the data set to use for training and so forth.

setData(Instances) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Sets the data.

setData(Instances) - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer

Sets the data.

setData(Instances) - Method in class adams.gui.visualization.instance.InstanceTable

Sets the Instances object to display.

setData(Instances) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets the data to use.

setData(Instances) - Method in class weka.classifiers.AbstractSplitGenerator

Sets the original data.

setData(Instances) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Sets the original data.

setData(Instances) - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Sets the original data.

setData(Instances) - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Sets the original data.

setData(Instances) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Sets the original data.

setData(Instances) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Sets the original data.

setData(Instances) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Sets the original data.

setData(Instances) - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Sets the original data.

setData(Instances) - Method in interface weka.classifiers.SplitGenerator

Sets the original data.

setDatabaseConnection(AbstractDatabaseConnection) - Method in class adams.data.instances.AbstractInstanceGenerator

Sets the database connection object to use.

setDataGenerator(DataGenerator) - Method in class adams.flow.source.WekaDataGenerator

Sets the data generator to use.

setDataPaintlet(Paintlet) - Method in class adams.gui.visualization.instance.InstancePanel

Sets the paintlet to use for painting the data.

setDataRowClass(Class) - Method in class adams.ml.data.InstancesView

Sets the default data row class to use.

setDataRowType(DataRow) - Method in class adams.data.conversion.WekaInstancesToSpreadSheet

Sets the type of data row to use.

setDataset(PlaceholderFile) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Sets the filename of the dataset to use for cross-validation.

setDataset(StorageName) - Method in class adams.flow.transformer.WekaStoreInstance

Sets the name of the dataset in internal storage to append to.

setDataset(File) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Sets the dataset to use.

setDataset(Instances) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Sets the dataset to index.

setDataset(Instances) - Method in class weka.core.AbstractHashableInstance

Sets the reference to the dataset.

setDataset1(PlaceholderFile) - Method in class adams.tools.CompareDatasets

Sets the first dataset for the comparison.

setDataset2(PlaceholderFile) - Method in class adams.tools.CompareDatasets

Sets the second dataset for the comparison.

setDatasetNames(BaseString[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Sets the list of names to use in attribute renaming in place of the {DATASET} keyword.

setDatasets(PlaceholderFile[]) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets the datasets to use.

setDataType(WekaInstancesStatisticDataType) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Sets what type of data to retrieve from the Instances object.

setDataType(WekaInstancesStatisticDataType) - Method in class adams.flow.transformer.WekaInstancesStatistic

Sets what type of data to retrieve from the Instances object.

setDateLenient(boolean) - Method in class adams.ml.data.InstancesView

Sets whether parsing of dates is to be lenient or not.

setDateTimeLenient(boolean) - Method in class adams.ml.data.InstancesView

Sets whether parsing of date/times is to be lenient or not.

setDateTimeMsecLenient(boolean) - Method in class adams.ml.data.InstancesView

Sets whether parsing of date/time mses is to be lenient or not.

setDebug(boolean) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

sets whether or not debugging output shouild be printed

setDebug(boolean) - Method in class weka.classifiers.meta.LeastMedianSq

sets whether or not debugging output shouild be printed

setDebug(boolean) - Method in class weka.core.converters.SpreadSheetLoader

Sets whether to print some debug information.

setDebug(boolean) - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

Sets whether to output debugging information.

setDefaultAttributeRange(String) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Sets the default range of attributes to use.

setDefaultClassIndex(String) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Sets the default class index to use.

setDefaultColor(Color) - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Sets the default color to use when no color information in the report.

setDefaultIDIndex(String) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Sets the default ID index to use.

setDefaultIncludeAttributes(int, boolean) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Sets the default for the specified type of attribute.

setDefaultSortIndex(String) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Sets the default sort index to use.

setDeflationMode(NIPALS.DeflationMode) - Method in class adams.data.instancesanalysis.pls.NIPALS

Sets the deflation mode to use.

setDerivativeOrder(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Sets the order of the derivative.

setDerivativeOrder(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Sets the order of the derivative.

setDestination(File) - Method in class weka.core.converters.SimpleArffSaver

Sets the destination file (and directories if necessary).

setDestination(File) - Method in class weka.core.converters.SpreadSheetSaver

Sets the destination file (and directories if necessary).

setDestination(OutputStream) - Method in class weka.core.converters.SimpleArffSaver

Default implementation throws an IOException.

setDestination(OutputStream) - Method in class weka.core.converters.SpreadSheetSaver

Default implementation throws an IOException.

setDetector(AbstractOutlierDetector) - Method in class weka.filters.supervised.instance.RemoveOutliers

Sets the detector.

setDev(double) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

setDiameter(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets the cross diameter.

setDiffer(SelectedTag) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Sets the type of strategy to apply if the two values differ.

setDiffer(SelectedTag) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Sets the type of strategy to apply if the two values differ.

setDiscardPredictions(boolean) - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

Sets whether to discard the predictions instead of collecting them for future use, in order to conserve memory.

setDiscardPredictions(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Sets whether to discard the predictions instead of collecting them for future use, in order to conserve memory.

setDiscardPredictions(boolean) - Method in class adams.flow.transformer.WekaTestSetEvaluator

Sets whether to discard the predictions instead of collecting them for future use, in order to conserve memory.

setDiscardPredictions(boolean) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets whether to discard the predictions instead of collecting them for future use, in order to conserve memory.

setDisplayStdDevs(boolean) - Method in class weka.clusterers.SAXKMeans

Sets whether standard deviations and nominal count.

setDistanceFunction(DistanceFunction) - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient

Sets the distance function to use.

setDistanceFunction(DistanceFunction) - Method in class weka.clusterers.SAXKMeans

sets the distance function to use for instance comparison.

setDistributionFormat(String) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Sets the format for the 'Name' column for the class distribution.

setDistributionSorting(WekaPredictionContainerToSpreadSheet.Sorting) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Sets the sorting for the distribution array.

setDontReplaceMissingValues(boolean) - Method in class weka.clusterers.SAXKMeans

Sets whether missing values are to be replaced.

setDropAbove(double) - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Sets the threshold of the weights above which to drop instances.

setDropAtMost(double) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Sets the maximum percentage of instances to drop.

setDropBelow(double) - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Sets the threshold of the weights below which to drop instances.

setDropBelow(double) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Sets the threshold of the normalized weights below which to drop instances.

setDropNonClassYs(boolean) - Method in class weka.filters.supervised.attribute.MultiPLS

Sets whether to remove Y attributes from the output that are not the class attribute.

setEditor(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorDialog

Sets the editor to use.

setEliminateColinearAttributes(boolean) - Method in class weka.classifiers.functions.LinearRegressionJ

Set the value of EliminateColinearAttributes.

setEncoding(BaseCharset) - Method in class adams.data.io.input.NestedAdamsExperimentReader

Sets the encoding to use.

setEncoding(BaseCharset) - Method in class weka.core.converters.SimpleArffLoader

Sets the encoding to use.

setEncoding(BaseCharset) - Method in class weka.core.converters.SimpleArffSaver

Sets the encoding to use.

setEnsureEqualValues(boolean) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Sets whether to check all data-sources for a merged attribute have the same value.

setError(int) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

setError(int) - Method in class weka.classifiers.meta.LeastMedianSq

setErrorCalculation(WekaBootstrapping.ErrorCalculation) - Method in class adams.flow.transformer.WekaBootstrapping

Sets how to calculate the errors for the percentiles.

setErrorScaler(AbstractErrorScaler) - Method in class adams.flow.sink.WekaClassifierErrors

Sets the scheme for scaling the errors.

setEta(float) - Method in class weka.classifiers.trees.XGBoost

Sets the step size shrinkage to use in updates to prevent overfitting.

setEvaluationPostProcessor(AbstractWekaEvaluationPostProcessor) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the post-processing scheme for the evaluation.

setEvaluationType(WekaExperimentGenerator.EvaluationType) - Method in class adams.flow.sink.WekaExperimentGenerator

Sets the type of evaluation to perform.

setEvaluator(AbstractInstanceEvaluator) - Method in class adams.flow.transformer.WekaInstanceEvaluator

Sets the evaluator to use.

setEvaluator(ASEvaluation) - Method in class adams.flow.transformer.WekaAttributeSelection

Sets the evaluation method to use.

setExactMatch(boolean) - Method in class adams.data.conversion.SwapPLS

Sets whether to use the complete command-line for comparison rather than just the class name.

setExcludeClass(boolean) - Method in class weka.core.AbstractHashableInstance

Sets whether to exclude the class from the hashcode computation.

setExcludedAttributes(String) - Method in class adams.flow.transformer.WekaInstancesMerge

Sets the regular expression for excluding attributes.

setExcludeWeight(boolean) - Method in class weka.core.AbstractHashableInstance

Sets whether to exclude the weight from the hashcode computation.

setExperiment(AbstractExperiment) - Method in class adams.flow.source.WekaNewExperiment

Sets the experiment setup.

setExperiment(AbstractExperiment) - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel

Sets the experiment to use.

setExperiment(Object) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Sets the experiment to use.

setExperiment(T) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

Sets the experiment to use.

setExperiment(Experiment) - Method in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog

Sets the experiment to use.

setExperiment(Experiment) - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel

Sets the experiment to use.

setExperimentFile(WekaExperimentFile) - Method in class adams.flow.transformer.WekaExperiment

Sets the file the experiment is stored in.

setExperimentType(WekaExperimentGenerator.ExperimentType) - Method in class adams.flow.sink.WekaExperimentGenerator

Sets the type of experiment to perform.

setExplorer(Explorer) - Method in class weka.gui.explorer.ExperimentPanel

Sets the Explorer to use as parent frame (used for sending notifications about changes in the data).

setExplorer(Explorer) - Method in class weka.gui.explorer.SqlPanel

Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)

setExplorerOptions(Explorer, Hashtable<String, Object>) - Static method in class weka.gui.explorer.WorkspaceHelper

Restores the Explorer options from the hashtable.

setExpression(MathematicalExpressionText) - Method in class weka.classifiers.functions.MathExpressionClassifier

Sets the mathematical expression to evaluate.

setFallback(Classifier) - Method in class weka.classifiers.meta.Fallback

Sets the fallback classifier.

setFastDistanceCalc(boolean) - Method in class weka.clusterers.SAXKMeans

Sets whether to use faster distance calculation.

setFavorZeroes(boolean) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Sets whether 0s are favored over 1s.

setFeatureSelector(XGBoost.FeatureSelector) - Method in class weka.classifiers.trees.XGBoost

Gets the feature selection and ordering method.

setFields(Field[]) - Method in class adams.data.conversion.ReportToWekaInstance

Sets the fields to use.

setFields(Field[]) - Method in interface adams.data.instances.InstanceGeneratorWithFields

Sets the targets to add.

setFile(File) - Method in class weka.core.converters.SimpleArffLoader

Set the file to load from/ to save in

setFileChooserTitle(String) - Method in class adams.flow.source.WekaSelectDataset

Sets the title for the file chooser dialog.

setFiles(File[]) - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

Sets the files to use.

setFilter(Filter) - Method in class adams.data.spreadsheet.filter.WekaFilter

Sets the filter to use.

setFilter(Filter) - Method in class adams.data.weka.rowfinder.FilteredIQR

Sets the IQR filter.

setFilter(Filter) - Method in class adams.flow.transformer.WekaFilter

Sets the filter to use.

setFilter(Filter) - Method in class weka.classifiers.functions.ClassificationViaPLS

Set the PLS filter (only used for setup).

setFilter(Filter) - Method in class weka.classifiers.functions.PLSClassifierWeighted

Set the PLS filter (only used for setup).

setFilter(Filter) - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

setFilter(Filter) - Method in class weka.core.neighboursearch.FilteredSearch

Sets the filter

setFilter(Filter) - Method in class weka.filters.unsupervised.attribute.FastWavelet

Set the preprocessing filter (only used for setup).

setFilter(StreamableFilter) - Method in class adams.flow.transformer.WekaStreamFilter

Sets the filter to use.

setFilters(Filter[]) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Sets the list of possible filters to choose from.

setFilters(Filter[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Sets the list of possible filters to choose from.

setFilterSearch(Filter) - Method in class weka.classifiers.lazy.LWLSynchroSplit

Sets filter to generate the data for the search.

setFilterTrain(Filter) - Method in class weka.classifiers.lazy.LWLSynchroSplit

Sets filter to use for to generate the training data for the base classifier.

setFilterType(SelectedTag) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Sets how the training data will be transformed.

setFilterType(SelectedTag) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Sets how the training data will be transformed.

setFilterType(SelectedTag) - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Sets how the training data will be transformed.

setFilterType(SelectedTag) - Method in class weka.classifiers.functions.GPD

Sets how the training data will be transformed.

setFinalModel(boolean) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Sets whether to build a final model on the full dataset.

setFind(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Sets the regular expression to use for extracting the numeric part from the label.

setFind(String) - Method in class adams.flow.transformer.WekaRenameRelation

Sets the string to find.

setFinders(ColumnFinder[]) - Method in class adams.data.weka.columnfinder.MultiColumnFinder

Sets the column finders to use.

setFinders(RowFinder[]) - Method in class adams.data.weka.rowfinder.MultiRowFinder

Sets the row finders to use.

setFirstAttribute(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Sets the name of the first attribute.

setFirstAttributeRange(String) - Method in class adams.gui.InstanceCompare

Sets the first attribute range ('first' and 'last' can be used as well).

setFirstAttributeRange(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel

Sets the first attribute range ('first' and 'last' can be used as well).

setFirstDataset(PlaceholderFile) - Method in class adams.gui.InstanceCompare

Sets the first dataset.

setFirstDataset(File) - Method in class adams.gui.visualization.instance.InstanceComparePanel

Sets the first dataset.

setFirstRange(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Sets the first attribute range to use (regular expression on attribute names).

setFirstRowIndex(String) - Method in class adams.gui.InstanceCompare

Sets the first row index ('first' and 'last' can be used as well).

setFirstRowIndex(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel

Sets the first row index ('first' and 'last' can be used as well).

setFlowContext(Actor) - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction

Sets the flow context.

setFlowContext(Actor) - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction

Sets the flow context.

setFlowContext(Actor) - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction

Sets the flow context.

setFlowContext(Actor) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets the flow context.

setFlowContext(Actor) - Method in class adams.multiprocess.WekaCrossValidationJob

Sets the flow context.

setFlowContext(Actor) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the flow context, if any.

setFlowContext(Actor) - Method in class weka.classifiers.functions.PyroProxy

Sets the flow context.

setFlowFile(FlowFile) - Method in class weka.filters.FlowFilter

Sets the flow to process the data with.

setFolds(int) - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

Sets the number of folds for cross-validation.

setFolds(int) - Method in class adams.flow.sink.WekaExperimentGenerator

Sets the number of folds to use (only CV).

setFolds(int) - Method in class adams.flow.transformer.WekaAttributeSelection

Sets the number of folds.

setFolds(int) - Method in class adams.flow.transformer.WekaClassifierRanker

Sets the number of folds to use.

setFolds(int) - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Sets the number of folds.

setFolds(int) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Sets the number of folds.

setFolds(int) - Method in class adams.flow.transformer.WekaCrossValidationSplit

Sets the number of folds to use.

setFolds(int) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Sets the number of folds.

setFolds(int) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

Sets the number of folds.

setFolds(int) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets the number of folds.

setFolds(int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the number of folds to use in cross-validation.

setFolds(int) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Sets the number of folds to use in cross-validation.

setForceCompression(boolean) - Method in class weka.core.converters.SimpleArffLoader

Set whether the file gets interpreted as gzip-compressed ARFF file.

setFormat(String) - Method in class weka.filters.unsupervised.attribute.StringToDate

Sets the parse format to use.

setFormula(String) - Method in class adams.ml.data.DataCellView

Ignored.

setGamma(double) - Method in class weka.classifiers.functions.GPD

Set the gamma for the RBF kernel.

setGamma(float) - Method in class weka.classifiers.trees.XGBoost

Sets the minimum loss reduction required to make a further partition on a leaf node of the tree.

setGene(int, int, boolean) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Sets the value of the specified gene.

setGene(int, int, int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Sets the value of the specified gene.

setGenerateLine(boolean) - Method in class adams.data.baseline.AbstractLinearRegressionBased

Sets whether to return the line as fake data or the corrected data.

setGenerateRules(boolean) - Method in class weka.classifiers.trees.m5.M5Base2

Generate rules (decision list) rather than a tree

setGenerator(AbstractInstanceGenerator) - Method in class adams.flow.transformer.AbstractInstanceGenerator

Sets the generator to use.

setGenerator(AbstractWekaEnsembleGenerator) - Method in class adams.flow.transformer.WekaEnsembleGenerator

Sets the ensemble generator to use.

setGenerator(CrossValidationFoldGenerator) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Sets the scheme for generating the folds.

setGenerator(CrossValidationFoldGenerator) - Method in class adams.flow.transformer.WekaCrossValidationSplit

Sets the scheme for generating the folds.

setGenerator(CrossValidationFoldGenerator) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Sets the scheme for generating the folds.

setGenerator(CrossValidationFoldGenerator) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment

Sets the scheme for generating the folds.

setGenerator(CrossValidationFoldGenerator) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets the generator to use for generating the folds.

setGenerator(CrossValidationFoldGenerator) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the scheme for generating the folds.

setGenerator(RandomSplitGenerator) - Method in class adams.flow.transformer.WekaRandomSplit

Sets the scheme for generating the split.

setGenerator(RandomSplitGenerator) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Sets the scheme for generating the split.

setGenerator(SplitGenerator) - Method in class adams.flow.transformer.WekaSplitGenerator

Sets the scheme for generating the split.

setGlue(String) - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Sets the glue to use.

setGrid(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Sets the size of the grid.

setGroup(String) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Sets the replacement string to use as group (eg '$2').

setGroup(String) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Sets the replacement string to use as group (eg '$2').

setGroup(String) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Sets the replacement string to use as group (eg '$2').

setGroup(String) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Sets the replacement string to use as group (eg '$2').

setGroup(String) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Sets the replacement string to use as group (eg '$2').

setGroup(String) - Method in class weka.classifiers.GroupedRandomSplitGenerator

Sets the replacement string to use as group (eg '$2').

setGroup(String) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Sets the replacement string to use as group (eg '$2').

setGroups(BaseString[]) - Method in class weka.classifiers.MultiLevelSplitGenerator

Sets the groups to generate.

setGrowPolicy(XGBoost.GrowPolicy) - Method in class weka.classifiers.trees.XGBoost

Sets the way new nodes are added to the tree.

setHandler(AbstractExperimentIO) - Method in class adams.flow.sink.WekaExperimentFileWriter

Sets the IO handler.

setHandler(AbstractExperimentIO) - Method in class adams.flow.transformer.WekaExperimentFileReader

Sets the IO handler.

setHandlers(AbstractGeneticDiscoveryHandler[]) - Method in class adams.opt.genetic.Hermione

Sets the discovery handlers to use.

setHeader(PlaceholderFile) - Method in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader

Sets the file to load the dataset header from.

setHeader(StorageName) - Method in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader

Sets the name of the storage value representing the dataset header.

setHeaderPopupMenuCustomizer(PopupMenuCustomizer) - Method in class adams.gui.visualization.instances.InstancesTable

Sets the popup menu customizer to use (for the header).

setHiClassifier(Classifier) - Method in class weka.classifiers.meta.HighLowSplit

setHiLopoint(double) - Method in class weka.classifiers.meta.HighLowSplit

setHistogramOptions(HistogramOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Set the options for the histogram.

setHoldOutPercentage(double) - Method in class weka.classifiers.meta.ClassifierCascade

the percentage to use for validation set to determine termination criterion (0-100).

setICA(FastICA) - Method in class adams.data.instancesanalysis.FastICA

Sets the ICA analysis.

setID(WekaAttributeIndex) - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Sets the attribute name/index of attribute with IDs.

setID(WekaAttributeIndex) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Sets the attribute name/index to use for identifying rows.

setID(String) - Method in class adams.data.instance.Instance

Sets the ID of the sequence.

setID(String) - Method in class adams.flow.sink.WekaInstanceViewer

Sets the name of the attribute/field to use as ID in the display.

setID(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Sets the ID to use for the returned instances.

setID(String) - Method in class adams.gui.visualization.instance.InstanceContainer

Sets the container's ID.

setIDTest(WekaAttributeIndex) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Sets the attribute name/index to use for identifying rows in the test set.

setIgnoreChanges(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

Sets whether to ignore changes, ie don't set the modified flag.

setIgnoreClass(boolean) - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

Sets whether to ignore the class.

setIgnoredAttributes(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Sets the regular expression for ignored/skipped attributes.

setIncludeAttributes(int, boolean) - Method in class adams.gui.visualization.instance.LoadDatasetDialog

Sets whether only numeric attributes should be used.

setIncludeClass(boolean) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Sets whether to include the class attribute in the comparison.

setIncludeClass(boolean) - Method in class weka.filters.unsupervised.instance.Sort

Sets whether to include the class attribute in the comparison.

setIncorrect(String) - Method in class weka.filters.unsupervised.attribute.SpellChecker

Sets the incorrect labels, blank-separated list.

setIncremental(boolean) - Method in class adams.flow.source.WekaDatabaseReader

Sets whether to output single Instance objects or just one Instances object.

setIndex(Index) - Method in class adams.flow.transformer.WekaExtractArray

Sets the type of extraction to perform.

setIndex(Index) - Method in class adams.flow.transformer.WekaGetInstanceValue

Sets the 1-based index of the attribute value to retrieve from the Instance.

setIndex(WekaAttributeIndex) - Method in class adams.data.weka.classattribute.AttributeIndex

Sets the index of the attribute to select.

setIndex(WekaAttributeIndex) - Method in class adams.data.weka.relationname.AttributeIndex

Sets the index of the attribute to select.

setIndex(WekaAttributeIndex) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Sets the attribute index to use for grouping.

setIndex(WekaAttributeIndex) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Sets the attribute index to use for grouping.

setIndex(WekaAttributeIndex) - Method in class adams.flow.transformer.WekaSetInstanceValue

Sets the 1-based attribute index to set in the Instance.

setIndex(WekaAttributeIndex) - Method in class adams.flow.transformer.WekaSubsets

Sets the index of the attribute to split on.

setIndex(WekaAttributeIndex) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Sets the attribute index to use for grouping.

setIndex(WekaAttributeIndex) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Sets the attribute index to use for grouping.

setIndex(WekaAttributeIndex) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Sets the attribute index to use for grouping.

setIndex(WekaAttributeIndex) - Method in class weka.classifiers.GroupedRandomSplitGenerator

Sets the attribute index to use for grouping.

setIndex(WekaAttributeIndex) - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Sets the attribute index to use for grouping.

setIndex(WekaAttributeIndex) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Sets the index of the attribute to convert.

setIndex(WekaAttributeIndex) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Sets the attribute index to use for grouping.

setIndex(WekaAttributeIndex) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Sets the index of the attribute to convert.

setIndices(WekaAttributeIndex[]) - Method in class weka.classifiers.MultiLevelSplitGenerator

Sets the attribute indices.

setInfoData(Vector<Instances>) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Sets the underlying data.

setInitialDirectory(PlaceholderDirectory) - Method in class adams.flow.source.WekaSelectDataset

Sets the initial directory.

setInitialFiles(PlaceholderFile[]) - Method in class adams.flow.source.WekaSelectDataset

Sets the initial files.

setInitializationMethod(SelectedTag) - Method in class weka.clusterers.SAXKMeans

Set the initialization method to use

setInitializeOnce(boolean) - Method in class adams.flow.transformer.WekaFilter

Sets whether the filter gets initialized only with the first batch.

setInitializeOnce(boolean) - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Sets whether the internal reorder filter gets initialized only with the first batch.

setInlineValue(String) - Method in class adams.gui.goe.WekaExperimentFileEditor

Sets the value to use.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Sets the format of the input instances.

setInstanceClass(BaseClassname) - Method in class adams.flow.transformer.WekaNewInstance

Sets the class name of the Instance object to create.

setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel

Sets the tablemodel to look at a new set of instances.

setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Sets the instances to display the attribute names for.

setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel

Tells the panel to use a new set of instances.

setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel

Sets the instances for use

setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

Tells the panel to use a new set of instances.

setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

Sets the instances to display.

setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

Sets the instances to display.

setInstances(Instances) - Method in class adams.gui.visualization.instances.InstancesPanel

Sets the instances to display.

setInstances(Instances) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Sets the Instances to use.

setInstances(Instances) - Method in class adams.gui.visualization.instances.InstancesTable

sets the data

setInstances(Instances) - Method in class adams.gui.visualization.instances.InstancesTableModel

sets the data

setInstances(Instances) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the data to use for cross-validation.

setInstances(Instances) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Sets the data to use for cross-validation.

setInstances(Instances) - Method in class weka.core.neighboursearch.FilteredSearch

Sets the instances comprising the current neighbourhood.

setInstances(Instances) - Method in class weka.core.neighboursearch.NewNNSearch

Sets the instances comprising the current neighbourhood.

setInstances(Instances) - Method in class weka.core.neighboursearch.PCANNSearch

Sets the instances comprising the current neighbourhood.

setInstances(Instances) - Method in class weka.core.neighboursearch.PLSNNSearch

Sets the instances comprising the current neighbourhood.

setInstances(Instances) - Method in class weka.gui.explorer.ExperimentPanel

Tells the panel to use a new set of instances.

setInstances(Instances) - Method in class weka.gui.explorer.SqlPanel

ignored

setInstancesActor(CallableActorReference) - Method in class adams.flow.transformer.WekaInstanceEvaluator

Sets the callable actor from which to retrieve Instances in case of AbstractDatasetInstanceEvaluator-derived evaluators.

setInstancesIndices(String) - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Sets the range of instances to be selected.

setInt(int[], int, int, int) - Method in class adams.opt.optimise.genetic.PackData

setInterval(int) - Method in class adams.flow.transformer.WekaInstanceBuffer

Sets the interval for outputting the Instances objects.

setInterval(int) - Method in class adams.flow.transformer.WekaStreamEvaluator

Sets the output interval.

setInverseTransform(boolean) - Method in class weka.filters.unsupervised.attribute.FastWavelet

Sets whether to use the inverse tranform.

setInverseTransform(boolean) - Method in class weka.filters.unsupervised.attribute.FFT

Sets whether to compute inverse.

setInvert(boolean) - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Sets whether to invert the matching sense of the capabilities.

setInvert(boolean) - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Sets whether to invert the matching sense.

setInvert(boolean) - Method in class adams.flow.transformer.WekaRegexToRange

Invert match?

setInvert(boolean) - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

Sets whether to invert the matching sense, ie keep only the emoticons rather than removing them.

setInvert(boolean) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Set whether the invert the column indices.

setInvert(boolean) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Set whether the invert the row indices.

setInvert(boolean) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Set whether selection is inverted.

setInvert(boolean) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Set whether selection is inverted.

setInvert(boolean) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Sets whether to invert the matching sense (ie keep rather than remove).

setInvert(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Sets whether to invert the matching sense.

setInvertMatchingSense(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge

Sets whether to invert the matching sense.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.KennardStone

Sets if selection is to be inverted.

setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Sets if selection is to be inverted.

setIqr(double) - Method in class adams.data.weka.rowfinder.FilteredIQR

Sets the IQR multiplier.

setIterations(int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Sets the iterations to use.

setJobRunner(JobRunner) - Method in class adams.flow.transformer.WekaExperimentExecution

Sets the jobrunner for the experiment.

setJobRunner(JobRunner) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets the jobrunner for the experiment.

setJobRunner(JobRunner) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets the JobRunner.

setJobRunnerSetup(JobRunnerSetup) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets the JobRunnerSetup.

setJobRunnerSetup(JobRunnerSetup) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the jobrunner setup to use.

setKeepAttributeNames(boolean) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Sets whether to keep the original attribute names.

setKeepAttributeNames(boolean) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Sets whether to keep the original attribute names.

setKeepExisting(boolean) - Method in class adams.flow.transformer.WekaInstanceDumper

Sets whether to keep any existing file on first execution.

setKeepNumComponents(boolean) - Method in class adams.data.conversion.SwapPLS

Sets whether the 'number of components' of the old filter are retained.

setKeepOnlySingleUniqueID(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge

Sets whether to keep only a single instance of the unique ID attribute.

setKeepRelationName(boolean) - Method in class adams.flow.transformer.WekaFilter

Sets whether the filter doesn't change the relation name.

setKeepRelationName(boolean) - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Sets whether the filter doesn't change the relation name.

setKeepRelationName(boolean) - Method in class adams.flow.transformer.WekaStreamFilter

Sets whether the filter doesn't change the relation name.

setKeepSupervisedClass(boolean) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Sets whether to keep the class attribute of the summary attributes in the final dataset.

setKernel(AbstractKernel) - Method in class adams.data.instancesanalysis.pls.KernelPLS

Sets the kernel to use.

setKernel(Kernel) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Sets the kernel to use.

setKernel(Kernel) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Sets the kernel to use.

setKernel(Kernel) - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Sets the kernel to use.

setKeys(String) - Method in class adams.flow.source.WekaDatabaseReader

Sets the keys to use for identifying a single row (comma-separated list).

setKNN(int) - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Sets the number of neighbours used for kernel bandwidth setting.

setKNN(int) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Sets the number of neighbours used for kernel bandwidth setting.

setLabel(WekaLabelIndex) - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Sets the label index to use.

setLabel(WekaLabelIndex) - Method in class weka.classifiers.meta.Veto

Sets the label index to use.

setLabelIndex(WekaLabelIndex) - Method in class adams.flow.transformer.WekaInstancesInfo

Sets the index of the label to use.

setLabelIndex(String) - Method in class weka.classifiers.functions.ClassificationViaPLS

Set the label index to get the PLS matrices for.

setLabelMatch(String) - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Sets the label for the matching rows.

setLabelNonMatch(String) - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Sets the label for the non-matching rows.

setLabelRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Sets the regular expression for matching the labels to remove.

setLabelString(String) - Method in class weka.classifiers.functions.ClassificationViaPLS

Set the class attribute's label to get the PLS matrices for.

setLambda(double) - Method in class adams.data.instancesanalysis.pls.DIPLS

Sets the lambda.

setLambda(double) - Method in class adams.data.instancesanalysis.pls.SparsePLS

Sets sparsity parameter; determines sparseness.

setLambda(double) - Method in class adams.data.instancesanalysis.pls.VCPLS

Sets the lambda parameter.

setLambda(float) - Method in class weka.classifiers.trees.XGBoost

Sets the L2 regularisation term on weights.

setLenient(boolean) - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Sets whether to tolerate attributes that are missing in the incoming data.

setLimit(ActualVsPredictedPlot.LimitType) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets the limit to impose on the axes.

setListType(ListPackages.ListType) - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

Sets the type of list to generate.

setLoadingsCalculations(AbstractPLSAttributeEval.LoadingsCalculations) - Method in class weka.attributeSelection.AbstractPLSAttributeEval

sets the maximum number of attributes to use.

setLocal(BaseHostname) - Method in class weka.classifiers.meta.SocketFacade

Sets the return address for the remote process to use.

setLocale(Locale) - Method in class adams.ml.data.InstancesView

Sets the locale.

setLocations(BaseString[]) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Sets the locations of the data (indices/regular expressions on attribute name).

setLocations(BaseString[]) - Method in class adams.flow.transformer.WekaInstancesStatistic

Sets the locations of the data (indices/regular expressions on attribute name).

setLoClassifier(Classifier) - Method in class weka.classifiers.meta.HighLowSplit

setLog(Logger) - Method in class weka.gui.explorer.ExperimentPanel

Sets the Logger to receive informational messages.

setLog(Logger) - Method in class weka.gui.explorer.SqlPanel

Sets the Logger to receive informational messages

setLoggingLevel(LoggingLevel) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Sets the logging level.

setLoggingLevel(LoggingLevel) - Method in class adams.flow.transformer.WekaFilter

Sets the logging level.

setLoHipoint(double) - Method in class weka.classifiers.meta.HighLowSplit

setLoHipoint(double) - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

setLower(LowerStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Sets the lower value to output.

setLower(LowerStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Sets the lower value to output.

setLower(LowerStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Sets the lower value to output.

setLower(LowerStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Sets the lower value to output.

setMainFilter(Filter) - Method in class weka.filters.FilteredFilter

Sets the main filter to use.

setMakeClassLast(boolean) - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Sets whether to make the class attribute the last attribute.

setMakeThreadSafe(boolean) - Method in class adams.flow.transformer.WekaModelReader

Sets whether to wrap classifier inside a threadsafe ThreadSafeClassifierWrapper wrapper.

setManualClassifier(Classifier) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Sets the manual classifier to use instead of obtaining it from the flow.

setManualClassifier(Classifier) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Sets the manual classifier to use instead of obtaining it from the flow.

setManualMax(double) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Sets the maximum to use when using manual binning with user-supplied max/max enabled.

setManualMin(double) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Sets the minimum to use when using manual binning with user-supplied min/max enabled.

setMarkerExtent(int) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Sets the extent (width and height of the shape around the plotted point).

setMarkersDisabled(boolean) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet

Sets whether to draw markers or not.

setMatrix(String) - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess

Sets the name of matrix to extract.

setMatrix(Matrix) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter

setMatrix(Matrix) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

setMatrixType(WekaExtractPLSMatrix.MatrixType) - Method in class adams.flow.transformer.WekaExtractPLSMatrix

Sets the type of matrix to extract.

setMatrixValues(ConfusionMatrix.MatrixValues) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Sets the type of values to generate.

setMax(double) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

setMax(double) - Method in class weka.filters.unsupervised.instance.Scale

Sets the maximum for the values.

setMax(int) - Method in class adams.flow.transformer.WekaClassifierRanker

Sets the maximum number of top-ranked classifiers to forward.

setMax(int) - Method in class weka.classifiers.trees.RandomModelTrees

setMaxAttributeNames(int) - Method in class adams.data.instancesanalysis.PCA

Sets the maximum number of attribute names.

setMaxAttributes(int) - Method in class adams.data.instancesanalysis.PCA

Sets the maximum attributes.

setMaxBin(int) - Method in class weka.classifiers.trees.XGBoost

Sets the maximum number of discrete bins to bucket continuous features.

setMaxClassRangePercentage(double) - Method in class weka.classifiers.meta.MinMaxLimits

Set the percentage of leeway to apply to the upper limit determaxed by the range of the class attribute in the training data.

setMaxDecimalPlaces(int) - Method in class weka.core.converters.SimpleArffSaver

Set the maximum number of decimal places to print

setMaxDepth(int) - Method in class weka.classifiers.trees.XGBoost

Sets the maximum depth of a tree.

setMaxDifference(String) - Method in class weka.classifiers.meta.AbstainAverage

setMaxDifference(String) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

setMaxDifference(String) - Method in class weka.classifiers.meta.AbstainVote

setMaxDisplayItems(int) - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Sets the maximum number of array items to display via toString().

setMaxFactor(double) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Sets the upper limit for the multiplication factor for instances.

setMaxHandling(MinMaxLimits.LimitHandling) - Method in class weka.classifiers.meta.MinMaxLimits

Set how the upper limit is handled.

setMaximum(double) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Sets the maximum.

setMaximum(double) - Method in class adams.data.weka.rowfinder.ByNumericValue

Sets the maximum.

setMaximum(double) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Sets the maximum.

setMaximumAttributeNames(int) - Method in class adams.flow.transformer.WekaPrincipalComponents

Sets maximum number of attribute names.

setMaximumAttributeNames(int) - Method in class weka.core.neighboursearch.PCANNSearch

Sets maximum number of attributes to include in transformed attribute names.

setMaximumAttributeNames(int) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Sets maximum number of attributes to include in transformed attribute names.

setMaximumAttributes(int) - Method in class adams.flow.transformer.WekaPrincipalComponents

Sets maximum number of PC attributes to retain.

setMaximumAttributes(int) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Sets maximum number of PC attributes to retain.

setMaximumDeltaStep(float) - Method in class weka.classifiers.trees.XGBoost

Sets the maximum delta step we allow each leaf output to be.

setMaximumIncluded(boolean) - Method in class adams.data.weka.rowfinder.ByNumericValue

Sets whether to exclude the maximum.

setMaximumIncluded(boolean) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Sets whether to exclude the maximum.

setMaxIter(int) - Method in class adams.data.instancesanalysis.pls.KernelPLS

Sets the inner NIPALS loop improvement tolerance.

setMaxIter(int) - Method in class adams.data.instancesanalysis.pls.NIPALS

Sets the inner NIPALS loop maximum number of iterations.

setMaxIter(int) - Method in class adams.data.instancesanalysis.pls.PRM

Sets the inner NIPALS loop maximum number of iterations.

setMaxIter(int) - Method in class adams.data.instancesanalysis.pls.SparsePLS

Sets the inner NIPALS loop maximum number of iterations.

setMaxIterations(int) - Method in class weka.clusterers.SAXKMeans

set the maximum number of iterations to be executed.

setMaxIterations(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Sets the maximum number of cleansing iterations to perform - < 1 means go until fully cleansed

setMaxIterations(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Sets the maximum number of cleansing iterations to perform - < 1 means go until fully cleansed

setMaxLabels(int) - Method in class adams.data.conversion.SpreadSheetToWekaInstances

Sets the maximum number of labels a nominal attribute can have.

setMaxLabels(int) - Method in class adams.data.spreadsheet.filter.WekaFilter

Sets the maximum number of labels a nominal attribute can have.

setMaxLeaves(int) - Method in class weka.classifiers.trees.XGBoost

Sets the maximum number of nodes to be added.

setMaxLevels(int) - Method in class weka.classifiers.meta.ClassifierCascade

the maximum number of levels in the cascade.

setMaxManual(double) - Method in class weka.classifiers.meta.MinMaxLimits

Set the manual upper limit.

setMaxNeighbors(int) - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Sets the maximum number of neighbors to find.

setMaxSize(int) - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler

Sets the maximum size for the errors.

setMaxTrainTime(int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Sets the maximum number of seconds to perform training.

setMeasure(WekaClassifierRanker.Measure) - Method in class adams.flow.transformer.WekaClassifierRanker

Sets the measure to use for ranking the classifiers.

setMeasure(Measure) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the measure used for evaluating the fitness.

setMeasure(AbstractWEKAFitnessFunction.Measure) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Sets the measure used for evaluating the fitness.

setMeasuresPrefix(String) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Sets the prefix for the measure attributes.

setMenuItemText(String) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows

Sets the (optional) custom menu item text.

setMenuItemText(String) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows

Sets the (optional) custom menu item text.

setMergedIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Sets the position for the merged attribute.

setMergedIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Sets the position for the merged attribute.

setMergeMethod(AbstractMerge) - Method in class adams.flow.transformer.WekaDatasetsMerge

Sets the merge method to use to perform the merge.

setMessage(String) - Method in class adams.flow.transformer.WekaChooseAttributes

Sets the message to display to the user (variables get expanded).

setMetaDataColor(AbstractMetaDataColor) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets the scheme for extracting the color from the meta-data.

setMetaLevelClassifier(Classifier) - Method in class weka.classifiers.meta.PartitionedStacking

Sets the meta-level classifier.

setMethodNamePrediction(String) - Method in class weka.classifiers.functions.PyroProxy

Sets the name of the method to call for predictions.

setMethodNameTrain(String) - Method in class weka.classifiers.functions.PyroProxy

Sets the name of the method to call for training.

setMin(double) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

setMin(double) - Method in class weka.filters.unsupervised.instance.Scale

Sets the minimum for the values.

setMin(int) - Method in class weka.classifiers.trees.RandomRegressionForest

Sets the leaf threshold.

setMinChildWeight(float) - Method in class weka.classifiers.trees.XGBoost

Sets the minimum sum of instance weights (hessian) needed in a child.

setMinClassRangePercentage(double) - Method in class weka.classifiers.meta.MinMaxLimits

Set the percentage of leeway to apply to the lower limit determined by the range of the class attribute in the training data.

setMinHandling(MinMaxLimits.LimitHandling) - Method in class weka.classifiers.meta.MinMaxLimits

Set how the lower limit is handled.

setMinimal(boolean) - Method in class weka.attributeSelection.LinearRegressionAttributeEval

Sets whether to be more memory conservative or being able to output the model as string.

setMinimal(boolean) - Method in class weka.classifiers.functions.LinearRegressionJ

Sets whether to be more memory conservative or being able to output the model as string.

setMinImprovement(double) - Method in class weka.classifiers.meta.ClassifierCascade

the minimum improvement between levels that the statistic must improve.

setMinimum(double) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Sets the minimum.

setMinimum(double) - Method in class adams.data.weka.rowfinder.ByNumericValue

Sets the minimum.

setMinimum(double) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Sets the minimum.

setMinimumIncluded(boolean) - Method in class adams.data.weka.rowfinder.ByNumericValue

Sets whether to exclude the minimum.

setMinimumIncluded(boolean) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

Sets whether to exclude the minimum.

setMinManual(double) - Method in class weka.classifiers.meta.MinMaxLimits

Set the manual lower limit.

setMinMax(String, double, double) - Method in class adams.opt.optimise.genetic.PackDataDef

setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.M5Base2

Set the minimum number of instances to allow at a leaf node

setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.Rule2

Set the minumum number of instances to allow at a leaf node

setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.RuleNode2

Set the minumum number of instances to allow at a leaf node

setMinProbability(double) - Method in class weka.classifiers.meta.AbstainMinimumProbability

Sets the minimum probability that the chosen class label must meet.

setMinProbability(double) - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Sets the minimum probability for the selected label.

setMinSamples(int) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Sets the minimum number of samples that are required for calculating IQR stats.

setMissing() - Method in class adams.ml.data.DataCellView

Sets the cell to missing.

setMissing(int) - Method in class weka.core.AbstractHashableInstance

Sets a specific value to be "missing".

setMissing(PlaceholderFile) - Method in class adams.tools.CompareDatasets

Sets the first dataset for the comparison.

setMissing(Attribute) - Method in class weka.core.AbstractHashableInstance

Sets a specific value to be "missing".

