Index (adams-lts-pom 24.11.0-SNAPSHOT API)

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
All Classes All Packages

A

AArffLoader - Class in weka.core.converters: Safe version of the ArffLoader, always retaining string values.
AArffLoader() - Constructor for class weka.core.converters.AArffLoader
AArffLoader.AArffReader - Class in weka.core.converters
AArffReader(Reader) - Constructor for class weka.core.converters.AArffLoader.AArffReader: Reads the data completely from the reader.
AArffReader(Reader, int) - Constructor for class weka.core.converters.AArffLoader.AArffReader
AArffReader(Reader, int, boolean) - Constructor for class weka.core.converters.AArffLoader.AArffReader: Reads only the header and reserves the specified space for instances.
AArffReader(Reader, Instances, int) - Constructor for class weka.core.converters.AArffLoader.AArffReader: Reads the data without header according to the specified template.
AArffReader(Reader, Instances, int, int) - Constructor for class weka.core.converters.AArffLoader.AArffReader: Initializes the reader without reading the header according to the specified template.
AArffReader(Reader, Instances, int, int, boolean) - Constructor for class weka.core.converters.AArffLoader.AArffReader: Initializes the reader without reading the header according to the specified template.
abortExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner: Aborts the experiment.
abortExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Aborts the experiment.
abortExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.runner.RemoteWekaExperimentRunner: Aborts the experiment.
ABOVE - weka.classifiers.meta.ClassifierCascade.ThresholdCheck
absDev(int, Instances) - Static method in class weka.classifiers.trees.m5.Rule2: Returns the absolute deviation value of the supplied attribute index.
absErrTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Returns the tip text for this property
absErrTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Returns the tip text for this property
ABSOLUTE - adams.flow.transformer.WekaBootstrapping.ErrorCalculation
AbsolutePredictionErrorComparator - Class in adams.flow.transformer.wekaevaluationpostprocessor: Comparator for predictions using the (absolute) prediction error (sorting increasingly).
AbsolutePredictionErrorComparator() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.AbsolutePredictionErrorComparator
absoluteTipText() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: Returns the tip text for this property.
AbstainAttributePercentile - Class in weka.classifiers.meta: Only predict if attribute value within percentile range.
AbstainAttributePercentile() - Constructor for class weka.classifiers.meta.AbstainAttributePercentile
AbstainAverage - Class in weka.classifiers.meta: Average base classifiers, abstain if difference outside thresholds

Valid options are:
AbstainAverage() - Constructor for class weka.classifiers.meta.AbstainAverage
AbstainAverageWithClassifierWeights - Class in weka.classifiers.meta: Average base classifiers, abstain if difference outside thresholds

Valid options are:
AbstainAverageWithClassifierWeights() - Constructor for class weka.classifiers.meta.AbstainAverageWithClassifierWeights
AbstainingCascade - Class in weka.classifiers.meta: The specified classifiers represent a cascade: if the first one abstains, the second is used (and so on), otherwise the prediction is returned.
If all classifiers prior to the last one abstained then the prediction of the last one is returned.
AbstainingCascade() - Constructor for class weka.classifiers.meta.AbstainingCascade
AbstainingClassifier - Interface in weka.classifiers: Interface for classifiers that may support abstaining.
AbstainingClassifierWrapper - Class in weka.classifiers.meta: Wraps an abstaining classifier and allows turning on/of abstaining.
AbstainingClassifierWrapper() - Constructor for class weka.classifiers.meta.AbstainingClassifierWrapper: Initializes the classifier.
AbstainingLWL - Class in weka.classifiers.lazy: LWL variant that supports abstaining if the base classifier is able to.
AbstainingLWL() - Constructor for class weka.classifiers.lazy.AbstainingLWL
AbstainLeastMedianSq - Class in weka.classifiers.meta: Finds the base classifier with the best least median squared error.
AbstainLeastMedianSq() - Constructor for class weka.classifiers.meta.AbstainLeastMedianSq
AbstainMinimumProbability - Class in weka.classifiers.meta: Abstains if the probability of the chosen class label is below the specified threshold.
AbstainMinimumProbability() - Constructor for class weka.classifiers.meta.AbstainMinimumProbability
AbstainVote - Class in weka.classifiers.meta: Finds the base classifier with the best least median squared error.
AbstainVote() - Constructor for class weka.classifiers.meta.AbstainVote
AbstractAdamsExperimentIO<T extends AbstractExperiment> - Class in adams.gui.tools.wekamultiexperimenter.io: Ancestor for classes that handle loading/saving of experiments.
AbstractAdamsExperimentIO() - Constructor for class adams.gui.tools.wekamultiexperimenter.io.AbstractAdamsExperimentIO
AbstractAdamsExperimentReader - Class in adams.data.io.input: Ancestor for readers for ADAMS Experiments.
AbstractAdamsExperimentReader() - Constructor for class adams.data.io.input.AbstractAdamsExperimentReader
AbstractAdamsExperimentRunner<T extends AbstractExperiment> - Class in adams.gui.tools.wekamultiexperimenter.runner: Ancestor for classes that handle running a copy of the experiment in a separate thread.
AbstractAdamsExperimentRunner(ExperimenterPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner: Initializes the thread.
AbstractAdamsExperimentWriter - Class in adams.data.io.output: Ancestor for ADAMS Experiment writers.
AbstractAdamsExperimentWriter() - Constructor for class adams.data.io.output.AbstractAdamsExperimentWriter
AbstractAdamsSetupPanel - Class in adams.gui.tools.wekamultiexperimenter.setup: Ancestor for setup panels for ADAMS experiments.
AbstractAdamsSetupPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractAdamsSetupPanel
AbstractAdditionalExplorerPanel - Class in weka.gui.explorer.panels: Wrapper class for additional panels to be displayed in the Explorer.
AbstractAdditionalExplorerPanel() - Constructor for class weka.gui.explorer.panels.AbstractAdditionalExplorerPanel
AbstractAnalysisPanel - Class in adams.gui.tools.wekamultiexperimenter.analysis: Ancestor for panels that analysis experimental results.
AbstractAnalysisPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel
AbstractAssociatorEvaluation - Class in adams.gui.tools.wekainvestigator.tab.associatetab.evaluation: Ancestor for associator evaluation setups.
AbstractAssociatorEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation
AbstractAttributeCapabilities - Class in adams.flow.condition.bool: Ancestor for capabilities-based conditions.
AbstractAttributeCapabilities() - Constructor for class adams.flow.condition.bool.AbstractAttributeCapabilities
AbstractAttributeSelectionEvaluation - Class in adams.gui.tools.wekainvestigator.tab.attseltab.evaluation: Ancestor for attribute selection evaluation setups.
AbstractAttributeSelectionEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation
AbstractCallableWekaClassifierEvaluator - Class in adams.flow.transformer: Ancestor for classifier evaluators that make use of a callable classifier.
AbstractCallableWekaClassifierEvaluator() - Constructor for class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator
AbstractCallableWekaClustererEvaluator - Class in adams.flow.transformer: Ancestor for clusterer evaluators that make use of a callable clusterer.
AbstractCallableWekaClustererEvaluator() - Constructor for class adams.flow.transformer.AbstractCallableWekaClustererEvaluator
AbstractClassAttributeHeuristic - Class in adams.data.weka.classattribute: Ancestor for heuristics that determine the class attribute for a dataset.
AbstractClassAttributeHeuristic() - Constructor for class adams.data.weka.classattribute.AbstractClassAttributeHeuristic
AbstractClassifierBasedGeneticAlgorithm - Class in adams.opt.genetic: Ancestor for genetic algorithms that evaluate classifiers.
AbstractClassifierBasedGeneticAlgorithm() - Constructor for class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm
AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob<T extends AbstractClassifierBasedGeneticAlgorithm> - Class in adams.opt.genetic: Job class for algorithms with datasets.
AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation - Class in adams.opt.genetic: Ancestor for genetic algorithms that offer a second evaluation using a different seed value.
AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation() - Constructor for class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation
AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob<T extends AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation> - Class in adams.opt.genetic: Job class for algorithms with datasets.
AbstractClassifierBasedGeneticAlgorithmWizard - Class in adams.gui.menu: Ancestor for optimizing datasets (attribute selection) using a genetic algorithm.
AbstractClassifierBasedGeneticAlgorithmWizard() - Constructor for class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: Initializes the menu item with no owner.
AbstractClassifierBasedGeneticAlgorithmWizard(AbstractApplicationFrame) - Constructor for class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: Initializes the menu item.
AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot - Class in adams.gui.menu: For plotting the performance of the genetic algorithm.
AbstractClassifierEvaluation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation: Ancestor for classifier evaluation setups.
AbstractClassifierEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation
AbstractClassifierSetupProcessor - Class in adams.flow.transformer.wekaclassifiersetupprocessor: Ancestor for schemes that preprocess classifier arrays.
AbstractClassifierSetupProcessor() - Constructor for class adams.flow.transformer.wekaclassifiersetupprocessor.AbstractClassifierSetupProcessor
AbstractClustererEvaluation - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation: Ancestor for clusterer evaluation setups.
AbstractClustererEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation
AbstractClustererPostProcessor - Class in adams.flow.transformer.wekaclusterer: Ancestor for post-processors for output that the WekaClusterer transformer produces.
AbstractClustererPostProcessor() - Constructor for class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor
AbstractClusterMembershipPostProcessor - Class in adams.flow.transformer.wekaclusterer: Ancestor for post-processors that require a built clusterer and the dataset that was used to build the clusterer to be present in the model container.
AbstractClusterMembershipPostProcessor() - Constructor for class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor
AbstractColumnFinder - Class in adams.data.weka.columnfinder: Ancestor for classes that find columns of interest in datasets.
AbstractColumnFinder() - Constructor for class adams.data.weka.columnfinder.AbstractColumnFinder
AbstractColumnFinderApplier - Class in weka.filters.unsupervised.attribute: Ancestor for filters that apply ColumnFinder schemes to the data.
AbstractColumnFinderApplier() - Constructor for class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier
AbstractColumnFinderWithCapabilities - Class in adams.data.weka.columnfinder: Ancestor for classes that find columns of interest in datasets.
AbstractColumnFinderWithCapabilities() - Constructor for class adams.data.weka.columnfinder.AbstractColumnFinderWithCapabilities
AbstractCommunicationProcessor - Class in adams.data.wekapyroproxy: Ancestor for classes processing the communication to/fro Pyro proxy models.
AbstractCommunicationProcessor() - Constructor for class adams.data.wekapyroproxy.AbstractCommunicationProcessor
AbstractCrossvalidatedInstanceEvaluator<T extends AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer> - Class in adams.data.weka.evaluator: Ancestor for evalutors that use cross-validation for initialization.
AbstractCrossvalidatedInstanceEvaluator() - Constructor for class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator
AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer - Class in adams.data.weka.evaluator: Container for storing the evaluation results.
AbstractDataContainer - Class in adams.gui.tools.wekainvestigator.data: Ancestor for data containers.
AbstractDataContainer() - Constructor for class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Initializes the container with no data.
AbstractDataContainer(Instances) - Constructor for class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Initializes the container with just the data.
AbstractDataPreparation - Class in weka.classifiers.meta.socketfacade: Ancestor for classes that prepare data for the SocketFacade classifier.
AbstractDataPreparation() - Constructor for class weka.classifiers.meta.socketfacade.AbstractDataPreparation
AbstractDatasetInstanceEvaluator - Class in adams.data.weka.evaluator: Ancestor for evaluators that need a data set for initialization.
AbstractDatasetInstanceEvaluator() - Constructor for class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator
AbstractDetrend - Class in weka.filters.unsupervised.attribute.detrend: Ancestor for schemes that perform detrend.
AbstractDetrend() - Constructor for class weka.filters.unsupervised.attribute.detrend.AbstractDetrend
AbstractEditableDataTableAction - Class in adams.gui.tools.wekainvestigator.datatable.action: Ancestor for actions on the data displayed on a tab using a AbstractInvestigatorTabWithEditableDataTable.
AbstractEditableDataTableAction() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction
AbstractErrorScaler - Class in adams.data.weka.predictions: Ancestor for classes that scale predictions.
AbstractErrorScaler() - Constructor for class adams.data.weka.predictions.AbstractErrorScaler
AbstractEvaluation<T extends AbstractInvestigatorTab,R extends AbstractResultItem> - Class in adams.gui.tools.wekainvestigator.evaluation: Ancestor for evaluation setups.
AbstractEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Constructor.
AbstractExperiment - Class in adams.gui.tools.wekamultiexperimenter.experiment: Ancestor for simple experiments.
AbstractExperiment() - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment
AbstractExperiment.AbstractExperimentJob<T extends AbstractExperiment> - Class in adams.gui.tools.wekamultiexperimenter.experiment: For evaluating a single classifier/dataset combination.
AbstractExperimenterPanel - Class in adams.gui.tools.wekamultiexperimenter: Ancestor for panels in the experimenter.
AbstractExperimenterPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel
AbstractExperimentIO<T> - Class in adams.gui.tools.wekamultiexperimenter.io: Ancestor for classes that handle loading/saving of experiments.
AbstractExperimentIO() - Constructor for class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO
AbstractExperimentJob(T, int, Classifier, Instances) - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: Initializes the run.
AbstractExperimentRunner<T> - Class in adams.gui.tools.wekamultiexperimenter.runner: Ancestor for classes that handle running a copy of the experiment in a separate thread.
AbstractExperimentRunner(ExperimenterPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Initializes the thread.
AbstractExperimentSetup - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.setup: Ancestor for experiment setups.
AbstractExperimentSetup() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup
AbstractExplorerPanelHandler - Class in weka.gui.explorer: Ancestor for handlers for specific Explorer panels.
AbstractExplorerPanelHandler() - Constructor for class weka.gui.explorer.AbstractExplorerPanelHandler
AbstractFilteredColumnFinder - Class in adams.data.weka.columnfinder: Ancestor for column finders that pre-filter the columns.
AbstractFilteredColumnFinder() - Constructor for class adams.data.weka.columnfinder.AbstractFilteredColumnFinder
AbstractFilteredRowFinder - Class in adams.data.weka.rowfinder: Ancestor for row finders that pre-filter the rows.
AbstractFilteredRowFinder() - Constructor for class adams.data.weka.rowfinder.AbstractFilteredRowFinder
AbstractFinalModelGenerator - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel: .
AbstractFinalModelGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.AbstractFinalModelGenerator
AbstractGeneticAlgorithm - Class in adams.opt.optimise.genetic: Base class for genetic algorithms.
AbstractGeneticAlgorithm() - Constructor for class adams.opt.optimise.genetic.AbstractGeneticAlgorithm
AbstractGeneticDoubleMatrixDiscoveryHandler - Class in adams.core.discovery.genetic: Ancestor for genetic discovery handlers that handle matrix properties.
AbstractGeneticDoubleMatrixDiscoveryHandler() - Constructor for class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler
AbstractHashableInstance - Class in weka.core: Ancestor for instance classes that wraps around any WEKA Instance and allow them to be used in data structures that make use of on object's hash, like maps or hashtables.
AbstractHashableInstance(Instance) - Constructor for class weka.core.AbstractHashableInstance: Initializes the wrapper.
AbstractHistoryPopupMenuItem<H extends adams.gui.core.AbstractNamedHistoryPanel,T extends AbstractInvestigatorTab> - Class in adams.gui.tools.wekainvestigator.history: Ancestor for classes that add menu items to the history popup menu.
AbstractHistoryPopupMenuItem - Class in adams.gui.tools.wekainvestigator.tab.associatetab.history: Ancestor for classes that add menu items to the history popup menu.
AbstractHistoryPopupMenuItem - Class in adams.gui.tools.wekainvestigator.tab.attseltab.history: Ancestor for classes that add menu items to the history popup menu.
AbstractHistoryPopupMenuItem - Class in adams.gui.tools.wekainvestigator.tab.classifytab.history: Ancestor for classes that add menu items to the history popup menu.
AbstractHistoryPopupMenuItem - Class in adams.gui.tools.wekainvestigator.tab.clustertab.history: Ancestor for classes that add menu items to the history popup menu.
AbstractHistoryPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem
AbstractHistoryPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.history.AbstractHistoryPopupMenuItem
AbstractHistoryPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.history.AbstractHistoryPopupMenuItem
AbstractHistoryPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.history.AbstractHistoryPopupMenuItem
AbstractHistoryPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.history.AbstractHistoryPopupMenuItem
AbstractInstanceEvaluator - Class in adams.data.weka.evaluator: Ancestor for evaluators that evaluate weka.core.Instance objects.
AbstractInstanceEvaluator() - Constructor for class adams.data.weka.evaluator.AbstractInstanceEvaluator
AbstractInstanceGenerator<T extends adams.data.container.DataContainer & adams.data.report.ReportHandler> - Class in adams.data.instances: Abstract base class for schemes that turn temperature profiles into weka.core.Instance objects.
AbstractInstanceGenerator<T extends adams.data.container.DataContainer> - Class in adams.flow.transformer: Ancestor for transformers that turn data containers into WEKA Instance objects.
AbstractInstanceGenerator() - Constructor for class adams.data.instances.AbstractInstanceGenerator
AbstractInstanceGenerator() - Constructor for class adams.flow.transformer.AbstractInstanceGenerator
AbstractInstanceInfoFrame - Class in adams.gui.visualization.weka: Ancestor for frames for displaying information on the displayed data, with some more domain-specific functionality.
AbstractInstanceInfoFrame() - Constructor for class adams.gui.visualization.weka.AbstractInstanceInfoFrame
AbstractInstancePaintlet - Class in adams.gui.visualization.instance: Ancestor for Instance paintlets.
AbstractInstancePaintlet() - Constructor for class adams.gui.visualization.instance.AbstractInstancePaintlet
AbstractInstancePanelUpdater - Class in adams.gui.visualization.instance: Ancestor for classes that determine when to update the instance panel, i.e., repaint all of it.
AbstractInstancePanelUpdater() - Constructor for class adams.gui.visualization.instance.AbstractInstancePanelUpdater
AbstractInstancesAnalysis - Class in adams.data.instancesanalysis: Ancestor for data analysis classes.
AbstractInstancesAnalysis() - Constructor for class adams.data.instancesanalysis.AbstractInstancesAnalysis
AbstractInstancesIndexedSplitsRunsGenerator - Class in adams.flow.transformer.indexedsplitsrunsgenerator: Ancestor for generators that process Instances objects.
AbstractInstancesIndexedSplitsRunsGenerator() - Constructor for class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator
AbstractInvestigatorTab - Class in adams.gui.tools.wekainvestigator.tab: Ancestor for tabs in the Investigator.
AbstractInvestigatorTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab
AbstractInvestigatorTab.SerializationOption - Enum in adams.gui.tools.wekainvestigator.tab: options for serialization.
AbstractInvestigatorTabWithDataTable - Class in adams.gui.tools.wekainvestigator.tab: Ancestor for tabs that have the data table on top.
AbstractInvestigatorTabWithDataTable() - Constructor for class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable
AbstractInvestigatorTabWithEditableDataTable - Class in adams.gui.tools.wekainvestigator.tab: Ancestor for tabs with modifiable data table.
AbstractInvestigatorTabWithEditableDataTable() - Constructor for class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable
AbstractLinearRegressionBased<T extends adams.data.container.DataContainer> - Class in adams.data.baseline: Abstract ancestor for linear regression based baseline correction schemes.
AbstractLinearRegressionBased() - Constructor for class adams.data.baseline.AbstractLinearRegressionBased
AbstractMatchWekaInstanceAgainstHeader - Class in adams.data.conversion: Ancestor for classes that match Instance objects against Instances headers.
AbstractMatchWekaInstanceAgainstHeader() - Constructor for class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader
AbstractMerge - Class in adams.flow.transformer.wekadatasetsmerge
AbstractMerge() - Constructor for class adams.flow.transformer.wekadatasetsmerge.AbstractMerge
AbstractMerge.SourceAttribute - Class in adams.flow.transformer.wekadatasetsmerge: Helper class for determining the mapping from input attributes in the source datasets to output attributes in the merged dataset.
AbstractMultiClassPLS - Class in adams.data.instancesanalysis.pls: Ancestor for schemes that predict multiple classes.
AbstractMultiClassPLS() - Constructor for class adams.data.instancesanalysis.pls.AbstractMultiClassPLS
AbstractMultiplicativeScatterCorrection - Class in weka.filters.unsupervised.attribute.multiplicativescattercorrection: Ancestor for correction schemes.
AbstractMultiplicativeScatterCorrection() - Constructor for class weka.filters.unsupervised.attribute.multiplicativescattercorrection.AbstractMultiplicativeScatterCorrection
AbstractMultiRowProcessorPlugin - Class in weka.filters.unsupervised.instance.multirowprocessor: Ancestor for MultiRowProcessor plugins.
AbstractMultiRowProcessorPlugin() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin
AbstractNestableResultItem - Class in adams.gui.tools.wekainvestigator.output: Container for a data to be stored in result history that can also store nested result items.
AbstractNestableResultItem(Instances) - Constructor for class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem: Initializes the item.
AbstractNumericClassPostProcessor - Class in adams.flow.transformer.wekaevaluationpostprocessor: Ancestor for numeric class post-processors.
AbstractNumericClassPostProcessor() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.AbstractNumericClassPostProcessor
AbstractOutputGenerator<T extends AbstractResultItem> - Class in adams.gui.tools.wekainvestigator.output: Ancestor for output generators.
AbstractOutputGenerator - Class in adams.gui.tools.wekainvestigator.tab.associatetab.output: Ancestor for output generators using t.
AbstractOutputGenerator - Class in adams.gui.tools.wekainvestigator.tab.attseltab.output: Ancestor for output generators using t.
AbstractOutputGenerator - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Ancestor for output generators using the data from the per-fold pane.
AbstractOutputGenerator - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output: Ancestor for output generators using t.
AbstractOutputGenerator - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.output: Ancestor for output generators using the data from the per-fold pane.
AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator
AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.output.AbstractOutputGenerator
AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.output.AbstractOutputGenerator
AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.AbstractOutputGenerator
AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.AbstractOutputGenerator
AbstractOutputGenerator() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.output.AbstractOutputGenerator
AbstractOutputGeneratorWithSeparateFoldsSupport<T extends JComponent> - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Ancestor for output generators that can generate output for separate folds just using the Evaluation objects.
AbstractOutputGeneratorWithSeparateFoldsSupport() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.AbstractOutputGeneratorWithSeparateFoldsSupport
AbstractOutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka: Ancestor for panels that allow the user to configure ResultListeners.
AbstractOutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel
AbstractOutputPanelWithPopupMenu<T extends adams.gui.chooser.BaseFileChooser> - Class in adams.gui.tools.wekainvestigator.output: Ancestor for output panels that can save the displayed output to a file.
AbstractOutputPanelWithPopupMenu() - Constructor for class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu
AbstractPanelWithFile<T extends adams.gui.chooser.AbstractChooserPanel> - Class in adams.gui.tools.weka: Ancestor for panels that allow the user to select a file.
AbstractPanelWithFile() - Constructor for class adams.gui.tools.weka.AbstractPanelWithFile
AbstractParameterHandlingWekaMenuItemDefinition - Class in adams.gui.menu: Abstract menu item definition for Weka elements that also handle additional parameters.
AbstractParameterHandlingWekaMenuItemDefinition() - Constructor for class adams.gui.menu.AbstractParameterHandlingWekaMenuItemDefinition: Initializes the menu item with no owner.
AbstractParameterHandlingWekaMenuItemDefinition(AbstractApplicationFrame) - Constructor for class adams.gui.menu.AbstractParameterHandlingWekaMenuItemDefinition: Initializes the menu item.
AbstractPerFoldPopupMenuItem - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold: Ancestor for classes that add menu items to the per-fold popup menu.
AbstractPerFoldPopupMenuItem() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem
AbstractPlotColumn - Class in adams.gui.visualization.instances.instancestable: Ancestor for plugins that plot a column.
AbstractPlotColumn() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractPlotColumn
AbstractPlotRow - Class in adams.gui.visualization.instances.instancestable: Ancestor for plugins that plot a row.
AbstractPlotRow() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractPlotRow
AbstractPlotSelectedRows - Class in adams.gui.visualization.instances.instancestable: Ancestor for plugins that plot rows.
AbstractPlotSelectedRows() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows
AbstractPLS - Class in adams.data.instancesanalysis.pls: Ancestor for PLS implementations.
AbstractPLS() - Constructor for class adams.data.instancesanalysis.pls.AbstractPLS
AbstractPLSAttributeEval - Class in weka.attributeSelection: Ancestor for PLS attribute evaluators
AbstractPLSAttributeEval() - Constructor for class weka.attributeSelection.AbstractPLSAttributeEval
AbstractPLSAttributeEval.LoadingsCalculations - Enum in weka.attributeSelection
AbstractProcessCell - Class in adams.gui.visualization.instances.instancestable: Ancestor for plugins that process a cell.
AbstractProcessCell() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractProcessCell
AbstractProcessColumn - Class in adams.gui.visualization.instances.instancestable: Ancestor for plugins that process a column.
AbstractProcessColumn() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractProcessColumn
AbstractProcessRow - Class in adams.gui.visualization.instances.instancestable: Ancestor for plugins that process a row.
AbstractProcessRow() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractProcessRow
AbstractProcessSelectedRows - Class in adams.gui.visualization.instances.instancestable: Ancestor for plugins that process a row.
AbstractProcessSelectedRows() - Constructor for class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows
AbstractProcessWekaInstanceWithModel<T> - Class in adams.flow.transformer: Ancestor for transformers that user models for processing Instance objects, e.g., classifiers making predictions.
AbstractProcessWekaInstanceWithModel() - Constructor for class adams.flow.transformer.AbstractProcessWekaInstanceWithModel
AbstractRangeBasedSelectionProcessor - Class in weka.filters.unsupervised.instance.multirowprocessor.processor: Ancestor for processors that work on a range of attributes.
AbstractRangeBasedSelectionProcessor() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor
AbstractRelationNameHeuristic - Class in adams.data.weka.relationname: Ancestor for heuristics that determine the relation name for a dataset.
AbstractRelationNameHeuristic() - Constructor for class adams.data.weka.relationname.AbstractRelationNameHeuristic
AbstractResultItem - Class in adams.gui.tools.wekainvestigator.output: Container for a data to be stored in result history.
AbstractResultItem(Instances) - Constructor for class adams.gui.tools.wekainvestigator.output.AbstractResultItem: Initializes the item.
AbstractResultsHandler - Class in adams.gui.tools.wekamultiexperimenter.experiment: Ancestor for classes that store the results from an experiment run.
AbstractResultsHandler() - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.AbstractResultsHandler
AbstractResultsPanel - Class in adams.gui.tools.wekamultiexperimenter.analysis: Ancestor for displaying the results of an analysis.
AbstractResultsPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel
AbstractRowFinder - Class in adams.data.weka.rowfinder: Ancestor for classes that find rows of interest in datasets.
AbstractRowFinder() - Constructor for class adams.data.weka.rowfinder.AbstractRowFinder
AbstractRowFinderApplier - Class in weka.filters.unsupervised.instance: Ancestor for filters that apply RowFinder schemes to the data.
AbstractRowFinderApplier() - Constructor for class weka.filters.unsupervised.instance.AbstractRowFinderApplier
AbstractRowFinderWithCapabilities - Class in adams.data.weka.rowfinder: Ancestor for classes that find rows of interest in datasets.
AbstractRowFinderWithCapabilities() - Constructor for class adams.data.weka.rowfinder.AbstractRowFinderWithCapabilities
AbstractRowSelection - Class in weka.filters.unsupervised.instance.multirowprocessor.selection: Ancestor for row selection schemes.
AbstractRowSelection() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.selection.AbstractRowSelection
AbstractSelectedAttributesAction - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction: Ancestor for actions on ther checked attributes in the PreprocessTab.
AbstractSelectedAttributesAction() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction
AbstractSelectionProcessor - Class in weka.filters.unsupervised.instance.multirowprocessor.processor: Ancestor for row selection processors.
AbstractSelectionProcessor() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractSelectionProcessor
AbstractSetupOptionPanel - Class in adams.gui.tools.wekamultiexperimenter.setup: Ancestor for panels that get added to a AbstractSetupPanel.
AbstractSetupOptionPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel
AbstractSetupPanel<T> - Class in adams.gui.tools.wekamultiexperimenter.setup: Ancestor for setup panels.
AbstractSetupPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel
AbstractSetupPanel.ModificationActionListener - Class in adams.gui.tools.wekamultiexperimenter.setup: Action listener that just sets the modified flag.
AbstractSetupPanel.ModificationChangeListener - Class in adams.gui.tools.wekamultiexperimenter.setup: Change listener that just sets the modified flag.
AbstractSetupPanel.ModificationDocumentListener - Class in adams.gui.tools.wekamultiexperimenter.setup: Document listener that just sets the modified flag.
AbstractSimpleClassifier - Class in weka.classifiers.simple: Ancestor for classifiers using ADAMS option handling.
AbstractSimpleClassifier() - Constructor for class weka.classifiers.simple.AbstractSimpleClassifier
AbstractSimpleOptionHandler - Class in weka.core: Ancestor for Weka classes that use the ADAMS option handling framework.
AbstractSimpleOptionHandler() - Constructor for class weka.core.AbstractSimpleOptionHandler
AbstractSimpleRegressionMeasure - Class in weka.classifiers.evaluation: Computes the mean error.
AbstractSimpleRegressionMeasure() - Constructor for class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure
AbstractSingleClassPLS - Class in adams.data.instancesanalysis.pls: Ancestor for schemes that predict a single class.
AbstractSingleClassPLS() - Constructor for class adams.data.instancesanalysis.pls.AbstractSingleClassPLS
AbstractSource - Class in adams.gui.tools.wekainvestigator.source: Ancestor for additional "source" actions in the main menu.
AbstractSource() - Constructor for class adams.gui.tools.wekainvestigator.source.AbstractSource
AbstractSplitGenerator - Class in weka.classifiers: Ancestor for helper classes that generates dataset splits.
AbstractSplitGenerator() - Constructor for class weka.classifiers.AbstractSplitGenerator: Initializes the generator.
AbstractSplitter - Class in adams.data.weka.datasetsplitter: Parent class for different methods of splitting a dataset into smaller datasets.
AbstractSplitter() - Constructor for class adams.data.weka.datasetsplitter.AbstractSplitter
AbstractTokenCleaner - Class in weka.core.tokenizers.cleaners: Ancestor for cleaning tokens.
AbstractTokenCleaner() - Constructor for class weka.core.tokenizers.cleaners.AbstractTokenCleaner
AbstractTrainableColumnFinder - Class in adams.data.weka.columnfinder: Ancestor for ColumnFinder algorithms that can be trained.
AbstractTrainableColumnFinder() - Constructor for class adams.data.weka.columnfinder.AbstractTrainableColumnFinder
AbstractTrainableRowFinder - Class in adams.data.weka.rowfinder: Ancestor for RowFinder algorithms that can be trained.
AbstractTrainableRowFinder() - Constructor for class adams.data.weka.rowfinder.AbstractTrainableRowFinder
AbstractWekaClassifierEvaluator - Class in adams.flow.transformer: Ancestor for transformers that evaluate classifiers.
AbstractWekaClassifierEvaluator() - Constructor for class adams.flow.transformer.AbstractWekaClassifierEvaluator
AbstractWekaEnsembleGenerator - Class in adams.flow.transformer.wekaensemblegenerator: Ancestor for schemes that generate ensembles.
AbstractWekaEnsembleGenerator() - Constructor for class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator
AbstractWekaEvaluationPostProcessor - Class in adams.flow.transformer.wekaevaluationpostprocessor: Ancestor for classes that post-process Evaluation objects.
AbstractWekaEvaluationPostProcessor() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor
AbstractWekaExperimentIO<T extends weka.experiment.Experiment> - Class in adams.gui.tools.wekamultiexperimenter.io: Ancestor for classes that handle loading/saving of experiments.
AbstractWekaExperimentIO() - Constructor for class adams.gui.tools.wekamultiexperimenter.io.AbstractWekaExperimentIO
AbstractWekaExperimentRunner<T extends weka.experiment.Experiment> - Class in adams.gui.tools.wekamultiexperimenter.runner: Ancestor for classes that handle running a copy of the experiment in a separate thread.
AbstractWekaExperimentRunner(ExperimenterPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.runner.AbstractWekaExperimentRunner: Initializes the thread.
AbstractWEKAFitnessFunction - Class in adams.opt.optimise.genetic.fitnessfunctions: Perform attribute selection using WEKA classification.
AbstractWEKAFitnessFunction() - Constructor for class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction
AbstractWEKAFitnessFunction.Measure - Enum in adams.opt.optimise.genetic.fitnessfunctions: The measure to use for evaluating.
AbstractWekaMenuItemDefinition - Class in adams.gui.menu: Abstract menu item menu item definitions for Weka elements.
AbstractWekaMenuItemDefinition() - Constructor for class adams.gui.menu.AbstractWekaMenuItemDefinition: Initializes the menu item with no owner.
AbstractWekaMenuItemDefinition(AbstractApplicationFrame) - Constructor for class adams.gui.menu.AbstractWekaMenuItemDefinition: Initializes the menu item.
AbstractWekaModelReader - Class in adams.flow.transformer: Ancestor for actors that deserialize models.
AbstractWekaModelReader() - Constructor for class adams.flow.transformer.AbstractWekaModelReader
AbstractWekaModelWriter - Class in adams.flow.sink: Ancestor for actors that serialize models.
AbstractWekaModelWriter() - Constructor for class adams.flow.sink.AbstractWekaModelWriter
AbstractWekaPackageManagerAction - Class in adams.flow.source.wekapackagemanageraction: Ancestor for package manager actions.
AbstractWekaPackageManagerAction - Class in adams.flow.standalone.wekapackagemanageraction: Ancestor for package manager actions.
AbstractWekaPackageManagerAction - Class in adams.flow.transformer.wekapackagemanageraction: Ancestor for package manager actions.
AbstractWekaPackageManagerAction() - Constructor for class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction
AbstractWekaPackageManagerAction() - Constructor for class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction
AbstractWekaPackageManagerAction() - Constructor for class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction
AbstractWekaPredictionsTransformer - Class in adams.flow.transformer: Ancestor for transformers that convert the predictions stored in an Evaluation object into a different format.
AbstractWekaPredictionsTransformer() - Constructor for class adams.flow.transformer.AbstractWekaPredictionsTransformer
AbstractWekaRepeatedCrossValidationOutput<T> - Class in adams.flow.transformer.wekarepeatedcrossvalidationoutput: Ancestor for classes that generate output from repeated cross-validations.
AbstractWekaRepeatedCrossValidationOutput() - Constructor for class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput
AbstractWekaSetupGenerator<T> - Class in adams.flow.source: Abstract ancestor for setup generator sources.
AbstractWekaSetupGenerator() - Constructor for class adams.flow.source.AbstractWekaSetupGenerator
AbstractWekaSetupPanel - Class in adams.gui.tools.wekamultiexperimenter.setup: Ancestor for setup panels for Weka experiments.
AbstractWekaSetupPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractWekaSetupPanel
AbstractWekaSpreadSheetReader - Class in adams.data.io.input: Ancestor for WEKA file format readers.
AbstractWekaSpreadSheetReader() - Constructor for class adams.data.io.input.AbstractWekaSpreadSheetReader
AbstractWekaSpreadSheetWriter - Class in adams.data.io.output: Ancestor for WEKA file format readers.
AbstractWekaSpreadSheetWriter() - Constructor for class adams.data.io.output.AbstractWekaSpreadSheetWriter
ACC - adams.flow.transformer.WekaClassifierRanker.Measure: evaluation via: Accuracy.
ACC - adams.opt.genetic.Measure: Accuracy.
ACC - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure: evaluation via: Accuracy.
accepts() - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.AdamsInstanceToWekaInstance: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.MapToWekaInstance: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.ReportToWekaInstance: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.SpreadSheetToWekaInstances: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.WekaCapabilitiesToInstances: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.WekaCapabilitiesToSpreadSheet: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.WekaDrawableToString: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.WekaEvaluationToCostCurve: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.WekaEvaluationToMarginCurve: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.WekaInstanceToAdamsInstance: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.WekaInstanceToMap: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.WekaPackageToMap: Returns the class that is accepted as input.
accepts() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the class that is accepted as input.
accepts() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.condition.bool.AdamsInstanceCapabilities: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.condition.bool.WekaCapabilities: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.condition.bool.WekaClassification: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.AbstractWekaModelWriter: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaAttributeSummary: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaClassifierErrors: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaCostBenefitAnalysis: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaCostCurve: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaExperimentFileWriter: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaFileWriter: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaGraphVisualizer: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaInstancesDisplay: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaInstancesPlot: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaMarginCurve: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaThresholdCurve: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.sink.WekaTreeVisualizer: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.AbstractInstanceGenerator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.AbstractWekaModelReader: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: The accepted classes.
accepts() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: Returns the type of classes that are accepted as input.
accepts() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: The accepted classes.
accepts() - Method in class adams.flow.transformer.WekaAccumulatedError: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaAggregateEvaluations: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaAttributeIterator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaAttributeSelectionSummary: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaChooseAttributes: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaClassifierInfo: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaClassifierOptimizer: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaClassSelector: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaClusterAssignments: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaClustererInfo: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaClustererPostProcessor: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaDatasetsMerge: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaDatasetSplit: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator: Returns the input data the generator processes.
accepts() - Method in class adams.flow.transformer.WekaEnsembleGenerator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels: Returns the input data the generator processes.
accepts() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels: Returns the input data the generator processes.
accepts() - Method in class adams.flow.transformer.WekaEvaluationInfo: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaEvaluationValues: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaExperiment: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaExperimentExecution: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaExperimentFileReader: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaExtractArray: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaExtractPLSMatrix: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaFileReader: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaFilter: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaGetCapabilities: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaGetInstancesValue: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaGetInstanceValue: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaInstancesAppend: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaInstancesInfo: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaInstancesStatistic: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaNewInstance: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction: The types of data the action accepts.
accepts() - Method in class adams.flow.transformer.WekaPackageManagerAction: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromFile: The types of data the action accepts.
accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromURL: The types of data the action accepts.
accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: The types of data the action accepts.
accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallPackage: The types of data the action accepts.
accepts() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall: The types of data the action accepts.
accepts() - Method in class adams.flow.transformer.WekaPrincipalComponents: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaRandomSplit: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaRegexToRange: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaRelationName: Deprecated.

Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaRenameRelation: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaSetInstancesValue: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaSetInstanceValue: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaSplitGenerator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaStoreInstance: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaStreamEvaluator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaStreamFilter: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaSubsets: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaTestSetEvaluator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaTextDirectoryReader: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaTrainAssociator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaTrainClassifier: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaTrainClusterer: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator: Returns the class that the consumer accepts.
accepts() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator: Returns the class that the consumer accepts.
acceptSelection() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Generates the indices.
AccessibleGenericObjectEditor() - Constructor for class adams.gui.goe.WekaEditorsRegistration.AccessibleGenericObjectEditor
AccessiblePluginManager() - Constructor for class adams.gui.goe.WekaEditorsRegistration.AccessiblePluginManager
AccumulatedLWLWeights - Class in weka.filters.unsupervised.instance: Generates an LWL-like dataset for each instance of the data from the first batch and accumulate these weights.
AccumulatedLWLWeights() - Constructor for class weka.filters.unsupervised.instance.AccumulatedLWLWeights
actCol - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState: the actual column.
actionPerformed(ActionEvent) - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: Gets called when the one of the buttons in the GOE panel gets pressed.
actionPerformed(ActionEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationActionListener
actionTipText() - Method in class adams.flow.source.WekaPackageManagerAction: Returns the tip text for this property.
actionTipText() - Method in class adams.flow.standalone.WekaPackageManagerAction: Returns the tip text for this property.
actionTipText() - Method in class adams.flow.transformer.WekaPackageManagerAction: Returns the tip text for this property.
activate() - Method in class adams.gui.application.WekaExperimenterPreferencesPanel: Activates the settings.
activate() - Method in class adams.gui.application.WekaExplorerPreferencesPanel: Activates the settings.
activate() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel: Activates the settings.
activate(int) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Activates the selected dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Activates the specified dataset.
activate(int) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Activates the specified dataset.
actRow - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState: the actual row.
actRows - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState: the actual rows.
ACTUAL_MINUS_PREDICTED - adams.flow.transformer.WekaBootstrapping.ErrorCalculation
actualMaxTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
actualMinTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
actualTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the tip text for this property.
actualTipText() - Method in class weka.classifiers.functions.FromPredictions: Returns the tip text for this property.
ADAMS_FILE_EXTENSION - Static variable in class adams.gui.menu.MakeCompatibleDatasets
ADAMS_READER - Static variable in class adams.gui.menu.MakeCompatibleDatasets
adams.core.base - package adams.core.base
adams.core.discovery.genetic - package adams.core.discovery.genetic
adams.core.management - package adams.core.management
adams.core.option - package adams.core.option
adams.core.option.parsing - package adams.core.option.parsing
adams.data - package adams.data
adams.data.baseline - package adams.data.baseline
adams.data.binning - package adams.data.binning
adams.data.conversion - package adams.data.conversion
adams.data.featureconverter - package adams.data.featureconverter
adams.data.indexedsplits - package adams.data.indexedsplits
adams.data.instance - package adams.data.instance
adams.data.instances - package adams.data.instances
adams.data.instancesanalysis - package adams.data.instancesanalysis
adams.data.instancesanalysis.pls - package adams.data.instancesanalysis.pls
adams.data.io.input - package adams.data.io.input
adams.data.io.output - package adams.data.io.output
adams.data.spreadsheet.filter - package adams.data.spreadsheet.filter
adams.data.weka - package adams.data.weka
adams.data.weka.classattribute - package adams.data.weka.classattribute
adams.data.weka.columnfinder - package adams.data.weka.columnfinder
adams.data.weka.datasetsplitter - package adams.data.weka.datasetsplitter
adams.data.weka.evaluator - package adams.data.weka.evaluator
adams.data.weka.predictions - package adams.data.weka.predictions
adams.data.weka.relationname - package adams.data.weka.relationname
adams.data.weka.rowfinder - package adams.data.weka.rowfinder
adams.data.wekapyroproxy - package adams.data.wekapyroproxy
adams.env - package adams.env
adams.flow.condition.bool - package adams.flow.condition.bool
adams.flow.container - package adams.flow.container
adams.flow.core - package adams.flow.core
adams.flow.sink - package adams.flow.sink
adams.flow.source - package adams.flow.source
adams.flow.source.valuedefinition - package adams.flow.source.valuedefinition
adams.flow.source.wekapackagemanageraction - package adams.flow.source.wekapackagemanageraction
adams.flow.standalone - package adams.flow.standalone
adams.flow.standalone.wekapackagemanageraction - package adams.flow.standalone.wekapackagemanageraction
adams.flow.template - package adams.flow.template
adams.flow.transformer - package adams.flow.transformer
adams.flow.transformer.indexedsplitsrunsevaluation - package adams.flow.transformer.indexedsplitsrunsevaluation
adams.flow.transformer.indexedsplitsrunsgenerator - package adams.flow.transformer.indexedsplitsrunsgenerator
adams.flow.transformer.indexedsplitsrunspredictions - package adams.flow.transformer.indexedsplitsrunspredictions
adams.flow.transformer.wekaclassifiersetupprocessor - package adams.flow.transformer.wekaclassifiersetupprocessor
adams.flow.transformer.wekaclusterer - package adams.flow.transformer.wekaclusterer
adams.flow.transformer.wekadatasetsmerge - package adams.flow.transformer.wekadatasetsmerge
adams.flow.transformer.wekaensemblegenerator - package adams.flow.transformer.wekaensemblegenerator
adams.flow.transformer.wekaevaluationpostprocessor - package adams.flow.transformer.wekaevaluationpostprocessor
adams.flow.transformer.wekapackagemanageraction - package adams.flow.transformer.wekapackagemanageraction
adams.flow.transformer.wekarepeatedcrossvalidationoutput - package adams.flow.transformer.wekarepeatedcrossvalidationoutput
adams.gui - package adams.gui
adams.gui.application - package adams.gui.application
adams.gui.chooser - package adams.gui.chooser
adams.gui.event - package adams.gui.event
adams.gui.flow.tree.quickaction - package adams.gui.flow.tree.quickaction
adams.gui.goe - package adams.gui.goe
adams.gui.goe.popupmenu - package adams.gui.goe.popupmenu
adams.gui.help - package adams.gui.help
adams.gui.menu - package adams.gui.menu
adams.gui.tools - package adams.gui.tools
adams.gui.tools.previewbrowser - package adams.gui.tools.previewbrowser
adams.gui.tools.weka - package adams.gui.tools.weka
adams.gui.tools.wekainvestigator - package adams.gui.tools.wekainvestigator
adams.gui.tools.wekainvestigator.data - package adams.gui.tools.wekainvestigator.data
adams.gui.tools.wekainvestigator.datatable - package adams.gui.tools.wekainvestigator.datatable
adams.gui.tools.wekainvestigator.datatable.action - package adams.gui.tools.wekainvestigator.datatable.action
adams.gui.tools.wekainvestigator.evaluation - package adams.gui.tools.wekainvestigator.evaluation
adams.gui.tools.wekainvestigator.history - package adams.gui.tools.wekainvestigator.history
adams.gui.tools.wekainvestigator.job - package adams.gui.tools.wekainvestigator.job
adams.gui.tools.wekainvestigator.output - package adams.gui.tools.wekainvestigator.output
adams.gui.tools.wekainvestigator.source - package adams.gui.tools.wekainvestigator.source
adams.gui.tools.wekainvestigator.tab - package adams.gui.tools.wekainvestigator.tab
adams.gui.tools.wekainvestigator.tab.associatetab - package adams.gui.tools.wekainvestigator.tab.associatetab
adams.gui.tools.wekainvestigator.tab.associatetab.evaluation - package adams.gui.tools.wekainvestigator.tab.associatetab.evaluation
adams.gui.tools.wekainvestigator.tab.associatetab.history - package adams.gui.tools.wekainvestigator.tab.associatetab.history
adams.gui.tools.wekainvestigator.tab.associatetab.output - package adams.gui.tools.wekainvestigator.tab.associatetab.output
adams.gui.tools.wekainvestigator.tab.attseltab - package adams.gui.tools.wekainvestigator.tab.attseltab
adams.gui.tools.wekainvestigator.tab.attseltab.evaluation - package adams.gui.tools.wekainvestigator.tab.attseltab.evaluation
adams.gui.tools.wekainvestigator.tab.attseltab.history - package adams.gui.tools.wekainvestigator.tab.attseltab.history
adams.gui.tools.wekainvestigator.tab.attseltab.output - package adams.gui.tools.wekainvestigator.tab.attseltab.output
adams.gui.tools.wekainvestigator.tab.classifytab - package adams.gui.tools.wekainvestigator.tab.classifytab
adams.gui.tools.wekainvestigator.tab.classifytab.evaluation - package adams.gui.tools.wekainvestigator.tab.classifytab.evaluation
adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel - package adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel
adams.gui.tools.wekainvestigator.tab.classifytab.history - package adams.gui.tools.wekainvestigator.tab.classifytab.history
adams.gui.tools.wekainvestigator.tab.classifytab.output - package adams.gui.tools.wekainvestigator.tab.classifytab.output
adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold - package adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold
adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated - package adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated
adams.gui.tools.wekainvestigator.tab.clustertab - package adams.gui.tools.wekainvestigator.tab.clustertab
adams.gui.tools.wekainvestigator.tab.clustertab.evaluation - package adams.gui.tools.wekainvestigator.tab.clustertab.evaluation
adams.gui.tools.wekainvestigator.tab.clustertab.history - package adams.gui.tools.wekainvestigator.tab.clustertab.history
adams.gui.tools.wekainvestigator.tab.clustertab.output - package adams.gui.tools.wekainvestigator.tab.clustertab.output
adams.gui.tools.wekainvestigator.tab.experimenttab - package adams.gui.tools.wekainvestigator.tab.experimenttab
adams.gui.tools.wekainvestigator.tab.experimenttab.output - package adams.gui.tools.wekainvestigator.tab.experimenttab.output
adams.gui.tools.wekainvestigator.tab.experimenttab.setup - package adams.gui.tools.wekainvestigator.tab.experimenttab.setup
adams.gui.tools.wekainvestigator.tab.preprocesstab - package adams.gui.tools.wekainvestigator.tab.preprocesstab
adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction - package adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction
adams.gui.tools.wekamultiexperimenter - package adams.gui.tools.wekamultiexperimenter
adams.gui.tools.wekamultiexperimenter.analysis - package adams.gui.tools.wekamultiexperimenter.analysis
adams.gui.tools.wekamultiexperimenter.experiment - package adams.gui.tools.wekamultiexperimenter.experiment
adams.gui.tools.wekamultiexperimenter.io - package adams.gui.tools.wekamultiexperimenter.io
adams.gui.tools.wekamultiexperimenter.runner - package adams.gui.tools.wekamultiexperimenter.runner
adams.gui.tools.wekamultiexperimenter.setup - package adams.gui.tools.wekamultiexperimenter.setup
adams.gui.tools.wekamultiexperimenter.setup.weka - package adams.gui.tools.wekamultiexperimenter.setup.weka
adams.gui.visualization.debug.inspectionhandler - package adams.gui.visualization.debug.inspectionhandler
adams.gui.visualization.debug.objectexport - package adams.gui.visualization.debug.objectexport
adams.gui.visualization.debug.objectrenderer - package adams.gui.visualization.debug.objectrenderer
adams.gui.visualization.instance - package adams.gui.visualization.instance
adams.gui.visualization.instance.containerlistpopup - package adams.gui.visualization.instance.containerlistpopup
adams.gui.visualization.instance.plotpopup - package adams.gui.visualization.instance.plotpopup
adams.gui.visualization.instances - package adams.gui.visualization.instances
adams.gui.visualization.instances.instancestable - package adams.gui.visualization.instances.instancestable
adams.gui.visualization.weka - package adams.gui.visualization.weka
adams.gui.wizard - package adams.gui.wizard
adams.ml.data - package adams.ml.data
adams.ml.model.classification - package adams.ml.model.classification
adams.ml.model.clustering - package adams.ml.model.clustering
adams.ml.model.regression - package adams.ml.model.regression
adams.multiprocess - package adams.multiprocess
adams.opt.genetic - package adams.opt.genetic
adams.opt.genetic.initialsetups - package adams.opt.genetic.initialsetups
adams.opt.optimise - package adams.opt.optimise
adams.opt.optimise.genetic - package adams.opt.optimise.genetic
adams.opt.optimise.genetic.fitnessfunctions - package adams.opt.optimise.genetic.fitnessfunctions
adams.tools - package adams.tools
AdamsExperimentFileChooser - Class in adams.gui.chooser: A specialized JFileChooser that lists all available file Readers and Writers for ADAMS Experiments.
AdamsExperimentFileChooser() - Constructor for class adams.gui.chooser.AdamsExperimentFileChooser: Constructs a FileChooser pointing to the user's default directory.
AdamsExperimentFileChooser(File) - Constructor for class adams.gui.chooser.AdamsExperimentFileChooser: Constructs a FileChooser using the given File as the path.
AdamsExperimentFileChooser(String) - Constructor for class adams.gui.chooser.AdamsExperimentFileChooser: Constructs a FileChooser using the given path.
AdamsExperimentRunner<T extends AbstractExperiment> - Class in adams.gui.tools.wekamultiexperimenter.runner: Ancestor for classes that handle running a copy of the experiment in a separate thread.
AdamsExperimentRunner(ExperimenterPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.runner.AdamsExperimentRunner: Initializes the thread.
AdamsHelper - Class in weka.gui: Helper class to make Weka GUI more ADAMS-like.
AdamsHelper() - Constructor for class weka.gui.AdamsHelper
AdamsInstanceCapabilities - Class in adams.flow.condition.bool: Filters adams.data.instance.Instance based on defined capabilities.
AdamsInstanceCapabilities() - Constructor for class adams.flow.condition.bool.AdamsInstanceCapabilities
AdamsInstanceToWekaInstance - Class in adams.data.conversion: Converts adams.data.instance.Instance objects into weka.core.Instance ones.
AdamsInstanceToWekaInstance() - Constructor for class adams.data.conversion.AdamsInstanceToWekaInstance
add(int, Instance) - Method in class weka.core.InstancesView: Adds one instance at the given position in the list.
add(SpreadSheet, int, int, int, int[], boolean) - Method in class weka.classifiers.AggregateEvaluations: Adds the data from the spreadsheet as predictions.
add(ArrayHistogram, Instance) - Method in class adams.gui.visualization.instance.HistogramFactory.Dialog: Adds a plot of the given instance.
add(ArrayHistogram, Instance) - Method in class adams.gui.visualization.instance.HistogramFactory.Panel: Adds a plot of the given instance.
add(ArrayHistogram, Instance, String) - Method in class adams.gui.visualization.instance.HistogramFactory.Dialog: Adds a plot of the given instance.
add(ArrayHistogram, Instance, String) - Method in class adams.gui.visualization.instance.HistogramFactory.Panel: Adds a plot of the given instance.
add(DataContainer) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList: Adds the data container and sets the undo enabled flag accordingly.
add(InstanceContainer) - Method in class adams.gui.visualization.instance.InstanceContainerManager: Adds the given container to the list.
add(String, int, double, double) - Method in class adams.opt.optimise.genetic.PackDataDef
add(List<String>, char, boolean) - Static method in class weka.core.WekaOptionUtils: Adds the boolean flag (if true) to the options.
add(List<String>, char, double) - Static method in class weka.core.WekaOptionUtils: Adds the double value to the options.
add(List<String>, char, float) - Static method in class weka.core.WekaOptionUtils: Adds the float value to the options.
add(List<String>, char, int) - Static method in class weka.core.WekaOptionUtils: Adds the int value to the options.
add(List<String>, char, long) - Static method in class weka.core.WekaOptionUtils: Adds the long value to the options.
add(List<String>, char, BaseObject) - Static method in class weka.core.WekaOptionUtils: Adds the BaseObject to the options.
add(List<String>, char, BaseObject[]) - Static method in class weka.core.WekaOptionUtils: Adds the BaseObject to the options.
add(List<String>, char, Index) - Static method in class weka.core.WekaOptionUtils: Adds the Index to the options.
add(List<String>, char, Index[]) - Static method in class weka.core.WekaOptionUtils: Adds the Index to the options.
add(List<String>, char, OptionHandler) - Static method in class weka.core.WekaOptionUtils: Adds the adams.core.option.OptionHandler to the options.
add(List<String>, char, Range) - Static method in class weka.core.WekaOptionUtils: Adds the adams.core.Range to the options.
add(List<String>, char, Range[]) - Static method in class weka.core.WekaOptionUtils: Adds the adams.core.Range to the options.
add(List<String>, char, File) - Static method in class weka.core.WekaOptionUtils: Adds the File value to the options.
add(List<String>, char, Enum) - Static method in class weka.core.WekaOptionUtils: Adds the enum value to the options.
add(List<String>, char, Object) - Static method in class weka.core.WekaOptionUtils: Adds the array to the options.
add(List<String>, char, String) - Static method in class weka.core.WekaOptionUtils: Adds the String value to the options.
add(List<String>, char, OptionHandler) - Static method in class weka.core.WekaOptionUtils: Adds the OptionHandler to the options.
add(List<String>, String[]) - Static method in class weka.core.WekaOptionUtils: Adds the "super" options to the current list.
add(List<String>, String, boolean) - Static method in class weka.core.WekaOptionUtils: Adds the boolean flag (if true) to the options.
add(List<String>, String, double) - Static method in class weka.core.WekaOptionUtils: Adds the double value to the options.
add(List<String>, String, float) - Static method in class weka.core.WekaOptionUtils: Adds the float value to the options.
add(List<String>, String, int) - Static method in class weka.core.WekaOptionUtils: Adds the int value to the options.
add(List<String>, String, long) - Static method in class weka.core.WekaOptionUtils: Adds the long value to the options.
add(List<String>, String, BaseObject) - Static method in class weka.core.WekaOptionUtils: Adds the BaseObject to the options.
add(List<String>, String, BaseObject[]) - Static method in class weka.core.WekaOptionUtils: Adds the BaseObject to the options.
add(List<String>, String, Index) - Static method in class weka.core.WekaOptionUtils: Adds the Index to the options.
add(List<String>, String, Index[]) - Static method in class weka.core.WekaOptionUtils: Adds the Index to the options.
add(List<String>, String, OptionHandler) - Static method in class weka.core.WekaOptionUtils: Adds the adams.core.option.OptionHandler to the options.
add(List<String>, String, Range) - Static method in class weka.core.WekaOptionUtils: Adds the adams.core.Range to the options.
add(List<String>, String, Range[]) - Static method in class weka.core.WekaOptionUtils: Adds the adams.core.Range to the options.
add(List<String>, String, File) - Static method in class weka.core.WekaOptionUtils: Adds the File value to the options.
add(List<String>, String, Enum) - Static method in class weka.core.WekaOptionUtils: Adds the enum value to the options.
add(List<String>, String, Object) - Static method in class weka.core.WekaOptionUtils: Adds the array to the options.
add(List<String>, String, String) - Static method in class weka.core.WekaOptionUtils: Adds the String value to the options.
add(List<String>, String, OptionHandler) - Static method in class weka.core.WekaOptionUtils: Adds the OptionHandler to the options.
add(Vector, Enumeration) - Static method in class weka.core.WekaOptionUtils: Adds the option description of the super class.
add(Evaluation) - Method in class weka.classifiers.AggregateEvaluations: Adds the predictions of the given Evaluation object.
add(Prediction) - Method in class weka.classifiers.AggregateEvaluations: Adds the prediction.
add(Instance) - Method in class weka.core.InstancesView: Adds one instance to the end of the set.
ADD - adams.gui.event.InstancesSortSetupEvent.EventType: a definition was added.
addAction(InstancesTablePopupMenuItemHelper.TableState, boolean, JMenuItem, InstancesTablePopupMenuItem) - Static method in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper: Adds the appropriate action to the menuitem.
addAdditionalAttributes(SpreadSheet, Instances, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Adds the additional columns from the Instances to the spreadsheet.
addAdditionalAttributes(SpreadSheet, Instances, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Adds the additional columns from the Instances to the spreadsheet.
addAdditionalAttributes(SpreadSheet, Instances, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Adds the additional columns from the Instances to the spreadsheet.
addAll(Collection<? extends DataContainer>) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList: Adds all the data containers and sets their undo enabled flag accordingly.
addAttributeInformationTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: Returns the tip text for this property.
addCapabilities(String, Capabilities) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator: generates a string from the capapbilities, suitable to add to the help text.
addCell(int) - Method in class adams.ml.data.InstancesHeaderRow: Adds a cell with the key of the cell in the header at the specified location.
addCell(int) - Method in class adams.ml.data.InstanceView: Adds a cell with the key of the cell in the header at the specified location.
addCell(String) - Method in class adams.ml.data.InstancesHeaderRow: Adds a cell with the given key to the list and returns the created object.
addCell(String) - Method in class adams.ml.data.InstanceView: Adds a cell with the given key to the list and returns the created object.
addChangeListener(ChangeListener) - Method in class adams.gui.goe.WekaGenericObjectEditorPopupMenu: Adds the listener to the internal list of listeners that get notified when the user changes the setup.
addChangeListener(ChangeListener) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Adds the change listener to the internal list.
addChangeListener(ChangeListener) - Method in class adams.gui.visualization.instances.InstancesTable: Adds the listener to the pool of listeners that get notified when the data changes.
addClassificationLabelTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the tip text for this property.
addClassificationTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the tip text for this property.
addClassifier(Classifier) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Adds a classifier.
AddCluster - Class in adams.flow.transformer.wekaclusterer: Just adds the predicted cluster (or distribution) to the original dataset.
Stored in container under: Clustered dataset
AddCluster() - Constructor for class adams.flow.transformer.wekaclusterer.AddCluster
addComment(String) - Method in class adams.ml.data.InstancesView: Adds the comment to the internal list of comments.
addComment(List<String>) - Method in class adams.ml.data.InstancesView: Ignored.
addData(DataContainer) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource: Adds the data.
addDatabaseIDTipText() - Method in class adams.data.instances.AbstractInstanceGenerator: Returns the tip text for this property.
addDataset(PlaceholderFile) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Adds a dataset.
addDatasetInfo(JsonObject, Instances) - Method in class weka.classifiers.meta.socketfacade.Simple: Information about the dataset to the JSON object.
addDatasetInformationTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: Returns the tip text for this property.
addDefaultTabs() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Adds the default tabs.
addDefinition() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Adds a new definition.
addDistributionTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the tip text for this property.
addFlag(Vector, String, char) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addFlag(Vector, String, String) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addIndexTipText() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the tip text for this property.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.FilteredSearch: Adds the given instance info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.NewNNSearch: Adds the given instance info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.PCANNSearch: Adds the given instance info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.PLSNNSearch: Adds the given instance info.
addInstancesSortSetupListener(InstancesSortSetupListener) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Adds the specified listener.
addIQR(Integer, TDoubleArrayList) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Calculates and adds the IQR stats for this key.
AdditionalExplorerPanel - Interface in weka.gui.explorer.panels: Interface for classes that supply additional Explorer panels.
additionalFieldsTipText() - Method in interface adams.data.instances.InstanceGeneratorWithAdditionalFields: Returns the tip text for this property.
additionalTipText() - Method in class weka.classifiers.functions.FromPredictions: Returns the tip text for this property.
addLabelIndexTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the tip text for this property.
addLabelIndexTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Returns the tip text for this property.
addLastSetup(Class, boolean, boolean, Object) - Method in class adams.gui.visualization.instances.InstancesTable: Stores this last setup.
addMetaLevelPrediction(Instance, int, double) - Method in class weka.classifiers.meta.ClassifierCascade: Adds the class distribution of the specified classifier to the meta-level instance.
addMetaLevelPrediction(Instance, int, double[]) - Method in class weka.classifiers.meta.ClassifierCascade: Adds the class distribution of the specified classifier to the meta-level instance.
addMetric(SpreadSheet, String, Object) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: Adds the metric to the results, automatically expands spreadsheet.
addMetrics(SpreadSheet, int, Classifier, Instances, Evaluation) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: Adds the metrics from the Evaluation object to the results.
addNestedItem(String, AbstractNestableResultItem) - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem: Adds the nested item.
addObjectSize(MetaData, String, Object) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Adds the object size to the meta-data.
addOneTipText() - Method in class weka.filters.unsupervised.attribute.LogTransform: Returns the tip text for this property.
addOption(Vector, String, Index, char) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, Index, String) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, Range, char) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, Range, String) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, String, char) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, String, String) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, OptionHandler, char) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, OptionHandler, String) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, Range, char) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, Range, String) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, SingleIndex, char) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, SingleIndex, String) - Static method in class weka.core.WekaOptionUtils: Adds an Option for a flag to the list of options.
addPage(MultiPagePane, String, JComponent, int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.AbstractOutputGenerator: Adds a page for the confusion matrix.
addPage(String, Component, int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane: Adds the page at the end.
addPanel(ExplorerExt, String) - Method in class weka.gui.explorer.MultiExplorer: Adds the given explorer panel.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.SqlPanel: Adds a PropertyChangeListener who will be notified of value changes.
addRecentFile(File, AbstractFileLoader) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Adds the specified file/loader combination to the recent files list.
addResult(String, Double) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Adds a result to the cache.
addResult(String, Double) - Method in class adams.opt.optimise.GeneticAlgorithm: Adds a result to the cache.
addRow() - Method in class adams.ml.data.InstancesView: Appends a row to the spreadsheet.
addRow(String) - Method in class adams.ml.data.InstancesView: Adds a row with the given key to the list and returns the created object.
addSecondResult(String, Double) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Adds a result to the cache (second evaluation).
addSelectionListener(ListSelectionListener) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Add a listener to the list that's notified each time a change to the selection occurs.
addStatistic(SpreadSheet, String, Object) - Method in class adams.flow.transformer.WekaInstancesInfo: Adds a statistic to the dataset.
addStatistic(Evaluation, SpreadSheet, EvaluationStatistic, int, boolean) - Method in class adams.flow.transformer.WekaEvaluationValues: Adds the specified statistic to the spreadsheet.
addSubRangeInfo(MetaData, double[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation: Adds the range information to a clone of the provided meta-data info and returns it.
addSubRangeInfo(MetaData, double[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation: Adds the range information to a clone of the provided meta-data info and returns it.
addTab(AbstractInvestigatorTab) - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane: Adds the tab.
addTab(AbstractInvestigatorTab, boolean) - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane: Adds the tab.
addTab(T, JComponent) - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator: Adds the component as tab to the result item.
addTableModelListener(TableModelListener) - Method in class adams.gui.visualization.instances.InstancesTableModel: adds a listener to the list that is notified each time a change to data model occurs
addToHistory(AbstractNamedHistoryPanel<R>, R) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Adds the item to the history and selects it.
addToPopupMenu(InstancesTablePopupMenuItemHelper.TableState, boolean, JPopupMenu, List<InstancesTablePopupMenuItem>, Set<Class>) - Static method in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper: Adds the available menu items to the menu.
addToPopupMenu(InstancesTablePopupMenuItemHelper.TableState, JPopupMenu, boolean) - Static method in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper: Adds the available menu items to the menu.
addUndoPoint() - Method in class adams.gui.visualization.instances.InstancesTable: adds an undo point to the undo history, if the undo support is enabled
addUndoPoint() - Method in class adams.gui.visualization.instances.InstancesTableModel: adds an undo point to the undo history, if the undo support is enabled
addUndoPoint(String) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Adds an undo point with the given comment.
adjust(double) - Method in enum adams.opt.genetic.Measure: Adjusts the measure value for sorting: either multiplies it with -1 or 1.
adjust(double) - Method in enum adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure: Adjusts the measure value for sorting: either multiplies it with -1 or 1.
Adjust - Class in adams.gui.visualization.instance.plotpopup: Whether to adjust the plot to the loaded or visible data.
Adjust() - Constructor for class adams.gui.visualization.instance.plotpopup.Adjust
afterTableLayoutChanged() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTable: Can be called after the layout changed.
afterTableLayoutChanged() - Method in class adams.gui.visualization.instances.InstancesTable: Can be called after the layout changed.
aggregated() - Method in class weka.classifiers.AggregateEvaluations: Returns the aggregated evaluation.
AggregateEvaluations - Class in weka.classifiers: Allows the aggregation of Evaluation objects.
AggregateEvaluations() - Constructor for class weka.classifiers.AggregateEvaluations: Initializes the object.
ALGORITHM_CDF2_4 - Static variable in class weka.filters.unsupervised.attribute.FastWavelet: the type of algorithm: CDF2 4.
ALGORITHM_DAUBECHIES2 - Static variable in class weka.filters.unsupervised.attribute.FastWavelet: the type of algorithm: Daubechies2.
ALGORITHM_HAAR - Static variable in class weka.filters.unsupervised.attribute.FastWavelet: the type of algorithm: Haar.
ALGORITHM_SYMMLET8 - Static variable in class weka.filters.unsupervised.attribute.FastWavelet: the type of algorithm: Symmlet8.
algorithmsTipText() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Returns the tip text for this property.
algorithmTipText() - Method in class adams.data.instancesanalysis.PLS: Returns the tip text for this property.
algorithmTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns the tip text for this property.
algorithmTipText() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
algorithmTipText() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Returns the tip text for this property.
algorithmTipText() - Method in class weka.classifiers.functions.GeneticAlgorithm: Returns the tip text for this property.
algorithmTipText() - Method in class weka.classifiers.functions.PLSWeighted: Returns the tip text for this property
algorithmTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
algorithmTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns the tip text for this property.
algorithmTipText() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the tip text for this property
algorithmTipText() - Method in class weka.filters.supervised.attribute.PLS: Returns the tip text for this property
algorithmTipText() - Method in class weka.filters.unsupervised.attribute.FastWavelet: Returns the tip text for this property.
AlignDataset - Class in weka.filters.unsupervised.instance: Aligns the dataset(s) passing through to the reference dataset.
Makes use of the following other filters internally:
- weka.filters.unsupervised.attribute.AnyToString
- weka.filters.unsupervised.instance.RemoveWithLabels

