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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.
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() - 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
 
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
 
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
 
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.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.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.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
 
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.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.
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.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.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.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.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.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.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.
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.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
 
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
 

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
 
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.
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.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.
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.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.
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.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(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
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
 
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(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(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
 
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.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.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis
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.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.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.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.
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.
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.
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.
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.
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.
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.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(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.
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.
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.
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.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.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.
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.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.WekaSelectDataset
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.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.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.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.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.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(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.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.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.
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.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.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.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.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.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.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.WekaSelectDataset
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.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.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.
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.
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(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.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.
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 SingeClassifierEnhancer wrappers.
EncloseClassifier() - Constructor for class adams.gui.goe.popupmenu.EncloseClassifier
 
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, Evaluation, AbstractOutput) - Constructor for class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob
Initializes the job.
EvaluateJob(Evaluation, Classifier, Instances, AbstractOutput) - Constructor for class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob
Initializes the job.
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.
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.
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.
filterInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights
Filters an instance.
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.
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.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.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, 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[]) - 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) - 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(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(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.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.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.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.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.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.
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.
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.
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.
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.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.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.
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.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis
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(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
 
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
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.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.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.
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.
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.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.
getDefaultAxisY() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot
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.
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.
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.
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.
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.
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.
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.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.
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.
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.
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.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.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.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.
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).
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.
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.
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
 
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 disaply 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.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.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.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.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.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.
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.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.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.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.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.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.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.
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.
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.
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.
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.
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.
getPanelForReports(List) - Static method in class adams.gui.visualization.instance.InstanceReportFactory
Returns a new table for the given reports.
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.
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.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.
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.
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.
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.WekaSelectDataset
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.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.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.
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.
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.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.NewNNSearch
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.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.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(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.
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.
getRuns() - Method in class adams.flow.sink.WekaExperimentGenerator
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.
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).
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 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.
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.
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.
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.
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.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.
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.
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.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 table.
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.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.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.
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.
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.
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.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.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.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.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.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.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.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.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.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.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.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.NewNNSearch
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.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.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(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.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.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.
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.
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.
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(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
 
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.
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.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(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.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.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.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.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(AbstractApplicationFrame) - Method in class adams.gui.application.WekaPluginManagerExtensions
Performs the initialization.
initialize(AbstractApplicationFrame) - Method in class adams.gui.application.WekaSystemProperties
Performs the initialization.
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.
installLinearModels() - Method in class weka.classifiers.trees.m5.RuleNode2
Traverses the tree and installs linear models at each node.
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_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.
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.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.
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.
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.CrossValidation
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.MultiLevelSplitGenerator
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
 
kernelipText() - Method in class adams.data.instancesanalysis.pls.KernelPLS
Returns the tip text for this property
KernelPLS - Class in adams.data.instancesanalysis.pls
KernelPLS() - Constructor for class adams.data.instancesanalysis.pls.KernelPLS
 
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.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_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.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.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 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_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.clustertab.evaluation.CrossValidation
 
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.TrainTestSplit
 
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_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_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.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_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_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 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.
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_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.
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.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.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.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.
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.
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).
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.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.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.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
 
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.

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_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_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_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_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_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_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_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.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.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_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_CheckBoxShowPassword - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel
whether to show the password.
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.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis
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_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_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 - 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.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_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.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.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_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_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.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
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.gui.tools.wekainvestigator.tab.ClassifyTab
the current classifier.
m_CurrentClusterer - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab
the current clusterer.
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_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_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.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_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.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_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.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.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_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_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.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.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.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.TrainTestSplit
the split generator.
m_GOEJobRunner - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
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_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.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_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_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.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_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_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_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_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.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.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.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.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_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_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.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_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.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.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.transformer.WekaExperimentEvaluation
the output format.
m_OutputFormat - Variable in class adams.flow.transformer.WekaInstanceDumper
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_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_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.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_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_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_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.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.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.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.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.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.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_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_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_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_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_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_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_Runs - Variable in class adams.flow.sink.WekaExperimentGenerator
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.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_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.clustertab.evaluation.CrossValidation
the number of folds.
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.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 weka.classifiers.meta.ClassifierCascade
the statistic to use for termination.
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.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.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.MultiLevelSplitGenerator
whether the generation got stopped.
m_Stopping - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab
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_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_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_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_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_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_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_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_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.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.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_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.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.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.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 - 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
maxIteripText() - 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_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 - 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 - 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.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.
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
 
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.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.
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 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.transformer.WekaExperimentEvaluation
Returns the tip text for this property.
outputFormatTipText() - Method in class adams.flow.transformer.WekaInstanceDumper
Returns the tip text for this property.
outputHeaderTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation
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.
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
 
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.
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.
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.
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.
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.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.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.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.gui.tools.wekainvestigator.tab.classifytab.output
Displays the predictions.
Predictions() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.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
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.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.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
 
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
 
quartile3 - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp.IQRs
 
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
 
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.
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.
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.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 - 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.
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.wekamultiexperimenter.analysis.DefaultAnalysisPanel.HistoryPanel
Removes the specified entry.
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.
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
 
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.
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.
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.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.
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(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(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.
resultWriterTipText() - 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.
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() - 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.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() - 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
 
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.
runsTipText() - Method in class adams.flow.sink.WekaExperimentGenerator
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
 
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.
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() - 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.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(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.
serialVersionUID - Static variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp
for serialization
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, 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.
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.
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.
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.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis
Sets the index of class label (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.
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(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.
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.
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.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.
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.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.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.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.
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).
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.
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.
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
 
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.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.
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.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.
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.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.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.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.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(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(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.
setOutputGenerator(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem
Sets the output generator.
setOutputHeader(boolean) - Method in class adams.flow.transformer.WekaExperimentEvaluation
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.
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.
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.
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(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.
setRuns(int) - Method in class adams.flow.sink.WekaExperimentGenerator
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).
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.
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.
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.
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.
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.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.
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.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.
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.
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.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.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.
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.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.
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
 
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.
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.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.
StatisticsTable() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.StatisticsTable
 
statisticTipText() - Method in class adams.flow.transformer.WekaInstancesStatistic
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
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.WekaSplitGenerator
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.CrossValidation
Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab
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.opt.genetic.AbstractClassifierBasedGeneticAlgorithm
Stops the execution of the algorithm.
stopExecution() - Method in class weka.classifiers.MultiLevelSplitGenerator
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.
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.
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.

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.
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.
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.
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.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.
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.
tolipText() - Method in class adams.data.instancesanalysis.pls.KernelPLS
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.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
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.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.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.
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.
UNIFORM - weka.classifiers.trees.XGBoost.SampleType
 
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.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.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(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(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
 
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.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.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.
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.
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.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 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.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.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.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.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.MultiClassifiersCombinerModels
Returns the tip text for this property.
voteTipText() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels
Returns the tip text for this property.
voteTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds
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
 
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
 
WekaPackagesClassPathAugmenter - Class in adams.core.management
Returns the classpath augmentations for all the installed WEKA packages.
WekaPackagesClassPathAugmenter() - Constructor for class adams.core.management.WekaPackagesClassPathAugmenter
 
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
 
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.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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