SetMissingValue - Class in weka.filters.unsupervised.attribute

Attribute values in the given range are set to missing values.
NB: The class attribute is not excluded from this process.

SetMissingValue() - Constructor for class weka.filters.unsupervised.attribute.SetMissingValue

setModel(TableModel) - Method in class adams.gui.visualization.instances.InstancesPanel

Sets the model to use.

setModel(TableModel) - Method in class adams.gui.visualization.instances.InstancesTable

Sets the model to use.

setModel(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Sets the model to make available.

setModelActor(CallableActorReference) - Method in class adams.flow.condition.bool.WekaClassification

Sets the callable actor to obtain the model from if model file is pointing to a directory.

setModelActor(CallableActorReference) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Sets the filter source actor.

setModelActor(CallableActorReference) - Method in class adams.flow.transformer.WekaFilter

Sets the filter source actor.

setModelFile(PlaceholderFile) - Method in class adams.flow.condition.bool.WekaClassification

Sets the file to load the model from.

setModelFile(PlaceholderFile) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Sets the file to load the model from.

setModelFile(PlaceholderFile) - Method in class adams.flow.transformer.WekaFilter

Sets the file to load the model from.

setModelLoadingType(AbstractModelLoader.ModelLoadingType) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Sets the loading type.

setModelLoadingType(AbstractModelLoader.ModelLoadingType) - Method in class adams.flow.transformer.WekaFilter

Sets the loading type.

setModelName(String) - Method in class weka.classifiers.functions.PyroProxy

Sets the name of the model to use.

setModelResetVariable(VariableName) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Sets the variable to monitor for changes in order to reset the model.

setModelStorage(StorageName) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Sets the filter storage item.

setModelStorage(StorageName) - Method in class adams.flow.transformer.WekaFilter

Sets the filter storage item.

setModified(boolean) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Sets whether the data has been modified.

setModified(boolean) - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer

Sets whether the data has been modified.

setModified(boolean) - Method in class adams.gui.tools.wekainvestigator.data.FileContainer

Sets whether the data has been modified.

setModified(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel

Sets the modified state.

setMorphologies(PredictionEccentricity.Morphology[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Sets the morphologies to apply.

setMultiplier(double) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev

Sets the multiplier for the stdev.

setN(int) - Method in class weka.core.SAXDistance

Sets the nth point setting.

setN(int) - Method in class weka.filters.supervised.attribute.YGradientEPO

Sets the number of eigenvectors to keep.

setName(String) - Method in class adams.data.weka.classattribute.ByExactName

Sets the name to use.

setName(String) - Method in class adams.data.weka.columnfinder.ByExactName

Sets the name to use.

setName(String) - Method in class adams.ml.data.InstancesView

Sets the name of the spreadsheet.

setNames(BaseString[]) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Sets the names to use for the fusion subsets (corresponds to the subsets).

setNameServer(BaseHostname) - Method in class weka.classifiers.functions.PyroProxy

Sets the address of the Pyro nameserver.

setNameServer(BaseHostname) - Method in interface weka.core.PyroProxyObject

Sets the address of the Pyro nameserver.

setNameSuffix(String) - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem

Sets the optional name suffix.

setNative(Object) - Method in class adams.ml.data.DataCellView

Determines the best set-method based on the class of the provided object.

setNearestNeighbourSearchAlgorithm(NearestNeighbourSearch) - Method in class weka.classifiers.lazy.LWLSynchroSplit

Sets the nearestNeighbourSearch algorithm to be used for finding nearest neighbour(s).

setNearestNeighbourSearchAlgorithm(NearestNeighbourSearch) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Sets the nearestNeighbourSearch algorithm to be used for finding nearest neighbour(s).

setNewFilter(Filter) - Method in class adams.data.conversion.SwapPLS

Sets the new PLS filter to replace with.

setNoAdditionalFieldsPrefix(boolean) - Method in interface adams.data.instances.InstanceGeneratorWithAdditionalFields

Sets whether to drop the prefix for the additional fields.

setNoCheck(boolean) - Method in class adams.flow.transformer.WekaExperiment

Sets whether to avoid the check at setUp time whether the experiment file is present or not.

setNoCleanUp(boolean) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

Sets whether to suppress automatic clean ups.

setNoise(double) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Set the level of Gaussian Noise.

setNoise(double) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Set the level of Gaussian Noise.

setNoise(double) - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Set the level of Gaussian Noise.

setNoise(double) - Method in class weka.classifiers.functions.GPD

Set the level of Gaussian Noise.

setNominal(boolean) - Method in class weka.filters.unsupervised.attribute.SAX

Sets whether to output nominal or numeric values.

setNonInteractive(boolean) - Method in class adams.flow.source.WekaSelectDataset

Sets whether to enable/disable interactiveness.

setNonInteractive(boolean) - Method in class adams.flow.transformer.WekaChooseAttributes

Sets whether to enable/disable interactiveness.

setNoReplacement(boolean) - Method in class weka.classifiers.meta.VotedImbalance

Sets whether instances are drawn with or with out replacement.

setNormaliseType(XGBoost.NormaliseType) - Method in class weka.classifiers.trees.XGBoost

Sets the type of normalisation algorithm.

setNormalize(boolean) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Sets whether to normalize the data before generating the histogram.

setNormalPlotOptions(NormalPlotOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Set the options for the normal plot.

setNormYWeights(boolean) - Method in class adams.data.instancesanalysis.pls.NIPALS

Sets whether to normalize Y weights.

setNotes(BaseText) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets the notes for the experiment.

setNotificationEnabled(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel

sets whether the notification of changes is enabled

setNoUpdate(boolean) - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Sets whether to suppress updating the nearest-neighbor search algorithm when making predictions.

setNoUpdate(boolean) - Method in class weka.classifiers.lazy.LWLSynchro

Sets whether to suppress updating the nearest-neighbor search algorithm when making predictions.

setNoUpdate(boolean) - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

Sets whether to suppress updating the nearest-neighbor search algorithm when making predictions.

setNoUpdate(boolean) - Method in class weka.classifiers.lazy.LWLSynchroSplit

Sets whether to suppress updating the nearest-neighbor search algorithm when making predictions.

setNoUpdate(boolean) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Sets whether to suppress updating the nearest-neighbor search algorithm when making predictions.

setNthPoint(int) - Method in class weka.filters.unsupervised.attribute.DownSample

Sets the nth point setting.

setNumattrs(int) - Method in class weka.classifiers.meta.Corr

setNumBalanced(int) - Method in class weka.classifiers.meta.VotedImbalance

Set the number of balanced datasets to generated (= #classifiers).

setNumberInSubset(int) - Method in class weka.filters.unsupervised.instance.KennardStone

Sets the number of rws to select in subset.

setNumberOfParallelTrees(int) - Method in class weka.classifiers.trees.XGBoost

Sets the number of parallel trees constructed during each iteration.

setNumberOfRounds(int) - Method in class weka.classifiers.trees.XGBoost

Sets the number of boosting rounds to perform.

setNumBins(int) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Sets the number of bins to use in manual calculation.

setNumChrom(int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Sets the number of chromosomes to use.

setNumClusters(int) - Method in class weka.clusterers.SAXKMeans

set the number of clusters to generate.

setNumCoefficients(int) - Method in class adams.data.instancesanalysis.pls.SIMPLS

Sets the number of coefficients of W matrix to keep (rest gets zeroed).

setNumComponents(int) - Method in class adams.data.instancesanalysis.pls.AbstractPLS

sets the maximum number of attributes to use.

setNumComponents(int) - Method in class weka.attributeSelection.AbstractPLSAttributeEval

sets the maximum number of attributes to use.

setNumComponents(int) - Method in class weka.core.neighboursearch.PLSNNSearch

setNumComponents(Object, int) - Method in class adams.data.conversion.SwapPLS

Sets the number of components in the filter.

setNumCycles(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity

Sets the number of cycles to apply.

setNumDecimals(int) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Sets the number of decimals to show in the bin description.

setNumDecimals(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Sets the number of decimals to display.

setNumDecimals(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Sets the number of decimals to use for numeric values.

setNumDecimals(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Sets the number of decimals to use for numeric values.

setNumEvaluationBins(int) - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Sets the number of bints to use during evaluation.

setNumExecutionSlots(int) - Method in class weka.classifiers.meta.SubsetEnsemble

Set the number of execution slots (threads) to use for building the members of the ensemble.

setNumExecutionSlots(int) - Method in class weka.classifiers.meta.VotedImbalance

Set the number of execution slots (threads) to use for building the members of the ensemble.

setNumExecutionSlots(int) - Method in class weka.clusterers.SAXKMeans

Set the degree of parallelism to use.

setNumFolds(int) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Sets the number of folds to use.

setNumFolds(int) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Sets the number of folds to use.

setNumFolds(int) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Sets the number of folds to use.

setNumFolds(int) - Method in interface weka.classifiers.CrossValidationFoldGenerator

Sets the number of folds to use.

setNumFolds(int) - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Sets the number of folds to use.

setNumFolds(int) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Sets the number of folds to use.

setNumFolds(int) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Sets the number of folds to use.

setNumFolds(int) - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Sets the number of folds to use.

setNumFolds(int) - Method in class weka.classifiers.meta.ClassifierCascade

the number of folds for cross-validation.

setNumFolds(int) - Method in class weka.filters.supervised.instance.RemoveOutliers

Sets the number of folds to use.

setNumFolds(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Sets the number of cross-validation folds to use - < 2 means no cross-validation.

setNumFolds(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Sets the number of cross-validation folds to use - < 2 means no cross-validation.

setNumIterations(int) - Method in class weka.classifiers.trees.RandomModelTrees

Sets the number of iterations.

setNumIterations(int) - Method in class weka.classifiers.trees.RandomRegressionForest

Sets the number of iterations

setNumPoints(int) - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

Sets the number of points to generate.

setNumPoints(int) - Method in class weka.filters.unsupervised.attribute.EquiDistance

Sets the number of points to use.

setNumPoints(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Sets the number of points to the left of a data point.

setNumPointsLeft(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Sets the number of points to the left of a data point.

setNumPointsRight(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Sets the number of points to the right of a data point.

setNumRandomFeatures(int) - Method in class weka.classifiers.meta.SubsetEnsemble

Set the number of additional random features to use.

setNumRegressions(int) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

sets number of samples

setNumRegressions(int) - Method in class weka.classifiers.meta.LeastMedianSq

sets number of samples

setNumRows(int) - Method in class adams.data.conversion.WekaCapabilitiesToInstances

Sets the number of data rows to generate.

setNumSimplsCoefficients(int) - Method in class adams.data.instancesanalysis.pls.PRM

Sets the number of SIMPLS coefficients to keep.

setNumSubSamples(int) - Method in class adams.flow.transformer.WekaBootstrapping

Sets the number sub-samples to generate.

setNumThreads(int) - Method in class adams.flow.transformer.WekaClassifierRanker

Sets the number of threads to use.

setNumThreads(int) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Sets the number of threads to use for cross-validation.

setNumThreads(int) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Sets the number of threads to use for cross-validation.

setNumThreads(int) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets the number of threads to use for cross-validation (only used if no JobRunnerSetup/JobRunner set).

setNumThreads(int) - Method in class weka.classifiers.meta.ClassifierCascade

the number of threads to use.

setNumThreads(int) - Method in class weka.classifiers.trees.XGBoost

Sets the number of parallel threads used to run XGBoost.

setNumThreads(int) - Method in class weka.filters.supervised.instance.RemoveOutliers

Sets the number of threads to use for cross-validation.

setNumZeroes(double) - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Sets the number of zeroes a row must have at least in order to be removed.

setObject(Object) - Method in class adams.ml.data.DataCellView

Ignored.

setObjective(XGBoost.Objective) - Method in class weka.classifiers.trees.XGBoost

Sets the learning objective.

setOffline(boolean) - Method in class adams.data.instances.AbstractInstanceGenerator

Sets whether to operate in offline mode.

setOldFilter(Filter) - Method in class adams.data.conversion.SwapPLS

Sets the old PLS filter to replace.

setOneDrop(boolean) - Method in class weka.classifiers.trees.XGBoost

Sets whether at least one tree is always dropped during the dropout.

setOneMissing(SelectedTag) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Sets the type of strategy to apply if one of the values is missing.

setOneMissing(SelectedTag) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Sets the type of strategy to apply if one of the values is missing.

setOnlyFirstBatch(boolean) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Set whether to apply row finder during first batch.

setOnTheFly(boolean) - Method in class adams.flow.condition.bool.WekaClassification

Sets whether the model file gets built on the fly and might not be present at start up time.

setOnTheFly(boolean) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Sets whether the model file gets built on the fly and might not be present at start up time.

setOnTheFly(boolean) - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Sets whether the reference file gets built on the fly and might not be present at start up time.

setOperation(WekaInstanceBuffer.Operation) - Method in class adams.flow.transformer.WekaInstanceBuffer

Sets the way the buffer operates.

setOptimizer(Classifier) - Method in class adams.flow.transformer.WekaClassifierOptimizer

Sets the optimizer to use.

setOptional(boolean) - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Sets whether the callable sink is optional.

setOptions(Object, String[]) - Method in class adams.core.option.WekaCommandLineHandler

Sets the options of the specified object.

setOptions(String[]) - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.attributeSelection.LinearRegressionAttributeEval

setOptions(String[]) - Method in class weka.classifiers.functions.ClassificationViaPLS

Parses the options for this object.

setOptions(String[]) - Method in class weka.classifiers.functions.FakeClassifier

Parses the options for this object.

setOptions(String[]) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.GeneticAlgorithm

Parses the options for this object.

setOptions(String[]) - Method in class weka.classifiers.functions.GPD

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.LinearRegressionJ

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.functions.MathExpressionClassifier

Parses the options for this object.

setOptions(String[]) - Method in class weka.classifiers.functions.PLSClassifierWeighted

Parses the options for this object.

setOptions(String[]) - Method in class weka.classifiers.functions.PLSWeighted

Parses the options for this object.

setOptions(String[]) - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.lazy.LWLSynchro

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.lazy.LWLSynchroSplit

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.AbstainAttributePercentile

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.AbstainAverage

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.AbstainingCascade

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.AbstainMinimumProbability

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.AbstainVote

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.ClassifierCascade

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.Consensus

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.ConsensusOrVote

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.Corr

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.Fallback

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.FilteredClassifierExt

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.HighLowSplit

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.InputSmearing

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.LeastMedianSq

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.MinMaxLimits

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.PartitionedStacking

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.SocketFacade

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.SubsetEnsemble

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.meta.SuppressModelOutput

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.Veto

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.classifiers.meta.VotedImbalance

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.m5.M5Base2

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.M5P2

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.RandomModelTrees

Parses a given list of options.

setOptions(String[]) - Method in class weka.classifiers.trees.RandomRegressionForest

Parses a given list of options.

setOptions(String[]) - Method in class weka.clusterers.SAXKMeans

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.AbstractSimpleOptionHandler

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.core.converters.SimpleArffLoader

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.core.converters.SimpleArffSaver

Parses the options for this object.

setOptions(String[]) - Method in class weka.core.converters.SpreadSheetLoader

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.converters.SpreadSheetSaver

Parses the options for this object.

setOptions(String[]) - Method in class weka.core.neighboursearch.FilteredSearch

setOptions(String[]) - Method in class weka.core.neighboursearch.NewNNSearch

Parses a given list of options.

setOptions(String[]) - Method in class weka.core.neighboursearch.PCANNSearch

setOptions(String[]) - Method in class weka.core.neighboursearch.PLSNNSearch

setOptions(String[]) - Method in class weka.core.SAXDistance

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.core.tokenizers.cleaners.AbstractTokenCleaner

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.core.tokenizers.cleaners.MultiCleaner

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.core.tokenizers.MultiTokenizer

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.core.tokenizers.PreCleanedTokenizer

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.core.WeightedEuclideanDistanceRidge

Parses a given list of options.

setOptions(String[]) - Method in class weka.experiment.ResultMatrixMediaWiki

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.filters.FilteredFilter

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.FlowFilter

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.SerializedFilter

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.MultiPLS

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.PLS

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.YGradientEPO

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.supervised.attribute.YGradientGLSW

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.supervised.instance.RemoveOutliers

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AndrewsCurves

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AnyToString

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Detrend

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.DownSample

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.EquiDistance

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.FastWavelet

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.FFT

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.InputSmearing

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.JoinAttributes

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.LogTransform

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PAA

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SAX

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SetMissingValue

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SimpleDetrend

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SpellChecker

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.StringToDate

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.AlignDataset

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.DatasetLabeler

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.KeepRange

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.KennardStone

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.LatestRecords

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin

Sets the OptionHandler's options using the given list.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue

Parses the options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveWithWeights

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes

Parses a list of options for this object.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.SafeRemoveRange

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.Scale

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.Sort

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.SortOnAttribute

Parses a given list of options.

setOptions(String[]) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Parses a list of options for this object.

setOtherParameters(BaseKeyValuePair[]) - Method in class weka.classifiers.trees.XGBoost

Sets any additional XGBoost parameters.

setOutput(AbstractWekaRepeatedCrossValidationOutput) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput

Sets the output generator to use.

setOutput(AbstractOutput) - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Sets the prediction output generator to use.

setOutput(AbstractOutput) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets the prediction output generator to use.

setOutputAdditionalStats(boolean) - Method in class weka.attributeSelection.LinearRegressionAttributeEval

Set whether to output additional statistics (such as std.

setOutputAdditionalStats(boolean) - Method in class weka.classifiers.functions.LinearRegressionJ

Set whether to output additional statistics (such as std.

setOutputAdditionalStats(boolean) - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Set whether to output additional statistics (such as std.

setOutputArray(boolean) - Method in class adams.flow.source.AbstractWekaSetupGenerator

Sets whether to output an array or a sequence of classifier setups.

setOutputBestSetup(boolean) - Method in class adams.flow.transformer.WekaClassifierRanker

Sets whether to output the best setup found for optimizers like GridSearch and MultiSearch.

setOutputContainer(boolean) - Method in class adams.flow.transformer.WekaFilter

Sets whether to output a container with the filter alongside the filtered data or just the filtered data.

setOutputDirectory(PlaceholderDirectory) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the directory for the generated ARFF files.

setOutputDirectory(PlaceholderDirectory) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction

Sets the directory for the generated ARFF files.

setOutputDistribution(boolean) - Method in class adams.flow.transformer.wekaclusterer.AddCluster

Sets whether to output the cluster distribution instead of the cluster index.

setOutputFile(PlaceholderFile) - Method in class adams.flow.sink.WekaExperimentGenerator

Sets the file to store the experiment setup in (the extensions determines the type).

setOutputFile(PlaceholderFile) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Set output file.

setOutputFile(PlaceholderFile) - Method in class adams.tools.CompareDatasets

Sets the first dataset for the comparison.

setOutputFormat(ListPackages.OutputFormat) - Method in class adams.flow.source.wekapackagemanageraction.ListPackages

Sets the type of output format to generate.

setOutputFormat(WekaInstanceDumper.OutputFormat) - Method in class adams.flow.transformer.WekaInstanceDumper

Sets the output format.

setOutputFormat(ResultMatrix) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Sets the output format to use for generating the output.

setOutputFormat(ResultMatrix) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Sets the output format to use for generating the output.

setOutputGenerator(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem

Sets the output generator.

setOutputGenerators(AbstractOutputGenerator[]) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Sets the output generators to use.

setOutputGenerators(AbstractOutputGenerator[]) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Sets the output generators to use.

setOutputGenerators(AbstractOutputGenerator[]) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Sets the output generators to use.

setOutputGenerators(AbstractOutputGenerator[]) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Sets the output generators to use.

setOutputGenerators(AbstractOutputGenerator[]) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Sets the output generators to use.

setOutputHeader(boolean) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Sets whether to output the header of the result matrix as well.

setOutputHeader(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Sets whether to output the header of the result matrix as well.

setOutputIndices(boolean) - Method in class adams.flow.transformer.WekaAttributeIterator

Sets whether to output 1-based indices of matches instead of the names.

setOutputInstance(boolean) - Method in class adams.flow.transformer.WekaClassifying

Sets whether to output Instance objects instead of PredictionContainer ones.

setOutputModel(boolean) - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Sets whether to output the clusterer model as well.

setOutputModel(boolean) - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

Sets whether to output the clusterer model as well.

setOutputName(String) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Sets the name to use for the merged dataset.

setOutputOnlyModel(boolean) - Method in class adams.flow.transformer.AbstractWekaModelReader

Sets whether to output only the model instead of the container.

setOutputPrefix(PlaceholderFile) - Method in class adams.flow.transformer.WekaInstanceDumper

Sets the prefix for the output (path + partial filename).

setOutputPrefixType(OutputPrefixType) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the type of prefix to use for the output.

setOutputRelationName(boolean) - Method in class adams.flow.transformer.WekaEvaluationSummary

Sets whether to output the relation name as well.

setOutputType(WekaFileReader.OutputType) - Method in class adams.flow.transformer.WekaFileReader

Sets how to output the data.

setOutputType(OutputType) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the type of output to generate.

setOverlays(XYSequencePaintlet[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets the overlays to use in the plot.

setOverride(boolean) - Method in class adams.flow.transformer.WekaClassSelector

Sets whether to override any existing class index or nor.

setOverrideJobRunner(boolean) - Method in class adams.flow.transformer.WekaExperimentExecution

Sets whether to override the jobrunner of the experiment.

setOwner(Row) - Method in class adams.ml.data.DataCellView

Sets the row this cell belongs to.

setOwner(SpreadSheet) - Method in class adams.ml.data.InstancesHeaderRow

Sets the spreadsheet this row belongs to.

setOwner(SpreadSheet) - Method in class adams.ml.data.InstanceView

Sets the spreadsheet this row belongs to.

setOwner(InvestigatorPanel) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource

Sets the owner for this source.

setOwner(InvestigatorPanel) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Sets the owner for this tab.

setOwner(InvestigatorPanel) - Method in class adams.gui.tools.wekainvestigator.tab.LogTab

Sets the owner for this tab.

setOwner(AbstractInvestigatorTabWithEditableDataTable) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Sets the owner.

setOwner(PreprocessTab) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Sets the owner.

setOwner(ExperimenterPanel) - Method in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel

Sets the experimenter this panel belongs to.

setOwner(AbstractSetupPanel) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

Sets the setup panel this option panel belongs to.

setOwner(AbstractSetupPanel) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel

Sets the setup panel this option panel belongs to.

setOwner(AbstractClassifierBasedGeneticAlgorithm) - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot

Sets the owner for the plot.

setOwner(T) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Sets the owner.

setOwner(T) - Method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem

Sets the owner.

setPadding(SelectedTag) - Method in class weka.filters.unsupervised.attribute.FastWavelet

Sets the type of Padding to use.

setPaintlet(AbstractInstancePaintlet) - Method in class adams.flow.sink.WekaInstanceViewer

Sets the paintlet to use.

setPaintlet(XYSequencePaintlet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend

Sets the paintlet to use for the plot.

setPaintlet(XYSequencePaintlet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Sets the paintlet to use.

setPanel(BasePanel) - Method in class weka.gui.explorer.ExplorerEntryPanel

Sets the panel to display the results in.

setParameters(AbstractParameter[]) - Method in class adams.flow.source.AbstractWekaSetupGenerator

Sets the setup parameters.

setParentComponentActor(CallableActorReference) - Method in class adams.flow.source.WekaSelectDataset

Sets the (optional) callable actor to use as parent component instead of the flow panel.

setParentTitle(String) - Method in class weka.gui.explorer.ExplorerExt

Sets the new title for the parent.

setPassword(BasePassword) - Method in class adams.flow.sink.WekaDatabaseWriter

Sets the database password.

setPassword(BasePassword) - Method in class adams.flow.source.WekaDatabaseReader

Sets the database password.

setPct(int) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

setPct(int) - Method in class weka.classifiers.meta.LeastMedianSq

setPercent(double) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst

Sets the percentage to remove.

setPercentage(double) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Sets the split percentage.

setPercentage(double) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Sets the split percentage.

setPercentage(double) - Method in class adams.flow.transformer.WekaBootstrapping

Sets the percentage (0-1).

setPercentage(double) - Method in class adams.flow.transformer.WekaRandomSplit

Sets the percentage (0-1).

setPercentage(double) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Sets the split percentage.

setPercentage(double) - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Sets the split percentage.

setPercentage(double) - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Sets the split percentage.

setPercentage(double) - Method in class weka.classifiers.DefaultRandomSplitGenerator

Sets the split percentage.

setPercentage(double) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Sets the split percentage.

setPercentage(double) - Method in class weka.classifiers.GroupedRandomSplitGenerator

Sets the split percentage.

setPercentage(double) - Method in interface weka.classifiers.RandomSplitGenerator

Sets the split percentage.

setPercentile(double) - Method in class weka.classifiers.meta.AbstainAttributePercentile

setPercentiles(BaseDouble[]) - Method in class adams.flow.transformer.WekaBootstrapping

Sets the percentiles to calculate for the errors.

setPerformTraining(boolean) - Method in class weka.classifiers.functions.PyroProxy

Sets whether to train the model as well.

setPlotName(String) - Method in class adams.flow.transformer.WekaAccumulatedError

Sets the plot name.

setPLS(int) - Method in class weka.classifiers.trees.RandomRegressionForest

Sets the number of PLS components to generate.

setPolynomialOrder(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay

Sets the polynomial order.

setPolynomialOrder(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2

Sets the polynomial order.

setPostProcessor(AbstractClustererPostProcessor) - Method in class adams.flow.transformer.WekaClustererPostProcessor

Sets the post-processor to use.

setPostProcessor(AbstractClustererPostProcessor) - Method in class adams.flow.transformer.WekaTrainClusterer

Sets the post-processor to use.

setPostProcessor(AbstractWekaEvaluationPostProcessor) - Method in class adams.flow.transformer.WekaEvaluationPostProcessor

Sets the post-processor to use.

setPostProcessors(AbstractClustererPostProcessor[]) - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor

Sets the distance function to use.

setPostProcessors(AbstractWekaEvaluationPostProcessor[]) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor

Sets the post-processors to use.

setPostTokenizer(Tokenizer) - Method in class weka.core.tokenizers.PreCleanedTokenizer

Sets the tokenizer to use for the final tokenization (after cleaning).

setPredicted(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Sets the column with the predicted values.

setPredicted(SpreadSheetColumnIndex) - Method in class weka.classifiers.functions.FromPredictions

Sets the column with the predicted values.

setPredictedMax(double) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets the upper limit in use for the predicted values.

setPredictedMin(double) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets the lower limit in use for the predicted values.

setPredictionsFile(PlaceholderFile) - Method in class weka.classifiers.functions.FromPredictions

Sets the file with the predictions.

setPredictionType(PredictionType) - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Sets the type of prediction to perform.

setPredictMax(double) - Method in class weka.classifiers.functions.FakeClassifier

Sets the maximum value to predict.

setPredictMin(double) - Method in class weka.classifiers.functions.FakeClassifier

Sets the minimum value to predict.

setPredictor(Index) - Method in class weka.classifiers.meta.Consensus

Sets the index of the classifier for making the actual predictions.

setPredictor(XGBoost.Predictor) - Method in class weka.classifiers.trees.XGBoost

Sets the type of predictor algorithm to use.

setPredictWait(int) - Method in class weka.classifiers.functions.FakeClassifier

Sets the time in msec to wait when calling classifyInstance.

setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaFilter

Sets whether to offload processing to a JobRunner instance if available.

setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaTestSetEvaluator

Sets whether to offload processing to a JobRunner instance if available.

setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaTrainAssociator

Sets whether to offload processing to a JobRunner instance if available.

setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaTrainClassifier

Sets whether to offload processing to a JobRunner instance if available.

setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaTrainClusterer

Sets whether to offload processing to a JobRunner instance if available.

setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator

Sets whether to offload processing to a JobRunner instance if available.

setPreFilter(Filter) - Method in class adams.data.weka.rowfinder.FilteredIQR

Sets the pre filter.

setPreFilter(Filter) - Method in class weka.filters.FilteredFilter

Sets the pre-filter to use.

setPreFilter(Filter) - Method in class weka.filters.unsupervised.instance.KennardStone

Sets the pre-filter to apply to the data to perform the search on.

setPrefix(String) - Method in class adams.flow.transformer.WekaInstancesMerge

Sets the optional prefix string.

setPrefix(String) - Method in class weka.filters.unsupervised.attribute.EquiDistance

Sets the prefix for the new attributes.

setPrefixDatasetsWithIndex(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets whether to prefix the datasets with the index.

setPrefixDatasetsWithIndex(boolean) - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ExperimentWithCustomizableRelationNames

Sets whether to prefix the datasets with the index.

setPrefixDatasetsWithIndex(boolean) - Method in class weka.experiment.ExtExperiment

Sets whether to prefix the datasets with the index.

setPrefixes(BaseString[]) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Sets the list of prefixes to use.

setPrefixes(BaseString[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Sets the list of prefixes to use.

setPrefixSeparator(String) - Method in class adams.flow.transformer.WekaInstancesMerge

Sets the prefix separator string.

setPreparation(AbstractDataPreparation) - Method in class weka.classifiers.meta.SocketFacade

Sets the data preparation scheme to use.

setPreprocessing(SelectedTag) - Method in class weka.core.neighboursearch.PCANNSearch

Sets the type of preprocessing to use

setPreprocessing(SelectedTag) - Method in class weka.core.neighboursearch.PLSNNSearch

Sets the type of preprocessing to use

setPreprocessingType(PreprocessingType) - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Sets the type of preprocessing to perform.

setPreprocessingType(PreprocessingType) - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Sets the type of preprocessing to perform.

setPreSelection(BaseRegExp) - Method in class adams.flow.transformer.WekaChooseAttributes

Sets the regular expression to pre-select attributes for the dialog.

setPreserveIDColumn(boolean) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Sets whether the first non-summary attribute should be treated as an ID and moved to the first attribute position.

setPreserveInstancesOrder(boolean) - Method in class weka.clusterers.SAXKMeans

Sets whether order of instances must be preserved.

setPreserveOrder(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Sets whether to preserve the order.

setPreserveOrder(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Sets whether to preserve the order.

setPreserveOrder(boolean) - Method in class adams.flow.transformer.WekaRandomSplit

Sets whether to preserve order and suppress randomization.

setPreserveOrder(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

Sets whether to preserve the order.

setPreserveOrder(boolean) - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator

Sets whether to preserve the order.

setPreserveOrder(boolean) - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Sets whether to preserve the order.

setPreserveOrder(boolean) - Method in class weka.classifiers.DefaultRandomSplitGenerator

Sets whether to preserve the order.

setPreserveOrder(boolean) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Sets whether to preserve the order.

setPreserveOrder(boolean) - Method in class weka.classifiers.GroupedRandomSplitGenerator

Sets whether to preserve the order.

setPreserveOrder(boolean) - Method in interface weka.classifiers.RandomSplitGenerator

Sets whether to preserve the order.

setPreTokenizer(Tokenizer) - Method in class weka.core.tokenizers.PreCleanedTokenizer

Sets the tokenizer to use for the initial tokenization (before cleaning).

setProcessor(AbstractClassifierSetupProcessor) - Method in class adams.flow.transformer.WekaClassifierSetupProcessor

Sets the processor the incoming classifier arrays.

setProcessType(XGBoost.ProcessType) - Method in class weka.classifiers.trees.XGBoost

Sets the type of boosting process to run.

setProperties(Properties) - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

Sets the properties to base the properties on.

setProperties(Properties) - Method in class adams.gui.wizard.WekaSelectDatasetPage

Sets the content of the page (ie parameters) as properties.

setProperties(Properties) - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

Sets the content of the page (ie parameters) as properties.

setProperty(String) - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Sets the property to manage.

setProperty(String) - Method in class adams.core.discovery.genetic.GenericFloatResolution

Sets the property to manage.

setProperty(String) - Method in class adams.core.discovery.genetic.GenericInteger

Sets the property to manage.

setProperty(String) - Method in class adams.core.discovery.genetic.GenericString

Sets the property to manage.

setQuery(SQLStatement) - Method in class adams.flow.source.WekaDatabaseReader

Sets the query to execute.

setRandomize(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Sets whether to randomize the data.

setRandomize(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Sets whether to randomize the data.

setRandomize(boolean) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Sets whether to randomize the data.

setRandomize(boolean) - Method in interface weka.classifiers.CrossValidationFoldGenerator

Sets whether to randomize the data.

setRandomize(boolean) - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Sets whether to randomize the data.

setRandomize(boolean) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Sets whether to randomize the data.

setRandomize(boolean) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Sets whether to randomize the data.

setRandomize(boolean) - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Sets whether to randomize the data.

setRandomize(boolean) - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Sets whether to randomize the data.

setRandomize(boolean) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Sets whether to include the class attribute in the comparison.

setRandomSeed(long) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Set the seed for the random number generator

setRandomSeed(long) - Method in class weka.classifiers.meta.LeastMedianSq

Set the seed for the random number generator

setRange(Range) - Method in class adams.flow.transformer.WekaAttributeIterator

Sets the range of attributes to operate on.

setRange(Range) - Method in class weka.filters.unsupervised.attribute.EquiDistance

Sets the attribute range.

setRange(WekaAttributeRange) - Method in class adams.flow.sink.WekaAttributeSummary

Sets the ranges of attributes to visualize.

setRange(WekaAttributeRange) - Method in class weka.filters.unsupervised.attribute.AnyToString

Sets the attribute range to use.

setRange(WekaAttributeRange) - Method in class weka.filters.unsupervised.attribute.StringToDate

Sets the first attribute range to use (regular expression on attribute names).

setRange(WekaAttributeRange) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor

Sets the attribute range to work on.

setRange(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer

Sets the range of attributes to use.

setRange1(Range) - Method in class adams.tools.CompareDatasets

Sets the range of attributes of the first dataset.

setRange2(Range) - Method in class adams.tools.CompareDatasets

Sets the range of attributes of the second dataset.

setRangePaintlet(AbstractErrorPaintlet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Sets the paintlet to use for the lower/upper statistics.

setRanges(BaseInterval[]) - Method in class adams.data.weka.rowfinder.ByNumericRange

Sets the intervals.

setRanges(BaseInterval[]) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange

Sets the ranges to include.

setRanges(BaseInterval[]) - Method in class weka.filters.unsupervised.attribute.detrend.RangeBased

Sets the wave number ranges.

setRanges(BaseInterval[]) - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased

Sets the wave number ranges.

setRanges(Range[]) - Method in class weka.classifiers.meta.PartitionedStacking

Sets the attribute ranges for the base-classifiers.

setRanges(Range[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Sets the list of possible Ranges to choose from.

setRateDrop(float) - Method in class weka.classifiers.trees.XGBoost

Sets the dropout rate (a fraction of previous trees to drop during the dropout).

setReader(SpreadSheetReader) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Sets the spreadsheet reader to use.

setReader(SpreadSheetReader) - Method in class weka.classifiers.functions.FromPredictions

Sets the spreadsheet reader to use.

setReader(SpreadSheetReader) - Method in class weka.core.converters.SpreadSheetLoader

Sets the spreadsheet reader to use.

setReadOnly(boolean) - Method in class adams.gui.visualization.instances.InstancesTable

sets whether the model is read-only

setReadOnly(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel

sets whether the model is read-only

setReal(boolean) - Method in class weka.filters.unsupervised.attribute.FFT

Sets whether to return real or imaginary part.

setReduceNumberOfDistanceCalcsViaCanopies(boolean) - Method in class weka.clusterers.SAXKMeans