Valid options are:
AlignDataset() - Constructor for class weka.filters.unsupervised.instance.AlignDataset
alignIndices(int[]) - Static method in class weka.classifiers.CrossValidationHelper: Reorders the indices to align with the original data.
alignPredictions(ArrayList<Prediction>, int[]) - Static method in class weka.classifiers.CrossValidationHelper: Reorders the predictions to align with the original data.
ALL - adams.data.instancesanalysis.pls.PredictionType: predict all Ys.
ALL - adams.flow.source.wekapackagemanageraction.ListPackages.ListType
ALL - adams.opt.genetic.OutputType: setup and data.
AllFinder - Class in adams.data.weka.columnfinder: Dummy finder, finds all columns.
AllFinder - Class in adams.data.weka.rowfinder: Dummy finder, finds all rows.
AllFinder() - Constructor for class adams.data.weka.columnfinder.AllFinder
AllFinder() - Constructor for class adams.data.weka.rowfinder.AllFinder
allowAccessToFullInputFormat() - Method in class weka.filters.FilteredFilter: Returns whether to allow the determineOutputFormat(Instances) method access to the full dataset rather than just the header.
allowAccessToFullInputFormat() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Returns whether to allow the determineOutputFormat(Instances) method access to the full dataset rather than just the header.
allowAccessToFullInputFormat() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Returns whether to allow the determineOutputFormat(Instances) method access to the full dataset rather than just the header.
alphaTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the alpha option.
alphaTipText() - Method in class weka.filters.supervised.attribute.YGradientEPO: Returns the tip text for this property
alphaTipText() - Method in class weka.filters.supervised.attribute.YGradientGLSW: Returns the tip text for this property
alwaysShowMarkersTipText() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Returns the tip text for this property.
alwaysUseContainerTipText() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Returns the tip text for this property.
amountTipText() - Method in class weka.filters.unsupervised.instance.LatestRecords: Returns the tip text for this property.
AnalysisPanel - Class in adams.gui.tools.wekamultiexperimenter: The analysis panel.
AnalysisPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.AnalysisPanel
analyze() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Performs the analysis.
AndrewsCurves - Class in weka.filters.unsupervised.attribute: Generates Andrews Curves from array data.
César Ignacio García Osorio, Colin Fyfe (2003).
AndrewsCurves() - Constructor for class weka.filters.unsupervised.attribute.AndrewsCurves
antiAliasingEnabledTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
antiAliasingEnabledTipText() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Returns the tip text for this property.
antiAliasingEnabledTipText() - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet: Returns the tip text for this property.
AnyToString - Class in weka.filters.unsupervised.attribute: Turns the selected range of attributes into string ones.
AnyToString() - Constructor for class weka.filters.unsupervised.attribute.AnyToString
append(String) - Method in class adams.gui.tools.wekainvestigator.tab.LogTab: Appends the message to the log.
append(String) - Method in class adams.gui.tools.wekamultiexperimenter.LogPanel: Appends the log message.
Append - Class in adams.gui.tools.wekainvestigator.datatable.action: Appends the selected datasets into single dataset (one-after-the-other).
Append() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Append: Instantiates the action.
AppendDatasets - Class in adams.gui.menu: For appending datasets into single dataset.
AppendDatasets() - Constructor for class adams.gui.menu.AppendDatasets: Initializes the menu item with no owner.
AppendDatasets(AbstractApplicationFrame) - Constructor for class adams.gui.menu.AppendDatasets: Initializes the menu item.
AppendDatasetsPanel - Class in adams.gui.tools.weka: Wizard panel that allows appending datasets (one after the other).
AppendDatasetsPanel(boolean) - Constructor for class adams.gui.tools.weka.AppendDatasetsPanel: Initializes the panel.
appendResults(SpreadSheet) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Adds the results to the existing ones.
appliesToNominalClass() - Method in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure: Return true if this evaluation metric can be computed when the class is nominal
appliesToNominalClass() - Method in class weka.classifiers.evaluation.Dice: Return true if this evaluation metric can be computed when the class is nominal
appliesToNumericClass() - Method in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure: Return true if this evaluation metric can be computed when the class is numeric
appliesToNumericClass() - Method in class weka.classifiers.evaluation.Dice: Return true if this evaluation metric can be computed when the class is numeric
apply(Instances, int[]) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Applies the indices to the data.
apply(Instances, int[]) - Method in class weka.filters.unsupervised.attribute.DatasetCleaner: Applies the indices to the data.
apply(Instances, int[]) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Applies the indices to the data.
apply(Instances, int[]) - Method in class weka.filters.unsupervised.instance.DatasetCleaner: Applies the indices to the data.
apply(Instances, int[]) - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Applies the indices to the data.
applyCombination(double[]) - Method in class weka.classifiers.meta.ClassifierCascade: Applies the selected combination to the array.
applyIndexedSplit(IndexedSplit, Instances) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Applies the splits defined in the indexed split and returns the generated subsets.
applyIndexedSplit(IndexedSplit, Instances) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Applies the splits defined in the indexed split and returns the generated subsets.
applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Restores the data from the undo point.
applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer: Restores the data from the undo point.
applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer: Restores the data from the undo point.
applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.FileContainer: Restores the data from the undo point.
applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer: Restores the data from the undo point.
applyUndoData(Serializable[]) - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer: Restores the data from the undo point.
APPROVE_OPTION - Static variable in class adams.gui.goe.WekaGenericArrayEditorDialog: constant for dialog approval.
APPROVE_OPTION - Static variable in class adams.gui.goe.WekaGenericObjectEditorDialog: constant for dialog approval.
APPROX - weka.classifiers.trees.XGBoost.TreeMethod
AREA_UNDER_PRC - adams.flow.core.EvaluationStatistic
AREA_UNDER_PRC - adams.flow.core.ExperimentStatistic
AREA_UNDER_PRC - adams.opt.genetic.Measure: area under precision recall curve.
AREA_UNDER_ROC - adams.flow.core.EvaluationStatistic
AREA_UNDER_ROC - adams.flow.core.ExperimentStatistic
AREA_UNDER_ROC - adams.opt.genetic.Measure: area under receiver operator curve.
ARFF - adams.flow.sink.WekaExperimentGenerator.ResultFormat: ARFF.
ARFF - adams.flow.transformer.WekaInstanceDumper.OutputFormat: ARFF.
ArffOutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka: Stores the results in an ARFF file.
ArffOutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel
ArffSpreadSheetReader - Class in adams.data.io.input: Reads WEKA datasets in ARFF format and turns them into spreadsheets.
ArffSpreadSheetReader() - Constructor for class adams.data.io.input.ArffSpreadSheetReader
ArffSpreadSheetWriter - Class in adams.data.io.output: Writes a spreadsheet in ARFF file format.
ArffSpreadSheetWriter() - Constructor for class adams.data.io.output.ArffSpreadSheetWriter
ArffUtils - Class in adams.data.weka: A helper class for ARFF related stuff.
ArffUtils() - Constructor for class adams.data.weka.ArffUtils
ArffViewer - Class in adams.gui.menu: Opens the ARFF viewer.
ArffViewer() - Constructor for class adams.gui.menu.ArffViewer: Initializes the menu item with no owner.
ArffViewer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.ArffViewer: Initializes the menu item.
ArrayStatistic - Class in adams.gui.visualization.instances.instancestable: Allows the calculation of row statistics.
ArrayStatistic() - Constructor for class adams.gui.visualization.instances.instancestable.ArrayStatistic
arrayToHashSet(int[]) - Static method in class adams.data.weka.columnfinder.AbstractColumnFinder: Turns the array into a hashset.
arrayToHashSet(int[]) - Static method in class adams.data.weka.rowfinder.AbstractRowFinder: Turns the array into a hashset.
AS_IS - weka.classifiers.meta.MinMaxLimits.LimitHandling: no special handling, just as-is.
ASCENDING - adams.data.conversion.WekaPredictionContainerToSpreadSheet.Sorting: ascending.
assembleSetup(double, Classifier, int, int[]) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Assembles the data for the textual setup output.
assembleSetup(double, Classifier, int, int[]) - Method in class adams.opt.genetic.DarkLord.DarkLordJob: Assembles the data for the textual setup output.
assembleSetup(double, Classifier, int, int[]) - Method in class adams.opt.genetic.Hermione.HermioneJob: Assembles the data for the textual setup output.
assign(DataContainer<InstancePoint>) - Method in class adams.data.instance.Instance: Obtains the stored variables from the other data point, but not the actual data points.
assign(DataPoint) - Method in class adams.data.instance.InstancePoint: Obtains the stored variables from the other data point.
assign(Cell) - Method in class adams.ml.data.DataCellView: Obtains the content/type of the other cell, but not the owner.
assign(Row) - Method in class adams.ml.data.InstancesHeaderRow: Obtains copies of the cells from the other row, but not the owner.
assign(Row) - Method in class adams.ml.data.InstanceView: Obtains copies of the cells from the other row, but not the owner.
assign(SpreadSheet) - Method in class adams.ml.data.InstancesView: Clears this spreadsheet and copies all the data from the given one.
assign(InstanceContainer) - Method in class adams.gui.visualization.instance.InstanceContainer: Updates itself with the values from given container (the manager is excluded!).
assign(AbstractHashableInstance) - Method in class weka.core.AbstractHashableInstance: Assigns all the data, apart from wrapped instance, that the provided hashable instance provides.
assign(Experiment) - Method in class weka.experiment.ExtExperiment: Assigns the values from the other experiment.
assignIDs(int) - Method in class weka.classifiers.trees.m5.RuleNode2: Assigns a unique identifier to each node in the tree
AssociateTab - Class in adams.gui.tools.wekainvestigator.tab: Tab for associators.
AssociateTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.AssociateTab
AssociateTab.HistoryPanel - Class in adams.gui.tools.wekainvestigator.tab: Customized history panel.
AssociationsHandler - Class in weka.gui.explorer: Manages the AssociationsPanel.
AssociationsHandler() - Constructor for class weka.gui.explorer.AssociationsHandler
associatorTipText() - Method in class adams.flow.source.WekaAssociatorSetup: Returns the tip text for this property.
associatorTipText() - Method in class adams.flow.transformer.WekaTrainAssociator: Returns the tip text for this property.
ATT_CONSTANT - Static variable in class weka.classifiers.meta.LogTargetRegressor: Constant to add to attributes before logarithm is taken.
ATT_DATE - Static variable in class adams.core.base.AttributeTypeList: the type string for date attributes.
ATT_NOMINAL - Static variable in class adams.core.base.AttributeTypeList: the type string for nominal attributes.
ATT_NUMERIC - Static variable in class adams.core.base.AttributeTypeList: the type string for numeric attributes.
ATT_RANGE - Static variable in class weka.filters.unsupervised.instance.KennardStone
ATT_REGEXP - Static variable in class weka.filters.unsupervised.attribute.Detrend
ATT_REGEXP - Static variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection
ATT_STRING - Static variable in class adams.core.base.AttributeTypeList: the type string for string attributes.
attRangeTipText() - Method in class weka.filters.unsupervised.instance.KennardStone: Returns the tip text for this property.
attRegExpTipText() - Method in class weka.filters.unsupervised.attribute.Detrend: Returns the tip text for this property.
attRegExpTipText() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Returns the tip text for this property.
attribute(int) - Method in class weka.core.AbstractHashableInstance: Returns the attribute with the given index.
ATTRIBUTE_NAME - adams.flow.transformer.WekaInstancesInfo.InfoType: the name of the attribute (at specified index).
ATTRIBUTE_NAME - Static variable in class adams.flow.transformer.WekaInstanceEvaluator: the default name of the attribute with the evaluation value.
ATTRIBUTE_NAMES - adams.flow.transformer.WekaInstancesInfo.InfoType: the names of all attributes.
ATTRIBUTE_NAMES_SORTED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent: sort attribute names.
ATTRIBUTE_PREFIX - Static variable in class adams.flow.source.WekaNewInstances: the prefix for attributes (if nto specified explicitly).
ATTRIBUTE_PREFIX - Static variable in class weka.classifiers.meta.ClassifierCascade: the prefix for the additional cascade attributes.
ATTRIBUTE_RANGE - Static variable in class weka.filters.unsupervised.attribute.SimpleDetrend
ATTRIBUTE_SELECTION - Static variable in class weka.filters.unsupervised.attribute.EquiDistance: the option for the attribute selection.
ATTRIBUTE_TYPE - adams.flow.transformer.WekaInstancesInfo.InfoType: the attribute type (selected attribute).
attributeAsClassAt(int) - Method in class adams.gui.visualization.instances.InstancesTableModel: sets the attribute at the given col index as the new class attribute, i.e.
attributeIndex - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute: The index of the source attribute in the source dataset.
AttributeIndex - Class in adams.data.weka.classattribute: Uses the supplied attribute index to select the class attribute.
AttributeIndex - Class in adams.data.weka.relationname: Uses the name of the specified attribute as relation name.
AttributeIndex() - Constructor for class adams.data.weka.classattribute.AttributeIndex
AttributeIndex() - Constructor for class adams.data.weka.relationname.AttributeIndex
attributeIndexTipText() - Method in class adams.data.weka.rowfinder.ByLabel: Returns the tip text for this property.
attributeIndexTipText() - Method in class adams.data.weka.rowfinder.ByNumericRange: Returns the tip text for this property.
attributeIndexTipText() - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns the tip text for this property.
attributeIndexTipText() - Method in class adams.flow.transformer.WekaInstancesInfo: Returns the tip text for this property.
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.SpellChecker: Returns the tip text for this property.
attributeIndexTipText() - Method in class weka.filters.unsupervised.instance.SortOnAttribute: Returns the tip text for this property.
AttributeInfoPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel: Initializes the widget.
attributeName - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute: The name of the source attribute in the source dataset.
attributeNamesTipText() - Method in class adams.flow.source.WekaNewInstances: Returns the tip text for this property.
attributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Returns the tip text for this property.
attributeNameTipText() - Method in class adams.flow.transformer.WekaGetInstanceValue: Returns the tip text for this property.
attributeNameTipText() - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Returns the tip text for this property.
attributeNameTipText() - Method in class weka.filters.unsupervised.instance.LatestRecords: Returns the tip text for this property.
attributePrefixTipText() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Returns the tip text for this property.
attributeRangeTipText() - Method in class adams.data.instancesanalysis.FastICA: Returns the tip text for this property.
attributeRangeTipText() - Method in class adams.data.instancesanalysis.PCA: Returns the tip text for this property.
attributeRangeTipText() - Method in class adams.data.instancesanalysis.PLS: Returns the tip text for this property.
attributeRangeTipText() - Method in class adams.data.weka.rowfinder.FilteredIQR: Returns the tip text for this property.
attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: Returns the tip text for this property.
attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.InputSmearing: Returns the tip text for this property.
attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Returns the tip text for this property.
attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.LogTransform: Returns the tip text for this property.
attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.SetMissingValue: Returns the tip text for this property.
attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Returns the tip text for this property.
attributeRenamesExpTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the tip-text for the attribute-renaming regexs option.
attributeRenamesFormatTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the tip-text for the attribute renaming format strings option.
ATTRIBUTES_NAMES_UNSORTED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent: don't sort attribute names.
AttributeSelection - Class in adams.opt.optimise.genetic.fitnessfunctions: Perform attribute selection using WEKA classification.
AttributeSelection() - Constructor for class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection
AttributeSelectionHandler - Class in weka.gui.explorer: Manages the AttributeSelectionPanel.
AttributeSelectionHandler() - Constructor for class weka.gui.explorer.AttributeSelectionHandler
attributeSelectionMethodTipText() - Method in class weka.classifiers.functions.LinearRegressionJ: Returns the tip text for this property
AttributeSelectionPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab: Creates a panel that displays the attributes contained in a set of instances, letting the user toggle whether each attribute is selected or not (eg: so that unselected attributes can be removed before classification).
AttributeSelectionPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel
AttributeSelectionPanel.AttributeTableModel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab: A table model that looks at the names of attributes and maintains a list of attributes that have been "selected".
AttributeSelectionTab - Class in adams.gui.tools.wekainvestigator.tab: Tab for attribute selection.
AttributeSelectionTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab
AttributeSelectionTab.HistoryPanel - Class in adams.gui.tools.wekainvestigator.tab: Customized history panel.
attributeSelectionTipText() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the tip text for this property.
attributeSparse(int) - Method in class weka.core.AbstractHashableInstance: Returns the attribute with the given index in the sparse representation.
AttributeStatistics - Class in adams.gui.visualization.instances.instancestable: Displays statistics for the selected attribute.
AttributeStatistics() - Constructor for class adams.gui.visualization.instances.instancestable.AttributeStatistics
attributeStats(int) - Method in class weka.core.InstancesView: Calculates summary statistics on the values that appear in this set of instances for a specified attribute.
attributesTipText() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Returns the tip text for this property.
AttributeSummaryPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab: This panel displays summary statistics about an attribute: name, type number/% of missing/unique values, number of distinct values.
AttributeSummaryPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: Creates the instances panel with no initial instances.
AttributeSummaryPanel.AttributeInfoPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab: Panel with labels displaying some basic info.
AttributeSummaryPanel.StatisticsTable - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab: Displays other stats in a table.
AttributeSummaryTransferFilter - Class in weka.filters.unsupervised.attribute: Filter which trains another filter to summarise a sub-set of the data's attributes.
AttributeSummaryTransferFilter() - Constructor for class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter
AttributeTableModel(Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel: Creates the tablemodel with the given set of instances.
attributeTipText() - Method in class weka.classifiers.meta.AbstainAttributePercentile
AttributeTypeList - Class in adams.core.base: Wrapper for a comma-separated list of attribute types.
AttributeTypeList() - Constructor for class adams.core.base.AttributeTypeList: Initializes the list with length 0.
AttributeTypeList(String) - Constructor for class adams.core.base.AttributeTypeList: Initializes the object with the string to parse.
attributeTypesTipText() - Method in class adams.flow.source.WekaNewInstances: Returns the tip text for this property.
AttributeValueCellRenderer - Class in adams.gui.visualization.instances: Handles the background colors for missing values differently than the DefaultTableCellRenderer.
AttributeValueCellRenderer() - Constructor for class adams.gui.visualization.instances.AttributeValueCellRenderer: initializes the Renderer with a standard color
AttributeValueCellRenderer(Color, Color) - Constructor for class adams.gui.visualization.instances.AttributeValueCellRenderer: initializes the Renderer with the given colors
AttributeVisualizationPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab: Creates a panel that shows a visualization of an attribute in a dataset.
AttributeVisualizationPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Constructor - If used then the class will not show the class selection combo box.
AttributeVisualizationPanel(boolean) - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Constructor.
AttributeVisualizationPanel.BarCalc - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab: Internal class that calculates the barplot to display, in a separate thread.
AttributeVisualizationPanel.HistCalc - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab: Internal class that calculates the histogram to display, in a separate thread.
attributeXTipText() - Method in class adams.flow.sink.WekaInstancesPlot: Returns the tip text for this property.
attributeXTipText() - Method in class adams.flow.sink.WekaThresholdCurve: Returns the tip text for this property.
attributeXTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Returns the tip text for this property.
attributeYTipText() - Method in class adams.flow.sink.WekaInstancesPlot: Returns the tip text for this property.
attributeYTipText() - Method in class adams.flow.sink.WekaThresholdCurve: Returns the tip text for this property.
attributeYTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Returns the tip text for this property.
AUTO - weka.classifiers.trees.XGBoost.TreeMethod
autoKeyGenerationTipText() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the tip text for this property.
automaticOrderInfo() - Method in class adams.flow.core.WekaFilterModelLoader: Returns information how the model is loaded in case of AbstractModelLoader.ModelLoadingType.AUTO.
AutoScaler - Class in adams.data.weka.predictions: Applies the specified numeric scaler to the data in case of a numeric class attribute, otherwise just passes on the data.
AutoScaler() - Constructor for class adams.data.weka.predictions.AutoScaler
AVAILABLE - adams.flow.source.wekapackagemanageraction.ListPackages.ListType
Average - Class in weka.filters.unsupervised.instance.multirowprocessor.processor: Computes the average of the numeric attributes defined in the range.
Average() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.processor.Average
AVERAGE - weka.classifiers.meta.ClassifierCascade.Combination: average the probabilities/classifications.
AVERAGE_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType
AVERAGE_RULE - Static variable in class weka.classifiers.meta.AbstainVote: combination rule: Average of Probabilities
AverageSilhouetteCoefficient - Class in adams.flow.transformer.wekaclusterer: Computes the average Silhouette coefficient for the clusters.
AverageSilhouetteCoefficient() - Constructor for class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient
axisXTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the tip text for this property.
axisYTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the tip text for this property.