Set whether to use canopies to reduce the number of distance computations required

setReferenceActor(CallableActorReference) - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Sets the callable actor to obtain the reference dataset from if reference file is pointing to a directory.

setReferenceDataset(File) - Method in class weka.filters.unsupervised.instance.AlignDataset

Sets the file containing the reference dataset.

setReferenceError(double) - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference

Sets the absolute value of the reference error.

setReferenceFile(PlaceholderFile) - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Sets the file to load the reference dataset from.

setReferenceSize(int) - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference

Sets the size for the reference error.

setRegex(String) - Method in class adams.flow.transformer.WekaRegexToRange

Sets the regular expression for attribute matching.

setRegexName(BaseRegExp) - Method in class adams.flow.transformer.WekaClassSelector

Sets the regular expression for selecting the attributes.

setRegExp(BaseRegExp) - Method in class adams.data.weka.classattribute.ByName

Sets the index of the attribute to select.

setRegExp(BaseRegExp) - Method in class adams.data.weka.columnfinder.ByName

Sets the regular expression to use.

setRegExp(BaseRegExp) - Method in class adams.data.weka.rowfinder.ByLabel

Sets the regular expression to use.

setRegExp(BaseRegExp) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

setRegExp(BaseRegExp) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

setRegExp(BaseRegExp) - Method in class adams.flow.transformer.WekaAttributeIterator

Sets the regular expression for the names.

setRegExp(BaseRegExp) - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Sets the regular expression to match the strings against.

setRegExp(BaseRegExp) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

setRegExp(BaseRegExp) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

setRegExp(BaseRegExp) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

setRegExp(BaseRegExp) - Method in class weka.classifiers.GroupedRandomSplitGenerator

Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

setRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.EquiDistance

Sets the regular expression for identifying attributes.

setRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression

Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').

setRegExp(BaseRegExp[]) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Sets the list of possible regular expressions.

setRegExps(BaseRegExp[]) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Sets the regular expression to apply to the attribute names for identifying the fusion subsets (incl class).

setRegExps(BaseRegExp[]) - Method in class weka.classifiers.MultiLevelSplitGenerator

Sets the regular expressions to use for extracting the groups.

setRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.Rule2

Set the value of regressionTree.

setRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.RuleNode2

Set the value of regressionTree.

setRelationName(String) - Method in class adams.flow.source.WekaNewInstances

Sets the name of the relation.

setRelationName(String) - Method in class adams.flow.transformer.WekaCrossValidationSplit

Sets the pattern to use for renaming the relation.

setRelationName(String) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Sets the template for the relation name.

setRelationName(String) - Method in interface weka.classifiers.CrossValidationFoldGenerator

Sets the template for the relation name.

setRelationName(String) - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Sets the template for the relation name.

setRelationName(String) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Sets the template for the relation name.

setRelationName(String) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Sets the template for the relation name.

setRelationName(String) - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Sets the template for the relation name.

setRelationName(String) - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Sets the template for the relation name.

setRelationNameHeuristic(AbstractRelationNameHeuristic) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Sets the relation name heuristic.

setRelativeWidths(boolean) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased

Sets whether to divide the calculated widths by the class value.

setRemote(BaseHostname) - Method in class weka.classifiers.meta.SocketFacade

Sets address of the remote process.

setRemoteObjectName(String) - Method in class weka.classifiers.functions.PyroProxy

Sets the name of the remote object to use.

setRemoteObjectName(String) - Method in interface weka.core.PyroProxyObject

Sets the name of the remote object to use.

setRemove(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge

Sets whether to remove if not all present

setRemoveAttributeIndices(String) - Method in class weka.classifiers.meta.FilteredClassifierExt

Sets the attribute indices to remove before applying the actual filter.

setRemoveChars(String) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes

Sets the characters to remove from start/end of the generated name.

setRemoveChars(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Sets the characters to remove from start/end of the generated name.

setRemoveTrain(boolean) - Method in class weka.classifiers.meta.AbstainAttributePercentile

setRemoveUnused(boolean) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter

Sets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.

setRemoveUnused(boolean) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

Sets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.

setReplace(String) - Method in class adams.flow.transformer.WekaRenameRelation

Sets the replacement string.

setReplace(String) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Sets the expression to use for assembling the numeric part.

setReplaceMissing(boolean) - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Sets whether to replace missing values.

setReplaceMissing(boolean) - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Sets whether to replace missing values.

setReport(Report) - Method in class adams.data.instance.Instance

Sets a new report.

setResetResults(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets whether to clear the results before starting the experiment.

setResetResults(boolean) - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ResettableExperiment

Sets whether to clear the results before starting the experiment.

setResultFile(PlaceholderFile) - Method in class adams.flow.sink.WekaExperimentGenerator

Sets the file to store the experimental results in.

setResultFormat(WekaExperimentGenerator.ResultFormat) - Method in class adams.flow.sink.WekaExperimentGenerator

Sets the data format the results are stored in.

setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel

Sets the ResultListener.

setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel

Sets the ResultListener.

setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel

Sets the ResultListener.

setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel

Sets the ResultListener.

setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel

Sets the ResultListener.

setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel

Sets the ResultListener.

setResultMatrix(ResultMatrix) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Sets the matrix to use.

setResults(Instances) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

Sets the results to analyze.

setResults(Instances) - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

Sets the results to use for analysis.

setResultsHandler(AbstractResultsHandler) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets the results handler to use.

setRetainStringValues(boolean) - Method in class weka.core.converters.AArffLoader.AArffReader

Sets whether to retain string values (safe) or not.

setReverse(boolean) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Sets whether to reverse the sorting.

setReverse(boolean) - Method in class weka.classifiers.AggregateEvaluations

Sets whether to reverse the sorting.

setRidge(double) - Method in class adams.data.baseline.AbstractLinearRegressionBased

Sets the ridge parameter.

setRidge(double) - Method in class weka.attributeSelection.LinearRegressionAttributeEval

Set the value of Ridge.

setRidge(double) - Method in class weka.classifiers.functions.LinearRegressionJ

Set the value of Ridge.

setRidge(double) - Method in class weka.classifiers.trees.RandomModelTrees

setRidge(double) - Method in class weka.core.WeightedEuclideanDistanceRidge

Set the value of Ridge.

setRow(BaseString[]) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Sets the list of fields that identify a row.

setRow(BaseString[]) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Sets the list of fields that identify a row.

setRow(Index) - Method in class adams.flow.transformer.WekaGetInstancesValue

Sets the 1-based index of the row.

setRow(Index) - Method in class adams.flow.transformer.WekaSetInstancesValue

Sets the 1-based index of the row.

setRowAttribute1(String) - Method in class adams.tools.CompareDatasets

Sets the index of the attribute used for identifying rows to compare against each other (first dataset).

setRowAttribute2(String) - Method in class adams.tools.CompareDatasets

Sets the index of the attribute used for identifying rows to compare against each other (second dataset).

setRowFinder(RowFinder) - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder

Sets the row finder to use.

setRowFinder(RowFinder) - Method in class adams.data.weka.datasetsplitter.RowSplitter

Sets the row-finder to use to select rows for the first dataset.

setRowFinder(RowFinder) - Method in class adams.data.weka.rowfinder.AbstractFilteredRowFinder

Sets the row finder to use.

setRowFinder(RowFinder) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Sets the training data row selector.

setRowFinder(RowFinder) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier

Sets the row finder to use.

setRowFinder(RowFinder) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Sets the row finder scheme.

setRowFinderEnabled(boolean) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Sets the whether to use the row finder.

setRowIndex(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Sets the index of the attribute to use for matching rows (only works if dataset already loaded).

setRowRange(String) - Method in class weka.filters.unsupervised.instance.KeepRange

Sets the unordered range of rows to keep.

setRows(int) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Sets the size of array.

setRows(int) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

setRows(BaseInteger[]) - Method in class adams.data.weka.rowfinder.Constant

Sets the constant set of rows to find.

setRowSelection(AbstractRowSelection) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Sets the row selection scheme to use.

setRunInformation(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics

Sets whether the run information is output as well.

setRunInformation(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

Sets whether the run information is output as well.

setRunInformation(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics

Sets whether the run information is output as well.

setRunInformation(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Sets whether the run information is output as well.

setRuns(int) - Method in class adams.flow.sink.WekaExperimentGenerator

Sets the number of runs to perform.

setRuns(int) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Sets the number of runs to perform.

setRuns(int) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets the number of runs.

setSampleSize(int) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Sets the sample size to use.

setSampleType(XGBoost.SampleType) - Method in class weka.classifiers.trees.XGBoost

Sets the type of sampling algorithm.

setSaveInstances(boolean) - Method in class weka.classifiers.trees.m5.Rule2

Sets whether instances at each node in an M5 tree should be saved for visualization purposes.

setSaveInstances(boolean) - Method in class weka.classifiers.trees.m5.RuleNode2

Set whether to save instances for visualization purposes.

setSaveInstances(boolean) - Method in class weka.classifiers.trees.M5P2

Set whether to save instance data at each node in the tree for visualization purposes

setScale(double) - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive

setScalePositiveWeights(float) - Method in class weka.classifiers.trees.XGBoost

Sets the positive-weights scale factor.

setScaler(AbstractErrorScaler) - Method in class adams.data.weka.predictions.AutoScaler

Sets the scaler to use for numeric data.

setSearch(ASSearch) - Method in class adams.flow.transformer.WekaAttributeSelection

Sets the evaluation method to use.

setSearch(NearestNeighbourSearch) - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Sets the search algorithm.

setSearchAlgorithm(NearestNeighbourSearch) - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Sets the nearestNeighbourSearch algorithm to be used for finding nearest neighbour(s).

setSecondAttribute(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes

Sets the name of the second attribute.

setSecondAttributeRange(String) - Method in class adams.gui.InstanceCompare

Sets the second attribute range ('second' and 'last' can be used as well).

setSecondAttributeRange(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel

Sets the second attribute range ('second' and 'last' can be used as well).

setSecondCrossValidationSeed(int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Sets the seed value to use for cross-validation (second evaluation).

setSecondDataset(PlaceholderFile) - Method in class adams.gui.InstanceCompare

Sets the second dataset.

setSecondDataset(File) - Method in class adams.gui.visualization.instance.InstanceComparePanel

Sets the second dataset.

setSecondFolds(int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Sets the number of folds to use in cross-validation (second evaluation).

setSecondNewFitness(double, Object, int, int[]) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Sets a fitness and keep it if better (second evaluation).

setSecondRange(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis

Sets the prefix to use for the generated attributes.

setSecondRowIndex(String) - Method in class adams.gui.InstanceCompare

Sets the second row index ('second' and 'last' can be used as well).

setSecondRowIndex(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel

Sets the second row index ('second' and 'last' can be used as well).

setSeed(int) - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator

Sets the seed value for cross-validation.

setSeed(int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Sets the seed value to use, resets the random number generator.

setSeed(int) - Method in class weka.classifiers.functions.FakeClassifier

Sets the seed value for the random values.

setSeed(int) - Method in class weka.classifiers.trees.XGBoost

Sets the random number seed.

setSeed(int) - Method in class weka.filters.supervised.instance.RemoveOutliers

Sets the seed value.

setSeed(int) - Method in class weka.filters.unsupervised.attribute.InputSmearing

Set the seed for random number generation.

setSeed(int) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates

Set the seed for random number generation.

setSeed(int) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Set the seed for random number generation.

setSeed(long) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Sets the seed value.

setSeed(long) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Sets the seed value.

setSeed(long) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator

Sets the seed value.

setSeed(long) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator

Sets the seed value.

setSeed(long) - Method in class adams.flow.transformer.WekaAttributeSelection

Sets the seed value.

setSeed(long) - Method in class adams.flow.transformer.WekaBootstrapping

Sets the seed value.

setSeed(long) - Method in class adams.flow.transformer.WekaClassifierRanker

Sets the seed value.

setSeed(long) - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

Sets the seed value.

setSeed(long) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Sets the seed value.

setSeed(long) - Method in class adams.flow.transformer.WekaCrossValidationSplit

Sets the seed value.

setSeed(long) - Method in class adams.flow.transformer.WekaRandomSplit

Sets the seed value.

setSeed(long) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets the seed value.

setSeed(long) - Method in class weka.classifiers.AbstractSplitGenerator

Sets the seed value.

setSelectionProcessor(AbstractSelectionProcessor) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor

Sets the selection processor scheme to use.

setSeparateFolds(boolean) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets whether to separate the folds, an Evaluation object per fold.

setSerialized(PlaceholderFile) - Method in class weka.filters.SerializedFilter

Sets the serialized filter file.

setSetup(String) - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Sets the property in the incoming properties that contains the commandline of the genetic algorithm.

setSetup(Classifier) - Method in class adams.flow.source.WekaClassifierGenerator

Sets the base classifier.

setSetup(Clusterer) - Method in class adams.flow.source.WekaClustererGenerator

Sets the base clusterer.

setSetup(Filter) - Method in class adams.flow.source.WekaFilterGenerator

Sets the base clusterer.

setSetupUpload(AbstractSetupUpload) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the scheme for uploading the currently best job setup.

setShowAboutBox(boolean) - Method in class adams.gui.wizard.WekaPropertySheetPanelPage.CustomPropertySheetPanel

Sets whether to show the about box or not.

setShowAttributeIndex(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel

Sets whether to display the attribute index in the header.

setShowAttributeWeights(boolean) - Method in class adams.gui.visualization.instances.InstancesTable

Sets whether to display attribute weights.

setShowAttributeWeights(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel

Sets whether to display attribute weights.

setShowDistribution(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Sets whether to show the class distribution as well.

setShowDistribution(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Sets whether to show the class distribution as well.

setShowError(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Sets whether to show the error as well.

setShowError(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Sets whether to show the error as well.

setShowProbability(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Sets whether to show the probability of the prediction as well.

setShowProbability(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Sets whether to show the probability of the prediction as well.

setShowWeight(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Sets whether to show the weight as well.

setShowWeight(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Sets whether to show the weight as well.

setShowWeightsColumn(boolean) - Method in class adams.gui.visualization.instances.InstancesTable

Sets whether to display a weights column.

setShowWeightsColumn(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel

Sets whether to display a weights column.

setShowZeroInstancesAsUnknown(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel

Set whether to show zero instances as unknown (i.e.

setSidePanelVisible(boolean) - Method in class adams.gui.visualization.instance.InstanceExplorer

Whether to display the side panel or not.

setSignificance(double) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Sets the significance level (0-1).

setSignificance(double) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Sets the significance level (0-1).

setSilent(boolean) - Method in class weka.classifiers.MultiLevelSplitGenerator

Sets whether to suppress error messages.

setSimpleAttributeNames(boolean) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Set whether to just number the attributes rather than compiling names.

setSize(int) - Method in class adams.data.weka.predictions.FixedSizeErrorScaler

Sets the size for the errors.

setSizeLimit(double) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Sets the size limit for the final dataset.

setSkipBuild(boolean) - Method in class adams.flow.transformer.WekaTrainClassifier

Sets whether to skip the buildClassifier call for incremental classifiers.

setSkipDrop(float) - Method in class weka.classifiers.trees.XGBoost

Sets the probability of skipping the dropout procedure during a boosting iteration.

setSkipHistory(boolean) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler

Sets whether to skip history panels.

setSkipIdentical(boolean) - Method in class weka.core.neighboursearch.NewNNSearch

Sets the property to skip identical instances (with distance zero from the target) from the set of neighbours returned.

setSkipNominal(boolean) - Method in class adams.data.instancesanalysis.PCA

Sets whether to skip NOMINAL attributes from the PCA process by turning them into STRING attributes.

setSkipTrain(boolean) - Method in class weka.classifiers.meta.SocketFacade

Sets whether to skip training, eg when using a pre-built model.

setSmoothing(boolean) - Method in class weka.classifiers.trees.m5.Rule2

Smooth predictions

setSortAttributeNames(boolean) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Sets whether to sort the attribute names.

setSortAttributes(boolean) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTable

Sets whether to sort the attributes alphabetically for the dropdown list.

setSortAttributes(boolean) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableWithButtons

Sets whether to sort the attributes alphabetically for the dropdown list.

setSortLabels(boolean) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Sets whether to sort the labels with the specified comparator.

setSortLabels(boolean) - Method in class weka.classifiers.AggregateEvaluations

Sets whether to sort the labels with the specified comparator.

setSource(File) - Method in class weka.core.converters.SimpleArffLoader

Resets the Loader object and sets the source of the data set to be the supplied File object.

setSource(File) - Method in class weka.core.converters.SpreadSheetLoader

Resets the Loader object and sets the source of the data set to be the supplied File object.

setSourceCodeClass(String) - Method in class adams.flow.transformer.WekaClassifierInfo

Sets the class name for the generated source code.

setSparseFormat(boolean) - Method in class adams.flow.source.WekaDatabaseReader

Sets whether to output the data in sparse format.

setSplitPercentage(double) - Method in class adams.flow.sink.WekaExperimentGenerator

Sets the split percentage (only train/test splits).

setSplitpoint(double) - Method in class weka.classifiers.meta.HighLowSplit

setSplitpoint(double) - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

setSplits(int) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Sets the splits.

setSplits(int) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

setSplitter(AbstractSplitter) - Method in class adams.flow.transformer.WekaDatasetSplit

Sets the splitter to use.

setSpreadSheetType(SpreadSheet) - Method in class adams.data.conversion.WekaInstancesToSpreadSheet

Sets the type of spreadsheet to use.

setSpreadSheetWriter(SpreadSheetWriter) - Method in class weka.core.converters.SpreadSheetSaver

Sets the spreadsheet writer to use.

setStatement(SQLStatement) - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Sets the SQL statement.

setStatistic(AbstractArrayStatistic) - Method in class adams.flow.transformer.WekaInstancesStatistic

Sets the statistic to use.

setStatistic(EvaluationStatistic) - Method in class weka.classifiers.meta.ClassifierCascade

the statistic to use for termination.

setStatistic(CenterStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Sets the statistic to output.

setStatistic(CenterStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Sets the statistic to output.

setStatistic(CenterStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Sets the statistic to output.

setStatistic(CenterStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Sets the statistic to output.

setStatistics(EvaluationStatistic[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Sets the statistics to output.

setStatistics(EvaluationStatistic[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Sets the statistics to output.

setStatisticValue(EvaluationStatistic) - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Sets the value to extract.

setStatisticValues(EvaluationStatistic[]) - Method in class adams.flow.transformer.WekaBootstrapping

Sets the values to extract.

setStatisticValues(EvaluationStatistic[]) - Method in class adams.flow.transformer.WekaEvaluationValues

Sets the values to extract.

setStatusMessageHandler(StatusMessageHandler) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets the status message handler to use.

setStatusMessageHandler(StatusMessageHandler) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets the status message handler for outputting notifications.

setStdDev(double) - Method in class weka.classifiers.meta.InputSmearing

Sets the multiplier for the standard deviation to use for input smearing.

setStdDev(double) - Method in class weka.filters.unsupervised.attribute.InputSmearing

Sets the multiplier for the standard deviation to use for input smearing.

setStopFlowIfCanceled(boolean) - Method in class adams.flow.source.WekaSelectDataset

Sets whether to stop the flow if dialog canceled.

setStopMode(StopMode) - Method in class adams.flow.source.WekaSelectDataset

Sets the stop mode.

setStorage(StorageName) - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Sets the data storage item.

setStorageName(StorageName) - Method in class adams.data.conversion.MapToWekaInstance

Sets the name of the stored Instances object to use as template.

setStorageName(StorageName) - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Sets the name for the data in the internal storage.

setStoreFilename(boolean) - Method in class adams.flow.transformer.WekaTextDirectoryReader

Sets whether to store the filename in extra attribute.

setStratify(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Sets whether to stratify the data (nominal class).

setStratify(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Sets whether to stratify the data (nominal class).

setStratify(boolean) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Sets whether to stratify the data (nominal class).

setStratify(boolean) - Method in interface weka.classifiers.CrossValidationFoldGenerator

Sets whether to stratify the data (nominal class).

setStratify(boolean) - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Sets whether to stratify the data (nominal class).

setStratify(boolean) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Sets whether to stratify the data (nominal class).

setStratify(boolean) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Sets whether to stratify the data (nominal class).

setStratify(boolean) - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Sets whether to stratify the data (nominal class).

setStrict(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge

Sets whether to enforce uniqueness in IDs.

setSubsampleRatio(float) - Method in class weka.classifiers.trees.XGBoost

Sets the sub-sample ratio of the training instances.

setSummaryFilter(Filter) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Sets the filter to use to summarise the attributes.

setSuppliedPrefix(String) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the prefix to use in case of OutputPrefixType.SUPPLIED.

setSuppliedReferenceDataset(Instances) - Method in class weka.filters.unsupervised.instance.AlignDataset

Sets the reference dataset to use instead of loading one from disk.

setSuppliedTestSet(Instances) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Sets the test set to use instead of loading one from disk.

setSupport(double) - Method in class weka.classifiers.meta.ConsensusOrVote

Sets the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.

setSupport(double) - Method in class weka.classifiers.meta.Veto

Sets the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.

setSuppressErrorMessage(boolean) - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Turn off the error message that is reported when no useful attribute is found.

setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.AbstainingCascade

Sets whether to output the model with the toString() method or not.

setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.ConsensusOrVote

Sets whether to output the model with the toString() method or not.

setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.SuppressModelOutput

Sets whether to output the model with the toString() method or not.

setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Sets whether to output the model with the toString() method or not.

setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.Veto

Sets whether to output the model with the toString() method or not.

setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.VotedImbalance

Sets whether to output the model with the toString() method or not.

setSuppressModelOutput(boolean) - Method in interface weka.core.ModelOutputHandler

Sets whether to output the model with the toString() method or not.

setSwapAxes(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets whether to swap the axes.

setSwapRowsAndColumns(boolean) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Sets whether to swap rows and columns.

setSwapRowsAndColumns(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Sets whether to swap rows and columns.

setTableName(String) - Method in class adams.flow.sink.WekaDatabaseWriter

Sets the table name to store the data in.

setTarget(Object) - Method in class adams.gui.wizard.WekaPropertySheetPanelPage

Sets the object to display the properties for.

setTemplate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Sets the stored template object.

setTemplate(Vote) - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels

Sets the Vote template to use.

setTemplate(Vote) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds

Sets the Vote template to use.

setTemplate(MultipleClassifiersCombiner) - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels

Sets the MultipleClassifiersCombiner template to use.

setTemplate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Sets the stored template object.

setTest(CallableActorReference) - Method in class adams.flow.transformer.WekaClassifierRanker

Sets the name of the callable actor to obtain the test set.

setTestAttributes(WekaAttributeRange) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Sets the range of attributes from the test to add to the output.

setTestBase(int) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Sets the index of the test base.

setTestBase(int) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Sets the index of the test base.

setTestData(StorageName) - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Sets the (optional) storage item that contains the test data; cross-validation is performed if not present.

setTester(Tester) - Method in class adams.flow.transformer.WekaExperimentEvaluation

Sets the Tester to use.

setTester(Tester) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Sets the Tester to use.

setTester(Tester) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Sets the tester to use.

setTestInstances(Instances) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Sets the currently set test set (if null, cross-validation is used).

setTestset(CallableActorReference) - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Sets the name of the callable clusterer to use.

setTestset(CallableActorReference) - Method in class adams.flow.transformer.WekaTestSetEvaluator

Sets the name of the callable classifier to use.

setTestSet(File) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Sets the file containing the test set to remove from the data passing through the filter.

setTestSplitName(String) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Sets the name of the split to use for testing.

setTestSplitName(String) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Sets the name of the split to use for testing, ie generating predictions.

setThreshold(double) - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

Sets the threshold.

setThreshold(double) - Method in class adams.tools.CompareDatasets

Sets the threshold for the correlation coefficient.

setThreshold(double) - Method in class weka.classifiers.meta.ClassifierCascade

the threshold for the statistic for termination.

setThreshold(double) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Sets the threshold for the max error when predicting a numeric class.

setThreshold(double) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Sets the threshold for the max error when predicting a numeric class.

setThresholdCheck(ClassifierCascade.ThresholdCheck) - Method in class weka.classifiers.meta.ClassifierCascade

whether to go below or above the threshold.

setThresholds(String) - Method in class weka.classifiers.meta.VotedImbalance

Set the pairs of threshold/number of resampled models.

setTimeLenient(boolean) - Method in class adams.ml.data.InstancesView

Sets whether parsing of times is to be lenient or not.

setTimeMsecLenient(boolean) - Method in class adams.ml.data.InstancesView

Sets whether parsing of times/msec is to be lenient or not.

setTimeout(int) - Method in class weka.classifiers.meta.SocketFacade

Sets the timeout in milli-second to wait for new connections.

setTimeZone(TimeZone) - Method in class adams.ml.data.InstancesView

Sets the timezone to use.

setTitle(String) - Method in class weka.gui.explorer.ExplorerExt

Sets the base title to use for the title generator.

setTitleClassDetails(String) - Method in class adams.flow.transformer.WekaEvaluationSummary

Sets the title to use for the class details.

setTitleMatrix(String) - Method in class adams.flow.transformer.WekaEvaluationSummary

Sets the title to use for the confusion matrix.

setTitleNameColumn(String) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Sets the title of the "Name" column, i.e., the first column.

setTitleSummary(String) - Method in class adams.flow.transformer.WekaEvaluationSummary

Sets the title to use for the summary.

setTitleValueColumn(String) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Sets the title of the "Value" column, i.e., the first column.

setTokenizers(Tokenizer[]) - Method in class weka.core.tokenizers.MultiTokenizer

Sets the tokenizers to use.

setTol(double) - Method in class adams.data.instancesanalysis.pls.KernelPLS

Sets the inner NIPALS loop maximum number of iterations.

setTol(double) - Method in class adams.data.instancesanalysis.pls.NIPALS

Sets the inner NIPALS loop improvement tolerance.

setTol(double) - Method in class adams.data.instancesanalysis.pls.PRM

Sets the inner NIPALS loop improvement tolerance.

setTol(double) - Method in class adams.data.instancesanalysis.pls.SparsePLS

Sets the inner NIPALS loop improvement tolerance.

setTolerateHeaderChanges(boolean) - Method in class adams.data.instances.AbstractInstanceGenerator

Sets whether to tolerate header changes and merely re-generating the header instead of throwing an exception.

setToolTipsEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Sets whether to show tool tips.

setToolTipsEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Sets whether to show tool tips.

setToolTipsEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Sets whether to show tool tips.

setToolTipsEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Sets whether to show tool tips.

setToolTipsEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Sets whether to show tool tips.

setTopK(int) - Method in class weka.classifiers.trees.XGBoost

Sets the number of top features to select when using the greedy or thrifty feature selector.

setTrain(CallableActorReference) - Method in class adams.flow.transformer.WekaClassifierRanker

Sets the name of the callable actor to obtain the training set.

setTrain(Instances) - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Sets the training data to use.

setTrainSplitName(String) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Sets the name of the split to use for training.

setTrainSplitName(String) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Sets the name of the split to use for training.

setTreeMethod(XGBoost.TreeMethod) - Method in class weka.classifiers.trees.XGBoost

Sets the tree construction algorithm used in XGBoost.

setTrials(int) - Method in class weka.classifiers.trees.RandomModelTrees

setTurnOffAbstaining(boolean) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Sets whether to turn off abstaining of the base classifier.

setTweedieVariancePower(float) - Method in class weka.classifiers.trees.XGBoost

Sets the parameter that controls the variance of the Tweedie distribution.

setType(WekaClassifierInfo.InfoType) - Method in class adams.flow.transformer.WekaClassifierInfo

Sets the type of information to generate.

setType(WekaClustererInfo.InfoType) - Method in class adams.flow.transformer.WekaClustererInfo

Sets the type of information to generate.

setType(WekaEvaluationInfo.InfoType) - Method in class adams.flow.transformer.WekaEvaluationInfo

Sets the type of information to generate.

setType(WekaExtractArray.ExtractionType) - Method in class adams.flow.transformer.WekaExtractArray

Sets the type of extraction to perform.

setType(WekaInstancesInfo.InfoType) - Method in class adams.flow.transformer.WekaInstancesInfo

Sets the type of information to generate.

setType(NominalToNumeric.ConversionType) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Sets the conversion type to use.

setUndo(Undo) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Sets the undo manager to use, can be null if no undo-support wanted.

setUndo(Undo) - Method in class adams.gui.visualization.instance.InstancePanel

Sets the undo manager to use, can be null if no undo-support wanted.

setUndoEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList

Sets whether undo is enabled.

setUndoEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Sets the undo state.

setUndoEnabled(boolean) - Method in class adams.gui.visualization.instances.InstancesTable

sets whether undo support is enabled

setUndoEnabled(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel

sets whether undo support is enabled

setUndoHandler(UndoHandlerWithQuickAccess) - Method in class adams.gui.visualization.instances.InstancesTable

Sets the undo handler to use.

setUndoHandler(UndoHandlerWithQuickAccess) - Method in class adams.gui.visualization.instances.InstancesTableModel

Sets the undo handler to use.

setUniqueID(String) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Sets the name of the unique ID attribute that the merge is joining on.

setUniqueID(String) - Method in class adams.flow.transformer.WekaInstancesMerge

Sets the attribute (string/numeric) to use for uniquely identifying rows.

setUnpruned(boolean) - Method in class weka.classifiers.trees.m5.M5Base2

Use unpruned tree/rules

setUnpruned(boolean) - Method in class weka.classifiers.trees.m5.Rule2

Use unpruned tree/rules

setUnset(boolean) - Method in class adams.flow.transformer.WekaClassSelector

Sets whether to unset the class attribute.

setup(Instances) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Initializes the filter with the given input data.

setUp() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

Performs necessary initializations before being able to evaluate.

setUp() - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Performs necessary initializations before being able to evaluate.

setUp() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.AbstractInstanceGenerator

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaClassifierRanker

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator

setUp() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaExperiment

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaFilter

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaInstanceDumper

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaStoreInstance

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaTrainAssociator

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaTrainClassifier

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaTrainClusterer

Initializes the item for flow execution.

setUp() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator

Initializes the item for flow execution.

setUp(Actor) - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities

Configures the condition.

setUp(Actor) - Method in class adams.flow.condition.bool.WekaClassification

Initializes the item for flow execution.

setUp(Instances) - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

SETUP - adams.opt.genetic.OutputType

only the setup.

setUpCallableActor() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Configures the callable actor.

setUpdateContainerColor(boolean) - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Sets whether to update the container's color with the color determined by this paintlet.

setUpdateHeader(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Sets whether to remove the labels also from the attribute definition.

setUpdateInterval(int) - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater

Sets the number of tokens after which the display is being updated.

setUpdater(AbstractInstancePanelUpdater) - Method in class adams.flow.sink.WekaInstanceViewer

Sets the updater to use.

setUpdater(XGBoost.Updater) - Method in class weka.classifiers.trees.XGBoost

Sets the choice of algorithm to fit the linear model.

setUpdateRelationName(boolean) - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Sets whether to update the relation name with the new class attribute.

setUpdateWait(int) - Method in class weka.classifiers.functions.FakeClassifier

Sets the time in msec to wait when calling updateClassifier.

SetupDialog(Dialog, Dialog.ModalityType) - Constructor for class adams.gui.visualization.instance.HistogramFactory.SetupDialog

Initializes the dialog.

SetupDialog(Frame, boolean) - Constructor for class adams.gui.visualization.instance.HistogramFactory.SetupDialog

Initializes the dialog.

setUpEvaluator() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Initializes the evaluator.

setUpModel() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Loads the model from the model file.

setUpModel(Actor) - Method in class adams.flow.condition.bool.WekaClassification

Loads the model from the model file.

setupModified() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

Sends an event that the setup was modified.

setUpper(UpperStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Sets the upper value to output.

setUpper(UpperStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Sets the upper value to output.

setUpper(UpperStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Sets the upper value to output.

setUpper(UpperStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Sets the upper value to output.

setUpReference() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Loads the reference data.

setupTipText() - Method in class adams.flow.source.WekaClassifierGenerator

Returns the tip text for this property.

setupTipText() - Method in class adams.flow.source.WekaClustererGenerator

Returns the tip text for this property.

setupTipText() - Method in class adams.flow.source.WekaFilterGenerator

Returns the tip text for this property.

setupTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Returns the tip text for this property.

setupUploadTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

setURL(String) - Method in class adams.flow.sink.WekaDatabaseWriter

Sets the database URL to query.

setURL(String) - Method in class adams.flow.source.WekaDatabaseReader

Sets the database URL to query.

setUseAbsoluteError(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Sets whether to use an absolute error (ie no direction).

setUseAbsoluteError(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Sets whether to use an absolute error (ie no direction).

setUseColumnNamesAsClassLabels(boolean) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Sets whether to use the names of the class distribution columns as labels in the fake evaluation.

setUseCustomLoader(boolean) - Method in class adams.flow.transformer.WekaFileReader

Sets whether to use a custom loader or not.

setUseCustomLoader(boolean) - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Sets whether to use a custom loader or not.

setUseCustomLoader(boolean) - Method in class weka.filters.unsupervised.instance.AlignDataset

Sets whether to use a custom loader or automatic loading.

setUseCustomLoader(boolean) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Sets whether to use a custom loader or automatic loading.

setUseCustomPaintlet(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets whether to use the custom paintlet.

setUseCustomSaver(boolean) - Method in class adams.flow.sink.WekaFileWriter

Sets whether to use a custom saver or not.

setUseError(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Sets whether to use the numeric error for the cross size.

setUseFilename(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Sets whether to use the filename (w/o path) instead of the relationname.

setUseFilename(boolean) - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ExperimentWithCustomizableRelationNames

Sets whether to use the filename (w/o path) instead of the relationname.

setUseFilename(boolean) - Method in class weka.experiment.ExtExperiment

Sets whether to use the filename (w/o path) instead of the relationname.

setUseFixedMinMax(boolean) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Sets whether to use user-supplied min/max for bin calculation rather than obtain min/max from data.

setUseMedian(boolean) - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters

Sets whether to use the median instead of the mean.

setUseModelResetVariable(boolean) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Sets the whether to use a variable to monitor for changes in order to reset the model.

setUseOriginalIndices(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Sets whether to align with original data (requires: WekaEvaluationContainer as input and original indices in container).

setUseOuterWindow(boolean) - Method in class adams.flow.source.WekaSelectDataset

Sets whether to use the outer window as parent.

setUsePrefix(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge

Sets whether to use prefixes.

setUseProbabilities(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Sets whether to use probabilities instead of 0 and 1 for the counts.

setUser(String) - Method in class adams.flow.sink.WekaDatabaseWriter

Sets the database user.

setUser(String) - Method in class adams.flow.source.WekaDatabaseReader

Sets the database user.

setUseRelationNameAsFilename(boolean) - Method in class adams.flow.sink.WekaFileWriter

Sets whether to use the relation name as filename instead.

setUseRelationNameAsFilename(boolean) - Method in class adams.flow.transformer.WekaInstanceDumper

Sets whether to use the relation name as filename instead.

setUseRelationNameAsTable(boolean) - Method in class adams.flow.sink.WekaDatabaseWriter

Sets whether to output single Instance objects or just one Instances object.

setUseRelativePath(boolean) - Method in class weka.core.converters.SimpleArffLoader

Ignored.

setUseSaveDialog(boolean) - Method in class adams.gui.wizard.WekaSelectDatasetPage

Sets whether to use the save or open dialog.

setUseSecondEvaluation(boolean) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Sets whether to use the second evaluation.

setUseTree(boolean) - Method in class weka.classifiers.trees.m5.Rule2

Use an m5 tree rather than generate rules

setUseUnsmoothed(boolean) - Method in class weka.classifiers.trees.m5.M5Base2

Use unsmoothed predictions

setUseViews(boolean) - Method in interface adams.data.weka.InstancesViewSupporter

Sets whether to uses views.

setUseViews(boolean) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Sets whether to use views instead of dataset copies, in order to conserve memory.

setUseViews(boolean) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Sets whether to use views instead of dataset copies, in order to conserve memory.

setUseViews(boolean) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets whether to use views instead of dataset copies, in order to conserve memory.

setUseViews(boolean) - Method in class weka.classifiers.AbstractSplitGenerator

Sets whether to uses views only.

setValue(int, double) - Method in class weka.core.AbstractHashableInstance

Sets a specific value in the instance to the given value (internal floating-point format).

setValue(int, String) - Method in class weka.core.AbstractHashableInstance

Sets a value of a nominal or string attribute to the given value.

setValue(PropertyPath.PropertyContainer, double) - Method in class adams.core.discovery.genetic.GenericDoubleResolution

Sets the double value in the property container.

setValue(PropertyPath.PropertyContainer, double) - Method in class adams.core.discovery.genetic.GPDGamma

Sets the double value in the property container.

setValue(PropertyPath.PropertyContainer, double) - Method in class adams.core.discovery.genetic.GPDNoise

Sets the double value in the property container.

setValue(PropertyPath.PropertyContainer, float) - Method in class adams.core.discovery.genetic.GenericFloatResolution

Sets the float value in the property container.

setValue(PropertyPath.PropertyContainer, int) - Method in class adams.core.discovery.genetic.GenericInteger

Sets the double value in the property container.

setValue(PropertyPath.PropertyContainer, int) - Method in class adams.core.discovery.genetic.PLSFilterNumComponents

Sets the integer value in the property container.

setValue(PropertyPath.PropertyContainer, int) - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints

Sets the integer value in the property container.

setValue(PropertyPath.PropertyContainer, String) - Method in class adams.core.discovery.genetic.GenericString

Sets the string value in the property container.

setValue(PropertyPath.PropertyContainer, Matrix) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Sets the integer value in the property container.

setValue(PropertyPath.PropertyContainer, Matrix) - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix

Sets the integer value in the property container.

setValue(PropertyEditor, Object) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler

Sets the editor value.

setValue(String) - Method in class adams.flow.transformer.WekaSetInstancesValue

Sets the value to set in the report.

setValue(String) - Method in class adams.flow.transformer.WekaSetInstanceValue

Sets the value to set in the report.

setValue(Attribute, double) - Method in class weka.core.AbstractHashableInstance

Sets a specific value in the instance to the given value (internal floating-point format).

setValue(Attribute, String) - Method in class weka.core.AbstractHashableInstance

Sets a value of an nominal or string attribute to the given value.

setValue(Instance, int, Object) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge

Sets the value of the given attribute in the given instance to the given value (handles object conversion).

setValueAt(Object, int, int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

Sets the value at the specified position, if possible.

setValueAt(Object, int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel

sets the value in the cell at columnIndex and rowIndex to aValue.

setValueAt(Object, int, int, boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel

Sets the value in the cell at columnIndex and rowIndex to aValue.

setValueSparse(int, double) - Method in class weka.core.AbstractHashableInstance

Sets a specific value in the instance to the given value (internal floating-point format), given an index into the sparse representation.

setVariableName(VariableName) - Method in class adams.flow.template.InstanceDumperVariable

Sets the variable name to generate the sub-flow for.

setVariableName(VariableName) - Method in class adams.flow.transformer.WekaInstanceBuffer

Sets the name of the variable to monitor.

setVariableName(VariableName) - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Sets the name of the variable to monitor.

setVariance(double) - Method in class adams.data.instancesanalysis.PCA

Sets the variance.

setVariance(double) - Method in class weka.classifiers.meta.AbstainLeastMedianSq

setVarianceCovered(double) - Method in class adams.flow.transformer.WekaPrincipalComponents

Sets the amount of variance to account for when retaining principal components.

setVarianceCovered(double) - Method in class weka.core.neighboursearch.PCANNSearch

Sets the amount of variance to account for when retaining principal components.

setVarianceCovered(double) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Sets the amount of variance to account for when retaining principal components.

setVector(Matrix, Matrix, int) - Static method in class weka.core.matrix.MatrixHelper

stores the data from the (column) vector in the matrix at the specified index

setVerbosity(XGBoost.Verbosity) - Method in class weka.classifiers.trees.XGBoost

Sets the verbosity level.

setVersusFitOptions(VersusFitOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Set the options for the vsfit plot.

setVersusOrderOptions(VersusOrderOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Set the options for the vs order plot.

setVisible(boolean) - Method in class adams.gui.visualization.instance.InstanceContainer

Sets the instance's visibility.

setVisible(int, boolean) - Method in class adams.gui.visualization.instance.InstanceContainerManager

Sets the specified container's visibility.

setVotingType(VotedPairs.VotingType) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs

Sets the type of voting to use.

setWaitForJobs(boolean) - Method in class adams.multiprocess.WekaCrossValidationExecution

Sets whether to wait for jobs to finish when terminating.

setWaveNoRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.Detrend

Sets the regular expression used for extracting the wave number from the attribute name (using the first group).

setWaveNoRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Sets the regular expression used for extracting the wave number from the attribute name (using the first group).

setWeight(double) - Method in class weka.core.AbstractHashableInstance

Sets the weight of an instance.

setWeight(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Sets the (optional) column with the instance weight values.

setWeight(SpreadSheetColumnIndex) - Method in class weka.classifiers.functions.FromPredictions

Sets the column with the weight values.

setWeightingKernel(int) - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Sets the kernel weighting method to use.

setWeightingKernel(int) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Sets the kernel weighting method to use.

setWeights(String) - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Sets the optional property in the incoming properties for the initial weights to use.

setWindows(int) - Method in class weka.filters.unsupervised.attribute.PAA

Sets the nth point setting.

setWindows(int) - Method in class weka.filters.unsupervised.attribute.SAX

Sets the nth point setting.

setWithReplacement(boolean) - Method in class adams.flow.transformer.WekaBootstrapping

Sets whether to draw predictions using replacement.

setWriter(SpreadSheetWriter) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Sets the spreadsheet writer to use.

setX(Integer) - Method in class adams.data.instance.InstancePoint

Sets the X value.

setXRegExp(BaseRegExp) - Method in class weka.filters.supervised.attribute.MultiPLS

Sets the regular expression to identify the X attributes.

setY(Double) - Method in class adams.data.instance.InstancePoint

Sets the Y value.

setYRegExp(BaseRegExp) - Method in class weka.filters.supervised.attribute.MultiPLS

Sets the regular expression to identify the Y attributes.

setZoomOverview(boolean) - Method in class adams.flow.sink.WekaInstanceViewer

Sets whether to display the zoom overview.

setZoomOverviewPanelVisible(boolean) - Method in class adams.gui.visualization.instance.InstanceExplorer

Sets the zoom overview panel visible or not.

setZoomOverviewPanelVisible(boolean) - Method in class adams.gui.visualization.instance.InstancePanel

Sets the zoom overview panel visible or hides it.

SF_ENTROPY_GAIN - adams.flow.core.EvaluationStatistic

SF_ENTROPY_GAIN - adams.flow.core.ExperimentStatistic

SF_MEAN_ENTROPY_GAIN - adams.flow.core.EvaluationStatistic

SF_MEAN_ENTROPY_GAIN - adams.flow.core.ExperimentStatistic

SF_MEAN_PRIOR_ENTROPY - adams.flow.core.EvaluationStatistic

SF_MEAN_PRIOR_ENTROPY - adams.flow.core.ExperimentStatistic

SF_MEAN_SCHEME_ENTROPY - adams.flow.core.EvaluationStatistic

SF_MEAN_SCHEME_ENTROPY - adams.flow.core.ExperimentStatistic

SF_PRIOR_ENTROPY - adams.flow.core.EvaluationStatistic

SF_PRIOR_ENTROPY - adams.flow.core.ExperimentStatistic

SF_SCHEME_ENTROPY - adams.flow.core.EvaluationStatistic

SF_SCHEME_ENTROPY - adams.flow.core.ExperimentStatistic

shallowCopy() - Method in class adams.data.instances.AbstractInstanceGenerator

Returns a shallow copy of itself, i.e., based on the commandline options.

shallowCopy() - Method in class adams.data.weka.columnfinder.AbstractColumnFinder

Returns a shallow copy of itself, i.e., based on the commandline options.

shallowCopy() - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Returns a shallow copy of itself, i.e., based on the commandline options.

shallowCopy() - Method in class adams.data.weka.predictions.AbstractErrorScaler

Returns a shallow copy of itself, i.e., based on the commandline options.

shallowCopy() - Method in class adams.data.weka.rowfinder.AbstractRowFinder

Returns a shallow copy of itself, i.e., based on the commandline options.

shallowCopy(boolean) - Method in class adams.data.instances.AbstractInstanceGenerator

Returns a shallow copy of itself, i.e., based on the commandline options.

shallowCopy(boolean) - Method in class adams.data.weka.columnfinder.AbstractColumnFinder

Returns a shallow copy of itself, i.e., based on the commandline options.

shallowCopy(boolean) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator

Returns a shallow copy of itself, i.e., based on the commandline options.

shallowCopy(boolean) - Method in class adams.data.weka.predictions.AbstractErrorScaler

Returns a shallow copy of itself, i.e., based on the commandline options.

shallowCopy(boolean) - Method in class adams.data.weka.rowfinder.AbstractRowFinder

Returns a shallow copy of itself, i.e., based on the commandline options.

shortenCommandLine(Classifier) - Static method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns a shortened commandline string for the classifier.

SHOTGUN - weka.classifiers.trees.XGBoost.Updater

showCellPopup(MouseEvent) - Method in class adams.gui.visualization.instances.InstancesTable

Shows a popup menu for the cells.

showCredentials() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel

Displays a dialog for the user credentials.

showDataTablePopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

Displays popup for table.

showDialog() - Method in class adams.flow.source.WekaSelectObjects

Displays the dialog, prompting the user to select classes.

showDistributionTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the tip text for this property.

showDistributionTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Returns the tip text for this property.

showErrorTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the tip text for this property.

showErrorTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Returns the tip text for this property.

showHeaderPopup(MouseEvent) - Method in class adams.gui.visualization.instances.InstancesTable

Shows a popup menu for the header.

showHelp() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Displays the help for the queries.

showHistogram(List<InstanceContainer>) - Method in class adams.gui.visualization.instance.InstancePanel

Displays the histograms for the given instances.

showInstanceExplorer() - Method in class weka.gui.explorer.ExplorerExt

Displays the data in the Instance Explorer.

showListPopup(MouseEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

Displays the popup for the list.

showOutputGeneratorsFavorites() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Shows the favorites popup menu for the output generators.

showOutputGeneratorsFavorites() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Shows the favorites popup menu for the output generators.

showOutputGeneratorsFavorites() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Shows the favorites popup menu for the output generators.

showOutputGeneratorsFavorites() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Shows the favorites popup menu for the output generators.

showOutputGeneratorsFavorites() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Shows the favorites popup menu for the output generators.

showPopup(String, int, int) - Method in class weka.gui.explorer.ExperimentPanel

Handles constructing a popup menu with visualization options.

showProbabilityTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the tip text for this property.

showProbabilityTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Returns the tip text for this property.

showProgress() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Updates the progress of the experiment.

showProgress(String) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Displays a progresss message.

showStatus(String) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Displays a message.

showStatus(String) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Displays a message.

showStatus(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel

Displays a message.

showStatus(String) - Method in class adams.gui.visualization.instance.InstanceExplorer

Displays a message.

showWeightTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the tip text for this property.

showWeightTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions

Returns the tip text for this property.

SHUFFLE - weka.classifiers.trees.XGBoost.FeatureSelector

significanceTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the tip text for this property.

significanceTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the tip text for this property.

SILENT - weka.classifiers.trees.XGBoost.Verbosity

silentTipText() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns the tip text for this property.

Simple - Class in adams.flow.transformer.wekadatasetsmerge

Just merges the datasets side by side.

Simple - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel

Simply builds the classifier on the full dataset.

Simple - Class in weka.classifiers.meta.socketfacade

Simple preparation scheme, using JSON with the actual data in CSV format.

Simple() - Constructor for class adams.flow.transformer.wekadatasetsmerge.Simple

Simple() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.Simple

Simple() - Constructor for class weka.classifiers.meta.socketfacade.Simple

Simple.SimpleRowSetIterator - Class in adams.flow.transformer.wekadatasetsmerge

Enumeration class which just returns the concatenation of the source data rows in order.

SimpleArffLoader - Class in weka.core.converters

A simple ARFF loader, only supports batch loading.

SimpleArffLoader() - Constructor for class weka.core.converters.SimpleArffLoader

Initializes the loader.

SimpleArffSaver - Class in weka.core.converters

Writes the Instances to an ARFF file in batch mode.

SimpleArffSaver() - Constructor for class weka.core.converters.SimpleArffSaver

Constructor

simpleAttributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Returns the tip text for this property

SimpleDetrend - Class in weka.filters.unsupervised.attribute

Performs Detrend, using the specified correction scheme.

SimpleDetrend() - Constructor for class weka.filters.unsupervised.attribute.SimpleDetrend

SimpleInstanceLinePaintlet - Class in adams.gui.visualization.instance

Paintlet for generating a line plot for Instance objects (no markers).

SimpleInstanceLinePaintlet() - Constructor for class adams.gui.visualization.instance.SimpleInstanceLinePaintlet

SimpleInstancePanelUpdater - Class in adams.gui.visualization.instance

Updates the flow after the specified number of tokens have been processed.

SimpleInstancePanelUpdater() - Constructor for class adams.gui.visualization.instance.SimpleInstancePanelUpdater

SimpleJsonCommunicationProcessor - Class in adams.data.wekapyroproxy

Turns Instances/Instance into simple JSON.

SimpleJsonCommunicationProcessor() - Constructor for class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor

SimpleLinearRegressionIntervalEstimator - Class in weka.classifiers.functions

Learns a simple linear regression model.

SimpleLinearRegressionIntervalEstimator() - Constructor for class weka.classifiers.functions.SimpleLinearRegressionIntervalEstimator

SimpleLinearRegressionWithAccess - Class in weka.classifiers.functions

Learns a simple linear regression model.

SimpleLinearRegressionWithAccess() - Constructor for class weka.classifiers.functions.SimpleLinearRegressionWithAccess

SimplePlot - Class in adams.gui.visualization.instances.instancestable

Allows to perform a simple plot of a column or row.

SimplePlot() - Constructor for class adams.gui.visualization.instances.instancestable.SimplePlot

SimpleSetupDialog(Dialog) - Constructor for class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog

Initializes the dialog.

SimpleSetupDialog(Frame) - Constructor for class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog

Initializes the dialog.

SimpleSubRange - Class in adams.flow.transformer.wekaevaluationpostprocessor

Generates an Evaluation object based on the actual class values that fall within the specified interval ranges.

SimpleSubRange() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange

SIMPLS - Class in adams.data.instancesanalysis.pls

Implementation of SIMPLS algorithm.

Available matrices: W, B

For more information see:

Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002).

SIMPLS() - Constructor for class adams.data.instancesanalysis.pls.SIMPLS

SIMPLS_B - adams.flow.transformer.WekaExtractPLSMatrix.MatrixType

the B matrix for SIMPLS (used for prediction)

SIMPLS_W - adams.flow.transformer.WekaExtractPLSMatrix.MatrixType

the W matrix for SIMPLS

SIMPLSAttributeEval - Class in weka.attributeSelection

Uses the first component of SIMPLS to determine the importance of the attributes (defaults: no preprocessing, missing values not replaced, and 20 components)

SIMPLSAttributeEval() - Constructor for class weka.attributeSelection.SIMPLSAttributeEval

SIMPLSMatrixFilter - Class in weka.filters.supervised.attribute

Runs Partial Least Square Regression over the given instances and computes the resulting beta matrix for prediction.
By default it replaces missing values and centers the data.

Allows access to the internal matrices.

For more information see:

Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002).

SIMPLSMatrixFilter() - Constructor for class weka.filters.supervised.attribute.SIMPLSMatrixFilter

SIMPLSMatrixFilterFromGeneticString - Class in weka.filters.supervised.attribute

Runs Partial Least Square Regression over the given instances and computes the resulting beta matrix for prediction.
By default it replaces missing values and centers the data.

Allows access to the internal matrices.

For more information see:

Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002).

SIMPLSMatrixFilterFromGeneticString() - Constructor for class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

SIMPLSWeightsMatrix - Class in adams.core.discovery.genetic

SIMPLS pls internal weights handler.

SIMPLSWeightsMatrix() - Constructor for class adams.core.discovery.genetic.SIMPLSWeightsMatrix

size() - Method in class adams.opt.optimise.genetic.PackDataDef

size() - Method in class weka.core.InstanceGrouping

Returns the number of groups.

size() - Method in class weka.core.InstancesView

Returns the number of instances in the dataset.

sizeLimitTipText() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample

Returns the tip text for this property.

sizeTipText() - Method in class adams.data.weka.predictions.FixedSizeErrorScaler

Returns the tip text for this property.

skipBuildTipText() - Method in class adams.flow.transformer.WekaTrainClassifier

Returns the tip text for this property.

skipDropTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the skipDrop option.

skipIdenticalTipText() - Method in class weka.core.neighboursearch.NewNNSearch

Returns the tip text for this property.

skipNominalTipText() - Method in class adams.data.instancesanalysis.PCA

Returns the tip text for this property.

skipTrainTipText() - Method in class weka.classifiers.meta.SocketFacade

Returns the tip text for this property.

slim(Matrix) - Method in class adams.data.instancesanalysis.pls.SIMPLS

Zeroes the coefficients of the W matrix beyond the specified number of coefficients.

smoothingOriginal(double, double, double) - Static method in class weka.classifiers.trees.m5.RuleNode2

Applies the m5 smoothing procedure to a prediction

SocketFacade - Class in weka.classifiers.meta

Uses sockets to communicate with a process for training and making predictions.

SocketFacade() - Constructor for class weka.classifiers.meta.SocketFacade

SOFTMAX_MULTICLASS_CLASSIFICATION - weka.classifiers.trees.XGBoost.Objective

SOFTPROB_MULTICLASS_CLASSIFICATION - weka.classifiers.trees.XGBoost.Objective

solveChol(double[][], double[]) - Method in class weka.classifiers.functions.GPD

specialised to solve A * x = b, where x and b are one-dimensional

sort() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Sorts genes and fitness arrays according to fitness.

sort(int) - Method in class weka.core.InstancesView

Sorts the instances based on an attribute.

sort(int, boolean) - Method in class adams.ml.data.InstancesView

Sorts the rows based on the values in the specified column.

sort(InstanceComparator) - Method in class adams.gui.visualization.instances.InstancesTable

Sorts the data with the given comparator.

sort(RowComparator) - Method in class adams.ml.data.InstancesView

Sorts the rows using the given comparator.

sort(RowComparator, boolean) - Method in class adams.ml.data.InstancesView

Sorts the rows using the given comparator.

Sort - Class in weka.filters.unsupervised.instance

Sorts the instances.

Sort() - Constructor for class weka.filters.unsupervised.instance.Sort

SortablePrediction(Prediction) - Constructor for class adams.flow.transformer.WekaAccumulatedError.SortablePrediction

Initializes the container.

sortBasedOnNominalAttribute(int) - Method in class weka.core.InstancesView

Sorts a nominal attribute (stable, linear-time sort).

SortContainer(int, double) - Constructor for class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer

Initializes the container.

SortedInterval(Instance, double[][], boolean) - Constructor for class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval

Initializes the intervals.

sortInstances(int) - Method in class adams.gui.visualization.instances.InstancesTableModel

sorts the instances via the given attribute

sortInstances(int, boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel

sorts the instances via the given attribute

sortLabelsTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the tip text for this property.

SortOnAttribute - Class in weka.filters.unsupervised.instance

Sorts the instances on a particular attribute.

SortOnAttribute() - Constructor for class weka.filters.unsupervised.instance.SortOnAttribute

sortResults() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

sortRowKeys() - Method in class adams.ml.data.InstancesView

Sorts the rows according to the row keys.

sortRowKeys(Comparator<String>) - Method in class adams.ml.data.InstancesView

Sorts the rows according to the row keys.

sortSetupChanged(InstancesSortSetupEvent) - Method in interface adams.gui.event.InstancesSortSetupListener

Gets triggered whenever the sort setup changes.

SOURCE_CODE - adams.flow.transformer.WekaClassifierInfo.InfoType

source code (if available).

SourceAttribute(int, int, String) - Constructor for class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute

Standard constructor.

SourceCode - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Outputs source code from the model (if classifier implements Sourcable).

SourceCode() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode

sourceCodeClassTipText() - Method in class adams.flow.transformer.WekaClassifierInfo

Returns the tip text for this property.

sparseFormatTipText() - Method in class adams.flow.source.WekaDatabaseReader

Returns the tip text for this property.

SparsePLS - Class in adams.data.instancesanalysis.pls

SparsePLS() - Constructor for class adams.data.instancesanalysis.pls.SparsePLS

SpellChecker - Class in weka.filters.unsupervised.attribute

A simple filter that merges misspelled labels into a single correct one.

SpellChecker() - Constructor for class weka.filters.unsupervised.attribute.SpellChecker

split() - Method in class weka.classifiers.trees.m5.RuleNode2

Finds an attribute and split point for this node

split(Instances) - Method in class adams.data.weka.datasetsplitter.AbstractSplitter

Splits the given dataset into a number of other datasets.

split(Instances) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter

Splits the given dataset into a number of other datasets.

split(Instances) - Method in class adams.data.weka.datasetsplitter.RowSplitter

Splits the given dataset into a number of other datasets.

split(Instances, double) - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

Splits the dataset into two separate ones, according to the specified percentage (0-1).

Split - Class in adams.gui.tools.wekainvestigator.datatable.action

Creates train/test splits from a dataset and inserts these as new datasets.

Split() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Split

Instantiates the action.

splitAtt() - Method in class weka.classifiers.trees.m5.RuleNode2

Get the index of the splitting attribute for this node

splitAttributes(Instances) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter

Creates the attribute lists for the two datasets resulting from this split.

SplitGenerator - Interface in weka.classifiers

Interface for helper classes that generate dataset splits.

splitOptions(String) - Method in class adams.core.option.WekaCommandLineHandler

Splits the commandline into an array.

splitPercentageTipText() - Method in class adams.flow.sink.WekaExperimentGenerator

Returns the tip text for this property.

splitpointTipText() - Method in class weka.classifiers.meta.HighLowSplit

splitpointTipText() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

SPLITS - Static variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

splitsTipText() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler

Returns the tip text for this property.

splitsTipText() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString

splitterTipText() - Method in class adams.flow.transformer.WekaDatasetSplit

Gets the tip-text for the splitter option.

splitVal() - Method in class weka.classifiers.trees.m5.RuleNode2

Get the split point for this node

SpreadSheet - Class in adams.gui.tools.wekainvestigator.source

For loading ADAMS spreadsheets.

SpreadSheet() - Constructor for class adams.gui.tools.wekainvestigator.source.SpreadSheet

Instantiates the action.

SPREADSHEET - adams.flow.source.wekapackagemanageraction.ListPackages.OutputFormat

spreadSheetColumnInserted(SpreadSheetColumnInsertionEvent) - Method in class adams.ml.data.InstanceView

A column got inserted.

SpreadSheetContainer - Class in adams.gui.tools.wekainvestigator.data

SpreadSheet-based dataset.

SpreadSheetContainer(SpreadSheetReader, PlaceholderFile) - Constructor for class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer

Loads the data using the specified reader.

SpreadSheetContainer(SpreadSheetReader, File) - Constructor for class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer

Loads the data using the specified reader.

SpreadSheetLoader - Class in weka.core.converters

Loads a CSV file using an ADAMS spreadsheet reader and converts it into an Instances object.

SpreadSheetLoader() - Constructor for class weka.core.converters.SpreadSheetLoader

default constructor

SpreadSheetSaver - Class in weka.core.converters

Writes the Instances to a spreadsheet file using the specified ADAMS spreadsheet writer.

SpreadSheetSaver() - Constructor for class weka.core.converters.SpreadSheetSaver

Constructor

SpreadSheetToWekaInstances - Class in adams.data.conversion

Generates a weka.core.Instances object from a SpreadSheet object.
If there are too many unique lables for a NOMINAL attribute, it gets turned into a STRING attribute (see 'maxLabels' property).

SpreadSheetToWekaInstances() - Constructor for class adams.data.conversion.SpreadSheetToWekaInstances

spreadSheetTypeTipText() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet

Returns the tip text for this property.

spreadSheetWriterTipText() - Method in class weka.core.converters.SpreadSheetSaver

Returns the tip text for this property

sqDifference(int, double, double) - Method in class weka.core.SAXDistance

Returns the squared difference of two values of an attribute.

sqDifference(int, double, double) - Method in class weka.core.WeightedEuclideanDistance

Returns the squared difference of two values of an attribute.

sqDifference(int, double, double) - Method in class weka.core.WeightedEuclideanDistanceRidge

Returns the squared difference of two values of an attribute.

SqlPanel - Class in weka.gui.explorer

A simple demonstration for extending the Explorer by another tab, in this case the SqlViewer (as an extra tab instead of only the button in the PreprocessPanel).

SqlPanel() - Constructor for class weka.gui.explorer.SqlPanel

initializes the panel

SqlViewer - Class in adams.gui.menu

Opens the SQL viewer.

SqlViewer() - Constructor for class adams.gui.menu.SqlViewer

Initializes the menu item with no owner.

SqlViewer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.SqlViewer

Initializes the menu item.

squaredDistance(double[], double[]) - Method in class weka.classifiers.functions.GPD

Computes the squared distance.

stableSort(int) - Method in class weka.core.InstancesView

Sorts the instances based on an attribute, using a stable sort.

STANDARDIZE - adams.data.instancesanalysis.pls.PreprocessingType

startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Starts the evaluation.

startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Starts the evaluation.

startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Starts the evaluation.

startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Starts the evaluation.

startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Starts the evaluation.

startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Generates PCA visualization.

startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Generates PLS visualization.

startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Starts the filtering.

startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Generates PCA visualization.

startExecution() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Starts the execution.

startExecution(InvestigatorJob) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Starts a job.

startExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Starts the job.

startExecutorPool() - Method in class weka.classifiers.meta.SubsetEnsemble

Start the pool of execution threads.

startExecutorPool() - Method in class weka.classifiers.meta.VotedImbalance

Start the pool of execution threads.

startExecutorPool() - Method in class weka.clusterers.SAXKMeans

Start the pool of execution threads

startExperiment() - Method in class weka.gui.explorer.ExperimentPanel

Starts running the currently configured classifier with the current settings in an experiment.

stateChanged(ChangeEvent) - Method in class adams.gui.tools.wekainvestigator.tab.DataTab

Gets called when the data in the table changed.

stateChanged(ChangeEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab

Gets called when the data in the table changed.

stateChanged(ChangeEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationChangeListener

STATISTIC - Static variable in class weka.classifiers.meta.ClassifierCascade

statisticIsMaximisable(String) - Method in class weka.classifiers.evaluation.Bias

True if the optimum value of the named metric is a maximum value; false if the optimim value is a minimum value.

statisticIsMaximisable(String) - Method in class weka.classifiers.evaluation.MSLE

True if the optimum value of the named metric is a maximum value; false if the optimim value is a minimum value.

statisticIsMaximisable(String) - Method in class weka.classifiers.evaluation.SDR

True if the optimum value of the named metric is a maximum value; false if the optimim value is a minimum value.

Statistics - Class in adams.flow.transformer.wekarepeatedcrossvalidationoutput

Generates mean/stddev for the specified statistics.

Statistics - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated

Generates statistics for repeated cross-validation runs.

Statistics() - Constructor for class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Statistics() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

StatisticsTable() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.StatisticsTable

statisticsTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics

Returns the tip text for this property.

statisticsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics

Returns the tip text for this property.

statisticTipText() - Method in class adams.flow.transformer.WekaInstancesStatistic

Returns the tip text for this property.

statisticTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Returns the tip text for this property.

statisticTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Returns the tip text for this property.

statisticTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Returns the tip text for this property.

statisticTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the tip text for this property.

statisticTipText() - Method in class weka.classifiers.meta.ClassifierCascade

Returns the tip text for this property.

statisticValuesTipText() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the tip text for this property.

statisticValuesTipText() - Method in class adams.flow.transformer.WekaEvaluationValues

Returns the tip text for this property.

statisticValueTipText() - Method in class adams.flow.transformer.WekaEvaluationValuePicker

Returns the tip text for this property.

stdDev(int, Instances) - Static method in class weka.classifiers.trees.m5.Rule2

Returns the standard deviation value of the supplied attribute index.

stdDevs() - Method in class weka.filters.supervised.attribute.PLSFilterExtended

the standard deviation of the class

stdDevTipText() - Method in class weka.classifiers.meta.InputSmearing

Returns the tip text for this property

stdDevTipText() - Method in class weka.filters.unsupervised.attribute.InputSmearing

Returns the tip text for this property

STDEV - adams.flow.transformer.WekaInstancesInfo.InfoType

the stdev (selected attribute, only numeric).

stop() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Stops the execution of the algorithm.

stopExecution() - Method in class adams.flow.source.WekaSelectObjects

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaClassifierRanker

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaExperimentExecution

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaRandomSplit

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaSplitGenerator

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

Stops the execution.

stopExecution() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Stops the evaluation.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Stops the evaluation.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Stops the evaluation.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Stops the evaluation.

stopExecution() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment.CrossValidationExperimentJob

Stops the execution.

stopExecution() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Stops the execution.

stopExecution() - Method in class adams.multiprocess.WekaCrossValidationExecution

Stops the execution.

stopExecution() - Method in class adams.multiprocess.WekaCrossValidationJob

Stops the execution.

stopExecution() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Stops the execution of the algorithm.

stopExecution() - Method in class weka.classifiers.evaluation.StoppableEvaluation

Stops the execution.

stopExecution() - Method in class weka.classifiers.lazy.LWLSynchro

Stops the execution.

stopExecution() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Stops the execution.

stopExecution() - Method in class weka.classifiers.meta.FilteredClassifierExt

Stops the execution.

stopExecution() - Method in class weka.classifiers.MultiLevelSplitGenerator

Stops the execution.

stopExecution() - Method in class weka.classifiers.StoppableClassifier

Stops the execution.

stopExecution() - Method in class weka.classifiers.StoppableEvaluation

Stops the execution.

stopExecution() - Method in class weka.classifiers.StoppableRandomizableClassifier

Stops the execution.

stopExecution() - Method in class weka.classifiers.StoppableSingleClassifierEnhancer

Stops the execution.

stopExperiment() - Method in class weka.gui.explorer.ExperimentPanel

Stops the currently running experiment (if any).

stopFlowIfCanceledTipText() - Method in class adams.flow.source.WekaSelectDataset

Returns the tip text for this property.

stopModeTipText() - Method in class adams.flow.source.WekaSelectDataset

Returns the tip text for this property.

StoppableClassifier - Class in weka.classifiers

Ancestor for classifiers that can be stopped.

StoppableClassifier() - Constructor for class weka.classifiers.StoppableClassifier

StoppableEvaluation - Class in weka.classifiers.evaluation

Extended Evaluation class that can stop its evaluation processes better.

StoppableEvaluation - Class in weka.classifiers

Extended Evaluation class that can stop its evaluation processes better.

StoppableEvaluation(Instances) - Constructor for class weka.classifiers.evaluation.StoppableEvaluation

Initializes all the counters for the evaluation.

StoppableEvaluation(Instances) - Constructor for class weka.classifiers.StoppableEvaluation

Initializes all the counters for the evaluation.

StoppableEvaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.evaluation.StoppableEvaluation

Initializes all the counters for the evaluation and also takes a cost matrix as parameter.

StoppableEvaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.StoppableEvaluation

Initializes all the counters for the evaluation and also takes a cost matrix as parameter.

StoppableRandomizableClassifier - Class in weka.classifiers

Ancestor for randomizable classifiers that can be stopped.

StoppableRandomizableClassifier() - Constructor for class weka.classifiers.StoppableRandomizableClassifier

StoppableSingleClassifierEnhancer - Class in weka.classifiers

Stops the base classifier if it implements Stoppable.

StoppableSingleClassifierEnhancer() - Constructor for class weka.classifiers.StoppableSingleClassifierEnhancer

storageNameTipText() - Method in class adams.data.conversion.MapToWekaInstance

Returns the tip text for this property.

storageNameTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Returns the tip text for this property.

storageTipText() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns the tip text for this property.

storeColorInReport(int[], String) - Method in class adams.gui.visualization.instance.InstancePanel

Stores the color of the container in the report of container's data object.

storeFilenameTipText() - Method in class adams.flow.transformer.WekaTextDirectoryReader

Returns the tip text for this property.

storeSetup(Instances) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Generates a Properties file that stores information on the setup of the genetic algorithm.

storeSetup(Instances, AbstractGeneticAlgorithm.GeneticAlgorithmJob) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Generates a Properties file that stores information on the setup of the genetic algorithm.

storeSetup(Instances, AbstractGeneticAlgorithm.GeneticAlgorithmJob) - Method in class adams.opt.genetic.DarkLord

Generates a Properties file that stores information on the setup of the genetic algorithm.

storeValueInReport(int[], AbstractField, Object) - Method in class adams.gui.visualization.instance.InstancePanel

Stores the value in the report of container's data object.

stratifyTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator

Returns the tip text for this property.

stratifyTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator

Returns the tip text for this property.

stratifyTipText() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

stratifyTipText() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns the tip text for this property.

stratifyTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns the tip text for this property.

stratifyTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns the tip text for this property.

stratStep(int) - Method in class weka.core.InstancesView

Help function needed for stratification of set.

strictTipText() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the tip text for this property.

STRING_ATTRIBUTES - adams.flow.core.Capability

can handle string attributes.

STRING_CLASS - adams.flow.core.Capability

can handle string classes.

StringAttributeGroupExtractor(int, String, String) - Constructor for class adams.data.binning.BinnableInstances.StringAttributeGroupExtractor

Initializes the extractor.

stringFreeStructure() - Method in class weka.core.InstancesView

Create a copy of the structure.

StringToDate - Class in weka.filters.unsupervised.attribute

Parses the selected range of string attributes using the specified format and turns them into date ones.

StringToDate() - Constructor for class weka.filters.unsupervised.attribute.StringToDate

stringToIntArray(String) - Method in class adams.opt.genetic.Hermione

Converts the bit string into an int array.

stringValue(int) - Method in class weka.core.AbstractHashableInstance

Returns the value of a nominal, string, date, or relational attribute for the instance as a string.

stringValue(Attribute) - Method in class weka.core.AbstractHashableInstance

Returns the value of a nominal, string, date, or relational attribute for the instance as a string.

submitJob(Runnable) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Submits the job.

SubRange - Class in adams.flow.transformer.wekaevaluationpostprocessor

Generates an Evaluation object based on the actual class values that fall within the specified interval ranges.

SubRange() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.SubRange

SubRangeEvaluation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.history

Generates a fake evaluation using only predictions with an actual class value that fits in the specified sub-range.

SubRangeEvaluation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold

Generates a fake evaluation using only predictions with an actual class value that fits in the specified sub-range.

SubRangeEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation

SubRangeEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation

subsampleRatioTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the subsampleRatio option.

subset(double[], int[]) - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic

Returns the subset of the values.

subset(List<Instances>, int, boolean) - Method in class weka.classifiers.MultiLevelSplitGenerator

Generates the subset: either the specified index of the rest.

SubsetEnsemble - Class in weka.classifiers.meta

Generates an ensemble using the following approach:
- for each attribute apart from class attribute do:
* create new dataset with only this feature and the class attribute
* remove all instances that contain a missing value
* if no instances left in subset, don't build a classifier for this feature
* if at least 1 instance is left in subset, build base classifier with it
If no classifier gets built at all, use ZeroR as backup model, built on the full dataset.
In addition to the default feature for a subset, a number of random features can be added to the subset before the classifier is trained.
At prediction time, the Vote meta-classifier (using the pre-built classifiers) is used to determing the class probabilities or regression value.

SubsetEnsemble() - Constructor for class weka.classifiers.meta.SubsetEnsemble

subsetSizesOK(Instances, int) - Method in class weka.classifiers.trees.RandomRegressionForest.Node

tests whether the leaf threshold is OK

SUFFIX_NAME - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator

SUFFIX_TYPE - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator

summaryFilterTipText() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter

Gets the tip-text for the pca-filter option.

SumTransformed - Class in weka.classifiers.meta

Finds the base classifier with the best least median squared error.

SumTransformed() - Constructor for class weka.classifiers.meta.SumTransformed

sumXY(Instances) - Method in class weka.classifiers.meta.Corr

Supplementary - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output

Outputs the supplementary data if available.

Supplementary() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary

SUPPLIED - adams.opt.genetic.OutputPrefixType

the supplied prefix.

suppliedPrefixTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns the tip text for this property.

supplyComponent() - Method in class adams.flow.sink.WekaAttributeSummary

Returns the current component.

supplyComponent() - Method in class adams.flow.sink.WekaGraphVisualizer

Returns the current component.

supplyComponent() - Method in class adams.flow.sink.WekaInstancesDisplay

Supplies the component.

supplyComponent() - Method in class adams.flow.sink.WekaTreeVisualizer

Returns the current component.

supplyText() - Method in class adams.flow.sink.WekaInstancesDisplay

Supplies the text.

supplyText() - Method in class adams.flow.sink.WekaInstanceViewer

Supplies the text.

supplyText() - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel

Supplies the text.

supplyText(InstancePanel) - Static method in class adams.flow.sink.WekaInstanceViewer

Returns the displayed instances as ARFF.

SUPPORT - Static variable in class weka.classifiers.meta.ConsensusOrVote

SUPPORT - Static variable in class weka.classifiers.meta.Veto

supportsBatchPredictions() - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor

Returns whether batch predictions are supported.

supportsBatchPredictions() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

Returns whether batch predictions are supported.

supportsBatchPredictions() - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor

Returns whether batch predictions are supported.

supportsBatchPredictions() - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor

Returns whether batch predictions are supported.

supportsClear() - Method in class adams.flow.sink.WekaAttributeSummary

Whether "clear" is supported and shows up in the menu.

supportsClear() - Method in class adams.flow.sink.WekaClassifierErrors

Whether "clear" is supported and shows up in the menu.

supportsClear() - Method in class adams.flow.sink.WekaCostCurve

Whether "clear" is supported and shows up in the menu.

supportsClear() - Method in class adams.flow.sink.WekaGraphVisualizer

Whether "clear" is supported and shows up in the menu.

supportsClear() - Method in class adams.flow.sink.WekaInstancesDisplay

Whether "clear" is supported and shows up in the menu.

supportsClear() - Method in class adams.flow.sink.WekaInstancesPlot

Whether "clear" is supported and shows up in the menu.

supportsClear() - Method in class adams.flow.sink.WekaInstanceViewer

Whether "clear" is supported and shows up in the menu.

supportsClear() - Method in class adams.flow.sink.WekaMarginCurve

Whether "clear" is supported and shows up in the menu.

supportsClear() - Method in class adams.flow.sink.WekaThresholdCurve

Whether "clear" is supported and shows up in the menu.

supportsClear() - Method in class adams.flow.sink.WekaTreeVisualizer

Whether "clear" is supported and shows up in the menu.

supportsFavorites() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Whether the favorites button is shown or not.

supportsFavorites() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel

Whether the favorites button is shown or not.

supportsHeadlessInteraction() - Method in class adams.flow.source.WekaSelectDataset

Returns whether headless interaction is supported.

supportsLimit(Object) - Method in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer

Returns whether a limit is supported by the renderer.

supportsStoreColorInReport() - Method in class adams.gui.visualization.instance.InstancePanel

Returns true if storing the color in the report of container's data object is supported.

supportsStoreValueInReport() - Method in class adams.gui.visualization.instance.InstancePanel

Returns true if storing a value in the report of container's data object is supported.

supportTipText() - Method in class weka.classifiers.meta.ConsensusOrVote

Returns the tip text for this property.

supportTipText() - Method in class weka.classifiers.meta.Veto

Returns the tip text for this property.

SUPPRESS_MODEL_OUTPUT - Static variable in class weka.classifiers.meta.AbstainingCascade

SUPPRESS_MODEL_OUTPUT - Static variable in class weka.classifiers.meta.ConsensusOrVote

SUPPRESS_MODEL_OUTPUT - Static variable in class weka.classifiers.meta.SuppressModelOutput

SUPPRESS_MODEL_OUTPUT - Static variable in class weka.classifiers.meta.ThresholdedBinaryClassification

SUPPRESS_MODEL_OUTPUT - Static variable in class weka.classifiers.meta.Veto

SuppressModelOutput - Class in weka.classifiers.meta

Meta-classifier that enables the user to suppress the model output.
Useful for ensembles, since their output can be extremely long.

SuppressModelOutput() - Constructor for class weka.classifiers.meta.SuppressModelOutput

suppressModelOutputTipText() - Method in class weka.classifiers.meta.AbstainingCascade

Returns the tip text for this property.

suppressModelOutputTipText() - Method in class weka.classifiers.meta.ConsensusOrVote

Returns the tip text for this property.

suppressModelOutputTipText() - Method in class weka.classifiers.meta.SuppressModelOutput

Returns the tip text for this property.

suppressModelOutputTipText() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns the tip text for this property.

suppressModelOutputTipText() - Method in class weka.classifiers.meta.Veto

Returns the tip text for this property.

suppressModelOutputTipText() - Method in class weka.classifiers.meta.VotedImbalance

Returns the tip text for this property.

suppressModelOutputTipText() - Method in interface weka.core.ModelOutputHandler

Returns the tip text for this property.