B

BACKUP_ACCUMULATEDERROR - Static variable in class adams.flow.transformer.WekaAccumulatedError: the key for storing the current accumulated error in the backup.
BACKUP_ATTRIBUTESTOPROCESS - Static variable in class adams.flow.transformer.WekaMultiLabelSplitter: the key for storing the current attributes to process in the backup.
BACKUP_BUFFER - Static variable in class adams.flow.transformer.WekaInstanceBuffer: the key for storing the current buffer in the backup.
BACKUP_BUFFER - Static variable in class adams.flow.transformer.WekaInstanceDumper: the key for storing the buffer in the backup.
BACKUP_CALLABLEACTOR - Static variable in class adams.flow.transformer.WekaGeneticAlgorithm: the key for backing up the callable actor.
BACKUP_CLASSATTRIBUTES - Static variable in class adams.flow.transformer.WekaMultiLabelSplitter: the key for storing the current class attributes in the backup.
BACKUP_CLaSSIFIER - Static variable in class adams.flow.transformer.WekaStreamEvaluator: the backup key for the classifier.
BACKUP_CONFIGURED - Static variable in class adams.flow.transformer.WekaGeneticAlgorithm: the key for backing up the configured state.
BACKUP_COUNTER - Static variable in class adams.flow.transformer.WekaInstanceDumper: the key for storing the counter in the backup.
BACKUP_CURRENT - Static variable in class adams.flow.transformer.WekaStreamEvaluator: the backup key for the current counter.
BACKUP_EVALUATION - Static variable in class adams.flow.transformer.WekaAggregateEvaluations: the key for storing the current accumulated error in the backup.
BACKUP_EVALUATION - Static variable in class adams.flow.transformer.WekaStreamEvaluator: the backup key for the evaluation.
BACKUP_GENERATOR - Static variable in class adams.flow.transformer.WekaCrossValidationSplit: the key for storing the current fold in the backup.
BACKUP_HEADER - Static variable in class adams.flow.transformer.WekaInstanceDumper: the key for storing the header in the backup.
BACKUP_HEADER - Static variable in class adams.flow.transformer.WekaStreamEvaluator: the backup key for the current header.
BACKUP_INCREMENTALCLASSIFIER - Static variable in class adams.flow.transformer.WekaTrainClassifier: the key for storing the current incremental classifier in the backup.
BACKUP_INCREMENTALCLUSTERER - Static variable in class adams.flow.transformer.WekaTrainClusterer: the key for storing the current incremental clusterer in the backup.
BACKUP_INITIALIZED - Static variable in class adams.flow.transformer.WekaFilter: the key for storing the current initialized state in the backup.
BACKUP_INITIALIZED - Static variable in class adams.flow.transformer.WekaStreamFilter: the key for storing the current initialized state in the backup.
BACKUP_ITERATOR - Static variable in class adams.flow.transformer.WekaInstanceBuffer: the key for storing the current iterator in the backup.
BACKUP_MODEL - Static variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: the key for storing the current model in the backup.
BACKUP_NUMPREDICTIONS - Static variable in class adams.flow.transformer.WekaAccumulatedError: the key for storing the current number of predictions in the backup.
BACKUP_PREDICTIONS - Static variable in class adams.flow.transformer.WekaAccumulatedError: the key for storing the current predictions in the backup.
BACKUP_REFERENCE - Static variable in class adams.flow.transformer.WekaReorderAttributesToReference: the key for storing the reference dataset in the backup.
BACKUP_REORDER - Static variable in class adams.flow.transformer.WekaReorderAttributesToReference: the key for storing the reorder filter in the backup.
BACKUP_SAVER - Static variable in class adams.flow.sink.WekaDatabaseWriter: the key for storing the current incremental clusterer in the backup.
BACKUP_SEARCH - Static variable in class adams.flow.transformer.WekaNearestNeighborSearch: the key for storing the current initialized state in the backup.
BACKUP_SOURCE - Static variable in class adams.flow.transformer.WekaFileReader: the key for storing the current source in the backup.
BACKUP_STRUCTURE - Static variable in class adams.flow.transformer.WekaFileReader: the key for storing the current structure in the backup.
backupSelection() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Returns the data containers that are currently selected.
backupState() - Method in class adams.flow.sink.WekaDatabaseWriter: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaAccumulatedError: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaAggregateEvaluations: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaFileReader: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaFilter: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaInstanceBuffer: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaInstanceDumper: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaStreamEvaluator: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaStreamFilter: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaTrainClassifier: Backs up the current state of the actor before update the variables.
backupState() - Method in class adams.flow.transformer.WekaTrainClusterer: Backs up the current state of the actor before update the variables.
BarCalc(int, int) - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel.BarCalc
baseScoreTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the baseScore option.
baseTipText() - Method in class adams.data.instancesanalysis.pls.OPLS: Returns the tip text for this property
baseTipText() - Method in class weka.classifiers.meta.Fallback: Returns the tip text for this property.
BasicAdamsSetupPanel - Class in adams.gui.tools.wekamultiexperimenter.setup: Basic interface for setting up an ADAMS experiment.
BasicAdamsSetupPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel
BasicWekaSetupPanel - Class in adams.gui.tools.wekamultiexperimenter.setup: Basic interface for setting up a Weka experiment.
BasicWekaSetupPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel
batchFilter(String[], Filter, String, boolean, File) - Method in class adams.gui.tools.weka.BatchFilterDatasetsPanel: Performs the batch filtering.
BatchFilterDatasets - Class in adams.gui.menu: For batch filtering datasets using a single filter setup (files get output into a different directory).
BatchFilterDatasets() - Constructor for class adams.gui.menu.BatchFilterDatasets: Initializes the menu item with no owner.
BatchFilterDatasets(AbstractApplicationFrame) - Constructor for class adams.gui.menu.BatchFilterDatasets: Initializes the menu item.
BatchFilterDatasetsPanel - Class in adams.gui.tools.weka: Wizard panel that allows appending datasets (one after the other).
BatchFilterDatasetsPanel(boolean) - Constructor for class adams.gui.tools.weka.BatchFilterDatasetsPanel: Initializes the panel.
BatchFilterJob(Filter, Instances) - Constructor for class adams.flow.transformer.WekaFilter.BatchFilterJob: Initializes the job.
batchFinished() - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Signify that this batch of input to the filter is finished.
batchSizeTipText() - Method in class weka.classifiers.functions.PyroProxy: Returns the tip text for this property.
BatchTrainJob(Classifier, Instances) - Constructor for class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob: Initializes the job.
BatchTrainJob(Clusterer, Instances, AbstractClustererPostProcessor) - Constructor for class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob: Initializes the job.
BayesNetEditor - Class in adams.gui.menu: Opens the BayesNet Editor.
BayesNetEditor() - Constructor for class adams.gui.menu.BayesNetEditor: Initializes the menu item with no owner.
BayesNetEditor(AbstractApplicationFrame) - Constructor for class adams.gui.menu.BayesNetEditor: Initializes the menu item.
beforeShow() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog: Hook method just before the dialog is made visible.
beforeShow() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: Hook method just before the dialog is made visible.
beforeShow() - Method in class adams.gui.InstanceCompare: Hook method just before the dialog is made visible.
beforeShow() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Hook method just before the dialog is made visible.
BELOW - weka.classifiers.meta.ClassifierCascade.ThresholdCheck
BestBinnedNumericClassRandomSplitGenerator - Class in weka.classifiers: Picks the best binning algorithm from the provided ones.
BestBinnedNumericClassRandomSplitGenerator() - Constructor for class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator
bestRangeTipText() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns the tip text for this property.
Bias - Class in weka.classifiers.evaluation: Computes the bias (mean error) for regression models.
Bias() - Constructor for class weka.classifiers.evaluation.Bias
BIAS - adams.flow.core.EvaluationStatistic
BIAS - adams.flow.core.ExperimentStatistic
biasTipText() - Method in class weka.classifiers.meta.VotedImbalance: Returns the tip text for this property.
BINARY_ATTRIBUTES - adams.flow.core.Capability: can handle binary attributes.
BINARY_CLASS - adams.flow.core.Capability: can handle binary classes.
binCalculationTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the tip text for this property.
BinnableInstances - Class in adams.data.binning: Helper class for binning instances.
BinnableInstances() - Constructor for class adams.data.binning.BinnableInstances
BinnableInstances.ClassValueBinValueExtractor - Class in adams.data.binning: Uses the class value as bin value.
BinnableInstances.GroupedClassValueBinValueExtractor - Class in adams.data.binning: Uses the class value of the first instance in the group as bin value.
BinnableInstances.NumericClassGroupExtractor - Class in adams.data.binning: Group extractor for numeric class attributes (using string representation of values).
BinnableInstances.StringAttributeGroupExtractor - Class in adams.data.binning: Group extractor for string attributes.
BinnedNumericClassCrossValidationFoldGenerator - Class in weka.classifiers: Helper class for generating cross-validation folds.
BinnedNumericClassCrossValidationFoldGenerator() - Constructor for class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Initializes the generator.
BinnedNumericClassCrossValidationFoldGenerator(Instances, int, long, boolean) - Constructor for class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Initializes the generator.
BinnedNumericClassCrossValidationFoldGenerator(Instances, int, long, boolean, boolean, String) - Constructor for class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Initializes the generator.
BinnedNumericClassRandomSplitGenerator - Class in weka.classifiers: Generates random splits of datasets with numeric classes using a binning algorithm.
BinnedNumericClassRandomSplitGenerator() - Constructor for class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Initializes the generator.
BinnedNumericClassRandomSplitGenerator(Instances, double) - Constructor for class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Initializes the generator.
BinnedNumericClassRandomSplitGenerator(Instances, long, double) - Constructor for class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Initializes the generator.
BinnedNumericClassRandomSplitGenerator(Instances, long, double, boolean) - Constructor for class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Initializes the generator.
Binning - Class in adams.gui.visualization.instances.instancestable: Allows to perform binning of the values from a column or row.
Binning() - Constructor for class adams.gui.visualization.instances.instancestable.Binning
binsPointTipText() - Method in class weka.core.SAXDistance: Returns the tip text for this property.
binsPointTipText() - Method in class weka.filters.unsupervised.attribute.SAX: Returns the tip text for this property.
binWidthTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the tip text for this property.
bitsPerGeneTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
bitsTipText() - Method in class adams.opt.optimise.GeneticAlgorithm: Returns the tip text for this property.
bitsToMatrix(String, double, double, int, int, int, int) - Static method in class adams.core.discovery.genetic.WekaGeneticHelper: Convert bit string into weka Matrix
BITSTRING - Static variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
bitstringTipText() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
boosterTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the booster option.
borderTipText() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns the tip text for this property.
BOTH - adams.flow.transformer.WekaBootstrapping.ErrorCalculation
BoundaryVisualizer - Class in adams.gui.menu: Displays data in the boundary visualizer.
BoundaryVisualizer() - Constructor for class adams.gui.menu.BoundaryVisualizer: Initializes the menu item with no owner.
BoundaryVisualizer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.BoundaryVisualizer: Initializes the menu item.
BOX - adams.gui.visualization.instance.InstanceLinePaintlet.MarkerShape: a square box.
BoxPlotTab - Class in adams.gui.tools.wekainvestigator.tab: Visualizes the selected dataset as box plot.
BoxPlotTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.BoxPlotTab
bufferSizeTipText() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns the tip text for this property.
build(Instance) - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Constructs the weighted dataset.
build(Instance) - Method in class weka.classifiers.lazy.LWLSynchro: Builds the classifier.
build(Instance) - Method in class weka.classifiers.lazy.LWLSynchroPrefilter: Builds the classifier.
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.
calcStats(WekaEvaluationContainer[], SpreadSheet, MessageCollection, CenterStatistic, LowerStatistic, UpperStatistic, int, Logger, TIntList, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.PredictionUtils: Generates a spreadsheet with the statistics.
calcStats(ResultItem, MessageCollection, CenterStatistic, LowerStatistic, UpperStatistic, int, Logger, TIntList) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.PredictionUtils: Generates a spreadsheet with the statistics.
calcStats(ResultItem, MessageCollection, CenterStatistic, LowerStatistic, UpperStatistic, int, Logger, TIntList, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.PredictionUtils: Generates a spreadsheet with the statistics.
calculate() - Method in class adams.ml.data.DataCellView: Does nothing.
calculate() - Method in class adams.ml.data.InstancesView: Triggers all formula cells to recalculate their values.
calculateCenters(Instances, Clusterer, Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters: Calculates the centers.
calculateDistance(Instance, Instance) - Method in class weka.filters.unsupervised.instance.KennardStone: Calculate the distance between any two instances.
calculateModelSize() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns whether model sizes should get calculated.
calculateSE(boolean[], double[]) - Method in class weka.classifiers.functions.LinearRegressionJ: Calculate the squared error of a regression model on the training data
calculateStatistics(Instances, Clusterer, Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterStatistics: Calculates the statistics.
calcWidth(double[]) - Static method in class adams.data.weka.evaluator.IntervalEstimatorBased: Calculates the width of the interval.
callableNameTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns the tip text for this property.
canAbstain() - Method in interface weka.classifiers.AbstainingClassifier: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.lazy.AbstainingLWL: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.AbstainAttributePercentile: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.AbstainAverage: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.AbstainMinimumProbability: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.AbstainVote: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.Consensus: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.ConsensusOrVote: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.FilteredClassifierExt: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.MinMaxLimits: Whether abstaining is possible, e.g., used in meta-classifiers.
canAbstain() - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper: Whether abstaining is possible, e.g., used in meta-classifiers.
CANCEL_OPTION - Static variable in class adams.gui.goe.WekaGenericArrayEditorDialog: constant for dialog cancellation.
CANCEL_OPTION - Static variable in class adams.gui.goe.WekaGenericObjectEditorDialog: constant for dialog cancellation.
canCopyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu: Returns whether copying to the clipboard is supported.
canCopyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel: Returns whether copying to the clipboard is supported.
canCopyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel: Returns whether copying to the clipboard is supported.
canCopyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel: Returns whether copying to the clipboard is supported.
canEdit() - Method in class weka.gui.explorer.ExplorerExt: Checks whether editing the data is possible.
canEvaluate(Associator) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation: Tests whether the associator can be evaluated.
canEvaluate(Associator) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: Tests whether the associator can be evaluated.
canEvaluate(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation: Tests whether attribute selection can be performed.
canEvaluate(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: Tests whether attribute selection can be performed.
canEvaluate(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: Tests whether attribute selection can be performed.
canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation: Tests whether the classifier can be evaluated.
canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Tests whether the classifier can be evaluated.
canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Tests whether the classifier can be evaluated.
canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Tests whether the classifier can be evaluated.
canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: Tests whether the classifier can be evaluated.
canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Tests whether the classifier can be evaluated.
canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Tests whether the classifier can be evaluated.
canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Tests whether the classifier can be evaluated.
canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Tests whether the classifier can be evaluated.
canEvaluate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Tests whether the classifier can be evaluated.
canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation: Tests whether the clusterer can be evaluated.
canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: Tests whether the clusterer can be evaluated.
canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Tests whether the clusterer can be evaluated.
canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: Tests whether the clusterer can be evaluated.
canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Tests whether the clusterer can be evaluated.
canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: Tests whether the clusterer can be evaluated.
canEvaluate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: Tests whether the clusterer can be evaluated.
canExecute(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup: Tests whether the experiment setup can be executed for the classifier.
canExecute(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Tests whether the experiment setup can be executed for the classifier.
canExecute(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Tests whether the experiment setup can be executed for the classifier.
canFilter() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Checks whether data can be filtered.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.ModelOutput: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.Rules: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.RunInformation: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.ReducedData: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.RunInformation: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.GraphSource: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyClassifierErrors: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyGraphVisualizer: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyMarginCurve: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyTreeVisualizer: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ModelOutput: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsFitted: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsPredictor: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.RunInformation: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeVisualizer: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ClusterAssignments: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.GraphSource: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.LegacyTreeVisualizer: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ModelOutput: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.RunInformation: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.RunInformation: Checks whether output can be generated from this item.
canGenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Checks whether output can be generated from this item.
canGenerateOutput(T) - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator: Checks whether output can be generated from this item.
canNotify(InstancePanel, InstanceContainer) - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater: Checks whether all conditions are met to notify the listeners for changes in the plot.
CANOPY - Static variable in class weka.clusterers.SAXKMeans
canopyInit(Instances) - Method in class weka.clusterers.SAXKMeans: Initialize with the canopy centers of the Canopy clustering method
canopyMaxNumCanopiesToHoldInMemoryTipText() - Method in class weka.clusterers.SAXKMeans: Returns the tip text for this property.
canopyMinimumCanopyDensityTipText() - Method in class weka.clusterers.SAXKMeans: Returns the tip text for this property.
canopyPeriodicPruningRateTipText() - Method in class weka.clusterers.SAXKMeans: Returns the tip text for this property.
canopyT1TipText() - Method in class weka.clusterers.SAXKMeans: Tip text for this property
canopyT2TipText() - Method in class weka.clusterers.SAXKMeans: Tip text for this property
canPaint(Graphics) - Method in class adams.gui.visualization.instance.InstancePanel: Returns true if the paintlets can be executed.
canRandomize() - Method in class weka.classifiers.AbstractSplitGenerator: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.DefaultRandomSplitGenerator: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Returns whether randomization is enabled.
canRandomize() - Method in class weka.classifiers.MultiLevelSplitGenerator: Returns whether randomization is enabled.
canReload() - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer: Whether it is possible to reload this item.
canReload() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer: Whether it is possible to reload this item.
canReload() - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer: Whether it is possible to reload this item.
canReload() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer: Whether it is possible to reload this item.
canReload() - Method in class adams.gui.tools.wekainvestigator.data.MemoryContainer: Whether it is possible to reload this item.
canReload() - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer: Whether it is possible to reload this item.
canReload() - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer: Whether it is possible to reload this item.
canRenderCached(Object, JPanel) - Method in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer: Checks whether the renderer can use a cached setup to render an object.
canReset() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel: Returns whether the panel supports resetting the options.
canRevert() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Revert: Checks whether any selected container can be reverted.
canStartExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Returns whether a new job can be executed.
canSwap(PropertyPath.Path, PropertyDescriptor, Object, Object) - Method in class adams.data.conversion.SwapPLS: Checks whether a swap can be made.
canUndo() - Method in class adams.gui.visualization.instances.InstancesTable: returns whether an undo is possible, i.e.
canUndo() - Method in class adams.gui.visualization.instances.InstancesTableModel: returns whether an undo is possible, i.e.
canUndo() - Method in class weka.gui.explorer.ExplorerExt: Checks whether undo is possible.
canVisualize() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Returns whether data can be visualized.
canVisualize() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Returns whether data can be visualized.
canVisualize() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Returns whether data can be visualized.
canVisualize() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Returns whether data can be visualized.
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.ExperimentPanel: method gets called in case of a change event.
capabilitiesTipText() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities: Returns the tip text for this property.
Capability - Enum in adams.flow.core: Enumeration of all capabilities.
CC - adams.flow.transformer.WekaClassifierRanker.Measure: evaluation via: Correlation coefficient.
CC - adams.opt.genetic.Measure: Correlation coefficient.
CC - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure: evaluation via: Correlation coefficient.
cellKeys() - Method in class adams.ml.data.InstancesHeaderRow: Returns a collection of all stored cell keys.
cellKeys() - Method in class adams.ml.data.InstanceView: Returns a collection of all stored cell keys.
cellKeyToIndex(String) - Method in class adams.ml.data.InstancesHeaderRow: Turns the cellKey into a column index.
cellKeyToIndex(String) - Method in class adams.ml.data.InstancesView: Turns the cellKey into a column index.
cellKeyToIndex(String) - Method in class adams.ml.data.InstanceView: Turns the cellKey into a column index.
cellPaddingTipText() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns the tip text for this property.
cellRenderingCustomizerTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Returns the tip text for this property.
cells() - Method in class adams.ml.data.InstancesHeaderRow: Returns all cells.
cells() - Method in class adams.ml.data.InstanceView: Returns all cells.
cellSpacingTipText() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns the tip text for this property.
CENTER - adams.data.instancesanalysis.pls.PreprocessingType
centerClass(Instances) - Method in class weka.classifiers.trees.RandomRegressionForest: Centers the class value in the data.
centerDataTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Returns the tip text for this property
CenterStatistic - Enum in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated: Enumeration of available center statistics.
ChangeAttributeWeight - Class in adams.gui.visualization.instances.instancestable: Allows the user to change the weight of the selected attribute.
ChangeAttributeWeight() - Constructor for class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight
changeColorProvider() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Lets the user choose another color provider.
changedUpdate(DocumentEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationDocumentListener
ChangeInstanceWeights - Class in adams.gui.visualization.instances.instancestable: Allows the user to change the weight of the selected attribute.
ChangeInstanceWeights() - Constructor for class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights
charSetTipText() - Method in class adams.flow.transformer.WekaTextDirectoryReader: Returns the tip text for this property.
check() - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction: Hook method for performing checks.
check() - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction: Hook method for performing checks.
check(PlaceholderFile) - Method in class adams.data.io.input.AbstractAdamsExperimentReader: Performs checks.
check(WekaEvaluationContainer) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor: Checks the container whether it can be processed.
check(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor: Checks the model container.
check(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor: Checks the model container.
check(AbstractExperiment) - Method in class adams.data.io.output.AbstractAdamsExperimentWriter: Performs checks.
check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotColumn: Hook method for checks before attempting the plot.
check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotRow: Hook method for checks before attempting the plot.
check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: Hook method for checks before attempting processing.
check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell: Hook method for checks before attempting processing.
check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn: Hook method for checks before attempting processing.
check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow: Hook method for checks before attempting processing.
check(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: Hook method for checks before attempting processing.
check(Object) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Checks whether the data can be processed.
check(Object) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Checks whether the data can be processed.
check(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator: Check method before generating the ensemble.
check(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels: Check method before generating the ensemble.
check(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels: Check method before generating the ensemble.
check(Object) - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction: Hook method for performing checks.
check(List<Instance>) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractSelectionProcessor: Hook method for performing checks.
check(Classifier[]) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.AbstractClassifierSetupProcessor: Hook method for performing checks on the classifiers.
check(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractNumericClassPostProcessor: Checks the container whether it can be processed.
check(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor: Checks the evaluation whether it can be processed.
check(Instance) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Peforms checks on the instance that is about to be evaluated.
check(Instances) - Method in class adams.data.instancesanalysis.FastICA: Hook method for checks.
check(Instances) - Method in class adams.data.instancesanalysis.PCA: Hook method for checks.
check(Instances) - Method in class adams.data.instancesanalysis.PLS: Hook method for checks.
check(Instances) - Method in class adams.data.weka.columnfinder.AbstractColumnFinder: Checks the data.
check(Instances) - Method in class adams.data.weka.columnfinder.AbstractColumnFinderWithCapabilities: Checks the data.
check(Instances) - Method in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder: Checks the data.
check(Instances) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter: Checks that the input data is correctly formatted for our purposes.
check(Instances) - Method in class adams.data.weka.datasetsplitter.RowSplitter: Checks that the input data is correctly formatted for our purposes.
check(Instances) - Method in class adams.data.weka.rowfinder.AbstractRowFinder: Checks the data.
check(Instances) - Method in class adams.data.weka.rowfinder.AbstractRowFinderWithCapabilities: Checks the data.
check(Instances) - Method in class adams.data.weka.rowfinder.AbstractTrainableRowFinder: Checks the data.
check(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.AbstractRowSelection: Hook method for performing checks.
check(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Hook method for performing checks before attempting the merge.
check(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Hook method for performing checks before attempting the merge.
check(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.Simple: Hook method for performing checks before attempting the merge.
check(Instances, IndexedSplitsRuns) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: For checking the data.
checkAllDatasetsHaveIDAttribute(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Checks that each of the given datasets has the unique ID attribute.
checkAttributeMapping(Map<String, List<AbstractMerge.SourceAttribute>>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Makes sure the source data for each mapped attribute is the same type.
checkAttributeMapping(Map<String, List<AbstractMerge.SourceAttribute>>) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Makes sure the source data for each mapped attribute is the same type.
checkBest(Double, OptData, FitnessFunction, int) - Method in class adams.opt.optimise.GeneticAlgorithm
checkCompatibility(Instances, Instances) - Method in class weka.filters.unsupervised.instance.AlignDataset: Checks the compatibility between reference dataset and the one to be aligned with it.
checkDataset(Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Hook method for performing checks before converting a dataset.
checkDimensions() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: checks whether the dimensions of filters and ranges fit together.
checkDimensions() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: checks whether the dimensions of filters and ranges fit together.
checkHeader(T) - Method in class adams.data.instances.AbstractInstanceGenerator: Checks whether the number of waves are the same.
checkHeaderTipText() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns the tip text for this property.
checkHeaderTipText() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns the tip text for this property.
checkInitialize(Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Hook method for performing checks before initializing.
checkInput(T) - Method in class adams.data.instances.AbstractInstanceGenerator: Checks the input profile.
checkInstance(Instance) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Hook method for performing checks before converting the Instance.
checkNext() - Method in class weka.classifiers.AbstractSplitGenerator: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.DefaultRandomSplitGenerator: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Returns true if the iteration has more elements.
checkNext() - Method in class weka.classifiers.MultiLevelSplitGenerator: Returns true if the iteration has more elements.
checkOK(double, double) - Method in class weka.classifiers.meta.AbstainAverage: Check prediction difference against thresholds
checkOK(double, double) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Check prediction difference against thresholds
checkOK(double, double) - Method in class weka.classifiers.meta.AbstainVote
checkPrediction(Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Hook method for performing checks before parsing the prediction.
checkPredictions(Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Hook method for performing checks before parsing the predictions.
checkRangeForInstance(Instance) - Method in class weka.classifiers.meta.RangeCheck: Checks the range for the instance.
checkRangeForInstance(Instance) - Method in interface weka.classifiers.RangeCheckClassifier: Checks the range for the instance.
checkSetup() - Method in class adams.data.instances.AbstractInstanceGenerator: Checks whether the setup is consistent.
choleskyDecomposition(double[][]) - Method in class weka.classifiers.functions.GPD: Cholesky decomposition.
chooseClassAttributeHeuristic() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Lets the user choose the class attribute heuristic.
chooseColor(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, List<InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Viewport: Allows the user to choose the color for all the instances.
chooseRelationNameHeuristic() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Lets the user choose the relation name heuristic.
CIRCLE - adams.gui.visualization.instance.InstanceLinePaintlet.MarkerShape: a circle.
Class - Class in adams.data.weka.columnfinder: Column finder which finds the class column (if one is set).
Class() - Constructor for class adams.data.weka.columnfinder.Class
CLASS_ATTRIBUTE_NAME - adams.flow.transformer.WekaEvaluationInfo.InfoType
CLASS_ATTRIBUTE_NAME - adams.flow.transformer.WekaInstancesInfo.InfoType: the name of the class attribute.
CLASS_CONSTANT - Static variable in class weka.classifiers.meta.LogClassRegressor: Constant to add to class before logarithm is taken.
CLASS_CONSTANT - Static variable in class weka.classifiers.meta.LogTargetRegressor: Constant to add to class before logarithm is taken.
CLASS_INDEX - Static variable in class weka.classifiers.meta.ClassifierCascade
CLASS_LABEL_COUNT - adams.flow.transformer.WekaInstancesInfo.InfoType: the number of instances with the specified class label (only nominal).
CLASS_LABEL_COUNTS - adams.flow.transformer.WekaInstancesInfo.InfoType: the counts per class label (only nominal).
CLASS_LABEL_DISTRIBUTION - adams.flow.transformer.WekaInstancesInfo.InfoType: the distribution (percentages, 0-1) per class label (only nominal).
CLASS_LABELS - adams.flow.transformer.WekaInstancesInfo.InfoType: the class labels (only nominal class attribute).
CLASS_RANGE - weka.classifiers.meta.MinMaxLimits.LimitHandling: determined based on class attribute range.
CLASS_TYPE - adams.flow.transformer.WekaInstancesInfo.InfoType: the class attribute type.
classAttribute() - Method in class weka.core.AbstractHashableInstance: Returns class attribute.
ClassAttribute - Class in adams.data.weka.relationname: Uses the class attribute name.
ClassAttribute() - Constructor for class adams.data.weka.relationname.ClassAttribute
classAttributesTipText() - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: Returns the tip text for this property
classAttributeTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the tip text for this property.
classDetailsTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the tip text for this property.
classDetailsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Returns the tip text for this property.
classDistributionTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the tip text for this property.
classDistributionTipText() - Method in class weka.classifiers.functions.FromPredictions: Returns the tip text for this property.
ClassesToClusters - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation: Tries to map the clusters of the built clusterer to the class labels in the dataset.
ClassesToClusters() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters
classFinderTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the tip-text for the classFinder option.
CLASSIFICATION - adams.flow.sink.WekaExperimentGenerator.ExperimentType: classification.
classificationEntryTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the tip text for this property.
classificationLabelEntryTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the tip text for this property.
classificationNumericAverage(Instance) - Method in class weka.classifiers.meta.AbstainVote
classificationNumericAverage(Instance, boolean) - Method in class weka.classifiers.meta.AbstainAverage: Do the classification.
classificationNumericAverage(Instance, boolean) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Do the classification.
classificationNumericMedian(Instance) - Method in class weka.classifiers.meta.AbstainVote
ClassificationViaPLS - Class in weka.classifiers.functions: Performs ClassificationViaRegression using PLSClassifierWeightedWithLoadings as base classifier, allowing access to the PLS matrices.
ClassificationViaPLS() - Constructor for class weka.classifiers.functions.ClassificationViaPLS: Initializes the classifier.
ClassificationViaRegressionD - Class in weka.classifiers.meta: Class for doing classification using regression methods.
ClassificationViaRegressionD() - Constructor for class weka.classifiers.meta.ClassificationViaRegressionD: Default constructor.
CLASSIFIER - Static variable in class weka.filters.supervised.instance.RemoveOutliers
ClassifierBasedGeneticAlgorithmJob(T, int, int[], Instances, Instances) - Constructor for class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Initializes the job.
ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob(T, int, int[], Instances, Instances) - Constructor for class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob: Initializes the job.
ClassifierCascade - Class in weka.classifiers.meta: Generates a classifier cascade, with each deeper level of classifiers being built on the input data and either the class distributions (nominal class) or classification (numeric class) of the classifiers of the previous level in the cascade.
The build process is stopped when either the maximum number of levels is reached, the termination criterion is satisfied or no further improvement is achieved.
In case of a level performing worse than the prior one, the build process is terminated immediately and the current level discarded.
ClassifierCascade() - Constructor for class weka.classifiers.meta.ClassifierCascade
ClassifierCascade.Combination - Enum in weka.classifiers.meta: Defines how to combine the predictions of the final layer and turn it into actual predictions.
ClassifierCascade.ThresholdCheck - Enum in weka.classifiers.meta: Defines how to check the threshold.
ClassifierErrors - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Generates classifier errors plot.
ClassifierErrors() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors
ClassifierHandler - Class in weka.gui.explorer: Manages the ClassifierPanel.
ClassifierHandler() - Constructor for class weka.gui.explorer.ClassifierHandler
ClassifierPanel - Class in adams.gui.tools.wekamultiexperimenter.setup: Panel for listing datasets.
ClassifierPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel
classifiersTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the tip text for this property.
classifierTipText() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Returns the tip text for this property.
classifierTipText() - Method in class adams.flow.source.WekaClassifierSetup: Returns the tip text for this property.
classifierTipText() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator: Returns the tip text for this property.
classifierTipText() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns the tip text for this property.
classifierTipText() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Returns the tip text for this property.
classifierTipText() - Method in class adams.flow.transformer.WekaClassifierOptimizer: Returns the tip text for this property.
classifierTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the tip text for this property.
classifierTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the tip text for this property.
classifierTipText() - Method in class adams.flow.transformer.WekaStreamEvaluator: Returns the tip text for this property.
classifierTipText() - Method in class adams.flow.transformer.WekaTrainClassifier: Returns the tip text for this property.
classifierTipText() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator: Returns the tip text for this property.
classifierTipText() - Method in class adams.ml.model.classification.WekaClassifier: Returns the tip text for this property.
classifierTipText() - Method in class adams.ml.model.regression.WekaRegressor: Returns the tip text for this property.
classifierTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
classifierTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the tip text for this property.
classifierTipText() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the tip text for this property.
classifierTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Returns the tip text for this property
classifierTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Returns the tip text for this property
classifierWeightsTipText() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Returns the tip text for this property
classify(Row) - Method in class adams.ml.model.classification.WekaClassificationModel: Returns the class label for the given row.
classify(Row) - Method in class adams.ml.model.regression.WekaRegressionModel: Returns the regression for the given row.
classifyInstance(Instance) - Method in class weka.classifiers.functions.ClassificationViaPLS: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.FakeClassifier: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.FromPredictions: Always returns 0.
classifyInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.GeneticAlgorithm: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.GPD: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.LinearRegressionJ: Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.functions.MathExpressionClassifier: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.PLSClassifierWeighted: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.PLSWeighted: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Generate a prediction for the supplied instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainAttributePercentile: Returns the prediction.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainAverage: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainingCascade: Predicts the class label index for the given instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: Synchronized call of super method for making classification.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Returns the prediction.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AbstainVote: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.ClassifierCascade: Returns the classification for the instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.Consensus: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.ConsensusOrVote: Predicts the class label index for the given instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.Corr: Returns the prediction.
classifyInstance(Instance) - Method in class weka.classifiers.meta.Fallback: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.FilteredClassifierExt: Simply synchronized call of inherited method.
classifyInstance(Instance) - Method in class weka.classifiers.meta.HighLowSplit: Returns the prediction.
classifyInstance(Instance) - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier: Returns the prediction.
classifyInstance(Instance) - Method in class weka.classifiers.meta.LeastMedianSq: Returns the prediction.
classifyInstance(Instance) - Method in class weka.classifiers.meta.LogClassRegressor: Returns the prediction.
classifyInstance(Instance) - Method in class weka.classifiers.meta.LogTargetRegressor: Returns the prediction.
classifyInstance(Instance) - Method in class weka.classifiers.meta.MinMaxLimits: Returns the prediction.
classifyInstance(Instance) - Method in class weka.classifiers.meta.PartitionedStacking: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.PeakTransformed: Returns the prediction.
classifyInstance(Instance) - Method in class weka.classifiers.meta.SocketFacade: Generates a classification for the instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.SubsetEnsemble: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.SumTransformed: Returns the prediction.
classifyInstance(Instance) - Method in class weka.classifiers.meta.SuppressModelOutput: Classifies the given instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper: Synchronized method for classifying data.
classifyInstance(Instance) - Method in class weka.classifiers.meta.Veto: Predicts the class label index for the given instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.VotedImbalance: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.simple.AbstractSimpleClassifier: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.M5Base2: Calculates a prediction for an instance using a set of rules or an M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.Rule2: Calculates a prediction for an instance using this rule or M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.RuleNode2: Classify an instance using this node.
classifyInstance(Instance) - Method in class weka.classifiers.trees.RandomModelTrees: Calculates the class membership probabilities for the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.RandomRegressionForest: Calculates the class membership probabilities for the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.RandomRegressionForest.Node: classifies the given instance
classifyInstance(Instance) - Method in class weka.classifiers.trees.XGBoost: Classifies the given test instance.
classifyInstanceMedian(Instance) - Method in class weka.classifiers.meta.AbstainVote: Classifies the given test instance, returning the median from all classifiers.
ClassifyTab - Class in adams.gui.tools.wekainvestigator.tab: Tab for classification.
ClassifyTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.ClassifyTab
ClassifyTab.HistoryPanel - Class in adams.gui.tools.wekainvestigator.tab: Customized history panel.
classIndex() - Method in class weka.core.AbstractHashableInstance: Returns the class attribute's index.
classIndex(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Returns the index of the selected class attribute in the provided dataset.
classIndexTipText() - Method in class adams.flow.sink.WekaCostBenefitAnalysis: Returns the tip text for this property.
classIndexTipText() - Method in class adams.flow.source.WekaNewInstances: Returns the tip text for this property.
classIndexTipText() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the tip text for this property.
classIndexTipText() - Method in class adams.flow.transformer.WekaClassSelector: Returns the tip text for this property.
classIndexTipText() - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Returns the tip text for this property.
classIndexTipText() - Method in class adams.flow.transformer.WekaEvaluationValues: Returns the tip text for this property.
classIndexTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Returns the tip text for this property.
classIndexTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis: Returns the tip text for this property.
classIndexTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Returns the tip text for this property.
classIndexTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
classIndexTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the tip text for this property.
classIndexTipText() - Method in class weka.classifiers.meta.ClassifierCascade: Returns the tip text for this property.
classIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Returns the tip text for this property
classIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Returns the tip text for this property
classIsMissing() - Method in class weka.core.AbstractHashableInstance: Tests if an instance's class is missing.
classLabelIndexTipText() - Method in class adams.data.conversion.WekaEvaluationToCostCurve: Returns the tip text for this property.
classLabelIndexTipText() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve: Returns the tip text for this property.
classLabelIndexTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the tip text for this property.
classLabelIndexTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
classLabelRangeTipText() - Method in class adams.flow.sink.WekaCostCurve: Returns the tip text for this property.
classLabelRangeTipText() - Method in class adams.flow.sink.WekaThresholdCurve: Returns the tip text for this property.
classLabelRangeTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve: Returns the tip text for this property.
classLabelRangeTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Returns the tip text for this property.
classLabelTipText() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the tip text for this property.
classnameTipText() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the tip text for this property.
classnameTipText() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the tip text for this property.
classnameTipText() - Method in class adams.core.discovery.genetic.GenericInteger: Returns the tip text for this property.
classnameTipText() - Method in class adams.core.discovery.genetic.GenericString: Returns the tip text for this property.
classnameTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode: Returns the tip text for this property.
classNameTipText() - Method in class adams.flow.source.WekaNewInstances: Returns the tip text for this property.
classNameTipText() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the tip-text for the class-name option.
classNoiseTipText() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Returns the tip text for this property.
ClassRangeBasedClassifierErrors - Class in weka.gui.visualize.plugins: Displays the classifier errors using Weka panels, but with a sizes adjusted to the class range.
ClassRangeBasedClassifierErrors() - Constructor for class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors
classValue() - Method in class weka.core.AbstractHashableInstance: Returns an instance's class value as a floating-point number.
ClassValueBinValueExtractor() - Constructor for class adams.data.binning.BinnableInstances.ClassValueBinValueExtractor
clean(String) - Method in class weka.core.tokenizers.cleaners.AbstractTokenCleaner: Determines whether a token is clean or not.
clean(String) - Method in class weka.core.tokenizers.cleaners.MultiCleaner: Determines whether a token is clean or not.
clean(String) - Method in class weka.core.tokenizers.cleaners.NormalizeDuplicateChars: Determines whether a token is clean or not.
clean(String) - Method in class weka.core.tokenizers.cleaners.PassThrough: Passes tokens through.
clean(String) - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens: Determines whether a token is clean or not.
clean(String) - Method in interface weka.core.tokenizers.cleaners.TokenCleaner: Determines whether a token is clean or not.
CLEANER - Static variable in class weka.core.tokenizers.cleaners.MultiCleaner
CLEANER - Static variable in class weka.core.tokenizers.PreCleanedTokenizer
cleanersTipText() - Method in class weka.core.tokenizers.cleaners.MultiCleaner: Returns the tip text for this property.
cleanerTipText() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Returns the tip text for this property.
cleanOutputBuffer() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Cleans up the output buffer.
cleanUp() - Method in class adams.data.instances.AbstractInstanceGenerator: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.flow.transformer.WekaClassifierRanker: Frees up memory in a "destructive" non-reversible way.
cleanUp() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.flow.transformer.WekaTrainAssociator.TrainJob: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment.CrossValidationExperimentJob: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.visualization.instance.InstanceComparePanel: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.visualization.instance.InstanceExplorer: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.visualization.instance.InstancePanel: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.gui.visualization.instance.InstancePointHitDetector: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.multiprocess.WekaCrossValidationExecution: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.multiprocess.WekaCrossValidationJob: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.opt.optimise.GeneticAlgorithm: Cleans up data structures, frees up memory.
cleanUp() - Method in class adams.tools.CompareDatasets: Cleans up data structures, frees up memory.
cleanUpGUI() - Method in class adams.flow.sink.WekaClassifierErrors: Removes all graphical components.
cleanUpGUI() - Method in class adams.flow.sink.WekaCostBenefitAnalysis: Removes all graphical components.
cleanUpGUI() - Method in class adams.flow.sink.WekaCostCurve: Removes all graphical components.
cleanUpGUI() - Method in class adams.flow.sink.WekaInstancesDisplay: Removes all graphical components.