SVMLightSpreadSheetReader - Class in adams.data.io.input

Reads WEKA datasets in ARFF format and turns them into spreadsheets.

SVMLightSpreadSheetReader() - Constructor for class adams.data.io.input.SVMLightSpreadSheetReader

SVMLightSpreadSheetWriter - Class in adams.data.io.output

Writes a spreadsheet in SVMLight file format.

SVMLightSpreadSheetWriter() - Constructor for class adams.data.io.output.SVMLightSpreadSheetWriter

swap(int, int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel

Swaps the two rows.

swap(int, int) - Method in class weka.core.InstancesView

Swaps two instances in the set.

swapAxesTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

SwapPLS - Class in adams.data.conversion

Swaps one PLS filter for another.

SwapPLS() - Constructor for class adams.data.conversion.SwapPLS

swapRowsAndColumnsTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the tip text for this property.

swapRowsAndColumnsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the tip text for this property.

T

TAB - adams.flow.transformer.WekaInstanceDumper.OutputFormat

tab-separated.

table - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState

the table.

Table() - Constructor for class adams.gui.visualization.instance.InstanceReportFactory.Table

Initializes the table.

Table(Report) - Constructor for class adams.gui.visualization.instance.InstanceReportFactory.Table

Initializes the table.

Table(TableModel) - Constructor for class adams.gui.visualization.instance.InstanceReportFactory.Table

Initializes the table.

TABLE_CHANGED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent

the whole table changed.

tableChanged(TableModelEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

This fine grain notification tells listeners the exact range of cells, rows, or columns that changed.

TableContentPanel - Class in adams.gui.tools.wekainvestigator.output

Panel for exporting the table as spreadsheet.

TableContentPanel(BaseTable, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TableContentPanel

Initializes the panel with the specified textual component.

TableContentPanel(BaseTableWithButtons, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TableContentPanel

Initializes the panel with the specified textual component.

TableContentPanel(SortableAndSearchableTable, boolean, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TableContentPanel

Initializes the panel with the specified textual component.

TableContentPanel(SortableAndSearchableTableWithButtons, boolean, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TableContentPanel

Initializes the panel with the specified textual component.

TableContentPanel(JTable, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TableContentPanel

Initializes the panel with the specified textual component.

tableNameTipText() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the tip text for this property.

TableResultsPanel - Class in adams.gui.tools.wekamultiexperimenter.analysis

Displays the results in a table.

TableResultsPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel

TableState() - Constructor for class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState

TAGS_ALGORITHM - Static variable in class weka.filters.unsupervised.attribute.FastWavelet

the types of algorithm.

TAGS_FILTER - Static variable in class weka.classifiers.functions.GaussianProcessesAdaptive

The filter to apply to the training data

TAGS_FILTER - Static variable in class weka.classifiers.functions.GaussianProcessesNoWeights

The filter to apply to the training data

TAGS_FILTER - Static variable in class weka.classifiers.functions.GaussianProcessesWeighted

The filter to apply to the training data

TAGS_FILTER - Static variable in class weka.classifiers.functions.GPD

The filter to apply to the training data

TAGS_ONEMISSING - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

TAGS_ONEMISSING - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

TAGS_PADDING - Static variable in class weka.filters.unsupervised.attribute.FastWavelet

the types of padding.

TAGS_RULES - Static variable in class weka.classifiers.meta.AbstainVote

combination rules

TAGS_SELECTION - Static variable in class weka.classifiers.functions.LinearRegressionJ

Attribute selection methods

TAGS_SELECTION - Static variable in class weka.clusterers.SAXKMeans

Initialization methods

TAGS_VALUESDIFFER - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

the types of how to handle differing values.

TAGS_VALUESDIFFER - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

the types of how to handle differing values.

templateTipText() - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels

Returns the tip text for this property.

templateTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds

Returns the tip text for this property.

testAttributesTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the tip text for this property.

testBaseTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the tip text for this property.

testBaseTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the tip text for this property.

testDataTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithm

Returns the tip text for this property.

testerTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation

Returns the tip text for this property.

testerTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

Returns the tip text for this property.

TestingHelper - Class in weka.classifiers

Helper class for evaluating models on test data.

TestingHelper() - Constructor for class weka.classifiers.TestingHelper

TestingHelper.TestingUpdateListener - Interface in weka.classifiers

The interface for objects that listen for testing updates.

testingUpdateRequested(Instances, int, int) - Method in interface weka.classifiers.TestingHelper.TestingUpdateListener

Gets called when the testing interval reached or all instances processed.

testInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2

tests the data whether the filter can actually handle it.

testsetTipText() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator

Returns the tip text for this property.

testsetTipText() - Method in class adams.flow.transformer.WekaTestSetEvaluator

Returns the tip text for this property.

testSetTipText() - Method in class weka.filters.unsupervised.instance.AlignDataset

Returns the tip text for this property.

testSetTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the tip text for this property.

testSplitNameTipText() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns the tip text for this property.

testSplitNameTipText() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Returns the tip text for this property.

testTipText() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the tip text for this property.

TextDirectory - Class in adams.gui.tools.wekainvestigator.source

Uses the TextDirectoryLoader to load text documents.

TextDirectory() - Constructor for class adams.gui.tools.wekainvestigator.source.TextDirectory

Instantiates the action.

TextDirectoryLoaderContainer - Class in adams.gui.tools.wekainvestigator.data

Dataset generated by TextDirectoryLoader.

TextDirectoryLoaderContainer(TextDirectoryLoader) - Constructor for class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer

Loads the data using the specified loader.

TextOutput - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.output

Generates textual output.

TextOutput() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput

TextStatistics - Class in adams.gui.tools.wekainvestigator.tab.attseltab.output

Generates basic text statistic.

TextStatistics - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Generates basic text statistic.

TextStatistics - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output

Generates basic text statistic.

TextStatistics() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics

TextStatistics() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics

TextStatistics() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics

TextualContentPanel - Class in adams.gui.tools.wekainvestigator.output

Panel for exporting the textual component as text.

TextualContentPanel(BaseTextAreaWithButtons, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TextualContentPanel

Initializes the panel with the specified textual component.

TextualContentPanel(BaseTextPaneWithButtons, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TextualContentPanel

Initializes the panel with the specified textual component.

TextualContentPanel(JTextComponent, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TextualContentPanel

Initializes the panel with the specified textual component.

ThreadSafeClassifier - Interface in weka.classifiers

Indicator interface for thread-safe classifiers.

ThreadSafeClassifierWrapper - Class in weka.classifiers.meta

Wraps an abstaining classifier and allows turning on/of abstaining.

ThreadSafeClassifierWrapper() - Constructor for class weka.classifiers.meta.ThreadSafeClassifierWrapper

THRESHOLD - adams.flow.sink.WekaThresholdCurve.AttributeName

THRESHOLD - Static variable in class weka.classifiers.meta.ClassifierCascade

THRESHOLD_CHECK - Static variable in class weka.classifiers.meta.ClassifierCascade

thresholdCheckTipText() - Method in class weka.classifiers.meta.ClassifierCascade

Returns the tip text for this property.

ThresholdCurves - Class in weka.gui.visualize.plugins

Displays all the threshold curves (ROC) in a single plot.

ThresholdCurves() - Constructor for class weka.gui.visualize.plugins.ThresholdCurves

ThresholdedBinaryClassification - Class in weka.classifiers.meta

Meta classifier for binary classification problems that allows to specify a minimum probability threshold for one of the labels.

ThresholdedBinaryClassification() - Constructor for class weka.classifiers.meta.ThresholdedBinaryClassification

thresholdsTipText() - Method in class weka.classifiers.meta.VotedImbalance

Returns the tip text for this property.

thresholdTipText() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator

Returns the tip text for this property.

thresholdTipText() - Method in class adams.tools.CompareDatasets

Returns the tip text for this property.

thresholdTipText() - Method in class weka.classifiers.meta.ClassifierCascade

Returns the tip text for this property.

thresholdTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs

Returns the tip text for this property.

thresholdTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel

Returns the tip text for this property.

THRIFTY - weka.classifiers.trees.XGBoost.FeatureSelector

timeoutTipText() - Method in class weka.classifiers.meta.SocketFacade

Returns the tip text for this property.

titleClassDetailsTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the tip text for this property.

titleMatrixTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the tip text for this property.

titleNameColumnTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the tip text for this property.

titleSummaryTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary

Returns the tip text for this property.

titleValueColumnTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet

Returns the tip text for this property.

toAdams(Capabilities.Capability) - Static method in enum adams.flow.core.Capability

Turns the WEKA capability into an ADAMS one.

toAnyDateType() - Method in class adams.ml.data.DataCellView

Returns the date content, null if not a date, time or date/time.

toArray() - Method in class weka.experiment.ResultMatrixAdamsCSV

returns a 2-dimensional array with the prepared data.

toArray(Object) - Method in class adams.core.option.WekaCommandLineHandler

Generates an options array from the specified object.

toArray(List<String>) - Static method in class weka.core.WekaOptionUtils

Turns the list of options into an array.

toBinnableUsingClass(Instances) - Static method in class adams.data.binning.BinnableInstances

Turns Instances into a list of binnables using the class value.

toBinnableUsingIndex(Instances) - Static method in class adams.data.binning.BinnableInstances

Turns Instances into a list of binnables using the instance index.

toBits(double) - Method in class adams.opt.optimise.genetic.PackDataDef.DataInfo

toBoolean() - Method in class adams.ml.data.DataCellView

Checks whether the cell represents a boolean value.

toBufferedImage() - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel

Returns a buffered image.

toBytes(JsonObject) - Method in class weka.classifiers.meta.socketfacade.Simple

Turns the JSON object into bytes.

toCommandLine(Object) - Method in class adams.core.option.WekaCommandLineHandler

Generates a commandline from the specified object.

toCommandLine(Object) - Static method in class weka.core.WekaOptionUtils

Returns the commandline string for the object.

toCSV(Instance) - Method in class weka.classifiers.meta.socketfacade.Simple

Turns the instance into CSV.

toCSV(Instances) - Method in class weka.classifiers.meta.socketfacade.Simple

Turns the instances into CSV.

toCustomStringRepresentation(Object) - Method in class adams.gui.goe.WekaAttributeRangeEditor

Returns a custom string representation of the object.

toCustomStringRepresentation(Object) - Method in class adams.gui.goe.WekaExperimentFileEditor

Returns a custom string representation of the object.

toCustomStringRepresentation(Object) - Method in class adams.gui.goe.WekaUnorderedAttributeRangeEditor

Returns a custom string representation of the object.

toDataset(Instances) - Static method in class adams.ml.data.WekaConverter

Converts a Weka Instances object into an ADAMS Dataset.

toDate() - Method in class adams.ml.data.DataCellView

Returns the date content, null if not a date.

toDateTime() - Method in class adams.ml.data.DataCellView

Returns the date/time content, null if not a date/time.

toDateTimeMsec() - Method in class adams.ml.data.DataCellView

Returns the date/time msec content, null if not a date/time.

toDisplay() - Method in enum adams.flow.core.EvaluationStatistic

Returns the display string, including nominal/numeric if it applies.

toDisplay() - Method in enum adams.flow.core.ExperimentStatistic

Returns the display string.

toDisplay() - Method in enum adams.flow.sink.WekaThresholdCurve.AttributeName

Returns the display string.

toDisplay() - Method in enum adams.flow.transformer.WekaClassifierRanker.Measure

Returns the display string.

toDisplayShort() - Method in enum adams.flow.core.EvaluationStatistic

Returns the display string.

toDouble() - Method in class adams.ml.data.DataCellView

Returns the content as double, if possible.

toDoubleArray() - Method in class adams.data.instance.Instance

Returns the y values as double array.

toDoubleArray() - Method in class weka.core.AbstractHashableInstance

Returns the values of each attribute as an array of doubles.

toDoubleArray(Instance) - Static method in class adams.data.instance.InstanceUtils

Returns the points as double array.

toDoubleArray(List<InstancePoint>) - Static method in class adams.data.instance.InstanceUtils

Returns the points as double array.

toEnumeration(Vector) - Static method in class weka.core.WekaOptionUtils

Returns the option descriptions as an enumeration.

toEvaluationStatistic() - Method in enum adams.opt.genetic.Measure

Converts the measure into EvaluationStatistic.

toFile() - Method in class adams.data.WekaExperimentFile

Returns a file object.

toggleSortAttributeNames() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Toggles the "sort attribute names" option.

toggleUndo() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Toggles the undo state.

toGraphml(String, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML

Converts the dotty string and saves it as graphml file.

toHTML(SpreadSheet) - Static method in class adams.gui.tools.wekainvestigator.output.RunInformationHelper

Turns the run information into an html table.

toInstance() - Method in class adams.data.instance.Instance

Generates a weka instance, if a dataset header is available.

toInstance(Instances, Row) - Static method in class adams.ml.data.WekaConverter

Turns an ADAMS dataset row into a Weka Instance.

toInstances() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the collected results.

toInstances(SpreadSheet) - Method in class adams.data.spreadsheet.filter.WekaFilter

Converts the spreadsheet into an Instances object.

toInstances(TableRowRange) - Method in class adams.gui.visualization.instances.InstancesTable

Returns the data.

toInstances(TableRowRange, boolean) - Method in class adams.gui.visualization.instances.InstancesTable

Returns the data.

toInstances(Dataset) - Static method in class adams.ml.data.WekaConverter

Converts an ADAMS Dataset to Weka Instances.

toInstances(List<Binnable<Instance>>) - Static method in class adams.data.binning.BinnableInstances

Turns a binnable list back into Instances.

toInstances(Instances, Matrix, Matrix) - Static method in class weka.core.matrix.MatrixHelper

returns the X and Y matrix again as Instances object, based on the given header (must have a class attribute set).

toInstances(Instances, Matrix, Matrix) - Method in class weka.filters.supervised.attribute.PLSFilterExtended

Override superclass method, as this cannot deal with multiple y attributes Returns the X and Y matrix again as Instances object, based on the given header (must have a class attribute set).

TokenCleaner - Interface in weka.core.tokenizers.cleaners

Interface for token cleaners.

tokenize(String) - Method in class weka.core.tokenizers.MultiTokenizer

Sets the string to tokenize.

tokenize(String) - Method in class weka.core.tokenizers.PreCleanedTokenizer

Sets the string to tokenize.

TOKENIZER - Static variable in class weka.core.tokenizers.MultiTokenizer

tokenizersTipText() - Method in class weka.core.tokenizers.MultiTokenizer

Returns the tip text for this property.

tolerateHeaderChangesTipText() - Method in class adams.data.instances.AbstractInstanceGenerator

Returns the tip text for this property.

toLong() - Method in class adams.ml.data.DataCellView

Returns the content as long, if possible.

tolTipText() - Method in class adams.data.instancesanalysis.pls.KernelPLS

Returns the tip text for this property

tolTipText() - Method in class adams.data.instancesanalysis.pls.NIPALS

Returns the tip text for this property

tolTipText() - Method in class adams.data.instancesanalysis.pls.PRM

Returns the tip text for this property

tolTipText() - Method in class adams.data.instancesanalysis.pls.SparsePLS

Returns the tip text for this property

toMap(Package) - Static method in class weka.core.WekaPackageUtils

Turns the package into a map.

toMatrix() - Method in class adams.ml.data.InstancesView

Returns the spreadsheet as matrix, with the header as the first row.

toMatrixString(int, int[][], int[], Instances) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Returns a "confusion" style matrix of classes to clusters assignments

toParamsArray(Object) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab

Turns a parameter object into a string array.

topKTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the topK option.

topOfTree() - Method in class weka.classifiers.trees.m5.Rule2

Returns the top of the tree.

toRaw() - Method in enum adams.flow.core.EvaluationStatistic

Returns the raw enum string.

toRaw() - Method in enum adams.flow.core.ExperimentStatistic

Returns the raw enum string.

toRaw() - Method in enum adams.flow.sink.WekaThresholdCurve.AttributeName

Returns the raw enum string.

toRaw() - Method in enum adams.flow.transformer.WekaClassifierRanker.Measure

Returns the raw enum string.

toShortCommandLine(Object) - Method in class adams.core.option.WekaCommandLineHandler

Generates a commandline from the specified object.

toSpreadSheet() - Method in class adams.data.instance.Instance

Returns the content as spreadsheet.

toSpreadSheet() - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel

Returns the content as spreadsheet.

toSpreadSheet() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the collected results.

toSpreadSheet() - Method in class adams.gui.visualization.instances.InstancesTableModel

Returns the content as spreadsheet.

toSpreadSheet(LoggingSupporter, MessageCollection, ResultItem, boolean, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.PredictionHelper

Turns the result item into a spreadsheet with the predictions.

toSpreadSheet(LoggingSupporter, MessageCollection, ResultItem, boolean, boolean, boolean, boolean, boolean, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.PredictionHelper

Turns the result item into a spreadsheet with the predictions.

toSpreadSheet(LoggingSupporter, MessageCollection, Evaluation, int[], SpreadSheet, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.PredictionHelper

Turns the result item into a spreadsheet with the predictions.

toSpreadSheet(LoggingSupporter, MessageCollection, Evaluation, int[], SpreadSheet, boolean, boolean, boolean, boolean, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.PredictionHelper

Turns the result item into a spreadsheet with the predictions.

toSpreadSheet(Instances) - Method in class adams.data.spreadsheet.filter.WekaFilter

Converts the Instances into a SpreadSheet object.

toString() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer

Returns a short string description of the container.

toString() - Method in class adams.data.instance.InstancePoint

Returns a string representation of the point.

toString() - Method in class adams.data.instances.InstanceComparator

Returns a short description of the comparator.

toString() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer

Returns a string representation of the stored data.

toString() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval

Returns the intervals as string.

toString() - Method in class adams.data.weka.predictions.AbstractErrorScaler

Returns the commandline of this object.

toString() - Method in enum adams.flow.core.EvaluationStatistic

Returns the displays string.

toString() - Method in enum adams.flow.core.ExperimentStatistic

Returns the displays string.

toString() - Method in enum adams.flow.sink.WekaThresholdCurve.AttributeName

Returns the display string.

toString() - Method in class adams.flow.transformer.WekaAccumulatedError.SortablePrediction

Returns a string representation of the wrapped prediction.

toString() - Method in enum adams.flow.transformer.WekaClassifierRanker.Measure

Returns the display string.

toString() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob

Returns a string representation of the job.

toString() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute

toString() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob

Returns a string representation of this job.

toString() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob

Returns a string representation of this job.

toString() - Method in class adams.flow.transformer.WekaTrainAssociator.TrainJob

Returns a string representation of this job.

toString() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob

Returns a string representation of this job.

toString() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob

Returns a string representation of this job.

toString() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob

Returns a string representation of this job.

toString() - Method in class adams.gui.event.InstancesSortSetupEvent

Returns a short description of the object.

toString() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Returns a short description of the container.

toString() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Returns just the name of the evaluation.

toString() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem

Returns a short description of the container.

toString() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

Returns a short description of the container.

toString() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Returns a short description of the container.

toString() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Returns a short description of the container.

toString() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Returns a short description of the container.

toString() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

Returns a short description of the container.

toString() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

Returns the name of the panel.

toString() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel

Just returns the name of the panel.

toString() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob

Returns a string representation of this job.

toString() - Method in class adams.gui.visualization.instance.InstanceContainer

Returns a short string representation of the container.

toString() - Method in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer

Returns the name and index of the column as string representation.

toString() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

Returns a short description of the current setup.

toString() - Method in class adams.ml.data.InstancesHeaderRow

Simply returns the internal hashtable of cells as string.

toString() - Method in class adams.multiprocess.WekaCrossValidationJob

Returns a string representation of this job.

toString() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Returns a short string of the algorithm with the currently best fitness.

toString() - Method in class adams.opt.optimise.genetic.PackData

toString() - Method in class adams.opt.optimise.GeneticAlgorithm.GAJob

toString() - Method in class weka.attributeSelection.AbstractPLSAttributeEval

Outputs the underlying linear regression model.

toString() - Method in class weka.attributeSelection.LinearRegressionAttributeEval

Outputs the underlying linear regression model.

toString() - Method in class weka.classifiers.AbstractSplitGenerator

Returns a short description of the generator.

toString() - Method in class weka.classifiers.AggregateEvaluations

Returns a short description of current state.

toString() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator

Returns a short description of the generator.

toString() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator

Returns a short description of the generator.

toString() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator

Returns a short description of the generator.

toString() - Method in class weka.classifiers.DefaultRandomSplitGenerator

Returns a short description of the generator.

toString() - Method in class weka.classifiers.functions.ClassificationViaPLS

Returns a string representation of the built model.

toString() - Method in class weka.classifiers.functions.FakeClassifier

Returns a string representation of the built model.

toString() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive

Prints out the classifier.

toString() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights

Prints out the classifier.

toString() - Method in class weka.classifiers.functions.GaussianProcessesWeighted

Prints out the classifier.

toString() - Method in class weka.classifiers.functions.GeneticAlgorithm

Returns a string representation of the built model.

toString() - Method in class weka.classifiers.functions.GPD

Prints out the classifier.

toString() - Method in class weka.classifiers.functions.LinearRegressionJ

Outputs the linear regression model as a string.

toString() - Method in class weka.classifiers.functions.MathExpressionClassifier

Returns a string representation of the built model.

toString() - Method in class weka.classifiers.functions.PLSClassifierWeighted

returns a string representation of the classifier

toString() - Method in class weka.classifiers.functions.PLSWeighted

returns a string representation of the classifier

toString() - Method in class weka.classifiers.functions.PyroProxy

Returns a short description of the classifier.

toString() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess

Returns a description of this classifier as a string

toString() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator

Returns a short description of the generator.

toString() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator

Returns a short description of the generator.

toString() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator

Returns a short description of the generator.

toString() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues

Returns a short description of the generator.

toString() - Method in class weka.classifiers.GroupedRandomSplitGenerator

Returns a short description of the generator.

toString() - Method in class weka.classifiers.lazy.AbstainingLWL

Returns a description of this classifier.

toString() - Method in class weka.classifiers.lazy.LWLDatasetBuilder.LWLContainer

Outputs distances and original indices.

toString() - Method in class weka.classifiers.lazy.LWLDatasetBuilder

Returns a short string description of the setup.

toString() - Method in class weka.classifiers.lazy.LWLSynchro

Returns a description of this classifier.

toString() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter

Returns a description of this classifier.

toString() - Method in class weka.classifiers.lazy.LWLSynchroSplit

Returns a description of this classifier.

toString() - Method in class weka.classifiers.LeaveOneOutByValueGenerator

Returns a short description of the generator.

toString() - Method in class weka.classifiers.meta.AbstainAttributePercentile

Returns description of classifier.

toString() - Method in class weka.classifiers.meta.AbstainAverage

Output a representation of this classifier

toString() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights

Output a representation of this classifier

toString() - Method in class weka.classifiers.meta.AbstainingCascade

Outputs the ensemble model.

toString() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Returns the model.

toString() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

Returns description of classifier.

toString() - Method in class weka.classifiers.meta.AbstainMinimumProbability

Returns the model.

toString() - Method in class weka.classifiers.meta.AbstainVote

Output a representation of this classifier

toString() - Method in class weka.classifiers.meta.ClassificationViaRegressionD

Prints the classifiers.

toString() - Method in class weka.classifiers.meta.ClassifierCascade

Outputs a short description of the classifier model.

toString() - Method in class weka.classifiers.meta.ConsensusOrVote

Outputs the ensemble model.

toString() - Method in class weka.classifiers.meta.Corr

Returns description of classifier.

toString() - Method in class weka.classifiers.meta.Fallback

Returns a description of the model.

toString() - Method in class weka.classifiers.meta.HighLowSplit

Returns description of classifier.

toString() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier

Returns description of classifier.

toString() - Method in class weka.classifiers.meta.LeastMedianSq

Returns description of classifier.

toString() - Method in class weka.classifiers.meta.LogClassRegressor

Returns description of classifier.

toString() - Method in class weka.classifiers.meta.LogTargetRegressor

Returns description of classifier.

toString() - Method in class weka.classifiers.meta.MinMaxLimits

Returns description of classifier.

toString() - Method in class weka.classifiers.meta.PeakTransformed

Returns description of classifier.

toString() - Method in class weka.classifiers.meta.RangeCheck

Output a representation of this classifier

toString() - Method in class weka.classifiers.meta.SocketFacade

Just returns the commandline options.

toString() - Method in class weka.classifiers.meta.SubsetEnsemble

Returns a string representation of the classifier.

toString() - Method in class weka.classifiers.meta.SumTransformed

Returns description of classifier.

toString() - Method in class weka.classifiers.meta.SuppressModelOutput

Returns a string representation of the model.

toString() - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper

Returns the model.

toString() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification

Returns the classifier's model.

toString() - Method in class weka.classifiers.meta.Veto

Outputs the ensemble model.

toString() - Method in class weka.classifiers.meta.VotedImbalance

Returns a string representation of the classifier.

toString() - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper

Returns a string representation of the base classifier.

toString() - Method in class weka.classifiers.MultiLevelSplitGenerator

Returns a short description of the generator.

toString() - Method in interface weka.classifiers.SplitGenerator

Returns a short description of the generator.

toString() - Method in class weka.classifiers.trees.m5.M5Base2

Returns a description of the classifier

toString() - Method in class weka.classifiers.trees.m5.Rule2

Return a description of the m5 tree or rule

toString() - Method in class weka.classifiers.trees.m5.RuleNode2

print the linear model at this node

toString() - Method in class weka.classifiers.trees.RandomModelTrees

toString() - Method in class weka.classifiers.trees.RandomRegressionForest

Returns description of the classifier.

toString() - Method in class weka.classifiers.trees.XGBoost

Returns a description of this classifier.

toString() - Method in class weka.clusterers.SAXKMeans

return a string describing this clusterer.

toString() - Method in class weka.core.AbstractHashableInstance

Returns the value of the Instance's toString() method.

toString() - Method in class weka.core.InstanceGrouping

Returns the groups and their indices.

toString(int) - Method in class weka.core.AbstractHashableInstance

Returns the description of one value of the instance as a string.

toString(int, int) - Method in class weka.core.AbstractHashableInstance

Returns the description of one value of the instance as a string.

toString(int, StringBuffer, List<String>) - Method in class weka.classifiers.trees.RandomRegressionForest.Node

Generates a string representation of the node.

toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaAttributeIndexParsing

Returns the object as string.

toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaAttributeRangeParsing

Returns the object as string.

toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaExperimentFileParsing

Returns the file as string.

toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaLabelIndexParsing

Returns the object as string.

toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaLabelRangeParsing

Returns the object as string.

toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaUnorderedAttributeRangeParsing

Returns the object as string.

toString(AbstractOption, Object) - Static method in enum adams.flow.core.EvaluationStatistic

Returns the enum as string.

toString(AbstractOption, Object) - Static method in enum adams.flow.core.ExperimentStatistic

Returns the enum as string.

toString(AbstractOption, Object) - Static method in enum adams.flow.sink.WekaThresholdCurve.AttributeName

Returns the enum as string.

toString(AbstractOption, Object) - Static method in enum adams.flow.transformer.WekaClassifierRanker.Measure

Returns the enum as string.

toString(SpreadSheet) - Static method in class adams.gui.tools.wekainvestigator.output.RunInformationHelper

Turns the run information into a string representation.

toString(SpreadSheet) - Method in class weka.experiment.ResultMatrixAdamsCSV

Turns the spreadsheet into a string.

toString(Object) - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Not used.

toString(Object) - Method in class adams.gui.goe.WekaGenericObjectEditorPanel

Converts the value into its string representation.

toString(Attribute) - Method in class weka.core.AbstractHashableInstance

Returns the description of one value of the instance as a string.

toString(Attribute, int) - Method in class weka.core.AbstractHashableInstance

Returns the description of one value of the instance as a string.

toStringHeader() - Method in class weka.experiment.ResultMatrixAdamsCSV

returns the header of the matrix as a string.

toStringHeader() - Method in class weka.experiment.ResultMatrixMediaWiki

returns the header of the matrix as a string.

toStringKey() - Method in class weka.experiment.ResultMatrixAdamsCSV

returns a key for all the col names, for better readability if the names got cut off.

toStringKey() - Method in class weka.experiment.ResultMatrixMediaWiki

returns a key for all the col names, for better readability if the names got cut off.

toStringMatrix() - Method in class weka.experiment.ResultMatrixAdamsCSV

returns the matrix in CSV format.

toStringMatrix() - Method in class weka.experiment.ResultMatrixMediaWiki

returns the matrix in CSV format.

toStringMaxDecimalDigits(int) - Method in class weka.core.AbstractHashableInstance

Returns the description of one instance with any numeric values printed at the supplied maximum number of decimal places.

toStringNoWeight() - Method in class weka.core.AbstractHashableInstance

Returns the description of one instance (without weight appended).

toStringNoWeight(int) - Method in class weka.core.AbstractHashableInstance

Returns the description of one instance (without weight appended).

toStringOLD() - Method in class weka.classifiers.trees.RandomModelTrees

Returns description of the bagged classifier.

toStringRanking() - Method in class weka.experiment.ResultMatrixAdamsCSV

returns the ranking in a string representation.

toStringRanking() - Method in class weka.experiment.ResultMatrixMediaWiki

returns the ranking in a string representation.

toStringSummary() - Method in class weka.experiment.ResultMatrixAdamsCSV

returns the summary as string.

toStringSummary() - Method in class weka.experiment.ResultMatrixMediaWiki

returns the summary as string.

toSummaryString() - Method in class weka.classifiers.evaluation.Bias

Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.

toSummaryString() - Method in class weka.classifiers.evaluation.Dice

Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.

toSummaryString() - Method in class weka.classifiers.evaluation.MSLE

Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.

toSummaryString() - Method in class weka.classifiers.evaluation.RPD

Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.

toSummaryString() - Method in class weka.classifiers.evaluation.RSquared

Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.

toSummaryString() - Method in class weka.classifiers.evaluation.SDR

Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.

toTime() - Method in class adams.ml.data.DataCellView

Returns the time content, null if not a time.

toTimeMsec() - Method in class adams.ml.data.DataCellView

Returns the time/msec content, null if not a time/msec.

toView(int[], int[]) - Method in class adams.ml.data.InstancesView

Creates a view of the spreadsheet with the specified rows/columns.

toWeka(Capability) - Static method in enum adams.flow.core.Capability

Turns the ADAMS capability into a WEKA one.

TP_RATE - adams.flow.sink.WekaThresholdCurve.AttributeName

Train - Class in adams.gui.tools.wekainvestigator.tab.associatetab.evaluation

Builds an associator on a dataset.

Train - Class in adams.gui.tools.wekainvestigator.tab.attseltab.evaluation

Performs attribute selection on the train data.

Train() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

Train() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

TRAIN_TEST_SPLIT_ORDER_PRESERVED - adams.flow.sink.WekaExperimentGenerator.EvaluationType

train/test split order preserved.

TRAIN_TEST_SPLIT_RANDOMIZED - adams.flow.sink.WekaExperimentGenerator.EvaluationType

train/test split randomized.

TrainableColumnFinder - Interface in adams.data.weka.columnfinder

Interface for ColumnFinder algorithms that can be trained.

TrainableRowFinder - Interface in adams.data.weka.rowfinder

Interface for RowFinder algorithms that can be trained.

trainColumnFinder(Instances) - Method in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder

Trains the column finder with the specified dataset.

trainColumnFinder(Instances) - Method in interface adams.data.weka.columnfinder.TrainableColumnFinder

Trains the column finder with the specified dataset.

TrainJob(Associator, Instances) - Constructor for class adams.flow.transformer.WekaTrainAssociator.TrainJob

Initializes the job.

trainRowFinder(Instances) - Method in class adams.data.weka.rowfinder.AbstractTrainableRowFinder

Trains the row finder with the specified dataset.

trainRowFinder(Instances) - Method in interface adams.data.weka.rowfinder.TrainableRowFinder

Trains the row finder with the specified dataset.

trainSplitNameTipText() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation

Returns the tip text for this property.

trainSplitNameTipText() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions

Returns the tip text for this property.

TrainTestSet - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation

Uses dedicated train/test sets.

TrainTestSet - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation

Uses dedicated train/test sets.

TrainTestSet() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

TrainTestSet() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

TrainTestSplit - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation

Uses a (random) percentage split to generate train/test.

TrainTestSplit - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation

Uses a (random) percentage split to generate train/test.

TrainTestSplit() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

TrainTestSplit() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

TrainTestSplitExperiment - Class in adams.gui.tools.wekamultiexperimenter.experiment

Performs train-test splits.

TrainTestSplitExperiment() - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment

TrainTestSplitExperiment.TrainTestSplitExperimentJob - Class in adams.gui.tools.wekamultiexperimenter.experiment

TrainTestSplitExperimentJob(TrainTestSplitExperiment, int, Classifier, Instances) - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment.TrainTestSplitExperimentJob

Initializes the run.

TrainTestSplitSetup - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.setup

Setup for a train/test-split experiment.

TrainTestSplitSetup() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

trainTipText() - Method in class adams.flow.transformer.WekaClassifierRanker

Returns the tip text for this property.

TrainValidateTestSet - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation

Uses dedicated train/validate/test sets.

TrainValidateTestSet() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

transferAdditionalAttributes(SelectOptionPanel, Instances) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation

Transfers the additional attributes into a spreadsheet.

transferCapability(Capabilities, Capabilities.Capability, Capabilities, Capability) - Static method in class adams.ml.data.WekaConverter

Transfers the specified capability if enabled.

transform(Instance) - Method in class weka.classifiers.meta.LogClassRegressor

Transform instance.

transform(Instance) - Method in class weka.classifiers.meta.LogTargetRegressor

Transform instance.

transform(Instance) - Method in class weka.core.SAXDistance

transform(Instance) - Method in class weka.core.WeightedEuclideanDistance

transform(Instance) - Method in class weka.core.WeightedEuclideanDistanceRidge

transform(Instances) - Method in class adams.data.instancesanalysis.pls.AbstractPLS

Transforms the data, initializes if necessary.

transformInstance(Instance) - Method in class weka.classifiers.meta.PeakTransformed

Just finds the maximum peak.

transformInstance(Instance) - Method in class weka.classifiers.meta.SumTransformed

Just sums up all the peaks.

transformInstance(Instance) - Method in class weka.core.neighboursearch.FilteredSearch

transformInstance(Instance) - Method in class weka.core.neighboursearch.PCANNSearch

transformInstance(Instance) - Method in class weka.core.neighboursearch.PLSNNSearch

transformInstance(Instance) - Method in class weka.core.neighboursearch.TransformNNSearch

transformInstances(Instances) - Method in class weka.core.neighboursearch.FilteredSearch

transformInstances(Instances) - Method in class weka.core.neighboursearch.PCANNSearch

transformInstances(Instances) - Method in class weka.core.neighboursearch.PLSNNSearch

TransformNNSearch - Class in weka.core.neighboursearch

TransformNNSearch() - Constructor for class weka.core.neighboursearch.TransformNNSearch

TransformNNSearch(Instances) - Constructor for class weka.core.neighboursearch.TransformNNSearch

TREE - weka.classifiers.trees.XGBoost.NormaliseType

TreeGraphML - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Displays the GraphML source code of the tree graph.

TreeGraphML() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML

treeMethodTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the treeMethod option.

treeToString(int) - Method in class weka.classifiers.trees.m5.RuleNode2

Recursively builds a textual description of the tree

TreeVisualizer - Class in adams.gui.menu

Displays data in the tree visualizer.

TreeVisualizer - Class in adams.gui.tools.previewbrowser

Displays trees in dot notation.

TreeVisualizer - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output

Displays the tree that the model generated.

TreeVisualizer() - Constructor for class adams.gui.menu.TreeVisualizer

Initializes the menu item with no owner.

TreeVisualizer() - Constructor for class adams.gui.tools.previewbrowser.TreeVisualizer

TreeVisualizer() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeVisualizer

TreeVisualizer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.TreeVisualizer

Initializes the menu item.

trialsTipText() - Method in class weka.classifiers.trees.RandomModelTrees

Returns the tip text for this property.

TRIANGLE - adams.gui.visualization.instance.InstanceLinePaintlet.MarkerShape

a triangle.

trimIDs(List<String>) - Method in class adams.gui.visualization.instance.InstanceComparePanel

Removes the leading 0s.

TRUE_NEG - adams.flow.sink.WekaThresholdCurve.AttributeName

TRUE_NEG_RATE - adams.opt.genetic.Measure

true negative rate.

TRUE_NEGATIVE_RATE - adams.flow.core.EvaluationStatistic

TRUE_NEGATIVE_RATE - adams.flow.core.ExperimentStatistic

TRUE_POS - adams.flow.sink.WekaThresholdCurve.AttributeName

TRUE_POS_RATE - adams.opt.genetic.Measure

true positive rate.

TRUE_POSITIVE_RATE - adams.flow.core.EvaluationStatistic

TRUE_POSITIVE_RATE - adams.flow.core.ExperimentStatistic

TURN_OFF_ABSTAINING - Static variable in class weka.classifiers.meta.AbstainingClassifierWrapper

turnChecksOff() - Method in class weka.classifiers.functions.LinearRegressionJ

Turns off checks for missing values, etc.

turnChecksOn() - Method in class weka.classifiers.functions.LinearRegressionJ

Turns on checks for missing values, etc.

turnIntoLeaf(Instances) - Method in class weka.classifiers.trees.RandomRegressionForest.Node

turns the node into a leaf

turnOffAbstainingTipText() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper

Returns the tip text for this property

TWEEDIE_REGRESSION - weka.classifiers.trees.XGBoost.Objective

tweedieVariancePowerTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the tweedieVariancePower option.

TYPE - Static variable in class weka.filters.unsupervised.attribute.NominalToNumeric

typeTipText() - Method in class adams.flow.transformer.WekaClassifierInfo

Returns the tip text for this property.

typeTipText() - Method in class adams.flow.transformer.WekaClustererInfo

Returns the tip text for this property.

typeTipText() - Method in class adams.flow.transformer.WekaEvaluationInfo

Returns the tip text for this property.

typeTipText() - Method in class adams.flow.transformer.WekaExtractArray

Returns the tip text for this property.

typeTipText() - Method in class adams.flow.transformer.WekaInstancesInfo

Returns the tip text for this property.

typeTipText() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric

Returns the tip text for this property.

U

UI_DIVIDERLOCATION - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane

UNARY_ATTRIBUTES - adams.flow.core.Capability

can handle unary attributes.

UNARY_CLASS - adams.flow.core.Capability

can handle unary classes.

undo() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

Performs an undo if possible.

undo() - Method in class adams.gui.visualization.instances.InstancesTable

undoes the last action

undo() - Method in class adams.gui.visualization.instances.InstancesTableModel

undoes the last action

undo() - Method in class weka.gui.explorer.ExplorerExt

Performs an undo.

undo(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable

Performs undo on the selected rows.

UNDO_DISABLED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent

undo disabled.

UNDO_ENABLED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent

undo enabled.

undoOccurred(UndoEvent) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer

An undo event, like add or remove, has occurred.

undoOccurred(UndoEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

An undo event, like add or remove, has occurred.

unhandledInputType(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction

Adds an error message that the input type is not supported.

UNIFORM - weka.classifiers.trees.XGBoost.SampleType

Uninstall - Class in adams.flow.transformer.wekapackagemanageraction

Action that removes installed packages.

Uninstall() - Constructor for class adams.flow.transformer.wekapackagemanageraction.Uninstall

uniqueIDTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID

Gets the tip-text for the unique ID option.

uniqueIDTipText() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the tip text for this property.

unprunedTipText() - Method in class weka.classifiers.trees.m5.M5Base2

Returns the tip text for this property

unquoteAttribute(String) - Method in class weka.core.converters.SimpleArffLoader

Unquotes the attribute name.

unsetTipText() - Method in class adams.flow.transformer.WekaClassSelector

Returns the tip text for this property.

UNWEIGHTED_MACRO_F_MEASURE - adams.flow.core.EvaluationStatistic

UNWEIGHTED_MICRO_F_MEASURE - adams.flow.core.EvaluationStatistic

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Append

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Compatibility

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Copy

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Merge

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Randomize

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.RemoveTestSet

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Rename

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Revert

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Save

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Split

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup

Updates the settings panel.

update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToDate

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToNominal

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToString

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.Remove

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.Rename

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ReorderAttributes

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.UseAsClass

Updates the action.

update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel

Updates the display.

update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel

Updates the display.

update() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel

Updates the GUI.

update() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Updates the GUI.

update() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner

Updates the owner's state.

update() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel

Performs GUI updates.

update() - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel

Updates the buttons.

update() - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel

Updates the buttons.

update() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel

Updates buttons, etc.

update() - Method in class adams.gui.visualization.instances.InstancesColumnComboBox

Updates the content of the combobox.

update() - Method in class adams.gui.visualization.instances.InstancesPanel

Updates the combobox.

update() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

Resets the comboboxes.

update() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel

Updates the display.

update() - Method in class weka.gui.explorer.ExplorerExt

Updates title and menu items.

update(AbstractEnvironment) - Method in class adams.env.InstanceCompareDefinition

Updates the environment object with its definition for the props file (whether to add/replace/etc the values).

update(AbstractEnvironment) - Method in class adams.env.InstanceExplorerDefinition

Updates the environment object with its definition for the props file (whether to add/replace/etc the values).

update(AbstractEnvironment) - Method in class adams.env.WekaInvestigatorDefinition

Updates the environment object with its definition for the props file (whether to add/replace/etc the values).

update(AbstractEnvironment) - Method in class adams.env.WekaInvestigatorShortcutsDefinition

Updates the environment object with its definition for the props file (whether to add/replace/etc the values).

update(WekaExperimentContainer) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

Updates the item.

update(WekaExperimentContainer, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem

Updates the item.

update(String, Serializable, Clusterer, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Updates the item.

update(AssociatorEvaluation, Associator, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem

Updates the item.

update(AttributeSelection, int, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Updates the item.

update(AttributeSelection, int, Instances, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Updates the item.

update(AttributeSelection, Instances, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem

Updates the item.

update(Evaluation, Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Updates the item.

update(Evaluation, Classifier, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Updates the item.

update(Evaluation, Classifier, MetaData, int[], SpreadSheet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Updates the item.

update(Evaluation, Evaluation[], Classifier, Classifier[], MetaData, int[], SpreadSheet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Updates the item.

update(Evaluation, Evaluation[], Evaluation[], Classifier, Classifier[], Classifier[], MetaData, int[], int[][], SpreadSheet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem

Updates the item.

update(ClusterEvaluation, String, Serializable, Clusterer, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Updates the item.

update(ClusterEvaluation, Clusterer, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem

Updates the item.

update(Instance) - Method in class weka.core.neighboursearch.FilteredSearch

Updates the LinearNNSearch to cater for the new added instance.

update(Instance) - Method in class weka.core.neighboursearch.NewNNSearch

Updates the LinearNNSearch to cater for the new added instance.

update(Instance) - Method in class weka.core.neighboursearch.PCANNSearch

Updates the LinearNNSearch to cater for the new added instance.

update(Instance) - Method in class weka.core.neighboursearch.PLSNNSearch

Updates the LinearNNSearch to cater for the new added instance.

UPDATE - weka.classifiers.trees.XGBoost.ProcessType

UPDATE_HEADER - Static variable in class weka.filters.unsupervised.instance.RemoveWithLabels

updateActions() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Updates the actions.

updateAttributes() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Updates the attributes model.

updateAttributeSelection() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

For updating the state of the selected attributes text field and button.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable

Updates the state of the buttons.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab

Updates the buttons.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab

Updates the buttons.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab

Updates the buttons.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab

Updates the buttons.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab

Updates the state of the buttons.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab

Updates the buttons.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab

Updates the buttons.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Updates the buttons.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab

Updates the buttons.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab

Updates the buttons.

updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab

Updates the buttons.

updateButtons() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Updates the buttons.

updateButtons() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel

Updates the enabled status of the buttons.

updateButtons() - Method in class weka.gui.explorer.MultiExplorer

Updates the enabled state of the buttons.

updateCapabilitiesFilter(Capabilities) - Method in class weka.gui.explorer.ExperimentPanel

updates the capabilities filter of the GOE.

updateClassAttribute(Instances) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Updates the class attribute, if not set.

updateClassifier(Instance) - Method in class weka.classifiers.functions.FakeClassifier

Does nothing.

updateClassifier(Instance) - Method in class weka.classifiers.functions.MathExpressionClassifier

Does nothing.

updateComparisonBase() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel

Updates the base of comparison.

updateContainerColorTipText() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet

Returns the tip text for this property.

updateDataTable() - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame

Updates the data in the data table.

updateDisplay() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel

Updates the display.

updateDistance(double, double) - Method in class weka.core.SAXDistance

Updates the current distance calculated so far with the new difference between two attributes.

updateDistance(double, double) - Method in class weka.core.WeightedEuclideanDistance

Updates the current distance calculated so far with the new difference between two attributes.

updateDistance(double, double) - Method in class weka.core.WeightedEuclideanDistanceRidge

Updates the current distance calculated so far with the new difference between two attributes.

updateEditor(PropertyEditor, JComponent, String) - Method in class adams.gui.goe.WekaGenericObjectEditorPopupMenu

Updates the editor using the string.

updateEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel

Displays the specified entry.

updateEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Displays the specified entry.

updateEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel

Displays the specified entry.

updateEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel

Displays the specified entry.

updateEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel

Displays the specified entry.

updateEntry(String) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel.HistoryPanel

Displays the specified entry.

updateEntry(String) - Method in class weka.gui.explorer.ExplorerEntryPanel

Displays the specified entry.

updateEnvironment(List<String>) - Method in class adams.core.management.WekaHomeEnvironmentModifier

Updates the environment variables that the Launcher uses for launching the ADAMS process.

updateExperimentFromMenu(Object) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Updates the experiment using the state of some menu items.

updateFileChooserAccessory(JFileChooser) - Static method in class weka.gui.AdamsHelper

Updates the accessory panel of the filechooser.

updateHeader(Instances) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm

Creates a new dataset, with the setup as the new relation name.

updateHeader(Instances, AbstractGeneticAlgorithm.GeneticAlgorithmJob) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm

Creates a new dataset, with the setup as the new relation name.

updateHeaderTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels

Returns the tip text for this property.

updateIDs() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Updates the list with IDs.

updateIDs(int, Instances, HashSet) - Method in class adams.flow.transformer.WekaInstancesMerge

Updates the IDs in the hashset with the ones stored in the ID attribute of the provided dataset.

updateIntervalTipText() - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater

Returns the tip text for this property.

updateLabels(Attribute) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel

Sets the labels for fields we can determine just from the instance header.

updateListButtons() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage

Updates the enabled state of the buttons.

updateMenu() - Method in class adams.gui.tools.DatasetCompatibilityPanel

updates the enabled state of the menu items.

updateMenu() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

updates the enabled state of the menu items.

updateMenu() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

updates the enabled state of the menu items.

updateMenu() - Method in class adams.gui.visualization.instance.InstanceComparePanel

updates the enabled state of the menu items.

updateMenu() - Method in class adams.gui.visualization.instance.InstanceExplorer

updates the enabled state of the menu items.

updateMenu() - Method in class weka.gui.explorer.ExplorerExt

updates the enabled state of the menu items.

updateMenu(JMenuBar) - Method in class weka.gui.explorer.ExplorerEntryPanel

Updates the menu bar.

updateMenuFromExperiment(Object) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Updates some menu items from the experiment.

updatePanel() - Method in class weka.gui.explorer.ExplorerEntryPanel

Revalidates the panel to make changes visible.

updatePanel(AbstractAnalysisPanel) - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel

Sets the panel as the new analysis panel.

updatePopupMenu(AbstractNamedHistoryPanel, AbstractInvestigatorTab, int[], JPopupMenu, Class) - Static method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem

Updates the menu for the specified superclass of menu items.

updatePopupMenu(PerFoldMultiPagePane, AbstractOutputGenerator, int[], JPopupMenu) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem

Updates the menu.

updateRelationName(File, Instances) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Updates the relation name.

updateRelationNameTipText() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Returns the tip text for this property.

updateRows() - Method in class adams.gui.visualization.instance.InstanceComparePanel

Updates the combobox with the rows.

updaterTipText() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the tip text for this property.

updaterTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the updater option.

updateStatistics(AttributeStats) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel

Sets the gui elements for fields that are stored in the AttributeStats structure.

updateStatistics(AttributeStats, Attribute, boolean) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.StatisticsTable

Creates a tablemodel for the attribute being displayed

updateStatsForClassifier(double[], Instance) - Method in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure

Ignored.

updateStatsForClassifier(double[], Instance) - Method in class weka.classifiers.evaluation.Dice

Updates the statistics about a classifiers performance for the current test instance.

updateStatsForPredictor(double, Instance) - Method in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure

Updates the statistics about a predictors performance for the current test instance.

updateStatsForPredictor(double, Instance) - Method in class weka.classifiers.evaluation.Dice

Updates the statistics about a predictors performance for the current test instance.

updateTitle() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel

Updates the title of the dialog.

updateTitle() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel

Updates the title of the dialog.

updateTitle() - Method in class weka.gui.explorer.ExplorerExt

Updates the title of the dialog.

updateVariables() - Method in class adams.flow.transformer.WekaInstanceDumper

Gets called when the actor needs to be re-setUp when a variable changes.

updateWaitTipText() - Method in class weka.classifiers.functions.FakeClassifier

Returns the tip text for this property.

updateWidgets() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab

Updates the state of the widgets.

updateWidgets() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Updates the enabled state of the buttons/combobox.

UpperStatistic - Enum in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated

Enumeration of upper statistics to compute.

upperTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions

Returns the tip text for this property.

upperTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot

Returns the tip text for this property.

upperTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions

Returns the tip text for this property.

upperTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot

Returns the tip text for this property.

URLTipText() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the tip text for this property.

URLTipText() - Method in class adams.flow.source.WekaDatabaseReader

Returns the tip text for this property.

USE_FIRST_COMPONENT - weka.attributeSelection.AbstractPLSAttributeEval.LoadingsCalculations

useAbsoluteErrorTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the tip text for this property.

useAbsoluteErrorTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Returns the tip text for this property.

UseAsClass - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction

Uses the selected attribute as class attribute.

UseAsClass() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.UseAsClass

Instantiates the action.

useColumnNamesAsClassLabelsTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the tip text for this property.

useCustomLoaderTipText() - Method in class adams.flow.transformer.WekaFileReader

Returns the tip text for this property.

useCustomLoaderTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference

Returns the tip text for this property.

useCustomLoaderTipText() - Method in class weka.filters.unsupervised.instance.AlignDataset

Returns the tip text for this property.

useCustomLoaderTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances

Returns the tip text for this property.

useCustomPaintletTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

useCustomSaverTipText() - Method in class adams.flow.sink.WekaFileWriter

Returns the tip text for this property.

useErrorTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors

Returns the tip text for this property.

useFilenameTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment

Returns the tip text for this property.

useFixedMinMaxTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges

Returns the tip text for this property.

useMedianTipText() - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters

Returns the tip text for this property.

useModelResetVariableTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Returns the tip text for this property.

useOriginalIndicesTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer

Returns the tip text for this property.

useOuterWindowTipText() - Method in class adams.flow.source.WekaSelectDataset

Returns the tip text for this property.

usePrefixTipText() - Method in class adams.flow.transformer.WekaInstancesMerge

Returns the tip text for this property.

useProbabilitiesTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix

Returns the tip text for this property.

USERCPU_TIME_TESTING - adams.flow.core.ExperimentStatistic

USERCPU_TIME_TRAINING - adams.flow.core.ExperimentStatistic

useReducedData(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel

Makes the reduced data available as data container.

useRelationNameAsFilenameTipText() - Method in class adams.flow.sink.WekaFileWriter

Returns the tip text for this property.

useRelationNameAsFilenameTipText() - Method in class adams.flow.transformer.WekaInstanceDumper

Returns the tip text for this property.

useRelationNameAsTableTipText() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the tip text for this property.

userTipText() - Method in class adams.flow.sink.WekaDatabaseWriter

Returns the tip text for this property.

userTipText() - Method in class adams.flow.source.WekaDatabaseReader

Returns the tip text for this property.

useSecondEvaluationTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation

Returns the tip text for this property.

useUndoHandler() - Method in class adams.gui.visualization.instances.InstancesTableModel

Returns whether to use the undo handler.

useUnsmoothedTipText() - Method in class weka.classifiers.trees.m5.M5Base2

Returns the tip text for this property

useViewsTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Returns the tip text for this property.

useViewsTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Returns the tip text for this property.

useViewsTipText() - Method in class weka.classifiers.AbstractSplitGenerator

Returns the tip text for this property.

useWekaEditors() - Static method in class adams.gui.goe.WekaEditorsRegistration

Returns whether Weka editors should be used.

V

value() - Method in annotation type weka.classifiers.trees.XGBoost.XGBoostParameter

The name of the parameter this field corresponds to.

value(int) - Method in class weka.core.AbstractHashableInstance

Returns an instance's attribute value in internal format.

value(Attribute) - Method in class weka.core.AbstractHashableInstance

Returns an instance's attribute value in internal format.

VALUE_ABSTENTION_CLASSIFICATION - Static variable in class adams.flow.container.WekaPredictionContainer

the identifier for the classification of an abstaining classifier.

VALUE_ABSTENTION_CLASSIFICATION_LABEL - Static variable in class adams.flow.container.WekaPredictionContainer

the identifier for the classification label of an abstaining classifier.

VALUE_ABSTENTION_DISTRIBUTION - Static variable in class adams.flow.container.WekaPredictionContainer

the identifier for the distribution of an abstaining classifier.

VALUE_ALGORITHM - Static variable in class adams.flow.container.WekaGeneticAlgorithmInitializationContainer

the identifier for the algorithm instance.

VALUE_AVERAGE_SILHOUETTE_COEFFICIENT - Static variable in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient

the key in the container.

VALUE_CLASSES_TO_CLUSTERS - Static variable in class weka.gui.explorer.ClustererHandler

VALUE_CLASSIFICATION - Static variable in class adams.flow.container.WekaPredictionContainer

the identifier for the Classification.

VALUE_CLASSIFICATION_LABEL - Static variable in class adams.flow.container.WekaPredictionContainer

the identifier for the Classification's label.

VALUE_CLUSTER - Static variable in class adams.flow.container.WekaClusteringContainer

the identifier for the Cluster.

VALUE_CLUSTERED_DATASET - Static variable in class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor

the clustered full dataset.

VALUE_CROSS_VALIDATION - Static variable in class weka.gui.explorer.AttributeSelectionHandler

VALUE_CROSS_VALIDATION - Static variable in class weka.gui.explorer.ClassifierHandler

VALUE_DATA - Static variable in class adams.flow.container.WekaFilterContainer

the identifier for the Data.

VALUE_DATA - Static variable in class adams.flow.container.WekaGeneticAlgorithmInitializationContainer

the identifier for the data.

VALUE_DATASET - Static variable in class adams.flow.container.WekaModelContainer

the identifier for the full dataset.

VALUE_DISTANCES - Static variable in class adams.flow.container.WekaNearestNeighborSearchContainer

the identifier for the distances.

VALUE_DISTRIBUTION - Static variable in class adams.flow.container.WekaClusteringContainer

the identifier for the Distribution.

VALUE_DISTRIBUTION - Static variable in class adams.flow.container.WekaPredictionContainer

the identifier for the Distribution.

VALUE_EVALUATION - Static variable in class adams.flow.container.WekaAttributeSelectionContainer

the identifier for the evaluation object.

VALUE_EVALUATION - Static variable in class adams.flow.container.WekaClusterEvaluationContainer

the identifier for the ClusterEvaluation.

VALUE_EVALUATION - Static variable in class adams.flow.container.WekaEvaluationContainer

the identifier for the Evaluation.

VALUE_EXPERIMENT - Static variable in class adams.flow.container.WekaExperimentContainer

the identifier for the experiment.

VALUE_FILTER - Static variable in class adams.flow.container.WekaFilterContainer

the identifier for the Filter.

VALUE_FITNESS - Static variable in class adams.flow.container.WekaGeneticAlgorithmContainer

the identifier for the fitness.

VALUE_FOLD_COUNT - Static variable in class adams.flow.container.WekaAttributeSelectionContainer

the identifier for the fold count.

VALUE_FOLD_COUNT - Static variable in class adams.flow.container.WekaTrainTestSetContainer

the identifier for the fold count.

VALUE_FOLD_NUMBER - Static variable in class adams.flow.container.WekaTrainTestSetContainer

the identifier for the fold number.

VALUE_HEADER - Static variable in class adams.flow.container.WekaModelContainer

the identifier for the Header.

VALUE_INPUT - Static variable in class adams.flow.container.WekaFilterContainer

the identifier for the Input Data.

VALUE_INSTANCE - Static variable in class adams.flow.container.WekaClusteringContainer

the identifier for the Instance.

VALUE_INSTANCE - Static variable in class adams.flow.container.WekaNearestNeighborSearchContainer

the identifier for the Instance.

VALUE_INSTANCE - Static variable in class adams.flow.container.WekaPredictionContainer

the identifier for the Instance.

VALUE_INSTANCES - Static variable in class adams.flow.container.WekaExperimentContainer

the identifier for the results (instances).

VALUE_LOGDENSITY - Static variable in class adams.flow.container.WekaClusteringContainer

the identifier for the LogDensity.

VALUE_LOGDENSITYPERCLUSTER - Static variable in class adams.flow.container.WekaClusteringContainer

the identifier for the LogDensityPerCluster.

VALUE_LOGJOINTDENSITIES - Static variable in class adams.flow.container.WekaClusteringContainer

the identifier for the LogJointDensities.

VALUE_LOGLIKELIHOOD - Static variable in class adams.flow.container.WekaClusterEvaluationContainer

the identifier for the log-likelihood.

VALUE_MEASURE - Static variable in class adams.flow.container.WekaGeneticAlgorithmContainer

the identifier for the measure.

VALUE_MODEL - Static variable in class adams.flow.container.WekaClusterEvaluationContainer

the identifier for the Model.

VALUE_MODEL - Static variable in class adams.flow.container.WekaEvaluationContainer

the identifier for the Model.

VALUE_MODEL - Static variable in class adams.flow.container.WekaModelContainer

the identifier for the Model.

VALUE_NEIGHBORHOOD - Static variable in class adams.flow.container.WekaNearestNeighborSearchContainer

the identifier for the neighborhood.

VALUE_ORIGINALINDICES - Static variable in class adams.flow.container.WekaEvaluationContainer

the identifier for the original indices.

VALUE_PERCENTAGE_SPLIT - Static variable in class weka.gui.explorer.ClassifierHandler

VALUE_PERCENTAGE_SPLIT - Static variable in class weka.gui.explorer.ClustererHandler

VALUE_PREDICTIONOUTPUT - Static variable in class adams.flow.container.WekaEvaluationContainer

the identifier for the prediction output.

VALUE_RANGECHECK - Static variable in class adams.flow.container.WekaPredictionContainer

the identifier for the Range check.

VALUE_REDUCED - Static variable in class adams.flow.container.WekaAttributeSelectionContainer

the identifier for the reduced data.

VALUE_RULES - Static variable in class adams.flow.container.WekaAssociatorContainer

the identifier for the rules.

VALUE_SEED - Static variable in class adams.flow.container.WekaAttributeSelectionContainer

the identifier for the random seed.

VALUE_SEED - Static variable in class adams.flow.container.WekaTrainTestSetContainer

the identifier for the random seed.

VALUE_SELECTEDATTRIBUTES - Static variable in class adams.flow.container.WekaAttributeSelectionContainer

the identifier for the Remove filter setup.

VALUE_SETUP - Static variable in class adams.flow.container.WekaGeneticAlgorithmContainer

the identifier for the setup.

VALUE_SPREADSHEET - Static variable in class adams.flow.container.WekaExperimentContainer

the identifier for the results (spreadsheet).

VALUE_STATISTICS - Static variable in class adams.flow.container.WekaAttributeSelectionContainer

the identifier for the statistics object.

VALUE_SUPPLIED_TEST_SET - Static variable in class weka.gui.explorer.ClassifierHandler

VALUE_SUPPLIED_TEST_SET - Static variable in class weka.gui.explorer.ClustererHandler

VALUE_TEST - Static variable in class adams.flow.container.WekaAttributeSelectionContainer

the identifier for the test data.

VALUE_TEST - Static variable in class adams.flow.container.WekaTrainTestSetContainer

the identifier for the test data.

VALUE_TEST_ORIGINALINDICES - Static variable in class adams.flow.container.WekaTrainTestSetContainer

the identifier for the original indices (test).

VALUE_TEST_REDUCED - Static variable in class adams.flow.container.WekaAttributeSelectionContainer

the identifier for the reduced data.

VALUE_TEST_TRANSFORMED - Static variable in class adams.flow.container.WekaAttributeSelectionContainer

the identifier for the transformed data.

VALUE_TESTDATA - Static variable in class adams.flow.container.WekaEvaluationContainer

the identifier for the original data.

VALUE_TRAIN - Static variable in class adams.flow.container.WekaAttributeSelectionContainer

the identifier for the training data.

VALUE_TRAIN - Static variable in class adams.flow.container.WekaTrainTestSetContainer

the identifier for the training data.

VALUE_TRAIN_ORIGINALINDICES - Static variable in class adams.flow.container.WekaTrainTestSetContainer

the identifier for the original indices (train).

VALUE_TRAINING_SET - Static variable in class weka.gui.explorer.AttributeSelectionHandler

VALUE_TRAINING_SET - Static variable in class weka.gui.explorer.ClassifierHandler

VALUE_TRAINING_SET - Static variable in class weka.gui.explorer.ClustererHandler

VALUE_TRANSFORMED - Static variable in class adams.flow.container.WekaAttributeSelectionContainer

the identifier for the transformed data.

VALUE_WEIGHTS - Static variable in class adams.flow.container.WekaGeneticAlgorithmContainer

the identifier for the weights.

VALUE_WEIGHTSSTR - Static variable in class adams.flow.container.WekaGeneticAlgorithmContainer

the identifier for the weights string.

valueAtPct(double[], double) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp

Calculates the value at the specified percentage.

valueChanged(ListSelectionEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel

Called whenever the value of the selection changes.

valueIsSmallerEqual(Instance, int, double) - Method in class weka.core.SAXDistance

Returns true if the value of the given dimension is smaller or equal the value to be compared with.

valueIsSmallerEqual(Instance, int, double) - Method in class weka.core.WeightedEuclideanDistance

Returns true if the value of the given dimension is smaller or equal the value to be compared with.

valueIsSmallerEqual(Instance, int, double) - Method in class weka.core.WeightedEuclideanDistanceRidge

Returns true if the value of the given dimension is smaller or equal the value to be compared with.

valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaAttributeIndexParsing

Returns a object generated from the string.

valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaAttributeRangeParsing

Returns a object generated from the string.

valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaExperimentFileParsing

Returns a file generated from the string.

valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaLabelIndexParsing

Returns a object generated from the string.

valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaLabelRangeParsing

Returns a object generated from the string.

valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaUnorderedAttributeRangeParsing

Returns a object generated from the string.

valueOf(AbstractOption, String) - Static method in enum adams.flow.core.EvaluationStatistic

Returns an enum generated from the string.

valueOf(AbstractOption, String) - Static method in enum adams.flow.core.ExperimentStatistic

Returns an enum generated from the string.

valueOf(AbstractOption, String) - Static method in enum adams.flow.sink.WekaThresholdCurve.AttributeName

Returns an enum generated from the string.

valueOf(AbstractOption, String) - Static method in enum adams.flow.transformer.WekaClassifierRanker.Measure

Returns an enum generated from the string.

valueOf(String) - Static method in enum adams.data.conversion.WekaPredictionContainerToSpreadSheet.Sorting

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.data.instancesanalysis.pls.PredictionType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.data.instancesanalysis.pls.PreprocessingType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.data.weka.columnfinder.MultiColumnFinder.Combination

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.data.weka.rowfinder.MultiRowFinder.Combination

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.core.Capability

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.core.EvaluationStatistic

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.core.ExperimentStatistic

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.sink.WekaExperimentGenerator.EvaluationType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.sink.WekaExperimentGenerator.ExperimentType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.sink.WekaExperimentGenerator.ResultFormat

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.sink.WekaThresholdCurve.AttributeName

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.source.wekapackagemanageraction.ListPackages.ListType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.source.wekapackagemanageraction.ListPackages.OutputFormat

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaBootstrapping.ErrorCalculation

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaClassifierInfo.InfoType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaClassifierRanker.Measure

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaClustererInfo.InfoType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaEvaluationInfo.InfoType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaExtractArray.ExtractionType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaExtractPLSMatrix.MatrixType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaFileReader.OutputType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaInstanceBuffer.Operation

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaInstanceDumper.OutputFormat

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaInstancesInfo.InfoType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.flow.transformer.WekaInstancesStatisticDataType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.gui.event.InstancesSortSetupEvent.EventType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.CenterStatistic

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.LowerStatistic

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.UpperStatistic

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.gui.visualization.instance.InstanceLinePaintlet.MarkerShape

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.opt.genetic.Measure

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.opt.genetic.OutputPrefixType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.opt.genetic.OutputType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.attributeSelection.AbstractPLSAttributeEval.LoadingsCalculations

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.meta.ClassifierCascade.Combination

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.meta.ClassifierCascade.ThresholdCheck

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.meta.MinMaxLimits.LimitHandling

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.BoosterType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.FeatureSelector

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.GrowPolicy

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.NormaliseType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.Objective

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.Predictor

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.ProcessType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.SampleType

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.TreeMethod

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.Updater

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.Verbosity

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.filters.unsupervised.attribute.EquiDistance.AttributeSelection

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.filters.unsupervised.attribute.NominalToNumeric.ConversionType

Returns the enum constant of this type with the specified name.

values() - Static method in enum adams.data.conversion.WekaPredictionContainerToSpreadSheet.Sorting

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.data.instancesanalysis.pls.PredictionType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.data.instancesanalysis.pls.PreprocessingType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.data.weka.columnfinder.MultiColumnFinder.Combination

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.data.weka.rowfinder.MultiRowFinder.Combination

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.core.Capability

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.core.EvaluationStatistic

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.core.ExperimentStatistic

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.sink.WekaExperimentGenerator.EvaluationType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.sink.WekaExperimentGenerator.ExperimentType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.sink.WekaExperimentGenerator.ResultFormat

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.sink.WekaThresholdCurve.AttributeName

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.source.wekapackagemanageraction.ListPackages.ListType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.source.wekapackagemanageraction.ListPackages.OutputFormat

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaBootstrapping.ErrorCalculation

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaClassifierInfo.InfoType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaClassifierRanker.Measure

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaClustererInfo.InfoType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaEvaluationInfo.InfoType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaExtractArray.ExtractionType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaExtractPLSMatrix.MatrixType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaFileReader.OutputType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaInstanceBuffer.Operation

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaInstanceDumper.OutputFormat

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaInstancesInfo.InfoType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.flow.transformer.WekaInstancesStatisticDataType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.gui.event.InstancesSortSetupEvent.EventType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.CenterStatistic

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.LowerStatistic

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.UpperStatistic

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.gui.visualization.instance.InstanceLinePaintlet.MarkerShape

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.opt.genetic.Measure

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.opt.genetic.OutputPrefixType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.opt.genetic.OutputType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.attributeSelection.AbstractPLSAttributeEval.LoadingsCalculations

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.meta.ClassifierCascade.Combination

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.meta.ClassifierCascade.ThresholdCheck

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.meta.MinMaxLimits.LimitHandling

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.trees.XGBoost.BoosterType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.trees.XGBoost.FeatureSelector

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.trees.XGBoost.GrowPolicy

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.trees.XGBoost.NormaliseType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.trees.XGBoost.Objective

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.trees.XGBoost.Predictor

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.trees.XGBoost.ProcessType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.trees.XGBoost.SampleType

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.trees.XGBoost.TreeMethod

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.trees.XGBoost.Updater

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.classifiers.trees.XGBoost.Verbosity

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.filters.unsupervised.attribute.EquiDistance.AttributeSelection

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.filters.unsupervised.attribute.NominalToNumeric.ConversionType

Returns an array containing the constants of this enum type, in the order they are declared.

VALUESDIFFER_AVERAGE - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

how to handle differing values: average.

VALUESDIFFER_AVERAGE - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

how to handle differing values: average.

VALUESDIFFER_FIRST - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

how to handle differing values: first.

VALUESDIFFER_MISSING - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes

how to handle differing values: missing.

VALUESDIFFER_MISSING - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

how to handle differing values: missing.

VALUESDIFFER_SECOND - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes

how to handle differing values: SECOND.

valueSparse(int) - Method in class weka.core.AbstractHashableInstance

Returns an instance's attribute value in internal format, given an index in the sparse representation.

valueTipText() - Method in class adams.flow.transformer.WekaSetInstancesValue

Returns the tip text for this property.

valueTipText() - Method in class adams.flow.transformer.WekaSetInstanceValue

Returns the tip text for this property.

variableChanged(VariableChangeEvent) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Gets triggered when a variable changed (added, modified, removed).

variableChanged(VariableChangeEvent) - Method in class adams.flow.transformer.WekaInstanceBuffer

Gets triggered when a variable changed (added, modified, removed).

variableChanged(VariableChangeEvent) - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Gets triggered when a variable changed (added, modified, removed).

variableNameTipText() - Method in class adams.flow.template.InstanceDumperVariable

Returns the tip text for this property.

variableNameTipText() - Method in class adams.flow.transformer.WekaInstanceBuffer

Returns the tip text for this property.

variableNameTipText() - Method in class adams.flow.transformer.WekaNearestNeighborSearch

Returns the tip text for this property.

varianceCoveredTipText() - Method in class adams.flow.transformer.WekaPrincipalComponents

Returns the tip text for this property.

varianceCoveredTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ

Returns the tip text for this property.

varianceTipText() - Method in class adams.data.instancesanalysis.PCA

Returns the tip text for this property.

varianceTipText() - Method in class weka.classifiers.meta.AbstainLeastMedianSq

VCPLS - Class in adams.data.instancesanalysis.pls

VCPLS() - Constructor for class adams.data.instancesanalysis.pls.VCPLS

verbosityTipText() - Method in class weka.classifiers.trees.XGBoost

Gets the tip-text for the verbosity option.

versusFitOptionsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Tip text for the vs fit options property.

versusOrderOptionsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot

Tip text for the vsorder options property.

Veto - Class in weka.classifiers.meta

If the specified label is predicted by the required minimum number of classifiers of the ensemble, then this label is predicted.

Veto() - Constructor for class weka.classifiers.meta.Veto

ViewAsTable - Class in adams.gui.visualization.instance.containerlistpopup

Views the selected instance as table.

ViewAsTable() - Constructor for class adams.gui.visualization.instance.containerlistpopup.ViewAsTable

ViewCell - Class in adams.gui.visualization.instances.instancestable

For viewing the cell content.

ViewCell() - Constructor for class adams.gui.visualization.instances.instancestable.ViewCell

viewInstance(InstanceContainer) - Method in class adams.gui.visualization.instance.InstancePanel

Views the specified instance in a table.

Viewport - Class in adams.gui.visualization.instance.plotpopup

Allows the user to perform operations on the instances visible in the current viewport.

Viewport() - Constructor for class adams.gui.visualization.instance.plotpopup.Viewport

visualize() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab

Updates the visualization.

VotedFolds - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel

Generates a Vote meta-classifier from the models from the cross-validation folds.

VotedFolds() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds

VotedImbalance - Class in weka.classifiers.meta

Generates an ensemble using the following approach:
- do x times:
* create new dataset, resampled with specified bias
* build base classifier with it
If no classifier gets built at all, use ZeroR as backup model, built on the full dataset.
At prediction time, the Vote meta-classifier (using the pre-built classifiers) is used to determining the class probabilities or regression value.
Instead of just using a fixed number of resampled models, you can also specify thresholds (= probability that the minority class does not meet) with associated number of resampled models to use.

VotedImbalance() - Constructor for class weka.classifiers.meta.VotedImbalance

VotedModels - Class in adams.flow.transformer.wekaensemblegenerator

Generates a Vote meta-classifier from the incoming pre-built classifier models.

VotedModels() - Constructor for class adams.flow.transformer.wekaensemblegenerator.VotedModels

VotedPairs - Class in adams.flow.transformer.wekaclassifiersetupprocessor

Generates an array of classifiers that contains the original ones, but also all possible classifier pairs encapsulated in the Vote meta-classifier.

VotedPairs() - Constructor for class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs

VotedPairs.VotingType - Enum in adams.flow.transformer.wekaclassifiersetupprocessor

How the voting is done.

voteTipText() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels

Returns the tip text for this property.

votingTypeTipText() - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs

Returns the tip text for this property.

W

wait(int) - Method in class weka.classifiers.functions.FakeClassifier

Waits for a specified amount of time.

WARNING - weka.classifiers.trees.XGBoost.Verbosity

WAVENO_REGEXP - Static variable in class weka.filters.unsupervised.attribute.Detrend

WAVENO_REGEXP - Static variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

waveNoRegExpTipText() - Method in class weka.filters.unsupervised.attribute.Detrend

Returns the tip text for this property.

waveNoRegExpTipText() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection

Returns the tip text for this property.

weight() - Method in class weka.core.AbstractHashableInstance

Returns the instance's weight.

WEIGHTED - weka.classifiers.trees.XGBoost.SampleType

WEIGHTED_AREA_UNDER_PRC - adams.flow.core.EvaluationStatistic

WEIGHTED_AREA_UNDER_PRC - adams.flow.core.ExperimentStatistic

WEIGHTED_AREA_UNDER_ROC - adams.flow.core.EvaluationStatistic

WEIGHTED_AREA_UNDER_ROC - adams.flow.core.ExperimentStatistic

WEIGHTED_F_MEASURE - adams.flow.core.EvaluationStatistic

WEIGHTED_F_MEASURE - adams.flow.core.ExperimentStatistic

WEIGHTED_FALSE_NEGATIVE_RATE - adams.flow.core.EvaluationStatistic

WEIGHTED_FALSE_NEGATIVE_RATE - adams.flow.core.ExperimentStatistic

WEIGHTED_FALSE_POSITIVE_RATE - adams.flow.core.EvaluationStatistic

WEIGHTED_FALSE_POSITIVE_RATE - adams.flow.core.ExperimentStatistic

WEIGHTED_IR_PRECISION - adams.flow.core.EvaluationStatistic

WEIGHTED_IR_PRECISION - adams.flow.core.ExperimentStatistic

WEIGHTED_IR_RECALL - adams.flow.core.EvaluationStatistic

WEIGHTED_IR_RECALL - adams.flow.core.ExperimentStatistic

WEIGHTED_MATTHEWS_CORRELATION_COEFFICIENT - adams.flow.core.EvaluationStatistic

WEIGHTED_MATTHEWS_CORRELATION_COEFFICIENT - adams.flow.core.ExperimentStatistic

WEIGHTED_TRUE_NEGATIVE_RATE - adams.flow.core.EvaluationStatistic

WEIGHTED_TRUE_NEGATIVE_RATE - adams.flow.core.ExperimentStatistic

WEIGHTED_TRUE_POSITIVE_RATE - adams.flow.core.EvaluationStatistic

WEIGHTED_TRUE_POSITIVE_RATE - adams.flow.core.ExperimentStatistic

WeightedEuclideanDistance - Class in weka.core

Implementing Euclidean distance (or similarity) function.

One object defines not one distance but the data model in which the distances between objects of that data model can be computed.

Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.

For more information, see:

Wikipedia.

WeightedEuclideanDistance() - Constructor for class weka.core.WeightedEuclideanDistance

Constructs an Euclidean Distance object, Instances must be still set.

WeightedEuclideanDistance(Instances) - Constructor for class weka.core.WeightedEuclideanDistance

Constructs an Euclidean Distance object and automatically initializes the ranges.

WeightedEuclideanDistanceRidge - Class in weka.core

Implementing Euclidean distance (or similarity) function.

One object defines not one distance but the data model in which the distances between objects of that data model can be computed.

Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.

For more information, see:

Wikipedia.

WeightedEuclideanDistanceRidge() - Constructor for class weka.core.WeightedEuclideanDistanceRidge

Constructs an Euclidean Distance object, Instances must be still set.

WeightedEuclideanDistanceRidge(Instances) - Constructor for class weka.core.WeightedEuclideanDistanceRidge

Constructs an Euclidean Distance object and automatically initializes the ranges.

WeightedInstancesHandlerWrapper - Class in weka.classifiers.meta

A meta-classifier that implements the weka.core.WeightedInstancesHandler interface in order to enable all classifiers to be used in other meta-classifiers that require the base classifier to implem ent the WeightedInstancesHandler interface.

WeightedInstancesHandlerWrapper() - Constructor for class weka.classifiers.meta.WeightedInstancesHandlerWrapper

weightingKernelTipText() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights

Returns the tip text for this property.

WeightsBasedResample - Class in weka.filters.unsupervised.instance

Normalizes all instance weights and drops the ones that fall below the specified threshold, but at most the specified percentage.
Of the left over instances, the smallest weight, e.g., 0.2, represents one instance, which translates a weight of 1.0 to five instances.