cleanUpGUI() - Method in class adams.flow.sink.WekaInstancesPlot: Removes all graphical components.
cleanUpGUI() - Method in class adams.flow.sink.WekaInstanceViewer: Removes all graphical components.
cleanUpGUI() - Method in class adams.flow.sink.WekaMarginCurve: Removes all graphical components.
cleanUpGUI() - Method in class adams.flow.sink.WekaThresholdCurve: Removes all graphical components.
clear() - Method in class adams.data.instance.Instance: Removes all the points and report and nulls the header reference.
clear() - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList
clear() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Removes all currently loaded datasets.
clear() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Removes all entries and payloads.
clear() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Removes all entries and payloads.
clear() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Removes all entries and payloads.
clear() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Removes all entries and payloads.
clear() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Clears the content.
clear() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Saves the result as a new dataset.
clear() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Removes all entries and payloads.
clear() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel: Clears the display.
clear() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.StatisticsTable: Clears the table.
clear() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: Clears the display.
clear() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: Clears the display.
clear() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel.HistoryPanel: Removes all entries and payloads.
clear() - Method in class adams.gui.tools.wekamultiexperimenter.LogPanel: Clears the content.
clear() - Method in class adams.gui.visualization.instance.InstanceContainerManager: Clears the container list.
clear() - Method in class adams.ml.data.InstancesHeaderRow: Removes all cells.
clear() - Method in class adams.ml.data.InstancesView: Removes all cells, but leaves comments.
clear() - Method in class adams.ml.data.InstanceView: Removes all cells.
clear() - Method in class weka.experiment.ResultMatrixAdamsCSV: removes the stored data but retains the dimensions of the matrix.
clear() - Method in class weka.gui.explorer.MultiExplorer: Removes all panels.
clearBufferTipText() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns the tip text for this property.
clearData() - Method in class adams.gui.visualization.instance.InstanceExplorer: Removes all the data.
clearLog() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Empties the log.
clearLog() - Method in class adams.gui.tools.wekainvestigator.tab.LogTab: Clears the log.
clearPanel() - Method in class adams.flow.sink.WekaAttributeSummary: Clears the content of the panel.
clearPanel() - Method in class adams.flow.sink.WekaClassifierErrors: Clears the content of the panel.
clearPanel() - Method in class adams.flow.sink.WekaCostBenefitAnalysis: Clears the content of the panel.
clearPanel() - Method in class adams.flow.sink.WekaCostCurve: Clears the content of the panel.
clearPanel() - Method in class adams.flow.sink.WekaGraphVisualizer: Clears the content of the panel.
clearPanel() - Method in class adams.flow.sink.WekaInstancesDisplay: Clears the content of the panel.
clearPanel() - Method in class adams.flow.sink.WekaInstancesPlot: Clears the content of the panel.
clearPanel() - Method in class adams.flow.sink.WekaInstanceViewer: Clears the content of the panel.
clearPanel() - Method in class adams.flow.sink.WekaMarginCurve: Clears the content of the panel.
clearPanel() - Method in class adams.flow.sink.WekaThresholdCurve: Clears the content of the panel.
clearPanel() - Method in class adams.flow.sink.WekaTreeVisualizer: Clears the content of the panel.
clearProgress() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Clears the progress of the experiment.
clearRemainder() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp
clearResults() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Clears all currently stored results.
clearResults() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Clears all currently stored results.
clearResults() - Method in class adams.opt.optimise.GeneticAlgorithm: Clears all currently stored results.
clearUndo() - Method in class adams.gui.visualization.instances.InstancesTable: removes the undo history
clearUndo() - Method in class adams.gui.visualization.instances.InstancesTableModel: removes the undo history
clip(double) - Method in class weka.classifiers.evaluation.MSLE: Limits the value to MSLE.EPSILON or larger.
Clipboard - Class in adams.gui.tools.wekainvestigator.source: Parses content on the clipboard.
Clipboard() - Constructor for class adams.gui.tools.wekainvestigator.source.Clipboard: Instantiates the action.
cloneContent() - Method in class adams.data.instance.WekaInstanceContainer: Returns a clone of the content.
close() - Method in class adams.gui.tools.DatasetCompatibilityPanel: Closes the dialog.
close() - Method in class adams.gui.visualization.instance.InstanceComparePanel: closes the dialog/frame.
close() - Method in class adams.gui.visualization.instance.InstanceExplorer: closes the dialog/frame.
close() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Closes the dialog.
close() - Method in class weka.gui.explorer.ExplorerExt: Closes the dialog.
closeServer() - Method in class weka.classifiers.meta.SocketFacade: Closes the server socket if necessary.
cluster(Row) - Method in class adams.ml.model.clustering.WekaClusteringModel: Returns the cluster for the given row.
ClusterAssignments - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output: Displays the cluster assignments.
ClusterAssignments() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.ClusterAssignments
ClusterCenters - Class in adams.flow.transformer.wekaclusterer: Computes the cluster centers for the provided dataset.
ClusterCenters() - Constructor for class adams.flow.transformer.wekaclusterer.ClusterCenters
ClusterCounts - Class in adams.flow.transformer.wekaclusterer: Creates an overview of how many instances get clustered into each cluster.
Stored in container under: Clustered dataset
ClusterCounts() - Constructor for class adams.flow.transformer.wekaclusterer.ClusterCounts
ClustererHandler - Class in weka.gui.explorer: Manages the ClustererPanel.
ClustererHandler() - Constructor for class weka.gui.explorer.ClustererHandler
clustererTipText() - Method in class adams.flow.source.WekaClustererSetup: Returns the tip text for this property.
clustererTipText() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator: Returns the tip text for this property.
clustererTipText() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Returns the tip text for this property.
clustererTipText() - Method in class adams.flow.transformer.WekaTrainClusterer: Returns the tip text for this property.
clustererTipText() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator: Returns the tip text for this property.
clustererTipText() - Method in class adams.ml.model.clustering.WekaClusterer: Returns the tip text for this property.
clusterInstance(Instance) - Method in class weka.clusterers.SAXKMeans: Classifies a given instance.
ClusterStatistics - Class in adams.flow.transformer.wekaclusterer: Computes cluster statistics (min/max/mean/stdev) for the provided dataset.
ClusterStatistics() - Constructor for class adams.flow.transformer.wekaclusterer.ClusterStatistics
ClusterTab - Class in adams.gui.tools.wekainvestigator.tab: Tab for clustering.
ClusterTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.ClusterTab
ClusterTab.HistoryPanel - Class in adams.gui.tools.wekainvestigator.tab: Customized history panel.
coefficients() - Method in class weka.classifiers.functions.LinearRegressionJ: Returns the coefficients for this linear model.
collapse(Instances) - Method in class weka.core.InstanceGrouping: Collapses the data into a fake dataset with only the the group and the class attribute.
collapsedHeader() - Method in class weka.core.InstanceGrouping: Creates the header for the collapsed data.
colNameTipText() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: Returns the tip text for this property.
colNameTipText() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall: Returns the tip text for this property.
colorFieldTipText() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet: Returns the tip text for this property.
colorProviderTipText() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the tip text for this property.
colorProviderTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Returns the tip text for this property.
COLUMN - adams.flow.transformer.WekaExtractArray.ExtractionType: column.
COLUMN_BY_INDEX - adams.flow.transformer.WekaInstancesStatisticDataType: obtains columns (by index).
COLUMN_BY_REGEXP - adams.flow.transformer.WekaInstancesStatisticDataType: obtains columns (by reg exp).
COLUMN_NAME - Static variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: the name column in the spreadsheet.
COLUMN_VALUE - Static variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: the value column in the spreadsheet.
columnAsVector(Matrix, int) - Static method in class weka.core.matrix.MatrixHelper: returns the given column as a vector (actually a n x 1 matrix)
ColumnContainer(String, int) - Constructor for class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer: Initializes the container.
ColumnFinder - Interface in adams.data.weka.columnfinder: Interface for classes that "find" columns of interest in datasets.
columnFinderTipText() - Method in class adams.data.weka.columnfinder.AbstractFilteredColumnFinder: Returns the tip text for this property.
columnFinderTipText() - Method in class adams.data.weka.datasetsplitter.ColumnSplitter: Gets the tip-text for the columnFinder option.
columnFinderTipText() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Returns the tip text for this property.
columnFinderTipText() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the tip-text for the column-finder option.
columnFinderTipText() - Method in class weka.filters.unsupervised.attribute.DatasetCleaner: Returns the tip text for this property.
COLUMNS - Static variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
columnSampleByLevelTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the columnSampleByLevel option.
columnSampleByNodeTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the columnSampleByNode option.
columnSampleByTreeTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the columnSampleByTree option.
ColumnSplitter - Class in adams.data.weka.datasetsplitter: Splits a dataset in two based on the columns selected by a column-finder.
ColumnSplitter() - Constructor for class adams.data.weka.datasetsplitter.ColumnSplitter
ColumnStatistic - Class in adams.gui.visualization.instances.instancestable: Allows the calculation of column statistics.
ColumnStatistic() - Constructor for class adams.gui.visualization.instances.instancestable.ColumnStatistic
columnsTipText() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the tip text for this property.
columnsTipText() - Method in class adams.data.weka.columnfinder.Constant: Gets the tip-text for the columns option.
columnsTipText() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
columnTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the tip text for this property.
columnTipText() - Method in class adams.flow.transformer.WekaGetInstancesValue: Returns the tip text for this property.
columnTipText() - Method in class adams.flow.transformer.WekaSetInstancesValue: Returns the tip text for this property.
columnTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the tip text for this property.
colVersionTipText() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: Returns the tip text for this property.
COMBINATION - Static variable in class weka.classifiers.meta.ClassifierCascade
combinationRuleTipText() - Method in class weka.classifiers.meta.AbstainVote: Returns the tip text for this property
combinationRuleTipText() - Method in class weka.classifiers.meta.SubsetEnsemble: Returns the tip text for this property.
combinationRuleTipText() - Method in class weka.classifiers.meta.VotedImbalance: Returns the tip text for this property.
combinationTipText() - Method in class adams.data.weka.columnfinder.MultiColumnFinder: Returns the tip text for this property.
combinationTipText() - Method in class adams.data.weka.rowfinder.MultiRowFinder: Returns the tip text for this property.
combinationTipText() - Method in class weka.classifiers.meta.ClassifierCascade: Returns the tip text for this property.
COMBINE_COMPONENTS - weka.attributeSelection.AbstractPLSAttributeEval.LoadingsCalculations
COMBINED - adams.flow.transformer.WekaClassifierRanker.Measure: evaluation via: Combined = ("", Performance.1-CC) + RRSE + RAE.
commandlineToObject(String) - Method in class adams.flow.source.WekaSelectObjects: Turns a commandline into an object.
commentTipText() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary: Returns the tip text for this property.
commentTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the tip text for this property.
commonSubsequence(String, String, boolean) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Determines the common subsequence of the two strings.
commonSubsequence(String, String, boolean) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Determines the common subsequence of the two strings.
communicationTipText() - Method in class weka.classifiers.functions.PyroProxy: Returns the tip text for this property.
communicationTipText() - Method in interface weka.core.PyroProxyObject: Returns the tip text for this property.
compactify() - Method in class weka.core.InstancesView: Does nothing.
comparatorTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the tip text for this property.
compare(DataPoint, DataPoint) - Method in class adams.data.instance.InstancePointComparator: Compares its two arguments for order.
compare(AbstractHistoryPopupMenuItem, AbstractHistoryPopupMenuItem) - Method in class adams.gui.tools.wekainvestigator.history.MenuItemComparator: Compares the menu items based on category and title.
compare(AbstractPerFoldPopupMenuItem, AbstractPerFoldPopupMenuItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.MenuItemComparator: Compares the menu items based on category and title.
compare(File[], Instances[]) - Method in class adams.gui.tools.DatasetCompatibilityPanel: Performs the actual comparison.
compare(List<AbstractMerge.SourceAttribute>, List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Compares two lists of source attributes to determine the order in which their mapped attributes should appear in the merged dataset.
compare(List<AbstractMerge.SourceAttribute>, List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Compares two lists of source attributes to determine the order in which their mapped attributes should appear in the merged dataset.
compare(Prediction, Prediction) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbsolutePredictionErrorComparator: Compares the error of the predictions.
compare(Instance, Instance) - Method in class adams.data.instances.InstanceComparator: Compares its two arguments for order.
compareData() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Compares the data
CompareDatasets - Class in adams.tools: Compares two datasets, either row-by-row or using a row attribute listing a unique ID for matching the rows, outputting the correlation coefficient of the numeric attributes found in the ranges defined by the user.
In order to trim down the number of generated rows, a threshold can be specified.
CompareDatasets() - Constructor for class adams.tools.CompareDatasets
compareIDs() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Compares the IDs.
compareInstances() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Performs the comparison between the rows from the two datasets.
CompareModels - Class in adams.gui.tools.wekainvestigator.tab.classifytab.history: Compares the predictions of two models.
CompareModels() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.history.CompareModels
compareNumeric(String, ResultItem, String, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.CompareModels: Compares the two evaluations (numeric class).
compareOutput(AbstractOutputGenerator, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and then displays the generated outputs side by side.
compareOutput(AbstractOutputGenerator, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and then displays the generated outputs side by side.
compareOutput(AbstractOutputGenerator, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and then displays the generated outputs side by side.
compareOutput(AbstractOutputGenerator, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and then displays the generated outputs side by side.
compareStructure() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Compares the structure.
CompareTab - Class in adams.gui.tools.wekainvestigator.tab: For comparing datasets.
CompareTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.CompareTab
compareTo(WekaPredictionContainerToSpreadSheet.SortContainer) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer: Compares this object with the specified object for order.
compareTo(AbstractMerge.SourceAttribute) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute
compareTo(DataContainer) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Compares this container with the specified one.
compareTo(InstancesColumnComboBox.ColumnContainer) - Method in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer: Compares itself to the other container.
compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotColumn: For sorting the menu items.
compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotRow: For sorting the menu items.
compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: For sorting the menu items.
compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell: For sorting the menu items.
compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn: For sorting the menu items.
compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow: For sorting the menu items.
compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: For sorting the menu items.
compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.Binning: For sorting the menu items.
compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.Histogram: For sorting the menu items.
compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart: For sorting the menu items.
compareTo(InstancesTablePopupMenuItem) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot: For sorting the menu items.
compareTo(Object) - Method in class adams.data.instance.InstancePoint: Compares this object with the specified object for order.
compareTo(Object) - Method in class adams.data.instances.AbstractInstanceGenerator: Compares this object with the specified object for order.
compareTo(Object) - Method in class adams.data.weka.columnfinder.AbstractColumnFinder: Compares this object with the specified object for order.
compareTo(Object) - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer: Compares this object with the specified object for order.
compareTo(Object) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Compares this object with the specified object for order.
compareTo(Object) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval: Compares this object with the specified object for order.
compareTo(Object) - Method in class adams.data.weka.predictions.AbstractErrorScaler: Compares this object with the specified object for order.
compareTo(Object) - Method in class adams.data.weka.rowfinder.AbstractRowFinder: Compares this object with the specified object for order.
compareTo(Object) - Method in class adams.flow.transformer.WekaAccumulatedError.SortablePrediction: Compares this object with the specified object for order.
compareTo(Object) - Method in class weka.core.neighboursearch.NewNNSearch.InstanceNode
comparisonFieldTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the tip text for this property.
comparisonFieldTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the tip text for this property.
Compatibility - Class in adams.gui.tools.wekainvestigator.datatable.action: Checks the compatibility of the selected datasets.
Compatibility() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Compatibility: Instantiates the action.
completedClassifier(int, boolean) - Method in class weka.classifiers.meta.SubsetEnsemble: Records the completion of the training of a single classifier.
completedClassifier(int, boolean) - Method in class weka.classifiers.meta.VotedImbalance: Records the completion of the training of a single classifier.
completeRowsOnlyTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Gets the tip-text for the complete-rows-only option.
complexityStatisticsTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the tip text for this property.
complexityStatisticsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Returns the tip text for this property.
ComponentContentPanel - Class in adams.gui.tools.wekainvestigator.output: Panel for exporting the graphical component as image.
ComponentContentPanel(JComponent, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.ComponentContentPanel: Initializes the panel with the specified component.
componentRangeTipText() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Returns the tip text for this property
computeHashCode() - Method in class weka.core.AbstractHashableInstance: Computes the hashcode.
computeHashCode() - Method in class weka.core.HashableInstanceUsingString: Computes the hashcode.
computeHashCode() - Method in class weka.core.HashableInstanceUsingSum: Computes the hashcode.
computePercentage(double, double, double) - Static method in class weka.classifiers.RangeCheckHelper: Calculates the percentage of how much the value is outside the range.
computeStdDev(Instance, Matrix) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Computes standard deviation for given instance, without transforming target back into original space.
computeThresholds(Instances) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: computes the thresholds for outliers and extreme values
confidenceLevelTipText() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Returns the tip text for this property.
configureOutput(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and returns it if accepted.
configureOutput(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and returns it if accepted.
configureOutput(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and returns it if accepted.
configureOutput(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and returns it if accepted.
configureOutput(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and returns it if accepted.
configureRowFinder(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Configures the row finder that determines whether the classifier/dataset combination is still required.
ConfusionMatrix - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Displays the confusion matrix.
ConfusionMatrix() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix
confusionMatrixTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the tip text for this property.
confusionMatrixTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Returns the tip text for this property.
consensus(Instance) - Method in class weka.classifiers.meta.Consensus: Checks whether there is consensus between the classifiers.
Consensus - Class in weka.classifiers.meta: Outputs predictions only if the ensemble agrees.
Consensus() - Constructor for class weka.classifiers.meta.Consensus
ConsensusOrVote - Class in weka.classifiers.meta: If the required minimum number of classifiers of the ensemble agree on a label, then this label is predicted.
ConsensusOrVote() - Constructor for class weka.classifiers.meta.ConsensusOrVote
Constant - Class in adams.data.weka.columnfinder: Column finder that finds a constant set of columns.
Constant - Class in adams.data.weka.rowfinder: Row finder that finds a constant set of rows.
Constant() - Constructor for class adams.data.weka.columnfinder.Constant
Constant() - Constructor for class adams.data.weka.rowfinder.Constant
constructEnsemble() - Method in class weka.classifiers.meta.VotedImbalance: Constructs the ensemble.
constructEnsemble(Instance) - Method in class weka.classifiers.meta.SubsetEnsemble: Constructs the ensemble.
containersInViewport(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Viewport: Locates the visible instances that are on display in the current viewport.
conversionTipText() - Method in class weka.core.converters.SpreadSheetLoader: The tip text for this property.
convert() - Method in class adams.gui.tools.WekaOptionsConversionPanel: Performs the conversion.
convert(Class, String) - Method in class adams.flow.core.WekaPropertyValueConverter: Converts the variable value into the appropriate object, if possible.
convertCapabilities(Capabilities) - Static method in class adams.ml.data.WekaConverter: Converts Weka capabilities into ADAMS ones.
convertDataset(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Performs the dataset conversion.
converterTipText() - Method in class adams.data.conversion.WekaCommandToCode: Returns the tip text for this property.
convertInstance(PyroProxy, Instance) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Converts the instance into a different format.
convertInstance(Instance) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Transform an instance in original (unormalized) format.
ConvertToDate - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction: Converts the selected string attributes to date ones.
ConvertToDate() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToDate: Instantiates the action.
ConvertToNominal - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction: Converts the selected attributes to nominal ones.
ConvertToNominal() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToNominal: Instantiates the action.
ConvertToString - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction: Converts the selected attributes to string ones.
ConvertToString() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToString: Instantiates the action.
COORD_DESCENT - weka.classifiers.trees.XGBoost.Updater
copy() - Method in class weka.core.AbstractHashableInstance: This method produces a shallow copy of an object.
copy(double[]) - Method in class weka.core.AbstractHashableInstance: Copies the instance but fills up its values based on the given array of doubles.
copy(Instances) - Method in class adams.gui.visualization.instances.InstancesTableModel: Returns a new model with the same setup.
copy(ExplorerExt, boolean) - Static method in class weka.gui.explorer.WorkspaceHelper: Copies an explorer instance.
Copy - Class in adams.gui.tools.wekainvestigator.datatable.action: Copies the selected dataset.
Copy() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Copy: Instantiates the action.
copyGene(int, int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Copies the values of one gene to another.
copySelectedTab() - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane: Creates a copy of the current tab.
CopySetup - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold: Simply copies the classifier setup to the clipboard.
CopySetup() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.CopySetup
copyTabAt(int) - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane: Creates a copy of the specified tab.
copyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu: Copies the content to the clipboard.
copyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel: Copies the content to the clipboard.
copyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel: Copies the content to the clipboard.
copyToClipboard() - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel: Copies the content to the clipboard.
copyWorkspace() - Method in class adams.gui.tools.wekainvestigator.InvestigatorManagerPanel: Copies a workspace.
Corr - Class in weka.classifiers.meta: Assume NO MISSING VALUES, all attributes must be NUMERIC (or 0/1 maybe ...).
Corr() - Constructor for class weka.classifiers.meta.Corr
correct(double[], double[]) - Method in class weka.filters.unsupervised.attribute.detrend.AbstractDetrend: Corrects the spectrum.
correct(double[], double[]) - Method in class weka.filters.unsupervised.attribute.detrend.Mean: Corrects the spectrum.
correct(double[], double[]) - Method in class weka.filters.unsupervised.attribute.detrend.RangeBased: Corrects the spectrum.
correct(double[], double[], double[]) - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.AbstractMultiplicativeScatterCorrection: Corrects the spectrum.
correct(double[], double[], double[]) - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased: Corrects the spectrum.
correctData(T, double[]) - Method in class adams.data.baseline.AbstractLinearRegressionBased: Corrects the data with the given coefficients.
CORRECTION - Static variable in class weka.filters.unsupervised.attribute.Detrend
CORRECTION - Static variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection
CORRECTION - Static variable in class weka.filters.unsupervised.attribute.SimpleDetrend
correctionTipText() - Method in class weka.filters.unsupervised.attribute.Detrend: Returns the tip text for this property.
correctionTipText() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Returns the tip text for this property.
correctionTipText() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Returns the tip text for this property.
correctTipText() - Method in class weka.filters.unsupervised.attribute.SpellChecker: Returns the tip text for this property.
CORRELATION_COEFFICIENT - adams.flow.core.EvaluationStatistic
CORRELATION_COEFFICIENT - adams.flow.core.ExperimentStatistic
CORRELATION_COEFFICIENT - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel
CorrelationMatrix - Class in weka.filters.unsupervised.attribute: Computes a matrix with the correlation coefficients between attributes.
CorrelationMatrix() - Constructor for class weka.filters.unsupervised.attribute.CorrelationMatrix
CostCurve - Class in adams.gui.menu: Displays Cost curve data.
CostCurve() - Constructor for class adams.gui.menu.CostCurve: Initializes the menu item with no owner.
CostCurve(AbstractApplicationFrame) - Constructor for class adams.gui.menu.CostCurve: Initializes the menu item.
CostCurvePanel - Class in adams.gui.tools.weka: Displays cost curve data.
CostCurvePanel() - Constructor for class adams.gui.tools.weka.CostCurvePanel
count() - Method in class weka.gui.explorer.MultiExplorer: Returns the number of explorer panels.
countVisible() - Method in class adams.gui.visualization.instance.InstanceContainerManager: Returns the number of visible containers.
COX_REGRESSION - weka.classifiers.trees.XGBoost.Objective
CPU - weka.classifiers.trees.XGBoost.Predictor
create() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO: Creates a new experiment.
create() - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultAdamsExperimentIO: Creates a new experiment.
create() - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultWekaExperimentIO: Creates a new experiment.
create() - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO: Creates a new experiment.
createAttribute(String) - Method in class weka.core.converters.SimpleArffLoader: Creates an attribute from the specification line.
createAttributeMapping() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Creates a mapping from the attributes in each input dataset to the corresponding attribute in the merged dataset.
createCellPopup(MouseEvent) - Method in class adams.gui.visualization.instances.InstancesTable: Creates a popup menu for the cells.
createChooserPanel() - Method in class adams.gui.tools.weka.AbstractPanelWithFile: Generates the panel to use.
createChooserPanel() - Method in class adams.gui.tools.weka.CostCurvePanel: Generates the panel to use.
createComponent() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableWithButtons: Creates the component to use in the panel.
createContainerList() - Method in class adams.gui.visualization.instance.InstancePanel: Returns the container list.
createCustomEditor() - Method in class adams.gui.goe.WekaExperimentFileEditor: Gets the custom editor component.
createDataset(Evaluation) - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator: Generates a dataset, containing the predicted vs actual values.
createDefaultDataModel() - Method in class adams.gui.visualization.instance.InstanceTable: Creates an empty default model.
createDialog() - Method in class adams.gui.tools.wekainvestigator.source.Clipboard: Creates a new dialog.
createDialog(Container) - Static method in class adams.gui.goe.WekaGenericArrayEditorDialog: Creates a modal dialog for the parent.
createDialog(Container) - Static method in class adams.gui.goe.WekaGenericObjectEditorDialog: Creates a modal dialog for the parent.
createDialog(Container, PropertyEditor) - Static method in class adams.gui.goe.WekaGenericObjectEditorDialog: Creates a modal dialog for the parent with the provided editor.
createDialog(Container, PropertyEditor, Object) - Static method in class adams.gui.goe.WekaGenericObjectEditorDialog: Creates a modal dialog for the parent with the provided editor and initial value.
createDialog(Container, Object) - Static method in class adams.gui.goe.WekaGenericArrayEditorDialog: Creates a modal dialog for the parent with the provided editor and initial value.
createDisplayPanel(Token) - Method in class adams.flow.sink.WekaAttributeSummary: Creates a new display panel for the token.
createDisplayPanel(Token) - Method in class adams.flow.sink.WekaClassifierErrors: Creates a new panel for the token.
createDisplayPanel(Token) - Method in class adams.flow.sink.WekaCostBenefitAnalysis: Creates a new panel for the token.
createDisplayPanel(Token) - Method in class adams.flow.sink.WekaCostCurve: Creates a new panel for the token.
createDisplayPanel(Token) - Method in class adams.flow.sink.WekaGraphVisualizer: Creates a new display panel for the token.
createDisplayPanel(Token) - Method in class adams.flow.sink.WekaInstancesDisplay: Creates a new panel for the token.
createDisplayPanel(Token) - Method in class adams.flow.sink.WekaInstancesPlot: Creates a new panel for the token.
createDisplayPanel(Token) - Method in class adams.flow.sink.WekaInstanceViewer: Creates a new panel for the token.
createDisplayPanel(Token) - Method in class adams.flow.sink.WekaMarginCurve: Creates a new panel for the token.
createDisplayPanel(Token) - Method in class adams.flow.sink.WekaThresholdCurve: Creates a new panel for the token.
createDisplayPanel(Token) - Method in class adams.flow.sink.WekaTreeVisualizer: Creates a new display panel for the token.
createDummy() - Static method in class adams.ml.data.InstancesView: Returns a dummy dataset.
createEmptyResultantDataset(Map<String, List<AbstractMerge.SourceAttribute>>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Creates the resultant dataset, ready to be filled with data.
createExperimentIO() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: Creates the handler for the IO, i.e., loading/saving of experiments.
createExperimentIO() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: Creates the handler for the IO, i.e., loading/saving of experiments.
createExperimentIO() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: Creates the handler for the IO, i.e., loading/saving of experiments.
createFakeModel() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Creates the fake model.
createFileChooser() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu: Creates the filechooser to use.
createFileChooser() - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel: Creates the filechooser to use.
createFileChooser() - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel: Creates the filechooser to use.
createFileChooser() - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel: Creates the filechooser to use.
createFileChooser() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractAdamsExperimentIO: Creates and returns a file chooser for loading/saving experiments.
createFileChooser() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO: Creates and returns a file chooser for loading/saving experiments.
createFileChooser() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractWekaExperimentIO: Creates and returns a file chooser for loading/saving experiments.
createFilename(Instances) - Method in class adams.flow.transformer.WekaInstanceDumper: Generates the filename for the output.
createFileName(double, Instances, String) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Generates a file name for the fitness.
createFlow(PlaceholderFile[], AbstractFileLoader, SpreadSheetReader, String, PlaceholderDirectory) - Method in class adams.gui.menu.MakeCompatibleDatasets: Creates the flow.
createGraphVisualizer(Token) - Method in class adams.flow.sink.WekaGraphVisualizer: Creates a tree visualizer from the token.
createHeader(Instances) - Method in class adams.flow.transformer.WekaInstanceDumper: Turns the dataset header into the appropriate format.
createHeaderPopup(MouseEvent) - Method in class adams.gui.visualization.instances.InstancesTable: Shows a popup menu for the header.
createHistoryEntryToolTip(AbstractNamedHistoryPanel<ResultItem>, int) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Gets called when a tooltip needs to get generated.
createHistoryEntryToolTip(AbstractNamedHistoryPanel<ResultItem>, int) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Gets called when a tooltip needs to get generated.
createHistoryEntryToolTip(AbstractNamedHistoryPanel<ResultItem>, int) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Gets called when a tooltip needs to get generated.
createHistoryEntryToolTip(AbstractNamedHistoryPanel<ResultItem>, int) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Gets called when a tooltip needs to get generated.
createHistoryEntryToolTip(AbstractNamedHistoryPanel<ResultItem>, int) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Gets called when a tooltip needs to get generated.
createIDInfoPanel(BaseTextArea) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Generates an info panel for an ID text area.
createLastSetupKey(Class, boolean, boolean) - Method in class adams.gui.visualization.instances.InstancesTable: Generates a key for the HashMap used for the last setups.
createMappedAttribute(String, List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Creates the attribute for the output merged dataset for the given attribute mapping.
createMenuItem(ClassifyTab.HistoryPanel, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.CompareModels: Creates the menu item to add to the history's popup menu.
createMenuItem(ClassifyTab.HistoryPanel, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation: Creates the menu item to add to the history's popup menu.
createMenuItem(PerFoldMultiPagePane, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem: Creates the menu item to add to the pane's popup menu.
createMenuItem(PerFoldMultiPagePane, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.CopySetup: Creates the menu item to add to the pane's popup menu.
createMenuItem(PerFoldMultiPagePane, int[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation: Creates the menu item to add to the pane's popup menu.
createMenuItem(H, int[]) - Method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem: Creates the menu item to add to the history's popup menu.
createMetaLevelHeader(Instances) - Method in class weka.classifiers.meta.ClassifierCascade: Generates the dataset structure for the meta-levels.
createMetaLevelInstance(Instances, Instance) - Method in class weka.classifiers.meta.ClassifierCascade: Generates an instance for the meta-level using the original data.
createModel(InstanceContainerManager) - Method in class adams.gui.visualization.instance.InstanceContainerList: Creates a new model.
createName() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: Creates the name from the members.
createName() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: Creates the name from the members.
createName() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Creates the name from the members.
createName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Creates the name from the members.
createName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Creates the name from the members.
createName() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: Creates the name from the members.
createNext() - Method in class weka.classifiers.AbstractSplitGenerator: Creates the next result.
createNext() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Creates the next result.
createNext() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns the next element in the iteration.
createNext() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Creates the next result.
createNext() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns the next element in the iteration.
createNext() - Method in class weka.classifiers.DefaultRandomSplitGenerator: Creates the next result.
createNext() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the next element in the iteration.
createNext() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Creates the next result.
createNext() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the next element in the iteration.
createNext() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns the next element in the iteration.
createNext() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Creates the next result.
createNext() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Returns the next element in the iteration.
createNext() - Method in class weka.classifiers.MultiLevelSplitGenerator: Creates the next result.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.ModelOutput: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.Rules: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.RunInformation: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.ReducedData: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.RunInformation: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.AbstractOutputGeneratorWithSeparateFoldsSupport: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.GraphSource: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyGraphVisualizer: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyTreeVisualizer: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ModelOutput: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.RunInformation: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeVisualizer: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ClusterAssignments: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.GraphSource: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.LegacyTreeVisualizer: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ModelOutput: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.RunInformation: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.RunInformation: Generates output from the item.
createOutput(ResultItem, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Generates output from the item.
createOutput(T, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator: Generates output from the item.
createOutput(Evaluation, int[], SpreadSheet, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Generates a plot actor from the evaluation.
createOutput(Evaluation, int[], SpreadSheet, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Generates the output from the evaluation.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.AbstractOutputGeneratorWithSeparateFoldsSupport: Generates the table with the confusion matrix.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Generates the table with the confusion matrix.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Creates the 4-in-1 plot for the evaluation.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyClassifierErrors: Generates output from the evaluation.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis: Generates output from the evaluation.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve: Generates output from the evaluation.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyMarginCurve: Generates output from the evaluation.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Generates output from the evaluation.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Generates the output from the evaluation.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Generates the output for the evaluation.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsFitted: Generates output from the evaluation.
createOutput(Evaluation, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsPredictor: Generates the output from the evaluation.
createOutput(Evaluation, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Generates a panel from the results of the evaluation.
createOutputFormat(Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters: Generates the output format (additional attribute for cluster index).
createOutputFormat(Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterCounts: Generates the output format (additional attribute for cluster index).
createOutputFormat(Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterStatistics: Generates the output format (additional attribute for cluster index).
createParamsFromOptions() - Method in class weka.classifiers.trees.XGBoost: Converts the options into a parameter map as expected by XGBoost.
createPlot(InstancesTablePopupMenuItemHelper.TableState, boolean, TDoubleArrayList, String) - Method in class adams.gui.visualization.instances.instancestable.Binning: Generates the plot.
createPlot(InstancesTable, boolean, SpreadSheet, String, int[]) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart: Plots the data.
createPlot(InstancesTable, boolean, List<Double>[], String, String[]) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot: Generates the plot.
createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Generates the right-click menu for the JList.
createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Generates the right-click menu for the JList.
createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Generates the right-click menu for the JList.
createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane: Generates the right-click menu for the JList.
createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Generates the right-click menu for the JList.
createPopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Generates the right-click menu for the JList.
createPopupMenu() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu: Creates and returns the popup menu.
createPopupMenu() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Creates and returns the popup menu.
createPrefix(Instances, int) - Method in class adams.flow.transformer.WekaInstancesMerge: Generates the prefix for the dataset/index.
createPreview(File) - Method in class adams.gui.tools.previewbrowser.InstanceExplorerHandler: Creates the actual view.
createPreview(File) - Method in class adams.gui.tools.previewbrowser.WekaDatasetHandler: Creates the actual view.
createPreview(Object) - Method in class adams.gui.tools.previewbrowser.GraphSource: Creates the actual preview.
createPreview(Object) - Method in class adams.gui.tools.previewbrowser.GraphVisualizer: Creates the actual preview.
createPreview(Object) - Method in class adams.gui.tools.previewbrowser.InterQuartileRangeViewer: Creates the actual preview.
createPreview(Object) - Method in class adams.gui.tools.previewbrowser.TreeVisualizer: Creates the actual preview.
createRelationName(String, String, int, boolean) - Static method in class weka.classifiers.CrossValidationHelper: Generates a relation name for the current fold.
createRelationName(String, String, String, boolean) - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Generates a relation name for the current value.
createRow(int, String, Instances) - Method in class adams.flow.transformer.wekaclusterer.ClusterStatistics: Creates a new stats row.
createRow(Instance) - Method in class adams.flow.transformer.WekaInstanceDumper: Turns the row into the appropriate format.
createRunner(ExperimenterPanel) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO: Creates an experiment runner thread object.
createRunner(ExperimenterPanel) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultAdamsExperimentIO: Creates an experiment runner thread object.
createRunner(ExperimenterPanel) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultWekaExperimentIO: Creates an experiment runner thread object.
createRunner(ExperimenterPanel) - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO: Creates an experiment runner thread object.
createSubEvaluation(ClassifyTab.HistoryPanel, ResultItem, double[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation: Creates the sub-range evaluation and adds it to the history.
createSubEvaluation(PerFoldMultiPagePane, ResultItem, Evaluation, int, double[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation: Creates the sub-range evaluation and adds it to the pane.
createSubEvaluations(PerFoldMultiPagePane, ResultItem, Evaluation[], int[], double[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation: Creates the sub-range evaluation and adds it to the pane.
createToken(Object, Object) - Method in class adams.flow.transformer.WekaFilter: Creates a token with the data.
createTreeVisualizer(Token) - Method in class adams.flow.sink.WekaTreeVisualizer: Creates a tree visualizer from the token.
createViewTipText() - Method in interface adams.data.weka.InstancesViewCreator: Returns the tip text for this property.
createViewTipText() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the tip text for this property.
createViewTipText() - Method in class adams.flow.transformer.WekaRandomSplit: Returns the tip text for this property.
CROSS_VALIDATION - adams.flow.sink.WekaExperimentGenerator.EvaluationType: cross-validation.
crossValidate(Instances, int) - Method in class weka.filters.supervised.instance.RemoveOutliers: Cross-validates the classifier on the given data.
crossValidateModel(Classifier, Instances, int, Random, Object...) - Method in class weka.classifiers.evaluation.StoppableEvaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
CrossValidation - Class in adams.gui.tools.wekainvestigator.tab.attseltab.evaluation: Performs cross-validation.
CrossValidation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation: Performs cross-validation.
CrossValidation - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation: Performs cross-validation.
CrossValidation() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation
CrossValidation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
CrossValidation() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation
CrossValidationExperiment - Class in adams.gui.tools.wekamultiexperimenter.experiment: Performs cross-validation.
CrossValidationExperiment() - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment
CrossValidationExperiment.CrossValidationExperimentJob - Class in adams.gui.tools.wekamultiexperimenter.experiment: Performs cross-validation on the classifier/data combination.
CrossValidationExperimentJob(CrossValidationExperiment, int, Classifier, Instances) - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment.CrossValidationExperimentJob: Initializes the run.
CrossValidationFoldGenerator - Interface in weka.classifiers: Interface for generating cross-validation folds.
CrossValidationHelper - Class in weka.classifiers: Helper class for cross-validation.
CrossValidationHelper() - Constructor for class weka.classifiers.CrossValidationHelper
crossValidationIndices() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns the cross-validation indices.
crossValidationIndices() - Method in interface weka.classifiers.CrossValidationFoldGenerator: Returns the cross-validation indices.
crossValidationIndices() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns the cross-validation indices.
crossValidationIndices() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the cross-validation indices.
crossValidationIndices() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the cross-validation indices.
crossValidationIndices() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns the cross-validation indices.
crossValidationIndices(Instances, int, Random) - Static method in class weka.classifiers.CrossValidationHelper: Returns the indices from the original dataset for tracing the predictions back to the original dataset (stratified).
crossValidationIndices(Instances, int, Random, boolean) - Static method in class weka.classifiers.CrossValidationHelper: Returns the indices from the original dataset for tracing the predictions back to the original dataset.
crossValidationSeedTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
crossValidationSeedTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the tip text for this property.
CrossValidationSetup - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.setup: Setup for a cross-validation experiment.
CrossValidationSetup() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup
CSV - adams.flow.sink.WekaExperimentGenerator.ResultFormat: CSV.
CSV - adams.flow.transformer.WekaInstanceDumper.OutputFormat: comma-separated.
CsvOutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka: Stores the results in a CSV file.
CsvOutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel
CTipText() - Method in class adams.data.instancesanalysis.pls.PRM: Returns the tip text for this property
CUSTOM_ADAMS_READER - Static variable in class adams.gui.menu.MakeCompatibleDatasets
CUSTOM_WEKA_FILE_LOADER - Static variable in class adams.gui.menu.MakeCompatibleDatasets
customize(AbstractContainerListPopupCustomizer.Context<Instance, InstanceContainerManager, InstanceContainer>, JPopupMenu) - Method in class adams.gui.visualization.instance.containerlistpopup.SaveAs: Returns a popup menu for the table of the container list.
customize(AbstractContainerListPopupCustomizer.Context<Instance, InstanceContainerManager, InstanceContainer>, JPopupMenu) - Method in class adams.gui.visualization.instance.containerlistpopup.ViewAsTable: Returns a popup menu for the table of the container list.
customize(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, MouseEvent, JPopupMenu) - Method in class adams.gui.visualization.instance.plotpopup.Adjust: Returns a popup menu for the table of the container list.
customize(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, MouseEvent, JPopupMenu) - Method in class adams.gui.visualization.instance.plotpopup.Histogram: Returns a popup menu for the table of the container list.
customize(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, MouseEvent, JPopupMenu) - Method in class adams.gui.visualization.instance.plotpopup.SaveVisible: Returns a popup menu for the table of the container list.
customize(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, MouseEvent, JPopupMenu) - Method in class adams.gui.visualization.instance.plotpopup.Viewport: Returns a popup menu for the table of the container list.
customLoaderTipText() - Method in class adams.flow.transformer.WekaFileReader: Returns the tip text for this property.
customLoaderTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the tip text for this property.
customLoaderTipText() - Method in class weka.filters.unsupervised.instance.AlignDataset: Returns the tip text for this property.
customLoaderTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the tip text for this property.
CustomOutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka: Allows the user to configure any ResultListener.
CustomOutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel
customPaintletTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
CustomPropertySheetPanel() - Constructor for class adams.gui.wizard.WekaPropertySheetPanelPage.CustomPropertySheetPanel
customPropsFileTipText() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the tip text for this property.
customPropsFileTipText() - Method in class adams.flow.source.WekaDatabaseReader: Returns the tip text for this property.
customSaverTipText() - Method in class adams.flow.sink.WekaFileWriter: Returns the tip text for this property.
customStopMessageTipText() - Method in class adams.flow.source.WekaSelectDataset: Returns the tip text for this property.
CYCLIC - weka.classifiers.trees.XGBoost.FeatureSelector

D

DarkLord - Class in adams.gui.menu: For optimizing datasets (attribute selection) using genetic algorithm.
DarkLord - Class in adams.opt.genetic
DarkLord() - Constructor for class adams.gui.menu.DarkLord: Initializes the menu item with no owner.
DarkLord() - Constructor for class adams.opt.genetic.DarkLord
DarkLord(AbstractApplicationFrame) - Constructor for class adams.gui.menu.DarkLord: Initializes the menu item.
DarkLord.DarkLordJob - Class in adams.opt.genetic: A job class specific to The Dark Lord.
DarkLordJob(DarkLord, int, int[], Instances, Instances) - Constructor for class adams.opt.genetic.DarkLord.DarkLordJob: Initializes the job.
DART - weka.classifiers.trees.XGBoost.BoosterType
DATA - adams.opt.genetic.OutputType: only the data.
Database - Class in adams.gui.tools.wekainvestigator.source: For loading data from a database.
Database() - Constructor for class adams.gui.tools.wekainvestigator.source.Database: Instantiates the action.
DatabaseContainer - Class in adams.gui.tools.wekainvestigator.data: Dataset loaded from database.
DatabaseContainer(String, String, String, String) - Constructor for class adams.gui.tools.wekainvestigator.data.DatabaseContainer: Loads the data using the specified url/query.
DataCellView - Class in adams.ml.data: Wrapper for single cell values in a Instance object.
DataCellView(InstanceView, int) - Constructor for class adams.ml.data.DataCellView: Initializes the cell.
dataChanged(DataChangeEvent) - Method in class adams.gui.visualization.instance.InstanceExplorer: Gets called if the data of the instance panel has changed.
dataChanged(WekaInvestigatorDataEvent) - Method in interface adams.gui.event.WekaInvestigatorDataListener: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.DataTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.LogTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Notifies the tab that the data changed.
dataChanged(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab: Notifies the tab that the data changed.
DataContainer - Interface in adams.gui.tools.wekainvestigator.data: Interface for data containers.
DataContainerList - Class in adams.gui.tools.wekainvestigator.data: For managing the data containers.
DataContainerList() - Constructor for class adams.gui.tools.wekainvestigator.data.DataContainerList
DataGenerator - Class in adams.gui.tools.wekainvestigator.source: For generating data using a data generator.
DataGenerator() - Constructor for class adams.gui.tools.wekainvestigator.source.DataGenerator: Instantiates the action.
DataGenerator(Evaluation, AbstractErrorScaler) - Constructor for class adams.flow.sink.WekaClassifierErrors.DataGenerator: Initializes the generator.
DataGeneratorContainer - Class in adams.gui.tools.wekainvestigator.data: Dataset generated by datagenerator.
DataGeneratorContainer(DataGenerator) - Constructor for class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer: Loads the data using the specified loader.
dataGeneratorTipText() - Method in class adams.flow.source.WekaDataGenerator: Returns the tip text for this property.
DataInfo(String, int, double, double) - Constructor for class adams.opt.optimise.genetic.PackDataDef.DataInfo
DataQueryTab - Class in adams.gui.tools.wekainvestigator.tab: Allows the execution of an SQL-like query to manipulate datasets.
DataQueryTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.DataQueryTab
dataRowTypeTipText() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet: Returns the tip text for this property.
dataset - Variable in class weka.classifiers.lazy.LWLDatasetBuilder.LWLContainer: the weighted dataset.
dataset() - Method in class weka.core.AbstractHashableInstance: Returns the dataset this instance has access to.
DATASET - adams.flow.transformer.WekaFileReader.OutputType: the complete dataset.
DATASET_KEYWORD - Static variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: The keyword to replace with the dataset name in attribute renaming.
DATASET_NAME - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator
DATASET_NUMATTRIBUTES - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator
DATASET_NUMINSTANCES - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator
dataset1TipText() - Method in class adams.tools.CompareDatasets: Returns the tip text for this property.
dataset2TipText() - Method in class adams.tools.CompareDatasets: Returns the tip text for this property.
DatasetCleaner - Class in weka.filters.unsupervised.attribute: Removes all columns from the data data that have been indentified.
DatasetCleaner - Class in weka.filters.unsupervised.instance: Removes all rows from the data data that have been indentified.
DatasetCleaner() - Constructor for class weka.filters.unsupervised.attribute.DatasetCleaner
DatasetCleaner() - Constructor for class weka.filters.unsupervised.instance.DatasetCleaner
DatasetCompatibility - Class in adams.gui.menu: For checking compatibility of datasets.
DatasetCompatibility() - Constructor for class adams.gui.menu.DatasetCompatibility: Initializes the menu item with no owner.
DatasetCompatibility(AbstractApplicationFrame) - Constructor for class adams.gui.menu.DatasetCompatibility: Initializes the menu item.
DatasetCompatibilityPanel - Class in adams.gui.tools: Compares the headers of a number of datasets and outputs the results.
DatasetCompatibilityPanel() - Constructor for class adams.gui.tools.DatasetCompatibilityPanel
DatasetFileChooserPanel - Class in adams.gui.chooser: A panel that contains a text field with the current file and a button for bringing up a ConverterFileChooser.
DatasetFileChooserPanel() - Constructor for class adams.gui.chooser.DatasetFileChooserPanel: Initializes the panel with no file.
DatasetFileChooserPanel(File) - Constructor for class adams.gui.chooser.DatasetFileChooserPanel: Initializes the panel with the given filename/directory.
DatasetFileChooserPanel(String) - Constructor for class adams.gui.chooser.DatasetFileChooserPanel: Initializes the panel with the given filename/directory.
datasetForSingleInstance(Instance) - Method in class adams.flow.transformer.WekaDatasetsMerge: Creates an Instances dataset, containing a copy of the single instance provided.
DatasetHelper - Class in adams.gui.tools.wekainvestigator.evaluation: Helper class for dealing with datasets.
DatasetHelper() - Constructor for class adams.gui.tools.wekainvestigator.evaluation.DatasetHelper
datasetIndex - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute: The index of the source dataset.
DatasetIndexer() - Constructor for class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Initializes the indexer.
DatasetLabeler - Class in weka.filters.unsupervised.instance: Adds an additional attribute to the dataset containing a label whether it was a match or not, i.e., whether the row finder selected a particular row or not.
DatasetLabeler() - Constructor for class weka.filters.unsupervised.instance.DatasetLabeler
datasetNamesTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the tip-text for the dataset names option.
DatasetPanel - Class in adams.gui.tools.wekamultiexperimenter.setup: Panel for listing datasets.
DatasetPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel
DatasetPanel(String, String) - Constructor for class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Initializes the panel.
DATASETS - adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption
datasetsTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the tip text for this property.
datasetTipText() - Method in class adams.flow.transformer.WekaStoreInstance: Returns the tip text for this property.
datasetTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the tip text for this property.
DataSort - Class in adams.gui.visualization.instances.instancestable: Allows sorting the data using multiple columns.
DataSort() - Constructor for class adams.gui.visualization.instances.instancestable.DataSort
DataTab - Class in adams.gui.tools.wekainvestigator.tab: Lists the currently loaded datasets.
DataTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.DataTab
DataTable - Class in adams.gui.tools.wekainvestigator.datatable: Specialized table with custom cell editors for the class.
DataTable(DataTableModel) - Constructor for class adams.gui.tools.wekainvestigator.datatable.DataTable: Constructs a DataTable that is initialized with dm as the data model, a default column model, and a default selection model.
DataTableModel - Class in adams.gui.tools.wekainvestigator.datatable: Model for displaying the loaded data.
DataTableModel(List<DataContainer>, boolean) - Constructor for class adams.gui.tools.wekainvestigator.datatable.DataTableModel: Initializes the model.
dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Gets called when the user changes the selection.
dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: Gets called when the user changes the selection.
dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab: Gets called when the user changes the selection.
dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Gets called when the user changes the selection.
dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.DataTab: Gets called when the user changes the selection.
dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab: Gets called when the user changes the selection.
dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Gets called when the user changes the selection.
dataTableSelectionChanged() - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab: Gets called when the user changes the selection.
DataTableWithButtons - Class in adams.gui.tools.wekainvestigator.datatable: Specialized table with buttons.
DataTableWithButtons(DataTableModel) - Constructor for class adams.gui.tools.wekainvestigator.datatable.DataTableWithButtons: Constructs a DataTableWithButtons that is initialized with dm as the data model, a default column model, and a default selection model.
dataTypeTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the tip text for this property.
dataTypeTipText() - Method in class adams.flow.transformer.WekaInstancesStatistic: Returns the tip text for this property.
DATE_ATTRIBUTES - adams.flow.core.Capability: can handle date attributes.
DATE_CLASS - adams.flow.core.Capability: can handle date classes.
DEBUG - weka.classifiers.trees.XGBoost.Verbosity
DEBUG - Static variable in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin
debugMsg(String) - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin: Outputs a debugging message on stderr.
debugMsg(String) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Outputs a debugging message on stderr.
debugTipText() - Method in class weka.core.converters.SpreadSheetLoader: the tip text for this property
debugTipText() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin: Returns the tip text for this property.
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.WekaPackageManagerAction: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.source.WekaSelectDataset: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.standalone.WekaPackageManagerAction: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.template.InstanceDumperVariable: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.AbstractInstanceGenerator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.AbstractWekaModelReader: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaAccumulatedError: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaAttributeIterator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaAttributeSelection: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaBootstrapping: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaChooseAttributes: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaClassifierInfo: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaClassifierOptimizer: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaClassifierRanker: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaClassifying: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaClassSelector: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaclusterer.AddCluster: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaClustererInfo: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaClustererPostProcessor: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaDatasetsMerge: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaDatasetSplit: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaEnsembleGenerator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaEvaluationInfo: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaEvaluationSummary: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaEvaluationValues: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaExperiment: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaExperimentExecution: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaExperimentFileReader: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaExtractArray: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaExtractPLSMatrix: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaFileReader: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaFilter: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaGetInstancesValue: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaGetInstanceValue: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaInstanceBuffer: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaInstanceDumper: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaInstancesInfo: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaInstancesMerge: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaInstancesStatistic: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaModelReader: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaNewInstance: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaPackageManagerAction: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaPrincipalComponents: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaRandomSplit: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaRegexToRange: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaRenameRelation: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaSetInstancesValue: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaSetInstanceValue: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaSplitGenerator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaStoreInstance: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaStreamEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaStreamFilter: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaSubsets: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaTestSetEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaTextDirectoryReader: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaTrainAssociator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaTrainClassifier: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaTrainClusterer: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.InstanceCompare: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: Adds options to the internal list of options.
defineOptions() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: Adds options to the internal list of options.
defineOptions() - Method in class adams.ml.model.classification.WekaClassifier: Adds options to the internal list of options.
defineOptions() - Method in class adams.ml.model.clustering.WekaClusterer: Adds options to the internal list of options.
defineOptions() - Method in class adams.ml.model.regression.WekaRegressor: Adds options to the internal list of options.
defineOptions() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Adds options to the internal list of options.
defineOptions() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Adds options to the internal list of options.
defineOptions() - Method in class adams.opt.genetic.Hermione: Adds options to the internal list of options.
defineOptions() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Adds options to the internal list of options.
defineOptions() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Adds options to the internal list of options.
defineOptions() - Method in class adams.opt.optimise.GeneticAlgorithm: Adds options to the internal list of options.
defineOptions() - Method in class adams.tools.CompareDatasets: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.AbstractSplitGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.DefaultRandomSplitGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.functions.FromPredictions: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.functions.PyroProxy: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.MultiLevelSplitGenerator: Adds options to the internal list of options.
defineOptions() - Method in class weka.classifiers.trees.XGBoost: Adds options to the internal list of options.
defineOptions() - Method in class weka.filters.unsupervised.attribute.detrend.RangeBased: Adds options to the internal list of options.
defineOptions() - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased: Adds options to the internal list of options.
deflationModeTipText() - Method in class adams.data.instancesanalysis.pls.NIPALS: Returns the tip text for this property
delete() - Method in class weka.core.InstancesView: Removes all instances from the set.
delete(int) - Method in class weka.core.InstancesView: Removes an instance at the given position from the set.
deleteAttributeAt(int) - Method in class adams.gui.visualization.instances.InstancesTableModel: deletes the attribute at the given col index.
deleteAttributeAt(int) - Method in class weka.core.AbstractHashableInstance: Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in class weka.core.InstancesView: Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int, boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel: deletes the attribute at the given col index
deleteAttributes(int[]) - Method in class adams.gui.visualization.instances.InstancesTableModel: deletes the attributes at the given indices
deleteAttributeType(int) - Method in class weka.core.InstancesView: Deletes all attributes of the given type in the dataset.
deleteInstanceAt(int) - Method in class adams.gui.visualization.instances.InstancesTableModel: deletes the instance at the given index
deleteInstanceAt(int, boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel: deletes the instance at the given index
deleteInstances(int[]) - Method in class adams.gui.visualization.instances.InstancesTableModel: deletes the instances at the given positions
deleteWithMissing(int) - Method in class weka.core.InstancesView: Removes all instances with missing values for a particular attribute from the dataset.
DEPTHWISE - weka.classifiers.trees.XGBoost.GrowPolicy
derivativeOrderTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns the tip text for this property.
derivativeOrderTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Returns the tip text for this property.
DESCENDING - adams.data.conversion.WekaPredictionContainerToSpreadSheet.Sorting: descending.
deselectColinearAttributes(boolean[], double[]) - Method in class weka.classifiers.functions.LinearRegressionJ: Removes the attribute with the highest standardised coefficient greater than 1.5 from the selected attributes.
deserialize(InvestigatorPanel, Object, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper: Deserializes the data and configures the panel.
deserialize(ObjectInputStream) - Static method in class weka.gui.explorer.WorkspaceHelper: Deserializes an explorer instance from the input stream.
deserialize(Object, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Deserializes the data and configures the tab.
deserialize(Object, GenericObjectEditor) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Deserializes the data and configures the GenericObjectEditor with it.
deserialize(Object, ResultHistoryPanel) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Deserializes the data and configures the ResultHistoryPanel with it.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Restores the objects.
deserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Restores the objects.
deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Deserializes the data and configures the panel.
deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.AssociationsHandler: Deserializes the data and configures the panel.
deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.AttributeSelectionHandler: Deserializes the data and configures the panel.
deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.ClassifierHandler: Deserializes the data and configures the panel.
deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.ClustererHandler: Deserializes the data and configures the panel.
deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.DefaultHandler: Deserializes the data and configures the panel.
deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.ExperimentHandler: Deserializes the data and configures the panel.
deserialize(Explorer.ExplorerPanel, Object) - Method in class weka.gui.explorer.PreprocessHandler: Deserializes the data and configures the panel.
DESERIALIZED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent: the data got deserialized.
deserializeFile(MessageCollection) - Method in class adams.flow.core.WekaClassifierModelLoader: Deserializes the model file.
deserializeFile(MessageCollection) - Method in class adams.flow.core.WekaClustererModelLoader: Deserializes the model file.
destroy() - Method in class adams.data.instances.AbstractInstanceGenerator: Frees up memory in a "destructive" non-reversible way.
destroy() - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Frees up memory in a "destructive" non-reversible way.
DETECTOR - Static variable in class weka.filters.supervised.instance.RemoveOutliers
detectorTipText() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the tip text for this property.
determineAttributeName(Instances) - Method in class adams.flow.transformer.WekaInstanceEvaluator: Determines the name of the evaluation attribute.
determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.AbstractClassAttributeHeuristic: Determines the class attribute index for the given dataset.
determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.AttributeIndex: Determines the class attribute index for the given dataset.
determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.ByExactName: Determines the class attribute index for the given dataset.
determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.ByName: Determines the class attribute index for the given dataset.
determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.LastAttribute: Determines the class attribute index for the given dataset.
determineClassAttribute(Instances) - Method in class adams.data.weka.classattribute.NoClassAttribute: Determines the class attribute index for the given dataset.
determineColumnNames(BaseString[], String) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns a vector with column names of the dataset, listed in "list".
determineOutputFormat(Instances) - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class adams.data.instancesanalysis.pls.OPLS: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.FilteredFilter: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.FlowFilter: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.SerializedFilter: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.supervised.attribute.MultiPLS: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.supervised.attribute.PLS: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.supervised.attribute.PLSFilterExtended: Override original, in order to put more than one class attribute to the output format.
determineOutputFormat(Instances) - Method in class weka.filters.supervised.attribute.YGradientEPO: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.supervised.attribute.YGradientGLSW: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.supervised.instance.RemoveOutliers: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AndrewsCurves: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AnyToString: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.DatasetCleaner: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Detrend: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.DownSample: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.EquiDistance: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.FastWavelet: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.FFT: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.InputSmearing: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.LogTransform: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PAA: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Determines the output format based only on the full input dataset and returns this otherwise null is returned.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RowSum: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SAX: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SetMissingValue: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SpellChecker: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.StringToDate: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.AlignDataset: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.DatasetCleaner: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.KeepRange: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.KennardStone: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.LatestRecords: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RowNorm: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.Scale: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.Sort: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.SortOnAttribute: Determines the output format based on the input format and returns this.
determineOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Determines the output format based on the input format and returns this.
determineRelationName(File, Instances) - Method in class adams.data.weka.relationname.AbstractRelationNameHeuristic: Determines the relation name for the given file/dataset pair.
determineRelationName(File, Instances) - Method in class adams.data.weka.relationname.AttributeIndex: Determines the relation name for the given file/dataset pair.
determineRelationName(File, Instances) - Method in class adams.data.weka.relationname.ClassAttribute: Determines the relation name for the given file/dataset pair.
determineRelationName(File, Instances) - Method in class adams.data.weka.relationname.FileName: Determines the relation name for the given file/dataset pair.
determineRelationName(File, Instances) - Method in class adams.data.weka.relationname.NoChange: Determines the relation name for the given file/dataset pair.
determineUnusedIndices(Instances) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: determines the indices of unused attributes (ones that are not covered by any of the range).
Detrend - Class in weka.filters.unsupervised.attribute: Performs Detrend, using the specified correction scheme.
Detrend() - Constructor for class weka.filters.unsupervised.attribute.Detrend
devTipText() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Returns the tip text for this property.
Dialog(Dialog, Dialog.ModalityType) - Constructor for class adams.gui.visualization.instance.HistogramFactory.Dialog: Initializes the dialog.
Dialog(Frame, boolean) - Constructor for class adams.gui.visualization.instance.HistogramFactory.Dialog: Initializes the dialog.
diameterTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
Dice - Class in weka.classifiers.evaluation: Sørensen–Dice coefficient: https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient
Dice() - Constructor for class weka.classifiers.evaluation.Dice
difference(int, double, double) - Method in class weka.core.SAXDistance: Computes the difference between two given attribute values.
difference(int, double, double) - Method in class weka.core.WeightedEuclideanDistance: Computes the difference between two given attribute values.
difference(int, double, double) - Method in class weka.core.WeightedEuclideanDistanceRidge: Computes the difference between two given attribute values.
differTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Returns the tip text for this property.
differTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Returns the tip text for this property.
diffToString() - Method in class weka.classifiers.meta.AbstainAverage: Convert thresholds from array to string
diffToString() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Convert thresholds from array to string
diffToString() - Method in class weka.classifiers.meta.AbstainVote
DIPLS - Class in adams.data.instancesanalysis.pls
DIPLS() - Constructor for class adams.data.instancesanalysis.pls.DIPLS
disableButtons(Container) - Method in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog: Disables the buttons in the SimpleSetupPanel.
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.WekaPackageToMap: Performs the actual conversion.
doConvert() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Performs the actual conversion.
doConvertDataset(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Performs the dataset conversion.
doConvertDataset(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Performs the initialization.
doConvertDataset(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor: Performs the initialization.
doConvertDataset(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor: Performs the initialization.
doConvertInstance(PyroProxy, Instance) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Converts the instance into a different format.
doConvertInstance(PyroProxy, Instance) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Converts the instance into a different format.
doConvertInstance(PyroProxy, Instance) - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor: Converts the instance into a different format.
doConvertInstance(PyroProxy, Instance) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor: Converts the instance into a different format.
doCrossovers() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Performs cross-over.
doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.EncloseClassifier: Customizes the GOE popup menu.
doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.EncloseClusterer: Customizes the GOE popup menu.
doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.InvertInstancesColumnFinder: Customizes the GOE popup menu.
doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.InvertInstancesRowFinder: Customizes the GOE popup menu.
doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpClassifier: Customizes the GOE popup menu.
doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpClusterer: Customizes the GOE popup menu.
doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpInstancesColumnFinder: Customizes the GOE popup menu.
doCustomize(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpInstancesRowFinder: Customizes the GOE popup menu.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.LogTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Restores the objects.
doDeserialize(Map<String, Object>, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Restores the objects.
doDisplay() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel: Displays the results.
doDisplay() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel: Displays the results.
doDisplay() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel: Displays the results.
doEvaluate(Actor, Token) - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities: Performs the actual evaluation.
doEvaluate(Actor, Token) - Method in class adams.flow.condition.bool.AdamsInstanceCapabilities: Performs the actual evaluation.
doEvaluate(Actor, Token) - Method in class adams.flow.condition.bool.WekaCapabilities: Performs the actual evaluation.
doEvaluate(Actor, Token) - Method in class adams.flow.condition.bool.WekaClassification: Performs the actual evaluation.
doEvaluate(Associator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation: Evaluates the associator and updates the result item.
doEvaluate(Associator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: Evaluates the associator and updates the result item.
doEvaluate(ASEvaluation, ASSearch, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation: Performs attribute selections and updates the result item.
doEvaluate(ASEvaluation, ASSearch, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: Performs attribute selections and updates the result item.
doEvaluate(ASEvaluation, ASSearch, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: Performs attribute selections and updates the result item.
doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation: Evaluates the classifier and updates the result item.
doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Evaluates the classifier and updates the result item.
doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Evaluates the classifier and updates the result item.
doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Evaluates the classifier and updates the result item.
doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: Evaluates the classifier and updates the result item.
doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Evaluates the classifier and updates the result item.
doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Evaluates the classifier and updates the result item.
doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Evaluates the classifier and updates the result item.
doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Evaluates the classifier and updates the result item.
doEvaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Evaluates the classifier and updates the result item.
doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation: Evaluates the clusterer and updates the result item.
doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: Evaluates the clusterer and updates the result item.
doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Evaluates the clusterer and updates the result item.
doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: Evaluates the clusterer and updates the result item.
doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Evaluates the clusterer and updates the result item.
doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: Evaluates the clusterer and updates the result item.
doEvaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: Evaluates the clusterer and updates the result item.
doEvaluate(Instance) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Performs the actual evaluation.
doEvaluate(Instance) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Performs the actual evaluation.
doEvaluate(Instance) - Method in class adams.data.weka.evaluator.PassThrough: Performs no real evaluation, just returns 1.0.
doEvaluate(Instances, IndexedSplitsRuns, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Performs an evaluation by applying the indexed splits runs to the data.
doExecute() - Method in class adams.flow.sink.AbstractWekaModelWriter: Executes the flow item.
doExecute() - Method in class adams.flow.sink.WekaDatabaseWriter: Executes the flow item.
doExecute() - Method in class adams.flow.sink.WekaExperimentFileWriter: Executes the flow item.
doExecute() - Method in class adams.flow.sink.WekaExperimentGenerator: Executes the flow item.
doExecute() - Method in class adams.flow.sink.WekaFileWriter: Executes the flow item.
doExecute() - Method in class adams.flow.sink.WekaInstancesDisplay: Executes the flow item.
doExecute() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Executes the flow item.
doExecute() - Method in class adams.flow.source.WekaAssociatorSetup: Executes the flow item.
doExecute() - Method in class adams.flow.source.WekaClassifierSetup: Executes the flow item.
doExecute() - Method in class adams.flow.source.WekaClustererSetup: Executes the flow item.
doExecute() - Method in class adams.flow.source.WekaDatabaseReader: Executes the flow item.
doExecute() - Method in class adams.flow.source.WekaDataGenerator: Executes the flow item.
doExecute() - Method in class adams.flow.source.WekaNewExperiment: Executes the flow item.
doExecute() - Method in class adams.flow.source.WekaNewInstances: Executes the flow item.
doExecute() - Method in class adams.flow.source.WekaPackageManagerAction: Executes the flow item.
doExecute() - Method in class adams.flow.source.WekaSelectDataset: Executes the flow item.
doExecute() - Method in class adams.flow.standalone.WekaPackageManagerAction: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.AbstractInstanceGenerator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.AbstractWekaModelReader: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaAccumulatedError: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaAggregateEvaluations: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaAttributeIterator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaAttributeSelection: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaAttributeSelectionSummary: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaBootstrapping: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaChooseAttributes: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaClassifierInfo: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaClassifierOptimizer: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaClassifierRanker: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaClassSelector: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaClusterAssignments: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaClustererInfo: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaClustererPostProcessor: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaDatasetsMerge: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaDatasetSplit: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaEnsembleGenerator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaEvaluationInfo: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaEvaluationSummary: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaEvaluationValues: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaExperiment: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaExperimentExecution: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaExperimentFileReader: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaExtractArray: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaExtractPLSMatrix: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaFileReader: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaFilter: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaGetCapabilities: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaGetInstancesValue: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaGetInstanceValue: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaInstanceBuffer: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaInstanceDumper: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaInstancesAppend: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaInstancesInfo: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaInstancesMerge: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaInstancesStatistic: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaModelReader: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaNewInstance: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaPackageManagerAction: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaPredictionsToInstances: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaPredictionsToSpreadSheet: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaPrincipalComponents: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaRandomSplit: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaRegexToRange: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaRelationName: Deprecated.

Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaRenameRelation: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaSetInstancesValue: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaSetInstanceValue: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaSplitGenerator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaStoreInstance: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaStreamEvaluator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaStreamFilter: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaSubsets: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaTestSetEvaluator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaTextDirectoryReader: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaTrainAssociator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaTrainClassifier: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaTrainClusterer: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator: Executes the flow item.
doExecute() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator: Executes the flow item.
doExecute() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Runs the actual experiment.
doExecute(MessageCollection) - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction: Executes the action.
doExecute(MessageCollection) - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: Executes the action.
doExecute(MessageCollection) - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction: Executes the action.
doExecute(MessageCollection) - Method in class adams.flow.standalone.wekapackagemanageraction.RefreshCache: Executes the action.
doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction: Executes the action.
doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromFile: Executes the action.
doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromURL: Executes the action.
doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: Executes the action.
doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallPackage: Executes the action.
doExecute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall: Executes the action.
doExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup: Executes the experiment setup for the classifier and updates the result item.
doExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Executes the experiment setup for the classifier and updates the result item.
doExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Executes the experiment setup for the classifier and updates the result item.
doExport(Object, File) - Method in class adams.gui.visualization.debug.objectexport.WekaInstancesExporter: Performs the actual export.
doFilter(SpreadSheet) - Method in class adams.data.spreadsheet.filter.WekaFilter: Performs the actual filtering of the spreadsheet.
doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.AbstractColumnFinder: Returns the columns of interest in the dataset.
doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.AllFinder: Returns the columns of interest in the dataset.
doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.ByExactName: Returns the columns of interest in the dataset.
doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.ByName: Returns the columns of interest in the dataset.
doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.Class: Returns the columns of interest in the dataset.
doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.Constant: Returns the columns of interest in the dataset.
doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.Invert: Returns the columns of interest in the dataset.
doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.MultiColumnFinder: Returns the columns of interest in the dataset.
doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.NullFinder: Returns the columns of interest in the dataset.
doFindColumns(Instances) - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder: Returns the columns of interest in the dataset.
doFindRows(Instances) - Method in class adams.data.weka.rowfinder.AbstractRowFinder: Returns the rows of interest in the dataset.
doFindRows(Instances) - Method in class adams.data.weka.rowfinder.AllFinder: Returns the rows of interest in the dataset.
doFindRows(Instances) - Method in class adams.data.weka.rowfinder.ByLabel: Returns the rows of interest in the dataset.
doFindRows(Instances) - Method in class adams.data.weka.rowfinder.ByNumericRange: Returns the rows of interest in the spreadsheet.
doFindRows(Instances) - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns the rows of interest in the spreadsheet.
doFindRows(Instances) - Method in class adams.data.weka.rowfinder.Constant: Returns the rows of interest in the dataset.
doFindRows(Instances) - Method in class adams.data.weka.rowfinder.FilteredIQR: Returns the rows of interest in the dataset.
doFindRows(Instances) - Method in class adams.data.weka.rowfinder.Invert: Returns the rows of interest in the dataset.
doFindRows(Instances) - Method in class adams.data.weka.rowfinder.MultiRowFinder: Returns the rows of interest in the dataset.
doFindRows(Instances) - Method in class adams.data.weka.rowfinder.NullFinder: Returns the rows of interest in the dataset.
doGenerate() - Method in class adams.flow.template.InstanceDumperVariable: Generates the actor.
doGenerate(ChildFrame, Properties) - Method in class adams.gui.menu.MakeCompatibleDatasets: Performs the data generation.
doGenerate(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator: Generates the ensemble from the input.
doGenerate(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels: Generates the ensemble from the input.
doGenerate(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels: Generates the ensemble from the input.
doGenerate(Object, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Generates the indexed splits.
doGenerate(Object, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Generates the indexed splits.
doGenerate(Object, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Generates the indexed splits.
doGenerate(Object, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Generates the indexed splits.
doGenerate(Instances, IndexedSplitsRuns, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Generates predictions by applying the indexed splits runs to the data.
doGenerateHeader(HeaderDefinition) - Method in class adams.data.featureconverter.Weka: Performs the actual generation of a row from the raw data.
doGenerateOutput(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput: Generates the data.
doGenerateOutput(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Generates the data.
doGenerateOutput(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Generates the data.
doGenerateOutput(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Generates the data.
doGenerateRow(List<Object>) - Method in class adams.data.featureconverter.Weka: Performs the actual generation of a row from the raw data.
doInitialize() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner: Initializes the experiment.
doInitialize() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Initializes the experiment.
doInitialize() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractWekaExperimentRunner: Initializes the experiment.
doInitialize(AbstractApplicationFrame) - Method in class adams.gui.application.WekaPluginManagerExtensions: Performs the initialization.
doInitialize(AbstractApplicationFrame) - Method in class adams.gui.application.WekaSystemProperties: Performs the initialization.
doInitialize(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Performs the initialization.
doInitialize(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Performs the initialization.
doInitialize(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor: Performs the initialization.
doInitialize(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor: Performs the initialization.
doInitializeFilters() - Method in class adams.gui.chooser.AdamsExperimentFileChooser: Performs the actual initialization of the filters.
doInitializeFilters() - Method in class adams.gui.chooser.WekaFileChooser: Performs the actual initialization of the filters.
doInitializeIterator() - Method in class weka.classifiers.AbstractSplitGenerator: Initializes the iterator, randomizes the data if required.
doInitializeIterator() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Initializes the iterator.
doInitializeIterator() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Initializes the iterator, randomizes the data if required.
doInitializeIterator() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Initializes the iterator.
doInitializeIterator() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Initializes the iterator, randomizes the data if required.
doInitializeIterator() - Method in class weka.classifiers.DefaultRandomSplitGenerator: Initializes the iterator, randomizes the data if required.
doInitializeIterator() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Initializes the iterator, randomizes the data if required.
doInitializeIterator() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Initializes the iterator.
doInitializeIterator() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Initializes the iterator, randomizes the data if required.
doInitializeIterator() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Initializes the iterator, randomizes the data if required.
doInitializeIterator() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Initializes the iterator, randomizes the data if required.
doInitializeIterator() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Initializes the iterator, randomizes the data if required.
doInitializeIterator() - Method in class weka.classifiers.MultiLevelSplitGenerator: Initializes the iterator.
doInteract() - Method in class adams.flow.source.WekaSelectDataset: Performs the interaction with the user.
doInteract() - Method in class adams.flow.transformer.WekaChooseAttributes: Performs the interaction with the user.
doInteractHeadless() - Method in class adams.flow.source.WekaSelectDataset: Performs the interaction with the user in a headless environment.
doMerge(ChildFrame, File[], WekaMergeInstancesActor, File) - Method in class adams.gui.menu.MergeDatasets: Performs the merge.
doMutations() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Performs mutations.
doMutations2() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Performs mutations.
dontReplaceMissingValuesTipText() - Method in class weka.clusterers.SAXKMeans: Returns the tip text for this property.
doOptimize(ChildFrame, AbstractClassifierBasedGeneticAlgorithm, String[]) - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: Performs the optimization.
doPack(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the packed bits for the genetic algorithm.
doParsePrediction(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Parses the prediction.
doParsePrediction(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Parses the prediction.
doParsePrediction(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor: Parses the prediction.
doParsePrediction(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor: Parses the prediction.
doParsePredictions(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Parses the predictions.
doParsePredictions(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Parses the predictions.
doParsePredictions(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor: Parses the predictions.
doParsePredictions(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor: Parses the predictions.
doPerformPaint(Graphics, PaintEvent.PaintMoment) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: The paint routine of the paintlet.
doPerformPaint(Graphics, PaintEvent.PaintMoment) - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet: The paint routine of the paintlet.
doPlotColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotColumn: Plots the specified column.
doPlotRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotRow: Plots the specified row.
doPlotSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: Plots the specified rows.
doPostProcess(WekaEvaluationContainer) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor: Post-processes the evaluation container.
doPostProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor: Performs the actual post-processing.
doPostProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor: Performs the actual post-processing.
doPostProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient: Performs the actual post-processing.
doPostProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor: Performs the actual post-processing.
doPostProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.PassThrough: Simply returns the container, no post-processing done.
doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor: Post-processes the evaluation.
doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor: Post-processes the Evaluation.
doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.PassThrough: Post-processes the evaluation.
doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst: Post-processes the evaluation.
doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev: Post-processes the evaluation.
doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Post-processes the evaluation.
doPostProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange: Post-processes the evaluation.
doProcess(Classifier[]) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.AbstractClassifierSetupProcessor: Processes the classifier array.
doProcess(Classifier[]) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.PassThrough: Processes the classifier array.
doProcess(Classifier[]) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs: Processes the classifier array.
doProcessCell(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell: Processes the specified cell.
doProcessCell(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ViewCell: Processes the specified cell.
doProcessColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn: Processes the specified column.
doProcessColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AttributeStatistics: Processes the specified column.
doProcessColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight: Processes the specified column.
doProcessColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ColumnStatistic: Processes the specified column.
doProcessColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.DataSort: Processes the specified column.
doProcessRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow: Processes the specified row.
doProcessRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.RowStatistic: Processes the specified row.
doProcessRows(List<Instance>) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractSelectionProcessor: Returns the list of row indices generated from the data.
doProcessRows(List<Instance>) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.Average: Returns the list of row indices generated from the data.
doProcessRows(List<Instance>) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.PassThrough: Returns the list of row indices generated from the data.
doProcessSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: Processes the specified rows.
doProcessSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic: Processes the specified row.
doProcessSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights: Processes the specified rows.
doProcessSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset: Processes the specified rows.
doRead(PlaceholderFile) - Method in class adams.data.io.input.AbstractAdamsExperimentReader: Performs the actual reading of the experiment file.
doRead(PlaceholderFile) - Method in class adams.data.io.input.JsonAdamsExperimentReader: Performs the actual reading of the experiment file.
doRead(PlaceholderFile) - Method in class adams.data.io.input.NestedAdamsExperimentReader: Performs the actual reading of the experiment file.
doRead(PlaceholderFile) - Method in class adams.data.io.input.SerializedAdamsExperimentReader: Performs the actual reading of the experiment file.
doRead(File) - Method in class adams.data.io.input.AbstractWekaSpreadSheetReader: Performs the actual reading.
doRegister() - Method in class adams.gui.goe.WekaEditorsRegistration: Performs the registration of the editors.
doRegression(boolean[]) - Method in class weka.classifiers.functions.LinearRegressionJ: Calculate a linear regression using the selected attributes
doReload() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Reloads the data.
doReload() - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer: Reloads the data.
doReload() - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer: Reloads the data.
doReload() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer: Reloads the data.
doReload() - Method in class adams.gui.tools.wekainvestigator.data.MemoryContainer: Reloads the data.
doReload() - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer: Reloads the data.
doReload() - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer: Reloads the data.
doRender(Object, JPanel, Integer) - Method in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer: Performs the actual rendering.
doRenderCached(Object, JPanel, Integer) - Method in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer: Performs the actual rendering.
doRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob: Performs the actual execution.
doRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob: Performs the actual execution.
doRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabRunnableJob: Performs the actual execution.
doRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner: Performs the actual running of the experiment.
doRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Performs the actual running of the experiment.
doRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.DefaultWekaExperimentRunner: Performs the actual running of the experiment.
doRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.RemoteWekaExperimentRunner: Performs the actual running of the experiment.
doRun() - Method in class adams.tools.CompareDatasets: Performs the comparison.
doSelectRows(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.AbstractRowSelection: Returns the list of row indices generated from the data.
doSelectRows(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Returns the list of row indices generated from the data.
doSelectRows(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.IndividualRows: Returns the list of row indices generated from the data.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.LogTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Returns the objects for serialization.
doSerialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Returns the objects for serialization.
doTrain(SpreadSheet) - Method in class adams.data.spreadsheet.filter.WekaFilter: Performs the actual retraining on the spreadsheet.
doTrainColumnFinder(Instances) - Method in class adams.data.weka.columnfinder.AbstractFilteredColumnFinder: Performs the actual training of the column finder with the specified dataset.
doTrainColumnFinder(Instances) - Method in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder: Performs the actual training of the column finder with the specified dataset.
doTrainColumnFinder(Instances) - Method in class adams.data.weka.columnfinder.MultiColumnFinder: Performs the actual training of the column finder with the specified dataset.
doTrainColumnFinder(Instances) - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder: Performs the actual training of the column finder with the specified dataset.
doTrainRowFinder(Instances) - Method in class adams.data.weka.rowfinder.AbstractFilteredRowFinder: Performs the actual training of the row finder with the specified dataset.
doTrainRowFinder(Instances) - Method in class adams.data.weka.rowfinder.AbstractTrainableRowFinder: Performs the actual training of the row finder with the specified dataset.
doTrainRowFinder(Instances) - Method in class adams.data.weka.rowfinder.FilteredIQR: Performs the actual training of the row finder with the specified dataset.
doTrainRowFinder(Instances) - Method in class adams.data.weka.rowfinder.MultiRowFinder: Performs the actual training of the row finder with the specified dataset.
doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Transforms the data, initializes if necessary.
doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.DIPLS: Transforms the data, initializes if necessary.
doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.KernelPLS: Transforms the data, initializes if necessary.
doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.NIPALS: Transforms the data, initializes if necessary.
doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.OPLS: Transforms the data, initializes if necessary.
doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.PLS1: Transforms the data, initializes if necessary.
doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.PRM: Transforms the data, initializes if necessary.
doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.SIMPLS: Transforms the data, initializes if necessary.
doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.SparsePLS: Transforms the data, initializes if necessary.
doTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.VCPLS: Transforms the data, initializes if necessary.
doUnpack(PropertyPath.PropertyContainer, String) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Unpacks and applies the bits from the genetic algorithm.
DownSample - Class in weka.filters.unsupervised.attribute: A simple filter that retains only every nth attribute.
DownSample() - Constructor for class weka.filters.unsupervised.attribute.DownSample
doWrite(PlaceholderFile, AbstractExperiment) - Method in class adams.data.io.output.AbstractAdamsExperimentWriter: Performs the actual writing of the experiment file.
doWrite(PlaceholderFile, AbstractExperiment) - Method in class adams.data.io.output.JsonAdamsExperimentWriter: Performs the actual writing of the experiment file.
doWrite(PlaceholderFile, AbstractExperiment) - Method in class adams.data.io.output.NestedAdamsExperimentWriter: Performs the actual writing of the experiment file.
doWrite(PlaceholderFile, AbstractExperiment) - Method in class adams.data.io.output.SerializedAdamsExperimentWriter: Performs the actual writing of the experiment file.
doWrite(SpreadSheet, OutputStream) - Method in class adams.data.io.output.AbstractWekaSpreadSheetWriter: Performs the actual writing.
drawData(Graphics, Instance, Color) - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet: Draws the data with the given color.
drawData(Graphics, Instance, Color, InstanceLinePaintlet.MarkerShape) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Draws the data with the given color.
dropAboveTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Returns the tip text for this property.
dropAtMostTipText() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns the tip text for this property.
dropBelowTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Returns the tip text for this property.
dropBelowTipText() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns the tip text for this property.
dropNonClassYsTipText() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the tip text for this property

E

edit() - Method in class weka.gui.explorer.ExplorerExt: Performs an undo.
editOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Allows the user to modify the output generators.
editOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Allows the user to modify the output generators.
editOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Allows the user to modify the output generators.
editOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Allows the user to modify the output generators.
editOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Allows the user to modify the output generators.
EditWekaASEvaluator - Class in adams.gui.flow.tree.quickaction: Lets the user edit the Weka attribute selection evaluator.
EditWekaASEvaluator() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaASEvaluator
EditWekaASSearch - Class in adams.gui.flow.tree.quickaction: Lets the user edit the Weka attribute selection search.
EditWekaASSearch() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaASSearch
EditWekaClassifier - Class in adams.gui.flow.tree.quickaction: Lets the user edit the Weka classifier.
EditWekaClassifier() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaClassifier
EditWekaClusterer - Class in adams.gui.flow.tree.quickaction: Lets the user edit the Weka clusterer.
EditWekaClusterer() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaClusterer
EditWekaDataGenerator - Class in adams.gui.flow.tree.quickaction: Lets the user edit the Weka data generator.
EditWekaDataGenerator() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaDataGenerator
EditWekaFilter - Class in adams.gui.flow.tree.quickaction: Lets the user edit the Weka filter.
EditWekaFilter() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaFilter
EditWekaStreamableFilter - Class in adams.gui.flow.tree.quickaction: Lets the user edit the Weka filter.
EditWekaStreamableFilter() - Constructor for class adams.gui.flow.tree.quickaction.EditWekaStreamableFilter
ELAPSED_TIME_TESTING - adams.flow.core.ExperimentStatistic
ELAPSED_TIME_TRAINING - adams.flow.core.ExperimentStatistic
eliminateColinearAttributesTipText() - Method in class weka.classifiers.functions.LinearRegressionJ: Returns the tip text for this property
EMPTY_NOMINAL_ATTRIBUTES - adams.flow.core.Capability: can handle empty nominal attributes.
EMPTY_NOMINAL_CLASS - adams.flow.core.Capability: can handle empty nominal classes.
EncloseClassifier - Class in adams.gui.goe.popupmenu: For enclosing classifiers in SingleClassifierEnhancer wrappers.
EncloseClassifier() - Constructor for class adams.gui.goe.popupmenu.EncloseClassifier
EncloseClusterer - Class in adams.gui.goe.popupmenu: For enclosing clusterers in SingleClustererEnhancer wrappers.
EncloseClusterer() - Constructor for class adams.gui.goe.popupmenu.EncloseClusterer
encodingTipText() - Method in class adams.data.io.input.NestedAdamsExperimentReader: Returns the tip text for this property.
encodingTipText() - Method in class weka.core.converters.SimpleArffLoader: Returns the tip text for this property.
encodingTipText() - Method in class weka.core.converters.SimpleArffSaver: Returns the tip text for this property.
ensureEqualValuesTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the tip-text for the ensure-equal-values option.
enumerateAttributes() - Method in class weka.core.AbstractHashableInstance: Returns an enumeration of all the attributes.
enumerateInstances() - Method in class weka.core.InstancesView: Returns an enumeration of all instances in the dataset.
enumerateMeasures() - Method in class weka.classifiers.trees.m5.M5Base2: Returns an enumeration of the additional measure names
ENV_VAR - Static variable in class adams.core.management.WekaHomeEnvironmentModifier: the WEKA_HOME environment variable.
EPSILON - Static variable in class weka.classifiers.evaluation.MSLE
equal(Matrix, Matrix) - Static method in class weka.core.matrix.MatrixHelper: Compares the two matrices.
equal(Matrix, Matrix, double) - Static method in class weka.core.matrix.MatrixHelper: Compares the two matrices.
equalHeaders(Instance) - Method in class weka.core.AbstractHashableInstance: Tests if the headers of two instances are equivalent.
equalHeadersMsg(Instance) - Method in class weka.core.AbstractHashableInstance: Checks if the headers of two instances are equivalent.
equals(Object) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class adams.data.instances.AbstractInstanceGenerator: Returns whether the two objects are the same.
equals(Object) - Method in class adams.data.weka.columnfinder.AbstractColumnFinder: Returns whether the two objects are the same.
equals(Object) - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer: Returns whether the two objects are the same.
equals(Object) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Returns whether the two objects are the same.
equals(Object) - Method in class adams.data.weka.predictions.AbstractErrorScaler: Returns whether the two objects are the same.
equals(Object) - Method in class adams.data.weka.rowfinder.AbstractRowFinder: Returns whether the two objects are the same.
equals(Object) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Checks whether the specified object is the same.
equals(Object) - Method in class weka.core.AbstractHashableInstance: Returns only true if the same class and the same hashcode.
equalsHeader(SpreadSheet) - Method in class adams.ml.data.InstancesView: Compares the header of this spreadsheet with the other one.
EquiDistance - Class in weka.filters.unsupervised.attribute: A filter for interpolating the numeric attributes.Using the same number of points as are currently present in the input will have no effect.
EquiDistance() - Constructor for class weka.filters.unsupervised.attribute.EquiDistance
EquiDistance.AttributeSelection - Enum in weka.filters.unsupervised.attribute: Defines how the attributes are selected.
errorCalculationTipText() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the tip text for this property.
errorScalerTipText() - Method in class adams.flow.sink.WekaClassifierErrors: Returns the tip text for this property.
errorTipText() - Method in class weka.classifiers.meta.AbstainLeastMedianSq
errorTipText() - Method in class weka.classifiers.meta.LeastMedianSq
etaTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the eta option.
evaluate() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: Performs the evaluation.
evaluate() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment.CrossValidationExperimentJob: Performs the cross-validation.
evaluate() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment.TrainTestSplitExperimentJob: Performs the evaluation.
evaluate(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Creates a runnabel to evaluate the classifier on the dataset.
evaluate(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: Evaluates the classifier on the dataset.
evaluate(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: Evaluates the classifier on the dataset.
evaluate(OptData) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection
evaluate(Associator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation: Evaluates the associator and updates the result item.
evaluate(ASEvaluation, ASSearch, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation: Performs attribute selections and updates the result item.
evaluate(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation: Evaluates the classifier and updates the result item.
evaluate(Clusterer, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation: Evaluates the clusterer and updates the result item.
evaluate(Instance) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Evaluates the given instance.
evaluate(Instances, Instances) - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator: Performs an evaluation on the given train and test set.
evaluate(Instances, Instances) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Performs an evaluation on the given train and test set.
evaluateAttribute(int) - Method in class weka.attributeSelection.AbstractPLSAttributeEval: evaluates an individual attribute
evaluateAttribute(int) - Method in class weka.attributeSelection.LinearRegressionAttributeEval: evaluates an individual attribute
evaluateClassifier(Classifier, Instances, int, int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Evaluates the classifier on the dataset and returns the metric.
evaluateClassifier(Classifier, Instances, Instances) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Evaluates the classifier on the dataset and returns the metric.
evaluateExperiment(Instances) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Evaluates the experiment data.
EvaluateJob(Classifier, Instances, Instances, StoppableEvaluation, AbstractOutput) - Constructor for class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: Initializes the job.
EvaluateJob(StoppableEvaluation, Classifier, Instances, AbstractOutput) - Constructor for class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob: Initializes the job.
evaluateModel(Classifier, Instances, Object...) - Method in class weka.classifiers.evaluation.StoppableEvaluation: Evaluates the classifier on a given set of instances.
evaluateModel(Classifier, Instances, Evaluation, int, TestingHelper.TestingUpdateListener) - Static method in class weka.classifiers.TestingHelper: Evaluates the model on the test data and sends updates to the listener (if available).
evaluateModel(Classifier, Instances, Evaluation, int, TestingHelper.TestingUpdateListener, StoppableWithFeedback) - Static method in class weka.classifiers.TestingHelper: Evaluates the model on the test data and sends updates to the listener (if available).
EvaluationContainer(Instance) - Constructor for class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer: Initializes the container.
EvaluationHelper - Class in adams.flow.core: A helper class for Evaluation related things.
EvaluationHelper() - Constructor for class adams.flow.core.EvaluationHelper
evaluationPostProcessorTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
EvaluationStatistic - Enum in adams.flow.core: The enumeration for the comparison field.
evaluationToSpreadSheet(Evaluation) - Method in class weka.filters.supervised.instance.RemoveOutliers: Turns the predictions of the evaluation object into a spreadsheet.
evaluationTypeTipText() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the tip text for this property.
evaluatorTipText() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns the tip text for this property.
evaluatorTipText() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Returns the tip text for this property.
EXACT - weka.classifiers.trees.XGBoost.TreeMethod
exactMatchTipText() - Method in class adams.data.conversion.SwapPLS: Returns the tip text for this property.
EXCEPT_CLASS - adams.data.instancesanalysis.pls.PredictionType: predict all Ys except class attribute.
excludeAttributes(Instances) - Method in class adams.flow.transformer.WekaInstancesMerge: Excludes attributes from the data.
excludedAttributesTipText() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the tip text for this property.
execute() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Executes the experiment.
execute() - Method in class adams.multiprocess.WekaCrossValidationExecution: Executes the flow item.
execute(MessageCollection) - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction: Executes the action.
execute(MessageCollection) - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction: Executes the action.
execute(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction: Executes the action.
execute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup: Executes the experiment setup for the classifier and updates the result item.
executeQuery() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Applies the query to the dataset.
executionFinished() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Gets called when a job finishes.
executionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Gets called when a job finishes.
expand(Instances, boolean) - Method in class weka.core.InstanceGrouping: Expands the fake data into the original dataset space.
expand(Instances, TIntList) - Method in class weka.core.InstanceGrouping: Expands the fake data into the original dataset space.
expandCheck(Instances) - Method in class weka.core.InstanceGrouping: Ensures that the data to expand is in the right format.
Experimenter - Class in adams.gui.menu: Opens the WEKA Experimenter.
Experimenter() - Constructor for class adams.gui.menu.Experimenter: Initializes the menu item with no owner.
Experimenter(AbstractApplicationFrame) - Constructor for class adams.gui.menu.Experimenter: Initializes the menu item.
ExperimenterEntryPanel - Class in adams.gui.tools.wekamultiexperimenter: Allows the display of multiple Experimenter panels.
ExperimenterEntryPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.ExperimenterEntryPanel
ExperimenterPanel - Class in adams.gui.tools.wekamultiexperimenter: The Experimenter panel.
ExperimenterPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel
experimentFileTipText() - Method in class adams.flow.transformer.WekaExperiment: Returns the tip text for this property.
ExperimentHandler - Class in weka.gui.explorer: Manages the ExperimentPanel.
ExperimentHandler() - Constructor for class weka.gui.explorer.ExperimentHandler
ExperimentPanel - Class in weka.gui.explorer: This panel allows the user to select and configure a classifier, set the attribute of the current dataset to be used as the class, and perform an Experiment (like in the Experimenter) with this Classifier/Dataset combination.
ExperimentPanel() - Constructor for class weka.gui.explorer.ExperimentPanel: Creates the Experiment panel.
ExperimentStatistic - Enum in adams.flow.core: The enumeration for the comparison field.
ExperimentTab - Class in adams.gui.tools.wekainvestigator.tab: Tab for running experiment on selected dataset/classifier.
ExperimentTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.ExperimentTab
ExperimentTab.HistoryPanel - Class in adams.gui.tools.wekainvestigator.tab: Customized history panel.
experimentTipText() - Method in class adams.flow.source.WekaNewExperiment: Returns the tip text for this property.
experimentTypeTipText() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the tip text for this property.
ExperimentWithCustomizableRelationNames - Interface in adams.gui.tools.wekamultiexperimenter.experiment: Interface for experiments that allow customizing the relation names of the datasets.
Explorer - Class in adams.gui.menu: Opens the WEKA Explorer.
Explorer() - Constructor for class adams.gui.menu.Explorer: Initializes the menu item with no owner.
Explorer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.Explorer: Initializes the menu item.
ExplorerEntryPanel - Class in weka.gui.explorer: Allows the display of multiple Explorer panels.
ExplorerEntryPanel() - Constructor for class weka.gui.explorer.ExplorerEntryPanel
ExplorerExt - Class in weka.gui.explorer: An extended Explorer interface using menus instead of buttons, as well as remembering recent files.
ExplorerExt() - Constructor for class weka.gui.explorer.ExplorerExt: Default constructor.
export() - Method in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane: Exports the components using a AbstractMultiObjectExport scheme.
expressionTipText() - Method in class weka.classifiers.functions.MathExpressionClassifier: Returns the tip text for this property.
ExtExperiment - Class in weka.experiment: Extended version of the Weka Experiment class.
ExtExperiment() - Constructor for class weka.experiment.ExtExperiment: Default constructor.
ExtExperiment(Experiment) - Constructor for class weka.experiment.ExtExperiment: Assigns the values from the given experiment.
extract(Evaluation, boolean, int) - Method in enum adams.opt.genetic.Measure: Extracts the measure from the Evaluation object.
extractBinValue(BinnableGroup<Instance>) - Method in class adams.data.binning.BinnableInstances.GroupedClassValueBinValueExtractor: Extracts the numeric value to use for binning from the object.
extractBinValue(Instance) - Method in class adams.data.binning.BinnableInstances.ClassValueBinValueExtractor: Extracts the numeric value to use for binning from the object.
extractDatabaseID(String) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Extracts the database ID from a string in the comboxbox.
extractGroup(Binnable<Instance>) - Method in class adams.data.binning.BinnableInstances.NumericClassGroupExtractor: Extracts the group from the binnable object.
extractGroup(Binnable<Instance>) - Method in class adams.data.binning.BinnableInstances.StringAttributeGroupExtractor: Extracts the group from the binnable object.
extractLoadings(Instances, ArrayList<ArrayList<Double>>) - Method in class adams.data.instancesanalysis.PCA: Create a spreadsheet to output from the coefficients 2D array
extractPLSKey(String) - Method in class weka.filters.supervised.attribute.MultiPLS: Extracts key in the PLS map from the combined matrix name.