WeightsBasedResample() - Constructor for class weka.filters.unsupervised.instance.WeightsBasedResample

weightsTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer

Returns the tip text for this property.

weightsToString(int[]) - Method in class adams.opt.optimise.GeneticAlgorithm

Turns the weights into a string representation.

weightTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions

Returns the tip text for this property.

weightTipText() - Method in class weka.classifiers.functions.FromPredictions

Returns the tip text for this property.

Weka - Class in adams.data.featureconverter

Generates features in spreadsheet format.

Weka() - Constructor for class adams.data.featureconverter.Weka

WEKA_FILE_LOADER - Static variable in class adams.gui.menu.MakeCompatibleDatasets

weka.attributeSelection - package weka.attributeSelection

weka.classifiers - package weka.classifiers

weka.classifiers.evaluation - package weka.classifiers.evaluation

weka.classifiers.functions - package weka.classifiers.functions

weka.classifiers.lazy - package weka.classifiers.lazy

weka.classifiers.meta - package weka.classifiers.meta

weka.classifiers.meta.socketfacade - package weka.classifiers.meta.socketfacade

weka.classifiers.simple - package weka.classifiers.simple

weka.classifiers.trees - package weka.classifiers.trees

weka.classifiers.trees.m5 - package weka.classifiers.trees.m5

weka.clusterers - package weka.clusterers

weka.core - package weka.core

weka.core.converters - package weka.core.converters

weka.core.matrix - package weka.core.matrix

weka.core.neighboursearch - package weka.core.neighboursearch

weka.core.tokenizers - package weka.core.tokenizers

weka.core.tokenizers.cleaners - package weka.core.tokenizers.cleaners

weka.experiment - package weka.experiment

weka.filters - package weka.filters

weka.filters.supervised.attribute - package weka.filters.supervised.attribute

weka.filters.supervised.instance - package weka.filters.supervised.instance

weka.filters.unsupervised.attribute - package weka.filters.unsupervised.attribute

weka.filters.unsupervised.attribute.detrend - package weka.filters.unsupervised.attribute.detrend

weka.filters.unsupervised.attribute.multiplicativescattercorrection - package weka.filters.unsupervised.attribute.multiplicativescattercorrection

weka.filters.unsupervised.instance - package weka.filters.unsupervised.instance

weka.filters.unsupervised.instance.multirowprocessor - package weka.filters.unsupervised.instance.multirowprocessor

weka.filters.unsupervised.instance.multirowprocessor.processor - package weka.filters.unsupervised.instance.multirowprocessor.processor

weka.filters.unsupervised.instance.multirowprocessor.selection - package weka.filters.unsupervised.instance.multirowprocessor.selection

weka.gui - package weka.gui

weka.gui.explorer - package weka.gui.explorer

weka.gui.explorer.panels - package weka.gui.explorer.panels

weka.gui.visualize.plugins - package weka.gui.visualize.plugins

WekaAccumulatedError - Class in adams.flow.transformer

Generates plot containers from an evaluation object's predictions.

WekaAccumulatedError() - Constructor for class adams.flow.transformer.WekaAccumulatedError

WekaAccumulatedError.SortablePrediction - Class in adams.flow.transformer

Container for a classifier prediction, used for sorting.

WekaAggregateEvaluations - Class in adams.flow.transformer

Aggregates incoming weka.classifiers.Evaluation objects and forwards the current aggregated state.

WekaAggregateEvaluations() - Constructor for class adams.flow.transformer.WekaAggregateEvaluations

WekaAssociatorContainer - Class in adams.flow.container

Container for associators and their rules.

WekaAssociatorContainer() - Constructor for class adams.flow.container.WekaAssociatorContainer

Initializes the container.

WekaAssociatorContainer(Associator) - Constructor for class adams.flow.container.WekaAssociatorContainer

Initializes the container with no header.

WekaAssociatorContainer(Associator, Instances) - Constructor for class adams.flow.container.WekaAssociatorContainer

Initializes the container with no header.

WekaAssociatorContainer(Associator, Instances, Instances) - Constructor for class adams.flow.container.WekaAssociatorContainer

Initializes the container with no header.

WekaAssociatorContainer(Associator, Instances, Instances, List<AssociationRule>) - Constructor for class adams.flow.container.WekaAssociatorContainer

Initializes the container with no header.

WekaAssociatorSetup - Class in adams.flow.source

Outputs an instance of the specified associator.

WekaAssociatorSetup() - Constructor for class adams.flow.source.WekaAssociatorSetup

WekaAttributeIndex - Class in adams.data.weka

Extended Index class that can use an attribute name to determine an index of a attribute as well.

WekaAttributeIndex() - Constructor for class adams.data.weka.WekaAttributeIndex

Initializes with no index.

WekaAttributeIndex(String) - Constructor for class adams.data.weka.WekaAttributeIndex

Initializes with the given index, but no maximum.

WekaAttributeIndex(String, int) - Constructor for class adams.data.weka.WekaAttributeIndex

Initializes with the given index and maximum.

WekaAttributeIndexEditor - Class in adams.gui.goe

Editor for WekaAttributeIndex objects.

WekaAttributeIndexEditor() - Constructor for class adams.gui.goe.WekaAttributeIndexEditor

WekaAttributeIndexParsing - Class in adams.core.option.parsing

For parsing WekaAttributeIndex options.

WekaAttributeIndexParsing() - Constructor for class adams.core.option.parsing.WekaAttributeIndexParsing

WekaAttributeIterator - Class in adams.flow.transformer

Iterates through all attributes of a dataset and outputs the names.
The attributes can be limited with the range parameter and furthermore with the regular expression applied to the names.
Instead of outputting the names, it is also possible to output the 1-based indices.

WekaAttributeIterator() - Constructor for class adams.flow.transformer.WekaAttributeIterator

WekaAttributeRange - Class in adams.data.weka

Extended Range class that also allows attribute names for specifying attribute positions (names are case-insensitive, just like placeholders for 'first', 'second', etc).

WekaAttributeRange() - Constructor for class adams.data.weka.WekaAttributeRange

Initializes with no range.

WekaAttributeRange(String) - Constructor for class adams.data.weka.WekaAttributeRange

Initializes with the given range, but no maximum.

WekaAttributeRange(String, int) - Constructor for class adams.data.weka.WekaAttributeRange

Initializes with the given range and maximum.

WekaAttributeRangeEditor - Class in adams.gui.goe

A PropertyEditor for WekaAttributeRange objects.

WekaAttributeRangeEditor() - Constructor for class adams.gui.goe.WekaAttributeRangeEditor

WekaAttributeRangeParsing - Class in adams.core.option.parsing

For parsing WekaAttributeRange options.

WekaAttributeRangeParsing() - Constructor for class adams.core.option.parsing.WekaAttributeRangeParsing

WekaAttributeSelection - Class in adams.flow.transformer

Performs attribute selection on the incoming data.
In case of input in form of a class adams.flow.container.WekaTrainTestSetContainer object, the train and test sets stored in the container are being used.
NB: In case of cross-validation no reduced or transformed data can get generated!

Input/output:
- accepts:
weka.core.Instances
adams.flow.container.WekaTrainTestSetContainer
- generates:
adams.flow.container.WekaAttributeSelectionContainer


Container information:
- adams.flow.container.WekaTrainTestSetContainer: Train, Test, Seed, FoldNumber, FoldCount, Train original indices, Test original indices
- adams.flow.container.WekaAttributeSelectionContainer: Train, Reduced, Transformed, Test, Test reduced, Test transformed, Evaluation, Statistics, Selected attributes, Seed, FoldCount

WekaAttributeSelection() - Constructor for class adams.flow.transformer.WekaAttributeSelection

WekaAttributeSelectionContainer - Class in adams.flow.container

A container for storing results from attribute selection.

WekaAttributeSelectionContainer() - Constructor for class adams.flow.container.WekaAttributeSelectionContainer

Initializes the container.

WekaAttributeSelectionContainer(Instances, Instances, Instances, AttributeSelection, SpreadSheet, String) - Constructor for class adams.flow.container.WekaAttributeSelectionContainer

Initializes the container.

WekaAttributeSelectionContainer(Instances, Instances, Instances, AttributeSelection, SpreadSheet, String, Long, Integer) - Constructor for class adams.flow.container.WekaAttributeSelectionContainer

Initializes the container.

WekaAttributeSelectionContainer(Instances, Instances, Instances, AttributeSelection, Long, Integer) - Constructor for class adams.flow.container.WekaAttributeSelectionContainer

Initializes the container.

WekaAttributeSelectionSummary - Class in adams.flow.transformer

Outputs a summary string of the attribute selection.

WekaAttributeSelectionSummary() - Constructor for class adams.flow.transformer.WekaAttributeSelectionSummary

WekaAttributeSummary - Class in adams.flow.sink

Displays an attribute summary.

WekaAttributeSummary() - Constructor for class adams.flow.sink.WekaAttributeSummary

WekaBootstrapping - Class in adams.flow.transformer

Performs bootstrapping on the incoming evaluation and outputs a spreadsheet where each row represents the results from bootstrapping sub-sample.

WekaBootstrapping() - Constructor for class adams.flow.transformer.WekaBootstrapping

WekaBootstrapping.ErrorCalculation - Enum in adams.flow.transformer

how to calculate the error.

WekaCapabilities - Class in adams.flow.condition.bool

Filters weka.core.Instance and weka.core.Instances objects based on defined capabilities.

WekaCapabilities() - Constructor for class adams.flow.condition.bool.WekaCapabilities

WekaCapabilitiesToInstances - Class in adams.data.conversion

Turns a weka.core.Capabilities object into a Weka dataset filled with random data that is compatible with these capabilities.

WekaCapabilitiesToInstances() - Constructor for class adams.data.conversion.WekaCapabilitiesToInstances

WekaCapabilitiesToSpreadSheet - Class in adams.data.conversion

Turns a weka.core.Capabilities object into a spreadsheet, listing all individual capabilities and whether they are supported.

WekaCapabilitiesToSpreadSheet() - Constructor for class adams.data.conversion.WekaCapabilitiesToSpreadSheet

WekaChooseAttributes - Class in adams.flow.transformer

Lets the user select attributes interactively to use down the track.
Internally, a weka.filters.unsupervised.attribute.Remove WEKA filter is constructed from the selection, to remove the attributes that the user didn't select.

WekaChooseAttributes() - Constructor for class adams.flow.transformer.WekaChooseAttributes

WekaClassification - Class in adams.flow.condition.bool

Uses the index of the classification, i.e., the predicted label, as index of the switch

WekaClassification() - Constructor for class adams.flow.condition.bool.WekaClassification

WekaClassificationModel - Class in adams.ml.model.classification

Classification model for Weka classifiers.

WekaClassificationModel(Classifier, Dataset, Instances) - Constructor for class adams.ml.model.classification.WekaClassificationModel

Initializes the model.

WekaClassifier - Class in adams.ml.model.classification

Wraps around a Weka classifier that handles nominal classes (= classification).

WekaClassifier() - Constructor for class adams.ml.model.classification.WekaClassifier

WekaClassifierErrors - Class in adams.flow.sink

Actor for displaying classifier errors.

WekaClassifierErrors() - Constructor for class adams.flow.sink.WekaClassifierErrors

WekaClassifierErrors.DataGenerator - Class in adams.flow.sink

Helper class for generating visualization data.

WekaClassifierGenerator - Class in adams.flow.source

Generates multiple classifier setups.

WekaClassifierGenerator() - Constructor for class adams.flow.source.WekaClassifierGenerator

WekaClassifierInfo - Class in adams.flow.transformer

Outputs information of a trained weka.classifiers.Classifier object.

WekaClassifierInfo() - Constructor for class adams.flow.transformer.WekaClassifierInfo

WekaClassifierInfo.InfoType - Enum in adams.flow.transformer

The type of information to generate.

WekaClassifierModelLoader - Class in adams.flow.core

Manages classifier models.

WekaClassifierModelLoader() - Constructor for class adams.flow.core.WekaClassifierModelLoader

WekaClassifierOptimizer - Class in adams.flow.transformer

Evaluates a classifier optimizer on an incoming dataset.

WekaClassifierOptimizer() - Constructor for class adams.flow.transformer.WekaClassifierOptimizer

WekaClassifierRanker - Class in adams.flow.transformer

Performs a quick evaluation using cross-validation on a single dataset (or evaluation on a separate test set if the number of folds is less than 2) to rank the classifiers received on the input and forwarding the x best ones.

WekaClassifierRanker() - Constructor for class adams.flow.transformer.WekaClassifierRanker

WekaClassifierRanker.Measure - Enum in adams.flow.transformer

The performance measure to use.

WekaClassifierRanker.RankingJob - Class in adams.flow.transformer

A job class specific to ranking classifiers.

WekaClassifierSetup - Class in adams.flow.source

Outputs an instance of the specified classifier.

WekaClassifierSetup() - Constructor for class adams.flow.source.WekaClassifierSetup

WekaClassifierSetupProcessor - Class in adams.flow.transformer

Applies the specified processor to the incoming array of classifiers, e.g., for generating new or filtered setups.

WekaClassifierSetupProcessor() - Constructor for class adams.flow.transformer.WekaClassifierSetupProcessor

WekaClassifying - Class in adams.flow.transformer

Uses a serialized model to perform predictions on the data being passed through.
The following order is used to obtain the model (when using AUTO):
1.

WekaClassifying() - Constructor for class adams.flow.transformer.WekaClassifying

WekaClassManager - Class in adams.core.classmanager

Uses WekaPackageClassLoaderManager.forName(...).

WekaClassManager() - Constructor for class adams.core.classmanager.WekaClassManager

WekaClassSelector - Class in adams.flow.transformer

Sets the class index.

WekaClassSelector() - Constructor for class adams.flow.transformer.WekaClassSelector

WekaClusterAssignments - Class in adams.flow.transformer

Outputs the cluster assignments from the evaluation.

WekaClusterAssignments() - Constructor for class adams.flow.transformer.WekaClusterAssignments

WekaClusterer - Class in adams.ml.model.clustering

Wraps around a Weka clusterer.

WekaClusterer() - Constructor for class adams.ml.model.clustering.WekaClusterer

WekaClustererGenerator - Class in adams.flow.source

Generates multiple clusterer setups.

WekaClustererGenerator() - Constructor for class adams.flow.source.WekaClustererGenerator

WekaClustererInfo - Class in adams.flow.transformer

Outputs information of a trained weka.clusterers.Clusterer object.

WekaClustererInfo() - Constructor for class adams.flow.transformer.WekaClustererInfo

WekaClustererInfo.InfoType - Enum in adams.flow.transformer

The type of information to generate.

WekaClustererModelLoader - Class in adams.flow.core

Manages clusterer models.

WekaClustererModelLoader() - Constructor for class adams.flow.core.WekaClustererModelLoader

WekaClustererPostProcessor - Class in adams.flow.transformer

Applies the specified post-processor to the cluster container (adams.flow.container.WekaModelContainer)

See also:
adams.flow.transformer.WekaTrainClusterer

Input/output:
- accepts:
adams.flow.container.WekaModelContainer
- generates:
adams.flow.container.WekaModelContainer


Container information:
- adams.flow.container.WekaModelContainer: Model, Header, Dataset

WekaClustererPostProcessor() - Constructor for class adams.flow.transformer.WekaClustererPostProcessor

WekaClustererSetup - Class in adams.flow.source

Outputs an instance of the specified clusterer.

WekaClustererSetup() - Constructor for class adams.flow.source.WekaClustererSetup

WekaClusterEvaluationContainer - Class in adams.flow.container

A container for ClusterEvaluation objects, with optional trained model.

WekaClusterEvaluationContainer() - Constructor for class adams.flow.container.WekaClusterEvaluationContainer

Initializes the container.

WekaClusterEvaluationContainer(double) - Constructor for class adams.flow.container.WekaClusterEvaluationContainer

Initializes the container with the log-likelihood.

WekaClusterEvaluationContainer(ClusterEvaluation) - Constructor for class adams.flow.container.WekaClusterEvaluationContainer

Initializes the container.

WekaClusterEvaluationContainer(ClusterEvaluation, Object) - Constructor for class adams.flow.container.WekaClusterEvaluationContainer

Initializes the container.

WekaClusterEvaluationSummary - Class in adams.flow.transformer

Generates a summary string of the weka.clusterers.ClusterEvaluation objects that it receives.

WekaClusterEvaluationSummary() - Constructor for class adams.flow.transformer.WekaClusterEvaluationSummary

WekaClustering - Class in adams.flow.transformer

Uses a serialized model to cluster data being passed through.
The following order is used to obtain the model (when using AUTO):
1.

WekaClustering() - Constructor for class adams.flow.transformer.WekaClustering

WekaClusteringContainer - Class in adams.flow.container

A container for clusterings made by a clusterer.

WekaClusteringContainer() - Constructor for class adams.flow.container.WekaClusteringContainer

Initializes the container.

WekaClusteringContainer(Instance, int, double[]) - Constructor for class adams.flow.container.WekaClusteringContainer

Initializes the container.

WekaClusteringContainer(Instance, int, double[], double, double[], double[]) - Constructor for class adams.flow.container.WekaClusteringContainer

Initializes the container.

WekaClusteringModel - Class in adams.ml.model.clustering

Clustering model for Weka classifiers.

WekaClusteringModel(Clusterer, Dataset, Instances) - Constructor for class adams.ml.model.clustering.WekaClusteringModel

Initializes the model.

WekaCommandLineHandler - Class in adams.core.option

Handles objects of classes that implement the weka.core.OptionHandler interface.

WekaCommandLineHandler() - Constructor for class adams.core.option.WekaCommandLineHandler

WekaCommandToCode - Class in adams.data.conversion

Applies a commandline converter to the incoming commandline to generate code.
Uses the following project:
https://github.com/fracpete/command-to-code-weka-package

WekaCommandToCode - Class in adams.gui.menu

For turning Weka commandline strings into code.

WekaCommandToCode() - Constructor for class adams.data.conversion.WekaCommandToCode

WekaCommandToCode() - Constructor for class adams.gui.menu.WekaCommandToCode

Initializes the menu item with no owner.

WekaCommandToCode(AbstractApplicationFrame) - Constructor for class adams.gui.menu.WekaCommandToCode

Initializes the menu item.

WekaConverter - Class in adams.ml.data

Helper class for converting data to and fro Weka.

WekaConverter() - Constructor for class adams.ml.data.WekaConverter

WekaCostBenefitAnalysis - Class in adams.flow.sink

Actor for displaying a cost benefit analysis dialog.

WekaCostBenefitAnalysis() - Constructor for class adams.flow.sink.WekaCostBenefitAnalysis

WekaCostCurve - Class in adams.flow.sink

Actor for displaying a cost curve.

WekaCostCurve() - Constructor for class adams.flow.sink.WekaCostCurve

WekaCrossValidationClustererEvaluator - Class in adams.flow.transformer

Cross-validates a clusterer on an incoming dataset.

WekaCrossValidationClustererEvaluator() - Constructor for class adams.flow.transformer.WekaCrossValidationClustererEvaluator

WekaCrossValidationEvaluator - Class in adams.flow.transformer

Cross-validates a classifier on an incoming dataset.

WekaCrossValidationEvaluator() - Constructor for class adams.flow.transformer.WekaCrossValidationEvaluator

WekaCrossValidationExecution - Class in adams.multiprocess

Performs cross-validation, either single or multi-threaded.

WekaCrossValidationExecution() - Constructor for class adams.multiprocess.WekaCrossValidationExecution

Initializes the execution.

WekaCrossValidationJob - Class in adams.multiprocess

For evaluation of a single train/test fold in parallel.

WekaCrossValidationJob(Classifier, Instances, Instances, int, boolean) - Constructor for class adams.multiprocess.WekaCrossValidationJob

Initializes the job.

WekaCrossValidationJob(Classifier, Instances, Instances, int, boolean, StatusMessageHandler) - Constructor for class adams.multiprocess.WekaCrossValidationJob

Initializes the job.

WekaCrossValidationSplit - Class in adams.flow.transformer

Generates train/test pairs like during a cross-validation run.

WekaCrossValidationSplit() - Constructor for class adams.flow.transformer.WekaCrossValidationSplit

WekaDatabaseReader - Class in adams.flow.source

Executes a query and returns the data either in batch or incremental mode.

WekaDatabaseReader() - Constructor for class adams.flow.source.WekaDatabaseReader

WekaDatabaseWriter - Class in adams.flow.sink

Actor for saving a weka.core.Instances object in a database.
The relation name of the incoming dataset can be used to replace the current filename (path and extension are kept).

WekaDatabaseWriter() - Constructor for class adams.flow.sink.WekaDatabaseWriter

WekaDataGenerator - Class in adams.flow.source

Generates artificial data using a Weka data generator.

WekaDataGenerator() - Constructor for class adams.flow.source.WekaDataGenerator

WekaDatasetHandler - Class in adams.gui.tools.previewbrowser

Displays the following WEKA dataset types: csv,arff,arff.gz,xrff,xrff.gz

Valid options are:

WekaDatasetHandler() - Constructor for class adams.gui.tools.previewbrowser.WekaDatasetHandler

WekaDatasetsMerge - Class in adams.flow.transformer

Merges 2 or more datasets into a single dataset, under a selectable merge method.

WekaDatasetsMerge() - Constructor for class adams.flow.transformer.WekaDatasetsMerge

WekaDatasetSplit - Class in adams.flow.transformer

Splits the incoming dataset into sub-sets using the specified splitter.

WekaDatasetSplit() - Constructor for class adams.flow.transformer.WekaDatasetSplit

WekaDrawableToString - Class in adams.data.conversion

Extracts the string representation of a weka.core.Drawable object, e.g., the tree representation of a decision tree or the graph of a BayesNet.

WekaDrawableToString() - Constructor for class adams.data.conversion.WekaDrawableToString

WekaEditorsRegistration - Class in adams.gui.goe

Registers first the WEKA GenericObjectEditor editors and the ADAMS ones.

WekaEditorsRegistration() - Constructor for class adams.gui.goe.WekaEditorsRegistration

WekaEditorsRegistration.AccessibleGenericObjectEditor - Class in adams.gui.goe

Subclass of GenericObjectEditor to get access to the class hierarchies.

WekaEditorsRegistration.AccessiblePluginManager - Class in adams.gui.goe

For getting access to protected members in the package manager.

WekaEnsembleGenerator - Class in adams.flow.transformer

Uses the specified generator to create ensembles from the incoming data.

WekaEnsembleGenerator() - Constructor for class adams.flow.transformer.WekaEnsembleGenerator

WekaEvaluation - Class in adams.gui.visualization.debug.inspectionhandler

Provides further insight into an Evaluation object.

WekaEvaluation() - Constructor for class adams.gui.visualization.debug.inspectionhandler.WekaEvaluation

WekaEvaluationContainer - Class in adams.flow.container

A container for Evaluation objects, with optional trained model.

WekaEvaluationContainer() - Constructor for class adams.flow.container.WekaEvaluationContainer

Initializes the container.

WekaEvaluationContainer(Evaluation) - Constructor for class adams.flow.container.WekaEvaluationContainer

Initializes the container with no header.

WekaEvaluationContainer(Evaluation, Object) - Constructor for class adams.flow.container.WekaEvaluationContainer

Initializes the container with no header.

WekaEvaluationContainer(Evaluation, Object, String) - Constructor for class adams.flow.container.WekaEvaluationContainer

Initializes the container with no header.

WekaEvaluationContainer(Evaluation, Object, String, int[]) - Constructor for class adams.flow.container.WekaEvaluationContainer

Initializes the container with no header.

WekaEvaluationInfo - Class in adams.flow.transformer

Outputs information about a Weka weka.classifiers.Evaluation object.

WekaEvaluationInfo() - Constructor for class adams.flow.transformer.WekaEvaluationInfo

WekaEvaluationInfo.InfoType - Enum in adams.flow.transformer

The type of information to output.

WekaEvaluationPostProcessor - Class in adams.flow.transformer

Applies the specified post-processor to the incoming Evaluation data.

WekaEvaluationPostProcessor() - Constructor for class adams.flow.transformer.WekaEvaluationPostProcessor

WekaEvaluationSummary - Class in adams.flow.transformer

Generates a summary string of the weka.classifiers.Evaluation objects that it receives.

WekaEvaluationSummary() - Constructor for class adams.flow.transformer.WekaEvaluationSummary

WekaEvaluationToCostCurve - Class in adams.data.conversion

Generates cost-curve data from a WEKA Evaluation object.

WekaEvaluationToCostCurve() - Constructor for class adams.data.conversion.WekaEvaluationToCostCurve

WekaEvaluationToMarginCurve - Class in adams.data.conversion

Generates margin-curve data from a WEKA Evaluation object.

WekaEvaluationToMarginCurve() - Constructor for class adams.data.conversion.WekaEvaluationToMarginCurve

WekaEvaluationToThresholdCurve - Class in adams.data.conversion

Generates threshold-curve data from a WEKA Evaluation object.

WekaEvaluationToThresholdCurve() - Constructor for class adams.data.conversion.WekaEvaluationToThresholdCurve

WekaEvaluationValuePicker - Class in adams.flow.transformer

Picks a specific value from an evaluation object.

WekaEvaluationValuePicker() - Constructor for class adams.flow.transformer.WekaEvaluationValuePicker

WekaEvaluationValues - Class in adams.flow.transformer

Generates a spreadsheet from statistics of an Evaluation object.

WekaEvaluationValues() - Constructor for class adams.flow.transformer.WekaEvaluationValues

WekaExperiment - Class in adams.flow.transformer

Represents a Weka experiment, stored in a file.

WekaExperiment() - Constructor for class adams.flow.transformer.WekaExperiment

WekaExperimentContainer - Class in adams.flow.container

Container for Weka experiment results.

WekaExperimentContainer() - Constructor for class adams.flow.container.WekaExperimentContainer

Initializes the container.

WekaExperimentContainer(AbstractExperiment, Instances, SpreadSheet) - Constructor for class adams.flow.container.WekaExperimentContainer

Initializes the container.

WekaExperimentContainer(Instances) - Constructor for class adams.flow.container.WekaExperimentContainer

Initializes the container with just the Instances.

WekaExperimenterPreferencesPanel - Class in adams.gui.application

Preferences for the WEKA Experimenter.

WekaExperimenterPreferencesPanel() - Constructor for class adams.gui.application.WekaExperimenterPreferencesPanel

WekaExperimentEvaluation - Class in adams.flow.transformer

Generates evaluation output of an experiment that was run previously.

WekaExperimentEvaluation() - Constructor for class adams.flow.transformer.WekaExperimentEvaluation

WekaExperimentExecution - Class in adams.flow.transformer

Executes an experiment.

WekaExperimentExecution() - Constructor for class adams.flow.transformer.WekaExperimentExecution

WekaExperimentFile - Class in adams.data

A dummy class for the GOE, for special handling of experiments.

WekaExperimentFile(File) - Constructor for class adams.data.WekaExperimentFile

Creates a new ExperimentFile instance by using the given file.

WekaExperimentFile(File, String) - Constructor for class adams.data.WekaExperimentFile

Creates a new ExperimentFile instance from a parent abstract pathname and a child pathname string.

WekaExperimentFile(String) - Constructor for class adams.data.WekaExperimentFile

Creates a new ExperimentFile instance by converting the given pathname string into an abstract pathname.

WekaExperimentFile(String, String) - Constructor for class adams.data.WekaExperimentFile

Creates a new ExperimentFile instance from a parent pathname string and a child pathname string.

WekaExperimentFile(URI) - Constructor for class adams.data.WekaExperimentFile

Creates a new ExperimentFile instance by converting the given file: URI into an abstract pathname.

WekaExperimentFileEditor - Class in adams.gui.goe

A PropertyEditor for WekaExperimentFile objects that lets the user select a file.

WekaExperimentFileEditor() - Constructor for class adams.gui.goe.WekaExperimentFileEditor

WekaExperimentFileEditor.SimpleSetupDialog - Class in adams.gui.goe

A dialog for displaying the simple setup of an experiment.

WekaExperimentFileParsing - Class in adams.core.option.parsing

For parsing WekaExperimentFile options.

WekaExperimentFileParsing() - Constructor for class adams.core.option.parsing.WekaExperimentFileParsing

WekaExperimentFileReader - Class in adams.flow.transformer

Loads an experiment file.

WekaExperimentFileReader() - Constructor for class adams.flow.transformer.WekaExperimentFileReader

WekaExperimentFileWriter - Class in adams.flow.sink

Saves an experiment file.

WekaExperimentFileWriter() - Constructor for class adams.flow.sink.WekaExperimentFileWriter

WekaExperimentGenerator - Class in adams.flow.sink

Generates an experiment setup that can be used in conjunction with the Experiment transformer actor.

WekaExperimentGenerator() - Constructor for class adams.flow.sink.WekaExperimentGenerator

WekaExperimentGenerator.EvaluationType - Enum in adams.flow.sink

The evaluation type.

WekaExperimentGenerator.ExperimentType - Enum in adams.flow.sink

The experiment type.

WekaExperimentGenerator.ResultFormat - Enum in adams.flow.sink

The data format the experiment data is stored in.

WekaExplorerPreferencesPanel - Class in adams.gui.application

Preferences for the WEKA Explorer.

WekaExplorerPreferencesPanel() - Constructor for class adams.gui.application.WekaExplorerPreferencesPanel

WekaExtractArray - Class in adams.flow.transformer

Extracts a column or row of data from a weka.core.Instances or SpreadSheet object.
Only numeric columns can be returned.

WekaExtractArray() - Constructor for class adams.flow.transformer.WekaExtractArray

WekaExtractArray.ExtractionType - Enum in adams.flow.transformer

The type of extraction to perform.

WekaExtractPLSMatrix - Class in adams.flow.transformer

Transformer that allows the extraction of internal PLS filter/classifier matrices, forwarding them as spreadsheets.

WekaExtractPLSMatrix() - Constructor for class adams.flow.transformer.WekaExtractPLSMatrix

WekaExtractPLSMatrix.MatrixType - Enum in adams.flow.transformer

The type of PLS matrix to extract (either PLS1 or SIMPLS ones will be available).

WekaFileChooser - Class in adams.gui.chooser

A specialized JFileChooser that lists all available file Readers and Writers for Weka file formats.

WekaFileChooser() - Constructor for class adams.gui.chooser.WekaFileChooser

Constructs a FileChooser pointing to the user's default directory.

WekaFileChooser(File) - Constructor for class adams.gui.chooser.WekaFileChooser

Constructs a FileChooser using the given File as the path.

WekaFileChooser(String) - Constructor for class adams.gui.chooser.WekaFileChooser

Constructs a FileChooser using the given path.

WekaFileReader - Class in adams.flow.transformer

Reads any file format that Weka's converters can handle and returns the full dataset or single weka.core.Instance objects.

WekaFileReader() - Constructor for class adams.flow.transformer.WekaFileReader

WekaFileReader.OutputType - Enum in adams.flow.transformer

Defines how to output the data.

WekaFileWriter - Class in adams.flow.sink

Actor for saving a weka.core.Instances object as file.
The relation name of the incoming dataset can be used to replace the current filename (path and extension are kept).

WekaFileWriter() - Constructor for class adams.flow.sink.WekaFileWriter

WekaFilter - Class in adams.data.spreadsheet.filter

Applies a Weka filter to the data.

WekaFilter - Class in adams.flow.transformer

Filters Instances/Instance objects using the specified filter.
When re-using a trained filter, ensure that 'initializeOnce' is checked.

The following order is used to obtain the model (when using AUTO):
1.

WekaFilter() - Constructor for class adams.data.spreadsheet.filter.WekaFilter

WekaFilter() - Constructor for class adams.flow.transformer.WekaFilter

WekaFilter.BatchFilterJob - Class in adams.flow.transformer

WekaFilterContainer - Class in adams.flow.container

A container for filters and the filtered data.

WekaFilterContainer() - Constructor for class adams.flow.container.WekaFilterContainer

Initializes the container.

WekaFilterContainer(Filter, Instance) - Constructor for class adams.flow.container.WekaFilterContainer

Initializes the container with the filter and the associated data.

WekaFilterContainer(Filter, Instance) - Constructor for class adams.flow.container.WekaFilterContainer

Initializes the container with the filter and the associated data.

WekaFilterContainer(Filter, Instances) - Constructor for class adams.flow.container.WekaFilterContainer

Initializes the container with the filter and the associated data.

WekaFilterGenerator - Class in adams.flow.source

Generates multiple filter setups.

WekaFilterGenerator() - Constructor for class adams.flow.source.WekaFilterGenerator

WekaFilterModelLoader - Class in adams.flow.core

Model loader for Weka filters.

WekaFilterModelLoader() - Constructor for class adams.flow.core.WekaFilterModelLoader

WekaGenericArrayEditorDialog - Class in adams.gui.goe

Displays a GenericArrayEditor.

WekaGenericArrayEditorDialog(Dialog) - Constructor for class adams.gui.goe.WekaGenericArrayEditorDialog

Creates a modeless dialog without a title with the specified Dialog as its owner.

WekaGenericArrayEditorDialog(Dialog, Dialog.ModalityType) - Constructor for class adams.gui.goe.WekaGenericArrayEditorDialog

Creates a dialog with the specified owner Dialog and modality.

WekaGenericArrayEditorDialog(Dialog, String) - Constructor for class adams.gui.goe.WekaGenericArrayEditorDialog

Creates a modeless dialog with the specified title and with the specified owner dialog.

WekaGenericArrayEditorDialog(Dialog, String, Dialog.ModalityType) - Constructor for class adams.gui.goe.WekaGenericArrayEditorDialog

Creates a dialog with the specified title, modality and the specified owner Dialog.

WekaGenericArrayEditorDialog(Frame) - Constructor for class adams.gui.goe.WekaGenericArrayEditorDialog

Creates a modeless dialog without a title with the specified Frame as its owner.

WekaGenericArrayEditorDialog(Frame, boolean) - Constructor for class adams.gui.goe.WekaGenericArrayEditorDialog

Creates a dialog with the specified owner Frame, modality and an empty title.

WekaGenericArrayEditorDialog(Frame, String) - Constructor for class adams.gui.goe.WekaGenericArrayEditorDialog

Creates a modeless dialog with the specified title and with the specified owner frame.

WekaGenericArrayEditorDialog(Frame, String, boolean) - Constructor for class adams.gui.goe.WekaGenericArrayEditorDialog

Creates a dialog with the specified owner Frame, modality and title.

WekaGenericArrayEditorPanel - Class in adams.gui.goe

A panel that contains text field with the current setup of the array and a button for bringing up the GenericArrayEditor.

WekaGenericArrayEditorPanel(Object) - Constructor for class adams.gui.goe.WekaGenericArrayEditorPanel

Initializes the panel with the given class and default value.

WekaGenericObjectEditorDialog - Class in adams.gui.goe

Displays a GenericObjectEditor.

WekaGenericObjectEditorDialog(Dialog) - Constructor for class adams.gui.goe.WekaGenericObjectEditorDialog

Creates a modeless dialog without a title with the specified Dialog as its owner.

WekaGenericObjectEditorDialog(Dialog, Dialog.ModalityType) - Constructor for class adams.gui.goe.WekaGenericObjectEditorDialog

Creates a dialog with the specified owner Dialog and modality.

WekaGenericObjectEditorDialog(Dialog, String) - Constructor for class adams.gui.goe.WekaGenericObjectEditorDialog

Creates a modeless dialog with the specified title and with the specified owner dialog.

WekaGenericObjectEditorDialog(Dialog, String, Dialog.ModalityType) - Constructor for class adams.gui.goe.WekaGenericObjectEditorDialog

Creates a dialog with the specified title, modality and the specified owner Dialog.

WekaGenericObjectEditorDialog(Frame) - Constructor for class adams.gui.goe.WekaGenericObjectEditorDialog

Creates a modeless dialog without a title with the specified Frame as its owner.

WekaGenericObjectEditorDialog(Frame, boolean) - Constructor for class adams.gui.goe.WekaGenericObjectEditorDialog

Creates a dialog with the specified owner Frame, modality and an empty title.

WekaGenericObjectEditorDialog(Frame, String) - Constructor for class adams.gui.goe.WekaGenericObjectEditorDialog

Creates a modeless dialog with the specified title and with the specified owner frame.

WekaGenericObjectEditorDialog(Frame, String, boolean) - Constructor for class adams.gui.goe.WekaGenericObjectEditorDialog

Creates a dialog with the specified owner Frame, modality and title.

WekaGenericObjectEditorHandler - Class in adams.gui.goe

Handler for the WEKA GenericObjectEditor.

WekaGenericObjectEditorHandler() - Constructor for class adams.gui.goe.WekaGenericObjectEditorHandler

WekaGenericObjectEditorPanel - Class in adams.gui.goe

A panel that contains text field with the current setup of the object and a button for bringing up the GenericObjectEditor.

WekaGenericObjectEditorPanel(Class, Object) - Constructor for class adams.gui.goe.WekaGenericObjectEditorPanel

Initializes the panel with the given class and default value.

WekaGenericObjectEditorPanel(Class, Object, boolean) - Constructor for class adams.gui.goe.WekaGenericObjectEditorPanel

Initializes the panel with the given class and default value.

WekaGenericObjectEditorPopupMenu - Class in adams.gui.goe

Generic GOE popup menu, for copy/paste, etc.

WekaGenericObjectEditorPopupMenu(PropertyEditor, JComponent) - Constructor for class adams.gui.goe.WekaGenericObjectEditorPopupMenu

Initializes the menu.

WekaGenericPLSMatrixAccess - Class in adams.flow.transformer

Transformer that allows the extraction of internal PLS filter/classifier matrices, forwarding them as spreadsheets.
See the respective PLS implementation for details on available matrix names (derived from: weka.filters.supervised.attribute.pls.AbstractPLS)

Input/output:
- accepts:
weka.classifiers.Classifier
weka.filters.Filter
weka.core.GenericPLSMatrixAccess
adams.flow.container.WekaModelContainer
- generates:
adams.data.spreadsheet.SpreadSheet


Container information:
- adams.flow.container.WekaModelContainer: Model, Header, Dataset

WekaGenericPLSMatrixAccess() - Constructor for class adams.flow.transformer.WekaGenericPLSMatrixAccess

WekaGeneticAlgorithm - Class in adams.flow.transformer

Applies the genetic algorithm to the incoming dataset.
Forwards the best setup(s) after the algorithm finishes.
A callable sink can be specified for receiving intermediate performance results.

WekaGeneticAlgorithm() - Constructor for class adams.flow.transformer.WekaGeneticAlgorithm

WekaGeneticAlgorithmContainer - Class in adams.flow.container

A container for genetic algorithms output (setup, measure, fitness).

WekaGeneticAlgorithmContainer() - Constructor for class adams.flow.container.WekaGeneticAlgorithmContainer

Initializes the container.

WekaGeneticAlgorithmContainer(Classifier) - Constructor for class adams.flow.container.WekaGeneticAlgorithmContainer

Initializes the container the setup.

WekaGeneticAlgorithmContainer(Classifier, Measure, Double, String, int[]) - Constructor for class adams.flow.container.WekaGeneticAlgorithmContainer

Initializes the container.

WekaGeneticAlgorithmInitializationContainer - Class in adams.flow.container

A container for initializing genetic algorithms.

WekaGeneticAlgorithmInitializationContainer() - Constructor for class adams.flow.container.WekaGeneticAlgorithmInitializationContainer

Initializes the container.

WekaGeneticAlgorithmInitializationContainer(AbstractClassifierBasedGeneticAlgorithm, Instances) - Constructor for class adams.flow.container.WekaGeneticAlgorithmInitializationContainer

Initializes the container.

WekaGeneticAlgorithmInitializer - Class in adams.flow.transformer

Populates a adams.flow.container.WekaGeneticAlgorithmInitializationContainer container from the data obtained from the incoming setup (in properties format, can be gzip compressed).

WekaGeneticAlgorithmInitializer() - Constructor for class adams.flow.transformer.WekaGeneticAlgorithmInitializer

WekaGeneticHelper - Class in adams.core.discovery.genetic

Helper for Weka classes.

WekaGeneticHelper() - Constructor for class adams.core.discovery.genetic.WekaGeneticHelper

WekaGetCapabilities - Class in adams.flow.transformer

Retrieves the capabilities of a weka.core.CapabilitiesHandler (eg filter or classifier) and forwards them.

WekaGetCapabilities() - Constructor for class adams.flow.transformer.WekaGetCapabilities

WekaGetInstancesValue - Class in adams.flow.transformer

Retrieves a value from a WEKA Instances object.
Notes:
- date and relational values are forwarded as strings
- missing values are output as '?' (without the single quotes)


Input/output:
- accepts:
weka.core.Instances
- generates:
java.lang.Double
java.lang.String

WekaGetInstancesValue() - Constructor for class adams.flow.transformer.WekaGetInstancesValue

WekaGetInstanceValue - Class in adams.flow.transformer

Retrieves a value from a WEKA Instance object.
Notes:
- date and relational values are forwarded as strings
- missing values are output as '?' (without the single quotes)
- the 'attribute name' option overrides the 'index' option

Input/output:
- accepts:
weka.core.Instance
- generates:
java.lang.Double
java.lang.String


Valid options are:

WekaGetInstanceValue() - Constructor for class adams.flow.transformer.WekaGetInstanceValue

WekaGOEValueDefinition - Class in adams.flow.source.valuedefinition

Definition for generic WEKA GOE objects.

WekaGOEValueDefinition() - Constructor for class adams.flow.source.valuedefinition.WekaGOEValueDefinition

WekaGraphVisualizer - Class in adams.flow.sink

Displays BayesNet graphs in XML or BIF notation
Either displays the contents of a file or an object that implements weka.core.Drawable and generates a BayesNet graph.

WekaGraphVisualizer() - Constructor for class adams.flow.sink.WekaGraphVisualizer

WekaHomeEnvironmentModifier - Class in adams.core.management

Sets a custom WEKA_HOME environment variable inside the project's home directory.

WekaHomeEnvironmentModifier() - Constructor for class adams.core.management.WekaHomeEnvironmentModifier

WekaInstanceBuffer - Class in adams.flow.transformer

Can act in two different ways:
1.

WekaInstanceBuffer() - Constructor for class adams.flow.transformer.WekaInstanceBuffer

WekaInstanceBuffer.Operation - Enum in adams.flow.transformer

Defines how the buffer actor operates.

WekaInstanceContainer - Class in adams.data.instance

Encapsulates a Instance object.

WekaInstanceContainer() - Constructor for class adams.data.instance.WekaInstanceContainer

WekaInstanceDumper - Class in adams.flow.transformer

Dumps weka.core.Instance objects into an ARFF file.

WekaInstanceDumper() - Constructor for class adams.flow.transformer.WekaInstanceDumper

WekaInstanceDumper.OutputFormat - Enum in adams.flow.transformer

The format to output the data in.

WekaInstanceEvaluator - Class in adams.flow.transformer

Adds a new attribute to the data being passed through (normally 'evaluation') and sets the value to the evaluation value returned by the chosen evaluator scheme.

WekaInstanceEvaluator() - Constructor for class adams.flow.transformer.WekaInstanceEvaluator

WekaInstanceFileReader - Class in adams.flow.transformer

Loads a WEKA dataset from disk with a specified reader and passes on the adams.core.instance.Instance objects.

WekaInstanceFileReader() - Constructor for class adams.flow.transformer.WekaInstanceFileReader

WekaInstances - Class in adams.gui.visualization.debug.inspectionhandler

Provides further insight into Instance and Instances objects.

WekaInstances() - Constructor for class adams.gui.visualization.debug.inspectionhandler.WekaInstances

WekaInstancesAppend - Class in adams.flow.transformer

Creates one large dataset by appending all one after the other.

WekaInstancesAppend() - Constructor for class adams.flow.transformer.WekaInstancesAppend

WekaInstancesDisplay - Class in adams.flow.sink

Actor for displaying a weka.core.Instances object in table format.

WekaInstancesDisplay() - Constructor for class adams.flow.sink.WekaInstancesDisplay

WekaInstancesExporter - Class in adams.gui.visualization.debug.objectexport

Exports Weka Instances/Instance objects.

WekaInstancesExporter() - Constructor for class adams.gui.visualization.debug.objectexport.WekaInstancesExporter

WekaInstancesHistogramRanges - Class in adams.flow.transformer

Outputs the ranges generated by adams.data.statistics.ArrayHistogram using the incoming weka.core.Instances object.
The actor just uses the internal format (double array) and does not check whether the attributes are actually numeric.

WekaInstancesHistogramRanges() - Constructor for class adams.flow.transformer.WekaInstancesHistogramRanges

WekaInstancesInfo - Class in adams.flow.transformer

Outputs statistics of a weka.core.Instances object.
FULL_ATTRIBUTE and FULL_CLASS output a spreadsheet with detailed attribute statistics.

WekaInstancesInfo() - Constructor for class adams.flow.transformer.WekaInstancesInfo

WekaInstancesInfo.InfoType - Enum in adams.flow.transformer

The type of information to generate.

WekaInstancesMerge - Class in adams.flow.transformer

Merges multiple datasets, either from file or using Instances/Instance objects.
If no 'ID' attribute is named, then all datasets must contain the same number of rows.
Attributes can be excluded from ending up in the final dataset via a regular expression.

WekaInstancesMerge() - Constructor for class adams.flow.transformer.WekaInstancesMerge

WekaInstancesPlot - Class in adams.flow.sink

Actor for plotting one attribute vs another.

WekaInstancesPlot() - Constructor for class adams.flow.sink.WekaInstancesPlot

WekaInstancesRenderer - Class in adams.gui.visualization.debug.objectrenderer

Renders Weka Instances/Instance objects.

WekaInstancesRenderer() - Constructor for class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer

WekaInstancesStatistic - Class in adams.flow.transformer

Generates statistics from a weka.core.Instances object.
The actor just uses the internal format (double array) and does not check whether the attributes are actually numeric.

WekaInstancesStatistic() - Constructor for class adams.flow.transformer.WekaInstancesStatistic

WekaInstancesStatisticDataType - Enum in adams.flow.transformer

Defines what data to retrieve from an Instances object.

WekaInstancesToSpreadSheet - Class in adams.data.conversion

Generates a spreadsheet from a weka.core.Instances object.

WekaInstancesToSpreadSheet() - Constructor for class adams.data.conversion.WekaInstancesToSpreadSheet

WekaInstanceStreamPlotGenerator - Class in adams.flow.transformer

Generates plot containers from a range of attributes of the weka.core.Instance objects being passed through.
The generator merely uses the internal data representation for generating the Y value of the plot container.

WekaInstanceStreamPlotGenerator() - Constructor for class adams.flow.transformer.WekaInstanceStreamPlotGenerator

WekaInstanceToAdamsInstance - Class in adams.data.conversion

Converts weka.core.Instance objects into adams.data.instance.Instance ones.

WekaInstanceToAdamsInstance() - Constructor for class adams.data.conversion.WekaInstanceToAdamsInstance

WekaInstanceToMap - Class in adams.data.conversion

Turns the Weka Instance into a Map, with the attribute names the keys.

WekaInstanceToMap() - Constructor for class adams.data.conversion.WekaInstanceToMap

WekaInstanceViewer - Class in adams.flow.sink

Actor for displaying adams.data.instance.Instance objects in a graphical way (using the internal format), like the 'Instance Explorer' tool.

WekaInstanceViewer() - Constructor for class adams.flow.sink.WekaInstanceViewer

WekaInvestigator - Class in adams.gui.menu

Opens the WEKA Investigator.

WekaInvestigator() - Constructor for class adams.gui.menu.WekaInvestigator

Initializes the menu item with no owner.

WekaInvestigator(AbstractApplicationFrame) - Constructor for class adams.gui.menu.WekaInvestigator

Initializes the menu item.

WekaInvestigatorDataEvent - Class in adams.gui.event

Event that gets sent when the data in an InvestigatorPanel changes.

WekaInvestigatorDataEvent(InvestigatorPanel) - Constructor for class adams.gui.event.WekaInvestigatorDataEvent

Constructor if the whole table changed.

WekaInvestigatorDataEvent(InvestigatorPanel, int) - Constructor for class adams.gui.event.WekaInvestigatorDataEvent

Constructor for specifying the type of change.

WekaInvestigatorDataEvent(InvestigatorPanel, int, int) - Constructor for class adams.gui.event.WekaInvestigatorDataEvent

Constructor for specifying the type of change.

WekaInvestigatorDataEvent(InvestigatorPanel, int, int[]) - Constructor for class adams.gui.event.WekaInvestigatorDataEvent

Constructor for specifying the type of change.

WekaInvestigatorDataListener - Interface in adams.gui.event

Interface for classes that get notified about changes in the data in an InvestigatorPanel.

WekaInvestigatorDefinition - Class in adams.env

Definition for the Weka Investigator props file.

WekaInvestigatorDefinition() - Constructor for class adams.env.WekaInvestigatorDefinition

WekaInvestigatorPreferencesPanel - Class in adams.gui.application

Preferences for the WEKA Investigator.

WekaInvestigatorPreferencesPanel() - Constructor for class adams.gui.application.WekaInvestigatorPreferencesPanel

WekaInvestigatorShortcutsDefinition - Class in adams.env

Definition for the Weka Investigator shortcuts props file.

WekaInvestigatorShortcutsDefinition() - Constructor for class adams.env.WekaInvestigatorShortcutsDefinition

WekaLabelIndex - Class in adams.data.weka

Extended Index class that can use a label name to determine an index of a label as well.

WekaLabelIndex() - Constructor for class adams.data.weka.WekaLabelIndex

Initializes with no index.

WekaLabelIndex(String) - Constructor for class adams.data.weka.WekaLabelIndex

Initializes with the given index, but no maximum.

WekaLabelIndex(String, int) - Constructor for class adams.data.weka.WekaLabelIndex

Initializes with the given index and maximum.

WekaLabelIndexEditor - Class in adams.gui.goe

Editor for WekaLabelIndex objects.

WekaLabelIndexEditor() - Constructor for class adams.gui.goe.WekaLabelIndexEditor

WekaLabelIndexParsing - Class in adams.core.option.parsing

For parsing WekaLabelIndex options.

WekaLabelIndexParsing() - Constructor for class adams.core.option.parsing.WekaLabelIndexParsing

WekaLabelRange - Class in adams.data.weka

Extended Range class that also allows attribute names for specifying attribute positions (names are case-insensitive, just like placeholders for 'first', 'second', etc).

WekaLabelRange() - Constructor for class adams.data.weka.WekaLabelRange

Initializes with no range.

WekaLabelRange(String) - Constructor for class adams.data.weka.WekaLabelRange

Initializes with the given range, but no maximum.

WekaLabelRange(String, int) - Constructor for class adams.data.weka.WekaLabelRange

Initializes with the given range and maximum.

WekaLabelRangeEditor - Class in adams.gui.goe

Editor for WekaLabelRange objects.

WekaLabelRangeEditor() - Constructor for class adams.gui.goe.WekaLabelRangeEditor

WekaLabelRangeParsing - Class in adams.core.option.parsing

For parsing WekaLabelRange options.

WekaLabelRangeParsing() - Constructor for class adams.core.option.parsing.WekaLabelRangeParsing

WekaMarginCurve - Class in adams.flow.sink

Actor for displaying margin errors.

WekaMarginCurve() - Constructor for class adams.flow.sink.WekaMarginCurve

WekaMergeInstancesActor - Interface in adams.flow.transformer

Interface for transformers that merge Weka Instances.

WekaModelContainer - Class in adams.flow.container

A container for models (e.g., classifier or clusterer) and an optional header of a dataset.

WekaModelContainer() - Constructor for class adams.flow.container.WekaModelContainer

Initializes the container.

WekaModelContainer(Object) - Constructor for class adams.flow.container.WekaModelContainer

Initializes the container with no header.

WekaModelContainer(Object, Instances) - Constructor for class adams.flow.container.WekaModelContainer

Initializes the container with no header.

WekaModelContainer(Object, Instances, Instances) - Constructor for class adams.flow.container.WekaModelContainer

Initializes the container with no header.

WekaModelReader - Class in adams.flow.transformer

Actor for loading a model (classifier or clusterer).

WekaModelReader() - Constructor for class adams.flow.transformer.WekaModelReader

WekaModelWriter - Class in adams.flow.sink

Actor for saving a model (classifier or clusterer) alongside an optional header (i.e., weka.core.Instances object) as file.

WekaModelWriter() - Constructor for class adams.flow.sink.WekaModelWriter

WekaMultiExperimenter - Class in adams.gui.menu

Opens the WEKA Multi-Experimenter.

WekaMultiExperimenter() - Constructor for class adams.gui.menu.WekaMultiExperimenter

Initializes the menu item with no owner.

WekaMultiExperimenter(AbstractApplicationFrame) - Constructor for class adams.gui.menu.WekaMultiExperimenter

Initializes the menu item.

WekaMultiLabelSplitter - Class in adams.flow.transformer

Splits a dataset containing multiple class attributes ('multi-label') into separate datasets with only a single class attribute.

WekaMultiLabelSplitter() - Constructor for class adams.flow.transformer.WekaMultiLabelSplitter

WekaNearestNeighborSearch - Class in adams.flow.transformer

Outputs the specified number of nearest neighbors for the incoming Weka Instance.
The data used for the nearest neighbor search is either obtained from storage.

WekaNearestNeighborSearch() - Constructor for class adams.flow.transformer.WekaNearestNeighborSearch

WekaNearestNeighborSearchContainer - Class in adams.flow.container

A container for nearest neighbor search (instance and neighborhood).

WekaNearestNeighborSearchContainer() - Constructor for class adams.flow.container.WekaNearestNeighborSearchContainer

Initializes the container.

WekaNearestNeighborSearchContainer(Instance, Instances) - Constructor for class adams.flow.container.WekaNearestNeighborSearchContainer

Initializes the container with the filter and the associated data.

WekaNearestNeighborSearchContainer(Instance, Instances, double[]) - Constructor for class adams.flow.container.WekaNearestNeighborSearchContainer

Initializes the container with the filter and the associated data.

WekaNewExperiment - Class in adams.flow.source

Generates a new ADAMS experiment setup.

WekaNewExperiment() - Constructor for class adams.flow.source.WekaNewExperiment

WekaNewInstance - Class in adams.flow.transformer

Creates a new weka.core.Instance-derived object, with all values marked as missing.
The class implementing the weka.core.Instance interface needs to have a constructor that takes the number of attributes as sole parameter.

WekaNewInstance() - Constructor for class adams.flow.transformer.WekaNewInstance

WekaNewInstances - Class in adams.flow.source

Generates an empty dataset, based on the attribute types and names specified.
Nominal attributes are generated with an empty set of labels.

WekaNewInstances() - Constructor for class adams.flow.source.WekaNewInstances

WekaOptionHandlerHelpGenerator - Class in adams.gui.help

Help generator for OptionHandler.

WekaOptionHandlerHelpGenerator() - Constructor for class adams.gui.help.WekaOptionHandlerHelpGenerator

WekaOptionsConversionPanel - Class in adams.gui.tools

Helper panel that turns Weka commandline strings into quoted strings suitable to be placed into code.

WekaOptionsConversionPanel() - Constructor for class adams.gui.tools.WekaOptionsConversionPanel

WekaOptionUtils - Class in weka.core

Helper class for option parsing.

WekaOptionUtils() - Constructor for class weka.core.WekaOptionUtils

WekaPackageManagerAction - Class in adams.flow.source

Executes the specified action and forwards the generated output.

WekaPackageManagerAction - Class in adams.flow.standalone

Executes the specified action and forwards the generated output.

WekaPackageManagerAction - Class in adams.flow.transformer

Applies the selected Weka Package Manager action to the incoming data and forwards the generated output.

WekaPackageManagerAction() - Constructor for class adams.flow.source.WekaPackageManagerAction

WekaPackageManagerAction() - Constructor for class adams.flow.standalone.WekaPackageManagerAction

WekaPackageManagerAction() - Constructor for class adams.flow.transformer.WekaPackageManagerAction

WekaPackagesClassPathAugmenter - Class in adams.core.management

Returns the classpath augmentations for all the installed WEKA packages.

WekaPackagesClassPathAugmenter() - Constructor for class adams.core.management.WekaPackagesClassPathAugmenter

WekaPackageToMap - Class in adams.data.conversion

Turns the Weka Package into a Map.

WekaPackageToMap() - Constructor for class adams.data.conversion.WekaPackageToMap

WekaPackageUtils - Class in weka.core

Utility functions for Weka packages.

WekaPackageUtils() - Constructor for class weka.core.WekaPackageUtils

WekaPluginManagerExtensions - Class in adams.gui.application

Enables further extensions through Weka's PluginManager.

WekaPluginManagerExtensions() - Constructor for class adams.gui.application.WekaPluginManagerExtensions

WekaPredictionContainer - Class in adams.flow.container

A container for predictions made by a classifier.

WekaPredictionContainer() - Constructor for class adams.flow.container.WekaPredictionContainer

Initializes the container.

WekaPredictionContainer(Instance, double, double[]) - Constructor for class adams.flow.container.WekaPredictionContainer

Initializes the container.

WekaPredictionContainer(Instance, double, double[], String) - Constructor for class adams.flow.container.WekaPredictionContainer

Initializes the container.

WekaPredictionContainerToSpreadSheet - Class in adams.data.conversion

Turns a WEKA prediction container into a SpreadSheet object.

WekaPredictionContainerToSpreadSheet() - Constructor for class adams.data.conversion.WekaPredictionContainerToSpreadSheet

WekaPredictionContainerToSpreadSheet.SortContainer - Class in adams.data.conversion

Helper class for sorting the distribution.

WekaPredictionContainerToSpreadSheet.Sorting - Enum in adams.data.conversion

How to sort the distribution.

WekaPredictionsToInstances - Class in adams.flow.transformer

Generates weka.core.Instances from the predictions of an Evaluation object.

WekaPredictionsToInstances() - Constructor for class adams.flow.transformer.WekaPredictionsToInstances

WekaPredictionsToSpreadSheet - Class in adams.flow.transformer

Generates a SpreadSheet object from the predictions of an Evaluation object.

See also:
adams.flow.transformer.WekaSpreadSheetToPredictions

Input/output:
- accepts:
weka.classifiers.Evaluation
adams.flow.container.WekaEvaluationContainer
- generates:
adams.data.spreadsheet.SpreadSheet


Container information:
- adams.flow.container.WekaEvaluationContainer: Evaluation, Model, Prediction output, Original indices

WekaPredictionsToSpreadSheet() - Constructor for class adams.flow.transformer.WekaPredictionsToSpreadSheet

WekaPrincipalComponents - Class in adams.flow.transformer

Performs principal components analysis on the incoming data and outputs the loadings and the transformed data as spreadsheet array.
Automatically filters out attributes that cannot be handled by PCA.

WekaPrincipalComponents() - Constructor for class adams.flow.transformer.WekaPrincipalComponents

WekaPropertySheetPanelPage - Class in adams.gui.wizard

Wizard page that use a PropertySheetPanel for displaying the properties of an object.

WekaPropertySheetPanelPage() - Constructor for class adams.gui.wizard.WekaPropertySheetPanelPage

Default constructor.

WekaPropertySheetPanelPage(String) - Constructor for class adams.gui.wizard.WekaPropertySheetPanelPage

Initializes the page with the given page name.

WekaPropertySheetPanelPage.CustomPropertySheetPanel - Class in adams.gui.wizard

Allowing better access to property sheet panel.

WekaPropertyValueConverter - Class in adams.flow.core

Handler for WEKA classes.

WekaPropertyValueConverter() - Constructor for class adams.flow.core.WekaPropertyValueConverter

WekaRandomSplit - Class in adams.flow.transformer

Splits a dataset into a training and test set according to a specified split percentage.

WekaRandomSplit() - Constructor for class adams.flow.transformer.WekaRandomSplit

WekaRegexToRange - Class in adams.flow.transformer

Produces a range string from a regular expression describing attributes.

WekaRegexToRange() - Constructor for class adams.flow.transformer.WekaRegexToRange

WekaRegressionModel - Class in adams.ml.model.regression

Regression model for Weka classifiers.

WekaRegressionModel(Classifier, Dataset, Instances) - Constructor for class adams.ml.model.regression.WekaRegressionModel

Initializes the model.

WekaRegressor - Class in adams.ml.model.regression

Wraps around a Weka classifier that handles numeric classes (= regression).

WekaRegressor() - Constructor for class adams.ml.model.regression.WekaRegressor

WekaRelationName - Class in adams.flow.transformer

Deprecated.

WekaRelationName() - Constructor for class adams.flow.transformer.WekaRelationName

Deprecated.

WekaRenameRelation - Class in adams.flow.transformer

Modifies relation names.

WekaRenameRelation() - Constructor for class adams.flow.transformer.WekaRenameRelation

WekaReorderAttributesToReference - Class in adams.flow.transformer

Reorders the attributes of the Instance/Instances passing through according to the provided reference dataset (callable actor or reference file).
This ensures that the generated data always has the same structure as the reference dataset.

WekaReorderAttributesToReference() - Constructor for class adams.flow.transformer.WekaReorderAttributesToReference

WekaRepeatedCrossValidationEvaluator - Class in adams.flow.transformer

Performs repeated cross-validation a classifier on an incoming dataset.

WekaRepeatedCrossValidationEvaluator() - Constructor for class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

WekaRepeatedCrossValidationOutput - Class in adams.flow.transformer

Generates output from the incoming repeated cross-validation data.

WekaRepeatedCrossValidationOutput() - Constructor for class adams.flow.transformer.WekaRepeatedCrossValidationOutput

WekaSelectDataset - Class in adams.flow.source

Pops up a file chooser dialog, prompting the user to select one or more datasets.

WekaSelectDataset() - Constructor for class adams.flow.source.WekaSelectDataset

WekaSelectDatasetPage - Class in adams.gui.wizard

Wizard page that allows the user to select a Weka dataset.

WekaSelectDatasetPage() - Constructor for class adams.gui.wizard.WekaSelectDatasetPage

whether to show the /** Default constructor.

WekaSelectDatasetPage(String) - Constructor for class adams.gui.wizard.WekaSelectDatasetPage

Initializes the page with the given page name.

WekaSelectMultipleDatasetsPage - Class in adams.gui.wizard

Wizard page that allows the user to select multiple datasets.

WekaSelectMultipleDatasetsPage() - Constructor for class adams.gui.wizard.WekaSelectMultipleDatasetsPage

Default constructor.

WekaSelectMultipleDatasetsPage(String) - Constructor for class adams.gui.wizard.WekaSelectMultipleDatasetsPage

Initializes the page with the given page name.

WekaSelectObjects - Class in adams.flow.source

Allows the user to select an arbitrary number of Weka objects from the specified class hierarchy using the GenericObjectArray.

WekaSelectObjects() - Constructor for class adams.flow.source.WekaSelectObjects

WekaSetInstancesValue - Class in adams.flow.transformer

Sets a value in a WEKA Instances object.
Notes:
- relational values cannot be set
- '?' (without single quotes) is interpreted as missing value

Input/output:
- accepts:
weka.core.Instances
- generates:
weka.core.Instances

WekaSetInstancesValue() - Constructor for class adams.flow.transformer.WekaSetInstancesValue

WekaSetInstanceValue - Class in adams.flow.transformer

Sets a value in a WEKA Instance.
Notes:
- relational values cannot be set
- '?' (without single quotes) is interpreted as missing value

Input/output:
- accepts:
weka.core.Instance
- generates:
weka.core.Instance


Valid options are:

WekaSetInstanceValue() - Constructor for class adams.flow.transformer.WekaSetInstanceValue

WekaSimpleCLI - Class in adams.gui.menu

Opens the WEKA SimpleCLI.

WekaSimpleCLI() - Constructor for class adams.gui.menu.WekaSimpleCLI

Initializes the menu item with no owner.

WekaSimpleCLI(AbstractApplicationFrame) - Constructor for class adams.gui.menu.WekaSimpleCLI

Initializes the menu item.

WekaSplitGenerator - Class in adams.flow.transformer

WekaSplitGenerator() - Constructor for class adams.flow.transformer.WekaSplitGenerator

WekaSpreadSheetToPredictions - Class in adams.flow.transformer

Turns the predictions stored in the incoming spreadsheet (actual and predicted) into a Weka weka.classifiers.Evaluation object.
For recreating the predictions of a nominal class, the class distributions must be present in the spreadsheet as well.

See also:
adams.flow.transformer.WekaPredictionsToSpreadSheet

Input/output:
- accepts:
adams.data.spreadsheet.SpreadSheet
- generates:
weka.classifiers.Evaluation

WekaSpreadSheetToPredictions() - Constructor for class adams.flow.transformer.WekaSpreadSheetToPredictions

WekaStoreInstance - Class in adams.flow.transformer

Appends the incoming weka.core.Instance to the dataset in storage.

WekaStoreInstance() - Constructor for class adams.flow.transformer.WekaStoreInstance

WekaStreamEvaluator - Class in adams.flow.transformer

Evaluates an incremental classifier on a data stream using prequential evaluation (first evaluate, then train).

WekaStreamEvaluator() - Constructor for class adams.flow.transformer.WekaStreamEvaluator

WekaStreamFilter - Class in adams.flow.transformer

Filters Instance objects using the specified filter.

WekaStreamFilter() - Constructor for class adams.flow.transformer.WekaStreamFilter

WekaSubsets - Class in adams.flow.transformer

Splits the dataset based on the unique values of the specified attribute: all rows with the same unique value form a subset.

WekaSubsets() - Constructor for class adams.flow.transformer.WekaSubsets

WekaSystemProperties - Class in adams.gui.application

Sets some Weka-specific system properties to improve performance.

WekaSystemProperties() - Constructor for class adams.gui.application.WekaSystemProperties

WekaTestSetClustererEvaluator - Class in adams.flow.transformer

Evaluates a trained clusterer (obtained from input) on the dataset obtained from the callable actor.
If a class attribute is set, a classes-to-clusters evaluation is performed automatically

Input/output:
- accepts:
weka.clusterers.Clusterer
adams.flow.container.WekaModelContainer
- generates:
adams.flow.container.WekaClusterEvaluationContainer


Container information:
- adams.flow.container.WekaModelContainer: Model, Header, Dataset
- adams.flow.container.WekaClusterEvaluationContainer: Evaluation, Model, Log-likelohood

WekaTestSetClustererEvaluator() - Constructor for class adams.flow.transformer.WekaTestSetClustererEvaluator

WekaTestSetEvaluator - Class in adams.flow.transformer

Evaluates a trained classifier (obtained from input) on the dataset obtained from the callable actor.

WekaTestSetEvaluator() - Constructor for class adams.flow.transformer.WekaTestSetEvaluator

WekaTestSetEvaluator.EvaluateJob - Class in adams.flow.transformer

WekaTextDirectoryReader - Class in adams.flow.transformer

Loads all text files in a directory and uses the subdirectory names as class labels.

WekaTextDirectoryReader() - Constructor for class adams.flow.transformer.WekaTextDirectoryReader

WekaThresholdCurve - Class in adams.flow.sink

Actor for displaying threshold curves, like ROC or precision/recall.

WekaThresholdCurve() - Constructor for class adams.flow.sink.WekaThresholdCurve

WekaThresholdCurve.AttributeName - Enum in adams.flow.sink

The type of the fields.

wekaToJama(Matrix) - Static method in class adams.data.instancesanalysis.pls.MatrixHelper

Turns a Weka matrix into a Jama one.

wekaToMatrixAlgo(Matrix) - Static method in class adams.data.instancesanalysis.pls.MatrixHelper

Turns a Weka matrix into a matrix-algorithm one.

WekaTrainAssociator - Class in adams.flow.transformer

Trains an associator based on the incoming dataset and outputs the built associator alongside the training header and rules (in a model container)..

WekaTrainAssociator() - Constructor for class adams.flow.transformer.WekaTrainAssociator

WekaTrainAssociator.TrainJob - Class in adams.flow.transformer

WekaTrainClassifier - Class in adams.flow.transformer

Trains a classifier based on the incoming dataset and outputs the built classifier alongside the training header (in a model container).
Incremental training is performed, if the input are weka.core.Instance objects and the classifier implements weka.classifiers.UpdateableClassifier.

WekaTrainClassifier() - Constructor for class adams.flow.transformer.WekaTrainClassifier

WekaTrainClassifier.BatchTrainJob - Class in adams.flow.transformer

WekaTrainClusterer - Class in adams.flow.transformer

Trains a clusterer based on the incoming dataset and output the built clusterer alongside the training header (in a model container).
Incremental training is performed, if the input are weka.core.Instance objects and the clusterer implements weka.clusterers.UpdateableClusterer.

WekaTrainClusterer() - Constructor for class adams.flow.transformer.WekaTrainClusterer

WekaTrainClusterer.BatchTrainJob - Class in adams.flow.transformer

WekaTrainTestSetClustererEvaluator - Class in adams.flow.transformer

Trains a clusterer on an incoming training dataset (from a container) and then evaluates it on the test set (also from a container).
The clusterer setup being used in the evaluation is a callable 'Clusterer' actor.
If a class attribute is set, a classes-to-clusters evaluation is performed automatically

Input/output:
- accepts:
adams.flow.container.WekaTrainTestSetContainer
- generates:
adams.flow.container.WekaClusterEvaluationContainer


Container information:
- adams.flow.container.WekaTrainTestSetContainer: Train, Test, Seed, FoldNumber, FoldCount
- adams.flow.container.WekaClusterEvaluationContainer: Evaluation, Model, Log-likelohood

WekaTrainTestSetClustererEvaluator() - Constructor for class adams.flow.transformer.WekaTrainTestSetClustererEvaluator

WekaTrainTestSetContainer - Class in adams.flow.container

A container for storing train and test set.

WekaTrainTestSetContainer() - Constructor for class adams.flow.container.WekaTrainTestSetContainer

Initializes the container.

WekaTrainTestSetContainer(Instances, Instances) - Constructor for class adams.flow.container.WekaTrainTestSetContainer

Initializes the container.

WekaTrainTestSetContainer(Instances, Instances, Long) - Constructor for class adams.flow.container.WekaTrainTestSetContainer

Initializes the container.

WekaTrainTestSetContainer(Instances, Instances, Long, Integer, Integer) - Constructor for class adams.flow.container.WekaTrainTestSetContainer

Initializes the container.

WekaTrainTestSetContainer(Instances, Instances, Long, Integer, Integer, int[], int[]) - Constructor for class adams.flow.container.WekaTrainTestSetContainer

Initializes the container.

WekaTrainTestSetEvaluator - Class in adams.flow.transformer

Trains a classifier on an incoming training dataset (from a container) and then evaluates it on the test set (also from a container).
The classifier setup being used in the evaluation is a callable 'Classifier' actor.

WekaTrainTestSetEvaluator() - Constructor for class adams.flow.transformer.WekaTrainTestSetEvaluator

WekaTrainTestSetEvaluator.EvaluateJob - Class in adams.flow.transformer

WekaTreeVisualizer - Class in adams.flow.sink

Displays trees in dot notation.

WekaTreeVisualizer() - Constructor for class adams.flow.sink.WekaTreeVisualizer

WekaUnorderedAttributeRange - Class in adams.data.weka

Extended UnorderedRange class that also allows attribute names for specifying attribute positions (names are case-insensitive, just like placeholders for 'first', 'second', etc).

WekaUnorderedAttributeRange() - Constructor for class adams.data.weka.WekaUnorderedAttributeRange

Initializes with no range.

WekaUnorderedAttributeRange(String) - Constructor for class adams.data.weka.WekaUnorderedAttributeRange

Initializes with the given range, but no maximum.

WekaUnorderedAttributeRange(String, int) - Constructor for class adams.data.weka.WekaUnorderedAttributeRange

Initializes with the given range and maximum.

WekaUnorderedAttributeRangeEditor - Class in adams.gui.goe

A PropertyEditor for WekaAttributeRange objects.

WekaUnorderedAttributeRangeEditor() - Constructor for class adams.gui.goe.WekaUnorderedAttributeRangeEditor

WekaUnorderedAttributeRangeParsing - Class in adams.core.option.parsing

For parsing WekaUnorderedAttributeRange options.

WekaUnorderedAttributeRangeParsing() - Constructor for class adams.core.option.parsing.WekaUnorderedAttributeRangeParsing

windowsPointTipText() - Method in class weka.filters.unsupervised.attribute.PAA

Returns the tip text for this property.

windowsPointTipText() - Method in class weka.filters.unsupervised.attribute.SAX

Returns the tip text for this property.

withReplacementTipText() - Method in class adams.flow.transformer.WekaBootstrapping

Returns the tip text for this property.

Workbench - Class in adams.gui.menu

Opens the WEKA Workbench.

Workbench() - Constructor for class adams.gui.menu.Workbench

Initializes the menu item with no owner.

Workbench(AbstractApplicationFrame) - Constructor for class adams.gui.menu.Workbench

Initializes the menu item.

WorkspaceHelper - Class in weka.gui.explorer

Helper class for loading/saving workspaces.

WorkspaceHelper() - Constructor for class weka.gui.explorer.WorkspaceHelper

wrapUp() - Method in class adams.flow.sink.WekaDatabaseWriter

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.sink.WekaInstanceViewer

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.source.AbstractWekaSetupGenerator

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.source.WekaDatabaseReader

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.source.WekaSelectObjects

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaAccumulatedError

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaCrossValidationSplit

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaFileReader

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaInstanceBuffer

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaInstanceDumper

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaInstanceEvaluator

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaMultiLabelSplitter

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaSubsets

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaTrainClassifier

Cleans up after the execution has finished.

wrapUp() - Method in class adams.flow.transformer.WekaTrainClusterer

Cleans up after the execution has finished.

write(PlaceholderFile, AbstractExperiment) - Method in class adams.data.io.output.AbstractAdamsExperimentWriter

Writes the experiment file.

write(SpreadSheet) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractResultsHandler

Stores the results.

write(SpreadSheet) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Stores the results.

write(MultiExplorer, File) - Static method in class weka.gui.explorer.WorkspaceHelper

Saves the explorer session to the given file.

writeBatch() - Method in class weka.core.converters.SimpleArffSaver

Writes a Batch of instances

writeBatch() - Method in class weka.core.converters.SpreadSheetSaver

Writes a Batch of instances

writerForFile(File) - Static method in class adams.gui.chooser.AdamsExperimentFileChooser

Returns the writer for the specified file.

writerForFile(File) - Static method in class adams.gui.chooser.WekaFileChooser

Returns the writer for the specified file.

writerTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler

Returns the tip text for this property.

writeToDisk(boolean) - Method in class adams.flow.transformer.WekaInstanceDumper

Writes the content of the buffer to disk.

X

XGBoost - Class in weka.classifiers.trees

Classifier implementing XGBoost.

XGBoost() - Constructor for class weka.classifiers.trees.XGBoost

XGBoost.BoosterType - Enum in weka.classifiers.trees

The available types of booster.

XGBoost.FeatureSelector - Enum in weka.classifiers.trees

Available feature selectors.

XGBoost.GrowPolicy - Enum in weka.classifiers.trees

Available grow policy settings.

XGBoost.NormaliseType - Enum in weka.classifiers.trees

Available normalisation-type settings.

XGBoost.Objective - Enum in weka.classifiers.trees

The set of possible learning objectives.

XGBoost.ParamValueProvider - Interface in weka.classifiers.trees

Provides a value suitable as a proxy for the XGBoost parameter system.

XGBoost.Predictor - Enum in weka.classifiers.trees

Available predictors.

XGBoost.ProcessType - Enum in weka.classifiers.trees

Available process-type settings.

XGBoost.SampleType - Enum in weka.classifiers.trees

Available sample-type settings.

XGBoost.TreeMethod - Enum in weka.classifiers.trees

Possible tree-method settings.

XGBoost.Updater - Enum in weka.classifiers.trees

Available updaters.

XGBoost.Verbosity - Enum in weka.classifiers.trees

The possible verbosity levels.

XGBoost.XGBoostParameter - Annotation Type in weka.classifiers.trees

Marks a field as participating in the XGBoost parameter system.

XRegExpTipText() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the tip text for this property

XrffSpreadSheetReader - Class in adams.data.io.input

Reads WEKA datasets in ARFF format and turns them into spreadsheets.

XrffSpreadSheetReader() - Constructor for class adams.data.io.input.XrffSpreadSheetReader

XrffSpreadSheetWriter - Class in adams.data.io.output

Writes a spreadsheet in XRFF file format.

XrffSpreadSheetWriter() - Constructor for class adams.data.io.output.XrffSpreadSheetWriter

Y

YGradientEPO - Class in weka.filters.supervised.attribute

Applies the External Parameter Orthogonalization (EPO) algorithm to the data.

For more information see:
http://wiki.eigenvector.com/index.php?title=Advanced_Preprocessing:_Multivariate_Filtering#External_Parameter_Orthogonalization_.28EPO.29

Valid options are:

YGradientEPO() - Constructor for class weka.filters.supervised.attribute.YGradientEPO

YGradientGLSW - Class in weka.filters.supervised.attribute

Applies the Generalized Least Squares Weighting (GLSW) algorithm to the data.

For more information see:
http://wiki.eigenvector.com/index.php?title=Advanced_Preprocessing:_Multivariate_Filtering#Y-Gradient_GLSW

Valid options are:

YGradientGLSW() - Constructor for class weka.filters.supervised.attribute.YGradientGLSW

YRegExpTipText() - Method in class weka.filters.supervised.attribute.MultiPLS

Returns the tip text for this property

Z

zoomOverviewTipText() - Method in class adams.flow.sink.WekaInstanceViewer

Returns the tip text for this property.

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