F

F_MEASURE - adams.flow.core.EvaluationStatistic
F_MEASURE - adams.flow.core.ExperimentStatistic
F_MEASURE - adams.opt.genetic.Measure: F measure.
FakeClassifier - Class in weka.classifiers.functions: Fake classifier that requires no dataset for training and just outputs random values within the specified bounds.
Fake build and prediction times can be set as well.
FakeClassifier() - Constructor for class weka.classifiers.functions.FakeClassifier
Fallback - Class in weka.classifiers.meta: In case the base classifier fails to make predictions, uses fallback one.
Fallback() - Constructor for class weka.classifiers.meta.Fallback
fallbackTipText() - Method in class weka.classifiers.meta.Fallback: Returns the tip text for this property.
FALLOUT - adams.flow.sink.WekaThresholdCurve.AttributeName
FALSE_NEG - adams.flow.sink.WekaThresholdCurve.AttributeName
FALSE_NEG_RATE - adams.opt.genetic.Measure: false negative rate.
FALSE_NEGATIVE_RATE - adams.flow.core.EvaluationStatistic
FALSE_NEGATIVE_RATE - adams.flow.core.ExperimentStatistic
FALSE_POS - adams.flow.sink.WekaThresholdCurve.AttributeName
FALSE_POS_RATE - adams.opt.genetic.Measure: false positive rate.
FALSE_POSITIVE_RATE - adams.flow.core.EvaluationStatistic
FALSE_POSITIVE_RATE - adams.flow.core.ExperimentStatistic
FARTHEST_FIRST - Static variable in class weka.clusterers.SAXKMeans
farthestFirstInit(Instances) - Method in class weka.clusterers.SAXKMeans: Initialize with the fartherst first centers
fastDistanceCalcTipText() - Method in class weka.clusterers.SAXKMeans: Returns the tip text for this property.
FastICA - Class in adams.data.instancesanalysis: Performs independent components analysis and allows access to components and sources.
FastICA() - Constructor for class adams.data.instancesanalysis.FastICA
FastWavelet - Class in weka.filters.unsupervised.attribute: A filter for wavelet transformation using the JSci library's fast wavelet transform (FWT) algorithms.

For more information see:

(2009).
FastWavelet() - Constructor for class weka.filters.unsupervised.attribute.FastWavelet: default constructor.
favorZeroesTipText() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns the tip text for this property.
featureSelectorTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the featureSelector option.
FFT - Class in weka.filters.unsupervised.attribute: A filter that transforms the data with Fast Fourier Transform.

Pads with zeroes.
For more information see:

Mark Hale (2009).
FFT() - Constructor for class weka.filters.unsupervised.attribute.FFT
fieldsTipText() - Method in class adams.data.conversion.ReportToWekaInstance: Returns the tip text for this property.
fieldsTipText() - Method in interface adams.data.instances.InstanceGeneratorWithFields: Returns the tip text for this property.
fileChooserTitleTipText() - Method in class adams.flow.source.WekaSelectDataset: Returns the tip text for this property.
FileContainer - Class in adams.gui.tools.wekainvestigator.data: File-based dataset.
FileContainer(AbstractFileLoader, PlaceholderFile) - Constructor for class adams.gui.tools.wekainvestigator.data.FileContainer: Loads the data using the specified loader.
FileContainer(AbstractFileLoader, File) - Constructor for class adams.gui.tools.wekainvestigator.data.FileContainer: Loads the data using the specified loader.
FileContainer(AbstractFileLoader, File, Instances) - Constructor for class adams.gui.tools.wekainvestigator.data.FileContainer: Uses the provided data, but also stores the reader/file for reloading it.
FileName - Class in adams.data.weka.relationname: Suggests the file name (without extension) as the relation name.
FileName() - Constructor for class adams.data.weka.relationname.FileName
FILENAME - Static variable in class adams.gui.application.WekaPluginManagerExtensions
FILENAME - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the name of the props file.
FILENAME - Static variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the name of the props file with the general properties.
FILENAME - Static variable in class adams.gui.visualization.instance.InstanceComparePanel: the name of the props file.
FILENAME - Static variable in class adams.gui.visualization.instance.InstanceExplorer: the name of the props file.
FILENAME_SHORTCUTS - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the name of the shortcut props file.
FileResultsHandler - Class in adams.gui.tools.wekamultiexperimenter.experiment: Writes the experiment results to a file.
FileResultsHandler() - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler
fillCovariance() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ
fillWithAttributeNames(SelectOptionPanel, int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation: Fills the panel for selection options with the attributes from the specified data container.
filter(Instance) - Method in class weka.classifiers.meta.FilteredClassifierExt: Filters the Instance through the remove filter if necessary.
filter(Instances) - Method in class weka.classifiers.meta.FilteredClassifierExt: Filters the dataset through the remove filter if necessary.
filter(Instances, List<Integer>) - Method in class adams.flow.transformer.WekaChooseAttributes: Filters the data.
filter(Filter, Instance) - Method in class weka.classifiers.meta.FilteredClassifierExt: Filters the Instance through the specified filter.
FILTER_NONE - Static variable in class weka.classifiers.functions.GaussianProcessesAdaptive: no filter
FILTER_NONE - Static variable in class weka.classifiers.functions.GaussianProcessesNoWeights: no filter
FILTER_NONE - Static variable in class weka.classifiers.functions.GaussianProcessesWeighted: no filter
FILTER_NONE - Static variable in class weka.classifiers.functions.GPD: no filter
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.GaussianProcessesAdaptive: normalizes the data
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.GaussianProcessesNoWeights: normalizes the data
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.GaussianProcessesWeighted: normalizes the data
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.GPD: normalizes the data
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.GaussianProcessesAdaptive: standardizes the data
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.GaussianProcessesNoWeights: standardizes the data
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.GaussianProcessesWeighted: standardizes the data
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.GPD: standardizes the data
FilteredClassifierExt - Class in weka.classifiers.meta: Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.
FilteredClassifierExt() - Constructor for class weka.classifiers.meta.FilteredClassifierExt
FilteredFilter - Class in weka.filters: First applies the pre-filter to the data and the generated data is fed into the main filter.
FilteredFilter() - Constructor for class weka.filters.FilteredFilter
FilteredIQR - Class in adams.data.weka.rowfinder: Returns indices of rows that got identified as outliers/extreme values.
FilteredIQR() - Constructor for class adams.data.weka.rowfinder.FilteredIQR
FilteredSearch - Class in weka.core.neighboursearch: Class implementing the brute force search algorithm for nearest neighbour search, filtered using PLS.
FilteredSearch() - Constructor for class weka.core.neighboursearch.FilteredSearch: Constructor.
FilteredSearch(Instances) - Constructor for class weka.core.neighboursearch.FilteredSearch: Constructor that uses the supplied set of instances.
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.ExperimentTab: Finishes up the initialization.
finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: finishes the initialization.
finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: finishes the initialization.
finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: finishes the initialization.
finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Finishes the initialization.
finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: Finalizes the initialization.
finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: Finalizes the initialization.
finishInit() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: finishes the initialization.
finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel: finishes the initialization.
finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel: finishes the initialization.
finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel: finishes the initialization.
finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: finishes the initialization.
finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: finishes the initialization.
finishInit() - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: Finalizes the initialization.
finishInit() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Finishes the initialization.
finishInit() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: finishes the initialization.
finishInit() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: finishes the initialization.
finishInit() - Method in class weka.gui.explorer.MultiExplorer: finishes the initialization.
fireDataChange() - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource: Notifies all the tabs that the data has changed.
fireDataChange(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Notifies all the tabs that the data has changed.
fireDataChange(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Notifies all the tabs that the data has changed.
fireDataChange(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Notifies all the tabs that the data has changed.
fireDataChange(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Notifies all the tabs that the data has changed.
fireDataChange(WekaInvestigatorDataEvent) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Notifies all the tabs that the data has changed.
fireSetupChanged() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Fires a ChangeEvent that the setup has changed.
firstAttributeRangeTipText() - Method in class adams.gui.InstanceCompare: Returns the tip text for this property.
firstAttributeTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Returns the tip text for this property.
firstDatasetTipText() - Method in class adams.gui.InstanceCompare: Returns the tip text for this property.
firstInstance() - Method in class weka.core.InstancesView: Returns the first instance in the set.
firstRangeTipText() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Returns the tip text for this property.
firstRowIndexTipText() - Method in class adams.gui.InstanceCompare: Returns the tip text for this property.
fitnessChanged(GeneticFitnessChangeEvent) - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Gets called when the fitness of the genetic algorithm changed.
fitnessChanged(GeneticFitnessChangeEvent) - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot: Adds the fitness measure to the plot.
FixedClassifierErrors - Class in weka.gui.visualize.plugins: Displays the classifier errors using Weka panels, but with a fixed size of the error plots.
FixedClassifierErrors() - Constructor for class weka.gui.visualize.plugins.FixedClassifierErrors
FixedClassifierErrorsPlot - Class in weka.gui.visualize.plugins: Displays the classifier errors using an ADAMS plot with fixed size crosses.
FixedClassifierErrorsPlot() - Constructor for class weka.gui.visualize.plugins.FixedClassifierErrorsPlot
FixedSizeErrorScaler - Class in adams.data.weka.predictions: Scales the errors to a fixed size.
FixedSizeErrorScaler() - Constructor for class adams.data.weka.predictions.FixedSizeErrorScaler
flowFileTipText() - Method in class weka.filters.FlowFilter: Returns the tip text for this property.
FlowFilter - Class in weka.filters: Processes the data with a flow.
FlowFilter() - Constructor for class weka.filters.FlowFilter
flowPauseStateChanged(FlowPauseStateEvent) - Method in class adams.flow.transformer.WekaClassifierRanker: Gets called when the pause state of the flow changes.
flowPauseStateChanged(FlowPauseStateEvent) - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Gets called when the pause state of the flow changes.
FMEASURE - adams.flow.sink.WekaThresholdCurve.AttributeName
foldsTipText() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator: Returns the tip text for this property.
foldsTipText() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the tip text for this property.
foldsTipText() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns the tip text for this property.
foldsTipText() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the tip text for this property.
foldsTipText() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Returns the tip text for this property.
foldsTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the tip text for this property.
foldsTipText() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the tip text for this property.
foldsTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the tip text for this property.
foldsTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: Returns the tip text for this property.
foldsTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
foldsTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the tip text for this property.
forceCompressionTipText() - Method in class weka.core.converters.SimpleArffLoader: Tip text suitable for displaying int the GUI
forCommandLine(String) - Static method in class adams.data.instances.AbstractInstanceGenerator: Instantiates the generator from the given commandline (i.e., classname and optional options).
forCommandLine(String) - Static method in class adams.data.weka.columnfinder.AbstractColumnFinder: Instantiates the column finder from the given commandline (i.e., classname and optional options).
forCommandLine(String) - Static method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Instantiates the evaluator from the given commandline (i.e., classname and optional options).
forCommandLine(String) - Static method in class adams.data.weka.predictions.AbstractErrorScaler: Instantiates the scaler from the given commandline (i.e., classname and optional options).
forCommandLine(String) - Static method in class adams.data.weka.rowfinder.AbstractRowFinder: Instantiates the row finder from the given commandline (i.e., classname and optional options).
forCommandLine(String) - Static method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Instantiates the genetic algorithm from the given commandline (i.e., classname and optional options).
FOREST - weka.classifiers.trees.XGBoost.NormaliseType
formatDate(double) - Method in class adams.flow.transformer.WekaInstancesInfo: Formats date stats.
formatOutput(Instances, Instances) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Handles merging of output datasets and formatting.
formatTipText() - Method in class weka.filters.unsupervised.attribute.StringToDate: Returns the tip text for this property.
forName(String, String[]) - Static method in class adams.data.instances.AbstractInstanceGenerator: Instantiates the generator with the given options.
forName(String, String[]) - Static method in class adams.data.weka.columnfinder.AbstractColumnFinder: Instantiates the column finder with the given options.
forName(String, String[]) - Static method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Instantiates the evaluator with the given options.
forName(String, String[]) - Static method in class adams.data.weka.predictions.AbstractErrorScaler: Instantiates the scaler with the given options.
forName(String, String[]) - Static method in class adams.data.weka.rowfinder.AbstractRowFinder: Instantiates the row finder with the given options.
forName(String, String[]) - Static method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Instantiates the genetic algorithm with the given options.
foundUsefulAttribute() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns true if a usable attribute was found.
FourInOnePlot - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Generates the 4-in-1 plot: normal plot, histogram, residuals vs fit and vs order.
FourInOnePlot() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot
FP_RATE - adams.flow.sink.WekaThresholdCurve.AttributeName
FROM_LABEL - weka.filters.unsupervised.attribute.NominalToNumeric.ConversionType
fromArray(String[], MessageCollection) - Method in class adams.core.option.WekaCommandLineHandler: Generates an object from the commandline options.
fromBits(int) - Method in class adams.opt.optimise.genetic.PackDataDef.DataInfo
fromBytes(byte[]) - Method in class weka.classifiers.meta.socketfacade.Simple: Turns the bytes back into a JSON object.
fromCommandLine(Class<T>, String) - Static method in class weka.core.WekaOptionUtils: Turns a commandline into an object.
fromCommandLine(String, MessageCollection) - Method in class adams.core.option.WekaCommandLineHandler: Generates an object from the specified commandline.
fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaAttributeIndexEditor: Returns an object created from the custom string representation.
fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaAttributeRangeEditor: Returns an object created from the custom string representation.
fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaExperimentFileEditor: Returns an object created from the custom string representation.
fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaLabelIndexEditor: Returns an object created from the custom string representation.
fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaLabelRangeEditor: Returns an object created from the custom string representation.
fromCustomStringRepresentation(String) - Method in class adams.gui.goe.WekaUnorderedAttributeRangeEditor: Returns an object created from the custom string representation.
FromPredictions - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation: Loads predictions from a spreadsheet for evaluation.
FromPredictions - Class in weka.classifiers.functions: Encapsulates predictions from a spreadsheet.
FromPredictions() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions
FromPredictions() - Constructor for class weka.classifiers.functions.FromPredictions
fromString(String) - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Not used.
fromString(String) - Method in class adams.gui.goe.WekaGenericObjectEditorPanel: Converts the string representation into its object representation.
FULL - adams.flow.transformer.WekaInstancesInfo.InfoType: full stats.
FULL_ATTRIBUTE - adams.flow.transformer.WekaInstancesInfo.InfoType: full attribute stats (nominal/numeric).
FULL_CLASS - adams.flow.transformer.WekaInstancesInfo.InfoType: full class attribute stats (nominal/numeric).
FusionJsonCommunicationProcessor - Class in adams.data.wekapyroproxy: Turns Instances/Instance into fusion JSON.
FusionJsonCommunicationProcessor() - Constructor for class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor

G

GAJob(GeneticAlgorithm, FitnessFunction, int[]) - Constructor for class adams.opt.optimise.GeneticAlgorithm.GAJob: Constructor.
GAMMA_REGRESSION - weka.classifiers.trees.XGBoost.Objective
gammaTipText() - Method in class weka.classifiers.functions.GPD: Returns the tip text for this property.
gammaTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the gamma option.
GaussianProcessesAdaptive - Class in weka.classifiers.functions: Implements Gaussian Processes for regression without hyperparameter-tuning.
GaussianProcessesAdaptive() - Constructor for class weka.classifiers.functions.GaussianProcessesAdaptive: the default constructor
GaussianProcessesNoWeights - Class in weka.classifiers.functions: * Implements Gaussian processes for regression without hyperparameter-tuning.
GaussianProcessesNoWeights() - Constructor for class weka.classifiers.functions.GaussianProcessesNoWeights
GaussianProcessesWeighted - Class in weka.classifiers.functions: Implements Gaussian Processes for regression without hyperparameter-tuning.
GaussianProcessesWeighted() - Constructor for class weka.classifiers.functions.GaussianProcessesWeighted: the default constructor
GBLINEAR - weka.classifiers.trees.XGBoost.BoosterType
GBTREE - weka.classifiers.trees.XGBoost.BoosterType
generate() - Method in class weka.gui.explorer.ExplorerExt: Pops up a dialog that allows the user to generate data.
generate(AbstractClassifierEvaluation, Instances, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.AbstractFinalModelGenerator: Builds the final model and stores it in the result item.
generate(AbstractClassifierEvaluation, Instances, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.Null: Builds the final model and stores it in the result item.
generate(AbstractClassifierEvaluation, Instances, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.Simple: Builds the final model and stores it in the result item.
generate(AbstractClassifierEvaluation, Instances, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds: Builds the final model and stores it in the result item.
generate(Class) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator: Generates and returns the help for the specified class.
generate(Object) - Method in class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator: Generates the ensemble from the input.
generate(Object) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator: Generates and returns the help for the specified object.
generate(T) - Method in class adams.data.instances.AbstractInstanceGenerator: Returns the generated data, generates it if necessary.
generateClassifier(int, int[]) - Method in class adams.opt.genetic.Hermione: Generate the classifier from current bit array
generateContainers() - Method in class weka.classifiers.MultiLevelSplitGenerator: Generates the containers.
generateDatasetList(List<DataContainer>) - Static method in class adams.gui.tools.wekainvestigator.evaluation.DatasetHelper: Generates the list of datasets for a combobox.
generateGroups(Instances, int, String, String) - Method in class weka.classifiers.MultiLevelSplitGenerator: Generates the groups from the data by applying the regexp/group.
generateHeader(T) - Method in class adams.data.instances.AbstractInstanceGenerator: Generates the header of the output data.
generateHeader(Instance) - Method in class adams.flow.transformer.WekaInstanceEvaluator: Generates the new header for the data.
generateLine(T, double[]) - Method in class adams.data.baseline.AbstractLinearRegressionBased: Generates fake data for the plotting the line.
generateLineTipText() - Method in class adams.data.baseline.AbstractLinearRegressionBased: Returns the tip text for this property.
generateNumPointsLabel(int) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Generates the string for the label displaying the number of points that are currently selected.
generateOutput(double, Instances, Classifier, int, int[]) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Generates the output requested output.
generateOutput(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput: Generates the data.
generateOutput(AbstractOutputGenerator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and then generates the output.
generateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Generates the output from the item.
generateOutput(AbstractOutputGenerator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and then generates the output.
generateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Generates the output from the item.
generateOutput(AbstractOutputGenerator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and then generates the output.
generateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Generates the output from the item.
generateOutput(AbstractOutputGenerator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and then generates the output.
generateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Generates the output from the item.
generateOutput(AbstractOutputGenerator, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Prompts the user with a GOE for configuring the output generator and then generates the output.
generateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Generates the output from the item.
generateOutput(T) - Method in class adams.data.instances.AbstractInstanceGenerator: Generates the actual data.
generateOutput(T) - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator: Generates output and adds it to the ResultItem.
generateOutput(Instances, List<Integer>) - Method in class adams.flow.transformer.WekaChooseAttributes: Creates the output token with the subset of data.
generateOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractSelectionProcessor: Returns the format for the output data.
generateOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.Average: Returns the format for the output data.
generateOutputFormat(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.PassThrough: Returns the format for the output data.
generateReducedData(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Generates the reduced data.
generateRulesTipText() - Method in class weka.classifiers.trees.m5.M5Base2: Returns the tip text for this property
generates() - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.AdamsInstanceToWekaInstance: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.MapToWekaInstance: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.ReportToWekaInstance: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.SpreadSheetToWekaInstances: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.WekaCapabilitiesToInstances: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.WekaCapabilitiesToSpreadSheet: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.WekaEvaluationToCostCurve: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.WekaEvaluationToMarginCurve: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.WekaInstanceToAdamsInstance: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.WekaInstanceToMap: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.WekaPackageToMap: Returns the class that is generated as output.
generates() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the class that is generated as output.
generates() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.source.WekaAssociatorSetup: Returns the class of objects that it generates.
generates() - Method in class adams.flow.source.WekaClassifierSetup: Returns the class of objects that it generates.
generates() - Method in class adams.flow.source.WekaClustererSetup: Returns the class of objects that it generates.
generates() - Method in class adams.flow.source.WekaDatabaseReader: Returns the class of objects that it generates.
generates() - Method in class adams.flow.source.WekaDataGenerator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.source.WekaNewExperiment: Returns the class of objects that it generates.
generates() - Method in class adams.flow.source.WekaNewInstances: Returns the class of objects that it generates.
generates() - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction: The types of data the action generates.
generates() - Method in class adams.flow.source.WekaPackageManagerAction: Returns the class of objects that it generates.
generates() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: The types of data the action generates.
generates() - Method in class adams.flow.transformer.AbstractInstanceGenerator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.AbstractWekaModelReader: Returns the class that the producer generates.
generates() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: The generated classes.
generates() - Method in class adams.flow.transformer.WekaAccumulatedError: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaAggregateEvaluations: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaAttributeSelectionSummary: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaChooseAttributes: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaClassifierInfo: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaClassifierOptimizer: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaClassifying: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaClassSelector: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaClusterAssignments: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaClustererInfo: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaClustererPostProcessor: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaClustering: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaDatasetsMerge: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaDatasetSplit: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.wekaensemblegenerator.AbstractWekaEnsembleGenerator: Returns the output data the generator generates.
generates() - Method in class adams.flow.transformer.WekaEnsembleGenerator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels: Returns the output data the generator generates.
generates() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels: Returns the output data the generator generates.
generates() - Method in class adams.flow.transformer.WekaEvaluationInfo: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaEvaluationValues: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaExperiment: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaExperimentExecution: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaExperimentFileReader: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaExtractArray: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaExtractPLSMatrix: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaFileReader: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaFilter: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaGetCapabilities: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaGetInstancesValue: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaGetInstanceValue: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaInstancesAppend: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaInstancesStatistic: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaNewInstance: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction: The types of data the action generates.
generates() - Method in class adams.flow.transformer.WekaPackageManagerAction: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromFile: The types of data the action generates.
generates() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromURL: The types of data the action generates.
generates() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: The types of data the action generates.
generates() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallPackage: The types of data the action generates.
generates() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall: The types of data the action generates.
generates() - Method in class adams.flow.transformer.WekaPredictionsToInstances: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaPredictionsToSpreadSheet: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaPrincipalComponents: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaRegexToRange: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaRelationName: Deprecated.

Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaRenameRelation: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput: Returns the class that it generates.
generates() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Returns the class that it generates.
generates() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Returns the class that it generates.
generates() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Returns the class that it generates.
generates() - Method in class adams.flow.transformer.WekaSetInstancesValue: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaSetInstanceValue: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaStoreInstance: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaStreamFilter: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaSubsets: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaTextDirectoryReader: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaTrainAssociator: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaTrainClassifier: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaTrainClusterer: Returns the class of objects that it generates.
generates() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator: Returns the class of objects that it generates.
generateSplits(Instances, int, String, String) - Method in class weka.classifiers.MultiLevelSplitGenerator: Generates the train/test splits.
generateSubset(Instances, Range) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: generates a subset of the dataset with only the attributes from the range (class is always added if present).
generatorTipText() - Method in class adams.flow.transformer.AbstractInstanceGenerator: Returns the tip text for this property.
generatorTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the tip text for this property.
generatorTipText() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the tip text for this property.
generatorTipText() - Method in class adams.flow.transformer.WekaEnsembleGenerator: Returns the tip text for this property.
generatorTipText() - Method in class adams.flow.transformer.WekaRandomSplit: Returns the tip text for this property.
generatorTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the tip text for this property.
generatorTipText() - Method in class adams.flow.transformer.WekaSplitGenerator: Returns the tip text for this property.
generatorTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: Returns the tip text for this property.
generatorTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: Returns the tip text for this property.
generatorTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
GenericDoubleResolution - Class in adams.core.discovery.genetic: Generic handler for double properties (using resolution).
GenericDoubleResolution() - Constructor for class adams.core.discovery.genetic.GenericDoubleResolution
GenericFloatResolution - Class in adams.core.discovery.genetic: Generic handler for float properties (using resolution).
GenericFloatResolution() - Constructor for class adams.core.discovery.genetic.GenericFloatResolution
GenericInteger - Class in adams.core.discovery.genetic: Generic handler for integer properties.
GenericInteger() - Constructor for class adams.core.discovery.genetic.GenericInteger
GenericPLSMatrixAccess - Interface in weka.core: For classes that allow access to PLS matrices.
GenericString - Class in adams.core.discovery.genetic: Generic handler for string properties.
GenericString() - Constructor for class adams.core.discovery.genetic.GenericString
GeneticAlgorithm - Class in adams.opt.optimise: Morticia (GEX).
GeneticAlgorithm - Class in weka.classifiers.functions: Applies the specified genetic algorithm to the training data and uses the best setup for the final model.
GeneticAlgorithm() - Constructor for class adams.opt.optimise.GeneticAlgorithm: The default constructor.
GeneticAlgorithm() - Constructor for class weka.classifiers.functions.GeneticAlgorithm
GeneticAlgorithm.GAJob - Class in adams.opt.optimise: Class for multithreading the ga.
genRegression(Random) - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Generates a LinearRegression classifier from the current m_SubSample.
genRegression(Random) - Method in class weka.classifiers.meta.LeastMedianSq: Generates a LinearRegression classifier from the current m_SubSample.
get(int) - Method in class weka.core.InstancesView: Returns the instance at the given position.
get(String) - Method in class adams.opt.optimise.genetic.PackData
get(String) - Method in class adams.opt.optimise.genetic.PackDataDef
get(String) - Method in class weka.core.InstanceGrouping: Returns the group.
getAbsErr() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Gets the threshold for the max error when predicting a numeric class.
getAbsErr() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Gets the threshold for the max error when predicting a numeric class.
getAbsolute() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: Returns whether the absolute values of coefficients are returned.
getAbsoluteDifference() - Method in class adams.flow.transformer.WekaAccumulatedError.SortablePrediction: Returns the absolute difference between actual and predicted value.
getAbstentionClassification(Instance) - Method in interface weka.classifiers.AbstainingClassifier: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.lazy.AbstainingLWL: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainAttributePercentile: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainAverage: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainLeastMedianSq: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainMinimumProbability: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.AbstainVote: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.Consensus: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.ConsensusOrVote: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.FilteredClassifierExt: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.MinMaxLimits: The prediction that made the classifier abstain.
getAbstentionClassification(Instance) - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper: The prediction that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in interface weka.classifiers.AbstainingClassifier: The class distribution that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in class weka.classifiers.lazy.AbstainingLWL: The class distribution that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainAttributePercentile: The class distribution that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainAverage
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: The class distribution that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainLeastMedianSq: The class distribution that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainMinimumProbability: The class distribution that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.AbstainVote: The class distribution that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.Consensus: The class distribution that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.ConsensusOrVote: The class distribution that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.FilteredClassifierExt: The class distribution that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.MinMaxLimits: The class distribution that made the classifier abstain.
getAbstentionDistribution(Instance) - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper: The class distribution that made the classifier abstain.
getAcceptListener() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the listener for the event that the user accepts the input.
getAction() - Method in class adams.flow.source.WekaPackageManagerAction: Returns the action in use.
getAction() - Method in class adams.flow.standalone.WekaPackageManagerAction: Returns the action in use.
getAction() - Method in class adams.flow.transformer.WekaPackageManagerAction: Returns the action in use.
getActionMethod(String) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Returns the method associated with the specified action.
getActions() - Static method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Returns the available actions.
getActions() - Static method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Returns the available actions.
getActions() - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Returns the available actions to list.
getActor() - Method in class adams.gui.menu.PlotAttributeVsAttribute: Used to create an instance of a specific actor.
getActual() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the column with the actual values.
getActual() - Method in class weka.classifiers.functions.FromPredictions: Returns the column with the actual values.
getActualClass() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the class that is being handled.
getActualClass() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the class that is being handled.
getActualClass() - Method in class adams.core.discovery.genetic.GenericInteger: Returns the class that is being handled.
getActualClass() - Method in class adams.core.discovery.genetic.GenericString: Returns the class that is being handled.
getActualComponentAt(int) - Method in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane: Returns the actual component at the position.
getActualFilter() - Method in class weka.filters.SerializedFilter: Returns the actual filter in use, loads it if necessary.
getActualFolds() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the actual number of folds used.
getActualIndex() - Method in class weka.classifiers.functions.FromPredictions: Returns the actual 0-based index.
getActualIndex(int) - Method in class weka.classifiers.meta.SubsetEnsemble: Returns the actual index in the data of the feature attribute.
getActualMax() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the upper limit in use for the actual values.
getActualMin() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the lower limit in use for the actual values.
getActualNumFolds() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns the actual number of folds used (eg when using LOO).
getActualNumFolds() - Method in interface weka.classifiers.CrossValidationFoldGenerator: Returns the actual number of folds used (eg when using LOO).
getActualNumFolds() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns the actual number of folds used (eg when using LOO).
getActualNumFolds() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the actual number of folds used (eg when using LOO).
getActualNumFolds() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the actual number of folds used (eg when using LOO).
getActualNumFolds() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns the actual number of folds used (eg when using LOO).
getActualParentComponent() - Method in class adams.flow.source.WekaSelectDataset: Returns the parent component to use.
getAddAttributeInformation() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: Returns whether to add attribute information to the metadata.
getAddClassification() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns whether to add the numeric classification (label index for nominal classes).
getAddClassificationLabel() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns whether to add the classification label (only for nominal classes).
getAddDatabaseID() - Method in class adams.data.instances.AbstractInstanceGenerator: Returns whether the database ID is added.
getAddDatasetInformation() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: Returns whether to add dataset information to the metadata.
getAddDistribution() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns whether to add the class distribution (only for nominal classes).
getAddIndex() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns whether to add the dataset index number to the prefix.
getAdditional() - Method in class weka.classifiers.functions.FromPredictions: Returns the additional columns to add to the plot containers.
getAdditionalAcceptedClasses() - Method in class adams.flow.sink.AbstractWekaModelWriter: Returns additional classes that are accepted as input.
getAdditionalAcceptedClasses() - Method in class adams.flow.sink.WekaModelWriter: Returns additional classes that are accepted as input (WEKA classifiers and clusterers).
getAdditionalAttributeIndices(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Returns the additional attribute indices.
getAdditionalAttributeIndices(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Returns the additional attribute indices.
getAdditionalAttributeIndices(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Returns the additional attribute indices.
getAdditionalAttributes() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns the stored additional attributes data.
getAdditionalAttributes() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the attributes indices of the original dataset to include in the reports.
getAdditionalErrorInformation() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Returns additional information to be added to the error message.
getAdditionalFieldName(AbstractField) - Static method in class adams.data.weka.ArffUtils: Returns the name of an attribute for an additional field.
getAdditionalFields() - Method in interface adams.data.instances.InstanceGeneratorWithAdditionalFields: Returns the additional fields to add.
getAdditionalIndices() - Method in class weka.classifiers.functions.FromPredictions: Returns the 0-based indices of the additional columns.
getAdditionalInformation() - Method in class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor: Returns the additional information.
getAddLabelIndex() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns whether to show the error as well.
getAddLabelIndex() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Returns whether to show the error as well.
getAddOne() - Method in class weka.filters.unsupervised.attribute.LogTransform: Returns whether to add '1' to the values before log-transform.
getAdjustToVisibleData() - Method in class adams.gui.visualization.instance.InstancePanel: Returns whether the display is adjusted to only the visible spectrums or all of them.
getAlgorithm() - Method in class adams.data.instancesanalysis.PLS: Returns the algorithm to use.
getAlgorithm() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns the genetic algorithm to apply to the dataset.
getAlgorithm() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns the binning algorithm.
getAlgorithm() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Returns the binning algorithm.
getAlgorithm() - Method in class weka.classifiers.functions.GeneticAlgorithm: Returns the seed value for the random values.
getAlgorithm() - Method in class weka.classifiers.functions.PLSWeighted: Get the PLS algorithm.
getAlgorithm() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the binning algorithm.
getAlgorithm() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns the binning algorithm.
getAlgorithm() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the PLS algorithm to use.
getAlgorithm() - Method in class weka.filters.supervised.attribute.PLS: Returns the PLS algorithm to use.
getAlgorithm() - Method in class weka.filters.unsupervised.attribute.FastWavelet: Gets the type of algorithm to use.
getAlgorithms() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Returns the binning algorithms to choose from.
getAll(Instances) - Static method in class weka.core.matrix.MatrixHelper: returns the data as matrix
getAllDatabaseIDs(int) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Returns all database IDs.
getAllVisible() - Method in class adams.gui.visualization.instance.InstanceContainerManager: Returns (a copy of) all currently stored containers.
getAlpha() - Method in class weka.classifiers.trees.XGBoost: Gets the L1 regularisation term on weights.
getAlpha() - Method in class weka.filters.supervised.attribute.YGradientEPO: Returns the alpha parameter.
getAlpha() - Method in class weka.filters.supervised.attribute.YGradientGLSW: Returns the alpha parameter.
getAlwaysShowMarkers() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Returns whether marker shapes are always drawn.
getAlwaysUseContainer() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Returns whether to always use an evaluation container as output.
getAmount() - Method in class weka.filters.unsupervised.instance.LatestRecords: Returns the amount of records to keep.
getAnalysisName() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel: Returns the name to display in the GUI.
getAnalysisName() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Returns the name to display in the GUI.
getAnalysisPanel() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Returns the analysis panel.
getAscending() - Method in class adams.data.instances.InstanceComparator: Returns whether a column is sorted in ascending or descending order.
getAssignments() - Method in class weka.clusterers.SAXKMeans: Gets the assignments for each instance.
getAssociator() - Method in class adams.flow.source.WekaAssociatorSetup: Returns the associator in use.
getAssociator() - Method in class adams.flow.transformer.WekaTrainAssociator: Returns the name of the callable associator in use.
getAssociatorInstance() - Method in class adams.flow.transformer.WekaTrainAssociator: Returns an instance of the callable associator.
getAttRange() - Method in class weka.filters.unsupervised.instance.KennardStone: Returns the attribute range to use for distance calculation (after applying pre-filter).
getAttRegExp() - Method in class weka.filters.unsupervised.attribute.Detrend: Returns the regular expression used for identifying the attributes to process.
getAttRegExp() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Returns the regular expression used for identifying the attributes to process.
getAttribute() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: Returns the currently set index.
getAttribute() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Returns the attribute being displayed.
getAttribute() - Method in class weka.classifiers.meta.AbstainAttributePercentile
getAttribute(int) - Method in class adams.gui.visualization.instance.InstanceTableModel: Returns the attribute for the given column.
getAttributeAt(int) - Method in class adams.gui.visualization.instances.InstancesTableModel: returns the attribute at the given index, can be NULL if not an attribute column
getAttributeColumn(String) - Method in class adams.gui.visualization.instances.InstancesTableModel: returns the column of the given attribute name, -1 if not found
getAttributeIndex() - Method in class adams.data.weka.rowfinder.ByLabel: Returns the index of the attribute to perform the matching on.
getAttributeIndex() - Method in class adams.data.weka.rowfinder.ByNumericRange: Returns the index of the column to perform the matching on.
getAttributeIndex() - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns the index of the column to perform the matching on.
getAttributeIndex() - Method in class adams.flow.transformer.WekaInstancesInfo: Returns the attribute index to use for attribute specific information.
getAttributeIndex() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Returns the index of the attribute to use for indexing.
getAttributeIndex() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns the index of the attribute used in the regression.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.SpellChecker: Returns the 1-based index of the attribute to process.
getAttributeIndex() - Method in class weka.filters.unsupervised.instance.SortOnAttribute: Returns the 1-based index of the attribute to sort on.
getAttributeIndex(String) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Returns the attribute index for the specified attribute name.
getAttributeName() - Method in class adams.flow.transformer.WekaGetInstanceValue: Returns the name of the attribute to get the value for.
getAttributeName() - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Get the name of the attribute to be created.
getAttributeName() - Method in class weka.filters.unsupervised.instance.LatestRecords: Returns the name of the attribute containing the numeric database ID.
getAttributeNames() - Method in class adams.flow.source.WekaNewInstances: Returns the list of attribute names.
getAttributeNames() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Gets the names of the attributes.
getAttributePrefix() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Returns the prefix to use for the generated attributes.
getAttributeRange() - Method in class adams.data.instancesanalysis.FastICA: Returns the attribute range parameter.
getAttributeRange() - Method in class adams.data.instancesanalysis.PCA: Returns the attribute range parameter.
getAttributeRange() - Method in class adams.data.instancesanalysis.PLS: Returns the attribute range parameter.
getAttributeRange() - Method in class adams.data.weka.rowfinder.FilteredIQR: Returns the attribute range to work on.
getAttributeRange() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Returns the current range of attributes.
getAttributeRange() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: Returns the range of attributes to compute the matrix for.
getAttributeRange() - Method in class weka.filters.unsupervised.attribute.InputSmearing: Returns the 1-based range of the attributes to work on.
getAttributeRange() - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Returns the 1-based range of the attributes to combine.
getAttributeRange() - Method in class weka.filters.unsupervised.attribute.LogTransform: Returns the range of attributes to process.
getAttributeRange() - Method in class weka.filters.unsupervised.attribute.SetMissingValue: Returns the range of attributes to compute the matrix for.
getAttributeRange() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Returns the range of attributes to detrend.
getAttributeRenamesExp() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the array of attribute rename expressions.
getAttributeRenamesFormat() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the array of format strings used for attribute renaming.
getAttributes() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Returns the range of attributes to create plot containers for.
getAttributeSelection() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Returns the stored AttributeSelection object.
getAttributeSelection() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns how the attributes get selected.
getAttributeSelectionMethod() - Method in class weka.classifiers.functions.LinearRegressionJ: Gets the method used to select attributes for use in the linear regression.
getAttributeSelectionPanel() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Returns the attribute selection panel.
getAttributeStats(Instances, int) - Method in class adams.flow.transformer.WekaInstancesInfo: Generates attributes statistics.
getAttributeTypes() - Method in class adams.flow.source.WekaNewInstances: Returns the list of attribute types.
getAttributeX() - Method in class adams.flow.sink.WekaInstancesPlot: Returns the attribute to show on the X axis.
getAttributeX() - Method in class adams.flow.sink.WekaThresholdCurve: Returns the attribute to show on the X axis.
getAttributeX() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Returns the attribute to show on the X axis.
getAttributeY() - Method in class adams.flow.sink.WekaInstancesPlot: Returns the attribute to show on the Y axis.
getAttributeY() - Method in class adams.flow.sink.WekaThresholdCurve: Returns the attribute to show on the Y axis.
getAttributeY() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Returns the attribute to show on the Y axis.
getAutoKeyGeneration() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns whether a primary key is automatically generated.
getAverageWidth() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval: Returns the average width of the stored intervals.
getAxisX() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the setup for the X axis.
getAxisY() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the setup for the Y axis.
getBase() - Method in class adams.data.instancesanalysis.pls.OPLS: Sets the base PLS algorithm to use.
getBase() - Method in class weka.classifiers.meta.Fallback: Returns the base classifier.
getBaseScore() - Method in class weka.classifiers.trees.XGBoost: Gets the initial prediction score of all instances (global bias).
getBatchSize() - Method in class weka.classifiers.functions.PyroProxy: Get the batch size to use.
getBestClassifier() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Returns the best classifier found.
getBestClassifier(Classifier, Classifier) - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: In case of GridSearch/MultiSearch the best setup is returned, otherwise the classifier itself.
getBestRange() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns the best range of attributes.
getbHat() - Method in class weka.filters.supervised.attribute.PLSFilterExtended
getBias() - Method in class weka.classifiers.meta.VotedImbalance: Gets the bias towards a uniform class.
getBinCalculation() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns how the number of bins is calculated.
getBins() - Method in class weka.core.SAXDistance: Returns the nth point setting.
getBins() - Method in class weka.filters.unsupervised.attribute.SAX: Returns the nth point setting.
getBinWidth() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the bin width in use (for some calculations).
getBits() - Method in class adams.opt.optimise.genetic.PackData
getBits() - Method in class adams.opt.optimise.GeneticAlgorithm: Gets the number of bits.
getBits(String) - Method in class adams.opt.optimise.genetic.PackData
getBitsForPosition(int[], List<Integer>, List<Integer>, int) - Method in class adams.opt.genetic.Hermione: get bit array for parameter at pos.
getBitsPerGene() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the currently set number of bits per gene.
getBitstring() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
getBooster() - Method in class weka.classifiers.trees.XGBoost: Gets the type of booster to use.
getBorder() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns the thickness of the border.
getBorderTitle() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Returns the title of the border.
getBufferSize() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns the number of instances to buffer before writing them to disk.
getBuildRegressionTree() - Method in class weka.classifiers.trees.m5.M5Base2: Get the value of regressionTree.
getBuildWait() - Method in class weka.classifiers.functions.FakeClassifier: Returns the time in msec to wait when calling buildClassifier.
getC() - Method in class adams.data.instancesanalysis.pls.PRM: Returns the tuning parameter.
getCallableActor() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns the currently set callable actor.
getCallableName() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns the name of the callable sink in use.
getCancelListener() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the listener for the event that the user discarded the input.
getCanChangeClassInDialog(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler: Returns whether the class can be changed in the dialog.
getCanChangeClassInDialog(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorPopupMenu: Returns whether the class can be changed in the editor.
getCanopyMaxNumCanopiesToHoldInMemory() - Method in class weka.clusterers.SAXKMeans: Get the maximum number of candidate canopies to retain in memory during training.
getCanopyMinimumCanopyDensity() - Method in class weka.clusterers.SAXKMeans: Get the minimum T2-based density below which a canopy will be pruned during periodic pruning.
getCanopyPeriodicPruningRate() - Method in class weka.clusterers.SAXKMeans: Get the how often to prune low density canopies during training (if using canopy clustering)
getCanopyT1() - Method in class weka.clusterers.SAXKMeans: Get the t1 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs
getCanopyT2() - Method in class weka.clusterers.SAXKMeans: Get the t2 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs
getCapabilities() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns the Capabilities of this filter.
getCapabilities() - Method in class adams.data.weka.columnfinder.AbstractColumnFinderWithCapabilities: Returns the capabilities of this object.
getCapabilities() - Method in class adams.data.weka.predictions.AbstractErrorScaler: Returns the capabilities of this object.
getCapabilities() - Method in class adams.data.weka.predictions.AutoScaler: Returns the capabilities of this object.
getCapabilities() - Method in class adams.data.weka.predictions.FixedSizeErrorScaler: Returns the capabilities of this object.
getCapabilities() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference: Returns the capabilities of this object.
getCapabilities() - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler: Returns the capabilities of this object.
getCapabilities() - Method in class adams.data.weka.predictions.RoundErrorScaler: Returns the capabilities of this object.
getCapabilities() - Method in class adams.data.weka.rowfinder.AbstractRowFinderWithCapabilities: Returns the capabilities of this object.
getCapabilities() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities: Returns the capabilities.
getCapabilities() - Method in class adams.ml.model.classification.WekaClassifier: Returns the algorithm's capabilities in terms of data.
getCapabilities() - Method in class adams.ml.model.clustering.WekaClusterer: Returns the algorithm's capabilities in terms of data.
getCapabilities() - Method in class adams.ml.model.regression.WekaRegressor: Returns the algorithm's capabilities in terms of data.
getCapabilities() - Method in class weka.attributeSelection.LinearRegressionAttributeEval: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns the Capabilities of this classifier.
getCapabilities() - Method in class weka.classifiers.functions.FakeClassifier: Returns the Capabilities of this classifier.
getCapabilities() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.GeneticAlgorithm: Returns the Capabilities of this classifier.
getCapabilities() - Method in class weka.classifiers.functions.GPD: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.LinearRegressionJ: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.MathExpressionClassifier: Returns the Capabilities of this classifier.
getCapabilities() - Method in class weka.classifiers.functions.PLSClassifierWeighted: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.PLSWeighted: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.PyroProxy: Returns the Capabilities of this classifier.
getCapabilities() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.AbstainAttributePercentile: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.meta.AbstainAverage: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.meta.AbstainMinimumProbability: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.meta.AbstainVote: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.ClassificationViaRegressionD: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.ClassifierCascade: Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.
getCapabilities() - Method in class weka.classifiers.meta.ConsensusOrVote: Returns the ensemble's capabilities.
getCapabilities() - Method in class weka.classifiers.meta.Fallback: Returns the Capabilities of this classifier.
getCapabilities() - Method in class weka.classifiers.meta.FilteredClassifierExt: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.HighLowSplit: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.meta.LeastMedianSq: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.meta.MinMaxLimits: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.meta.PartitionedStacking: Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.
getCapabilities() - Method in class weka.classifiers.meta.SocketFacade: Returns the Capabilities of this classifier.
getCapabilities() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Returns the ensemble's capabilities.
getCapabilities() - Method in class weka.classifiers.meta.Veto: Returns the ensemble's capabilities.
getCapabilities() - Method in class weka.classifiers.meta.VotedImbalance: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.simple.AbstractSimpleClassifier: Returns the Capabilities of this classifier.
getCapabilities() - Method in class weka.classifiers.trees.m5.M5Base2: Returns default capabilities of the classifier, i.e., of LinearRegression.
getCapabilities() - Method in class weka.classifiers.trees.RandomModelTrees: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.trees.RandomRegressionForest: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.trees.XGBoost: Returns the Capabilities of this classifier.
getCapabilities() - Method in class weka.clusterers.SAXKMeans: Returns default capabilities of the clusterer.
getCapabilities() - Method in class weka.core.converters.SimpleArffSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.SpreadSheetSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.filters.FilteredFilter: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.FlowFilter: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.SerializedFilter: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.attribute.PLS: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.attribute.YGradientEPO: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.attribute.YGradientGLSW: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the ensemble's capabilities.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.AnyToString: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Detrend
getCapabilities() - Method in class weka.filters.unsupervised.attribute.DownSample: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.FastWavelet: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.FFT: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.InputSmearing: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.LogTransform: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection
getCapabilities() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric
getCapabilities() - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.PAA: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.RowSum: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.SAX: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.SetMissingValue: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend
getCapabilities() - Method in class weka.filters.unsupervised.attribute.SpellChecker: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.StringToDate: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.AlignDataset: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.KeepRange: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.KennardStone: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.LatestRecords: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RowNorm: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.Scale: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.Sort: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.SortOnAttribute: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns the Capabilities of this filter.
getCapabilities(Instances) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Returns the Capabilities of this filter, customized based on the data.
getCaseIndex(Actor, Token) - Method in class adams.flow.condition.bool.WekaClassification: Returns the index of the case that should get executed.
getCategory() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.AbstractWekaMenuItemDefinition: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.AppendDatasets: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.ArffViewer: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.BatchFilterDatasets: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.BoundaryVisualizer: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.CostCurve: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.DatasetCompatibility: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.GraphVisualizer: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.InstanceCompare: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.InstanceExplorer: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.InstancesPlot: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.MakeCompatibleDatasets: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.MarginCurve: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.MergeDatasets: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.PackageManager: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.PlotAttributeVsAttribute: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.ROC: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.SqlViewer: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.TreeVisualizer: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.WekaCommandToCode: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.menu.WekaInvestigator: Returns the category of the menu item in which it should appear, i.e., the name of the menu.
getCategory() - Method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem: The category for grouping menu items.
getCategory() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.CompareModels: The category for grouping menu items.
getCategory() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation: The category for grouping menu items.
getCategory() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem: The category for grouping menu items.
getCategory() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.CopySetup: The category for grouping menu items.
getCategory() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation: The category for grouping menu items.
getCell(int) - Method in class adams.ml.data.InstancesHeaderRow: Returns the cell with the given index, null if not found.
getCell(int) - Method in class adams.ml.data.InstanceView: Returns the cell with the given index, null if not found.
getCell(int, int) - Method in class adams.ml.data.InstancesView: Returns the corresponding cell or null if not found.
getCell(String) - Method in class adams.ml.data.InstancesHeaderRow: Returns the cell with the given key, null if not found.
getCell(String) - Method in class adams.ml.data.InstanceView: Returns the cell with the given key, null if not found.
getCellCount() - Method in class adams.ml.data.InstancesHeaderRow: Returns the number of cells stored in the row.
getCellCount() - Method in class adams.ml.data.InstanceView: Returns the number of cells stored in the row.
getCellEditor(int, int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTable: Returns the cell editor for the specified cell.
getCellIndex(String) - Method in class adams.ml.data.InstancesView: Returns the cell index of the specified cell (in the header row).
getCellKey(int) - Method in class adams.ml.data.InstancesHeaderRow: Returns the cell key with the given column index.
getCellKey(int) - Method in class adams.ml.data.InstanceView: Returns the cell key with the given column index.
getCellPadding() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns the cell padding for the table.
getCellPopupMenuCustomizer() - Method in class adams.gui.visualization.instances.InstancesTable: Returns the current popup menu customizer (for the cells).
getCellPosition(String, String) - Method in class adams.ml.data.InstancesView: Returns the position of the cell or null if not found.
getCellRenderer(int, int) - Method in class adams.gui.visualization.instances.InstancesTable: Returns the renderer for this cell.
getCellRenderingCustomizer() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Returns the cell rendering customizer.
getCellSpacing() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns the cell spacing for the table.
getCellValues(int) - Method in class adams.ml.data.InstancesView: Returns the unique string values of the specified column.
getCellValues(String) - Method in class adams.ml.data.InstancesView: Returns the unique string values of the specified column.
getCenterData() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Get whether to center (rather than standardize) the data.
getCharSet() - Method in class adams.flow.transformer.WekaTextDirectoryReader: Returns the character set in use.
getCheckBoxBatchFilter() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Returns the batch filter checkbox.
getCheckBoxKeepName() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Returns the keep name checkbox.
getCheckBoxReplace() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Returns the replace checkbox.
getCheckHeader() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns whether the header gets checked or not.
getCheckHeader() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns whether the header gets checked or not.
getClassAttribute() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the heuristic for determining the class attribute (if not explicitly set).
getClassAttributeHeuristic() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns the current class attribute heuristic.
getClassAttributeIndices() - Method in class adams.ml.data.InstancesView: Returns all the class attributes that are currently set.
getClassAttributeKeys() - Method in class adams.ml.data.InstancesView: Returns all the class attributes that are currently set.
getClassAttributeNames() - Method in class adams.ml.data.InstancesView: Returns all the class attributes that are currently set.
getClassAttributes() - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: Returns the regular expression for identifying the class attributes (besides an explicitly set one).
getClassCrossReferences() - Method in class adams.flow.transformer.WekaClustererPostProcessor: Returns the cross-referenced classes.
getClassCrossReferences() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the cross-referenced classes.
getClassCrossReferences() - Method in class adams.flow.transformer.WekaPredictionsToSpreadSheet: Returns the cross-referenced classes.
getClassCrossReferences() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the cross-referenced classes.
getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaASEvaluator: Returns the description of the class used in errors/undo points.
getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaASSearch: Returns the description of the class used in errors/undo points.
getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaClassifier: Returns the description of the class used in errors/undo points.
getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaClusterer: Returns the description of the class used in errors/undo points.
getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaDataGenerator: Returns the description of the class used in errors/undo points.
getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaFilter: Returns the description of the class used in errors/undo points.
getClassDescription() - Method in class adams.gui.flow.tree.quickaction.EditWekaStreamableFilter: Returns the description of the class used in errors/undo points.
getClassDetails() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns whether the class details are output as well.
getClassDetails() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Returns whether the class details are output as well.
getClassDistribution() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the columns with the class distribution (nominal class).
getClassDistribution() - Method in class weka.classifiers.functions.FromPredictions: Returns the class distribution columns.
getClassDistributionIndices() - Method in class weka.classifiers.functions.FromPredictions: Returns the 0-based indices of the class distribution columns.
getClassFinder() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the finder to use for finding class attributes in the source datasets.
getClassificationEntry() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the value for the 'Name' column for the numeric classification.
getClassificationLabelEntry() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the value for the 'Name' column for the classification label.
getClassifier() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Returns the classifier.
getClassifier() - Method in class adams.flow.source.WekaClassifierSetup: Returns the classifier in use.
getClassifier() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator: Returns the name of the callable classifier in use.
getClassifier() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns the name of the callable classifier in use.
getClassifier() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Returns the name of the callable classifier in use.
getClassifier() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Returns the classifier being used.
getClassifier() - Method in class adams.flow.transformer.WekaTrainClassifier: Returns the name of the callable classifier in use.
getClassifier() - Method in class adams.ml.model.classification.WekaClassifier: Returns the classifier to use.
getClassifier() - Method in class adams.ml.model.regression.WekaRegressor: Returns the classifier to use.
getClassifier() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the classifier in use.
getClassifier() - Method in class adams.multiprocess.WekaCrossValidationJob: Returns the classifier (should be built after the job finished).
getClassifier() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the currently set classifier.
getClassifier() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the currently set classifier.
getClassifier() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the classifier.
getClassifier() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Gets the classifier used by the filter.
getClassifier() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Gets the classifier used by the filter.
getClassifier(int) - Method in class weka.classifiers.meta.ClassificationViaRegressionD: Returns the classifier for the specified label index (0-based).
getClassifier(int) - Method in class weka.classifiers.meta.LeanMultiScheme: Gets a single classifier from the set of available classifiers.
getClassifierInstance() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator: Returns an instance of the callable classifier.
getClassifierInstance() - Method in class adams.flow.transformer.WekaStreamEvaluator: Returns an instance of the callable classifier.
getClassifierInstance() - Method in class adams.flow.transformer.WekaTrainClassifier: Returns an instance of the callable classifier.
getClassifierInstance(MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns an instance of the callable classifier.
getClassifierInstance(MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Returns an instance of the callable classifier.
getClassifiers() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the classifiers.
getClassifiers() - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: Returns the current classifiers.
getClassifiers() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the classifiers per fold.
getClassifierSpec() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Gets the classifier specification string, which contains the class name of the classifier and any options to the classifier.
getClassifierSpec() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Gets the classifier specification string, which contains the class name of the classifier and any options to the classifier.
getClassifierWeights() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
getClassifyTab() - Method in class weka.gui.explorer.ExplorerExt: Returns the classify tab, if available.
getClassIndex() - Method in class adams.flow.sink.WekaCostBenefitAnalysis: Returns the current index of class label (1-based).
getClassIndex() - Method in class adams.flow.source.WekaNewInstances: Returns the index of the class attribute.
getClassIndex() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the current index of class label (1-based).
getClassIndex() - Method in class adams.flow.transformer.WekaClassSelector: Returns the class index.
getClassIndex() - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Returns the current class label index (1-based).
getClassIndex() - Method in class adams.flow.transformer.WekaEvaluationValues: Returns the current range of class label indices (1-based).
getClassIndex() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Returns the current index of class label (1-based).
getClassIndex() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis: Returns the current index of class label (1-based).
getClassIndex() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Returns the current index of class label (1-based).
getClassIndex() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the current class index.
getClassIndex() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the current class index.
getClassIndex() - Method in class weka.classifiers.meta.ClassifierCascade: the class index.
getClassIndex() - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive
getClassIndex() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Gets the attribute on which misclassifications are based.
getClassIndex() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Gets the attribute on which misclassifications are based.
getClassLabel() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the class label index to use for class-specific measures.
getClassLabelIndex() - Method in class adams.data.conversion.WekaEvaluationToCostCurve: Returns the class label index (1-based index).
getClassLabelIndex() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve: Returns the class label index (1-based index).
getClassLabelIndex() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the index of the class label to use when generating per-class statistics.
getClassLabelIndex() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the index of the class label to use for statistics that work on a per-label-basis.
getClassLabelRange() - Method in class adams.flow.sink.WekaCostCurve: Returns the class label indices.
getClassLabelRange() - Method in class adams.flow.sink.WekaThresholdCurve: Returns the class label indices.
getClassLabelRange() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve: Returns the class label indices.
getClassLabelRange() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Returns the class label indices.
getClassLabels() - Method in class weka.classifiers.AggregateEvaluations: Returns the currently set class labels, if any.
getClassname() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the classname to be the handler for.
getClassname() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the classname to be the handler for.
getClassname() - Method in class adams.core.discovery.genetic.GenericInteger: Returns the classname to be the handler for.
getClassname() - Method in class adams.core.discovery.genetic.GenericString: Returns the classname to be the handler for.
getClassname() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode: Returns the classanme to use.
getClassName() - Method in class adams.flow.source.WekaNewInstances: Returns the name of the class attribute.
getClassName() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the name of the attribute to use as the class attribute for supervised summary filters.
getClassNoise() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Get the value of noise for the class.
getClassPathAugmentation() - Method in class adams.core.management.WekaPackagesClassPathAugmenter: Returns the classpath parts (jars, directories) to add to the classpath.
getClassType() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel: Returns the class type.
getClassType(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler: Returns the class type currently in use.
getClassWeightedAverageStatistic(String) - Method in class weka.classifiers.evaluation.Dice: Get the weighted (by class) average for this statistic.
getCleaner() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Returns the cleaner to use for cleaning the tokens from the initial tokenization.
getCleaners() - Method in class weka.core.tokenizers.cleaners.MultiCleaner: Returns the cleaners to use.
getClearBuffer() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns whether to clear the buffer once the dataset has been forwarded.
getClone() - Method in class adams.data.weka.WekaAttributeIndex: Returns a clone of the object.
getClone() - Method in class adams.data.weka.WekaAttributeRange: Returns a clone of the object.
getClone() - Method in class adams.data.weka.WekaLabelIndex: Returns a clone of the object.
getClone() - Method in class adams.data.weka.WekaLabelRange: Returns a clone of the object.
getClone() - Method in class adams.data.weka.WekaUnorderedAttributeRange: Returns a clone of the object.
getClone() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel: Returns a clone of the object.
getClone() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel: Returns a clone of the object.
getClone() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Returns a clone of the object.
getClone() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel: Returns a clone of the object.
getClone() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel: Returns a clone of the object.
getClone() - Method in class adams.ml.data.InstancesView: Returns a clone of itself.
getClone(SpreadSheet) - Method in class adams.ml.data.InstancesHeaderRow: Returns a clone of itself.
getClone(SpreadSheet) - Method in class adams.ml.data.InstanceView: Returns a clone of itself.
getClusterCentroids() - Method in class weka.clusterers.SAXKMeans: Gets the cluster centroids.
getClusterer() - Method in class adams.flow.source.WekaClustererSetup: Returns the clusterer in use.
getClusterer() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator: Returns the name of the callable clusterer in use.
getClusterer() - Method in class adams.flow.transformer.WekaTrainClusterer: Returns the clusterer in use.
getClusterer() - Method in class adams.ml.model.clustering.WekaClusterer: Returns the clusterer to use.
getClustererInstance() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator: Returns an instance of the callable clusterer.
getClustererInstance() - Method in class adams.flow.transformer.WekaTrainClusterer: Returns an instance of the callable clusterer.
getClusterNominalCounts() - Method in class weka.clusterers.SAXKMeans: Returns for each cluster the frequency counts for the values of each nominal attribute.
getClusterSizes() - Method in class weka.clusterers.SAXKMeans: Gets the number of instances in each cluster.
getClusterStandardDevs() - Method in class weka.clusterers.SAXKMeans: Gets the standard deviations of the numeric attributes in each cluster.
getClusterTab() - Method in class weka.gui.explorer.ExplorerExt: Returns the cluster tab, if available.
getCoefficients() - Method in class weka.filters.unsupervised.attribute.PublicPrincipalComponents: Get the components from the principal components model
getCoeffs() - Method in class weka.classifiers.meta.Corr
getColName() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: Returns the spreadsheet column with the name.
getColName() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall: Returns the spreadsheet column with the name.
getColor() - Method in class adams.gui.visualization.instance.InstanceContainer: Returns the current color in use.
getColor(int) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Returns the color for the data with the given index.
getColor(int) - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet: Returns the color for the data with the given index.
getColor(int) - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet: Returns the color for the data with the given index.
getColor(InstanceContainer) - Method in class adams.gui.visualization.instance.InstanceContainerManager: Returns the color for the container.
getColorBox() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Returns the class selection combo box if the parent component wants to place it in itself or in some component other than this component.
getColorField() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet: Returns the report field that contains the color.
getColoringIndex() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Get the coloring (class) index for the plot
getColorList() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Returns the list of colors to use.
getColorProvider() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the color provider in use.
getColorProvider() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Returns the color provider for the plots.
getColorProvider() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Returns the color provider to use.
getColorProvider() - Method in class adams.gui.visualization.instance.InstanceContainerManager: Returns the color provider to use.
getColumn() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the list of fields that identify a column.
getColumn() - Method in class adams.flow.transformer.WekaGetInstancesValue: Returns the column.
getColumn() - Method in class adams.flow.transformer.WekaSetInstancesValue: Returns the column index.
getColumn() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the list of fields that identify a column.
getColumn() - Method in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer: Returns the column index.
getColumnClass(int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: Returns the class type for the column.
getColumnClass(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel: Gets the class of elements in a column.
getColumnClass(int) - Method in class adams.gui.visualization.instance.InstanceTableModel: Returns the class for the column.
getColumnClass(int) - Method in class adams.gui.visualization.instances.InstancesTableModel: returns the most specific superclass for all the cell values in the column (always String)
getColumnCount() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: The number of columns.
getColumnCount() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel: Gets the number of columns: 3
getColumnCount() - Method in class adams.gui.visualization.instance.InstanceTableModel: Returns the number of columns in the table.
getColumnCount() - Method in class adams.gui.visualization.instances.InstancesTableModel: returns the number of columns in the model
getColumnCount() - Method in class adams.ml.data.InstancesView: Returns the number of columns.
getColumnFinder() - Method in class adams.data.weka.columnfinder.AbstractFilteredColumnFinder: Returns the column finder in use.
getColumnFinder() - Method in class adams.data.weka.datasetsplitter.ColumnSplitter: Gets the column finder.
getColumnFinder() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Returns the column finder used by the filter.
getColumnFinder() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the column finder which selects the attributes for summarisation.
getColumnFinders() - Static method in class adams.data.weka.columnfinder.AbstractColumnFinder: Returns a list with classnames of column finders.
getColumnName() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: Returns the selected column name.
getColumnName(int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: Returns the column name.
getColumnName(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel: Gets the name for a column.
getColumnName(int) - Method in class adams.gui.visualization.instance.InstanceTableModel: Returns the name of the column.
getColumnName(int) - Method in class adams.gui.visualization.instances.InstancesTableModel: returns the name of the column at columnIndex
getColumnName(int) - Method in class adams.ml.data.InstancesView: Returns the name of the specified column.
getColumnNames() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Returns the column names in use.
getColumnNames() - Method in class adams.ml.data.InstancesView: Returns a list of the names of all columns (i.e., the content the header row cells).
getColumns() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the size.
getColumns() - Method in class adams.data.weka.columnfinder.Constant: Gets the constant set of columns to find.
getColumns() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
getColumnSampleByLevel() - Method in class weka.classifiers.trees.XGBoost: Gets the sub-sample ratio of columns for each level.
getColumnSampleByNode() - Method in class weka.classifiers.trees.XGBoost: Gets the sub-sample ratio of columns for each node (split).
getColumnSampleByTree() - Method in class weka.classifiers.trees.XGBoost: Gets the sub-sample ratio of columns when constructing each tree.
getColVersion() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: Returns the (optional) spreadsheet column with the version.
getCombination() - Method in class adams.data.weka.columnfinder.MultiColumnFinder: Returns how the indices are combined.
getCombination() - Method in class adams.data.weka.rowfinder.MultiRowFinder: Returns how the indices are combined.
getCombination() - Method in class weka.classifiers.meta.ClassifierCascade: how to combine the statistics.
getCombinationRule() - Method in class weka.classifiers.meta.AbstainVote: Gets the combination rule used
getCombinationRule() - Method in class weka.classifiers.meta.SubsetEnsemble: Gets the combination rule used
getCombinationRule() - Method in class weka.classifiers.meta.VotedImbalance: Gets the combination rule used
getComment() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary: Returns the comment to output in the summary.
getComment() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the comment to output in the summary.
getComments() - Method in class adams.ml.data.InstancesView: Returns the comments.
getCommunication() - Method in class weka.classifiers.functions.PyroProxy: Returns the model proxy to use for communication.
getCommunication() - Method in interface weka.core.PyroProxyObject: Returns the handler for the communication.
getComparator() - Method in class adams.data.instance.Instance: Returns the comparator in use.
getComparator() - Static method in class adams.data.instance.InstanceUtils: Returns the comparator used for finding X values.
getComparator() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the comparator to use.
getComparator() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Returns a comparator for sorting the Instances.
getComparator() - Method in class weka.classifiers.AggregateEvaluations: Returns the comparator to use.
getComparators(int) - Method in class weka.classifiers.trees.RandomModelTrees
getComparisonField() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the comparison field.
getComparisonField() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the comparison field.
getCompleteRowsOnly() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Gets whether incomplete rows should be skipped.
getComplexityStatistics() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns whether the complexity stats are output as well.
getComplexityStatistics() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Returns whether the complexity stats are output as well.
getComponent() - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel: Returns the embedded component.
getComponent() - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel: Returns the embedded component.
getComponent() - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel: Returns the embedded component.
getComponentRange() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Returns the range of components to be used.
getComponents() - Method in class adams.data.instancesanalysis.FastICA: Returns the components.
getConfidenceLevel() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Returns the confidence level.
getConfusionMatrix() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns whether to output the confusion matrix as well.
getConfusionMatrix() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Returns whether to output the confusion matrix as well.
getContainer() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob: Returns the generated model container.
getContainer() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob: Returns the generated model container.
getContainerKeys() - Method in class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor: Returns the keys that the processor adds/modifies.
getContainerKeys() - Method in class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor: Returns the keys that the processor adds/modifies.
getContainerKeys() - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient: Returns the keys that the processor adds/modifies.
getContainerKeys() - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor: Returns the keys that the processor adds/modifies.
getContainerKeys() - Method in class adams.flow.transformer.wekaclusterer.PassThrough: Returns the keys that the processor adds/modifies.
getContainerManager() - Method in class adams.gui.visualization.instance.InstanceExplorer: Returns the current container manager.
getContainerPaintlet() - Method in class adams.gui.visualization.instance.InstancePanel: Returns the paintlet used for painting the containers.
getContainerPanel() - Method in class adams.gui.visualization.instance.InstanceZoomOverviewPaintlet: Returns the panel to obtain plot and containers from.
getContent() - Method in class adams.ml.data.DataCellView: Returns the content of the cell.
getContent(int) - Method in class adams.ml.data.InstancesHeaderRow: Returns the cell content with the given index.
getContent(int) - Method in class adams.ml.data.InstanceView: Returns the cell content with the given index.
getContentType() - Method in class adams.ml.data.DataCellView: Returns the content type.
getContentType(int) - Method in class adams.ml.data.InstancesView: Returns the pure content type of the given column, if available.
getContentTypes(int) - Method in class adams.ml.data.InstancesView: Returns the all content types of the given column, if available.
getConversion() - Method in class adams.core.base.AttributeTypeList: Returns the conversion of the string before setting its value.
getConversion() - Method in class weka.core.converters.SpreadSheetLoader: Returns the conversion in use for converting the spreadsheet into an Instances object.
getConverter() - Method in class adams.data.conversion.WekaCommandToCode: Returns the converter to use.
getCorrect() - Method in class weka.filters.unsupervised.attribute.SpellChecker: Returns the correct label.
getCorrection() - Method in class weka.filters.unsupervised.attribute.Detrend: Returns the correction scheme to apply.
getCorrection() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Returns the correction scheme to apply.
getCorrection() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Returns the correction scheme to apply.
getCorrelation(Instance, Instance) - Method in class adams.tools.CompareDatasets: Returns the correlation between the two rows.
getCorrespondingReader() - Method in class adams.data.io.output.AbstractAdamsExperimentWriter: Returns, if available, the corresponding reader.
getCorrespondingReader() - Method in class adams.data.io.output.ArffSpreadSheetWriter: Returns, if available, the corresponding reader.
getCorrespondingReader() - Method in class adams.data.io.output.JsonAdamsExperimentWriter: Returns, if available, the corresponding reader.
getCorrespondingReader() - Method in class adams.data.io.output.JSONSpreadSheetWriter: Returns, if available, the corresponding reader.
getCorrespondingReader() - Method in class adams.data.io.output.LibSVMSpreadSheetWriter: Returns, if available, the corresponding reader.
getCorrespondingReader() - Method in class adams.data.io.output.MatlabSpreadSheetWriter: Returns, if available, the corresponding reader.
getCorrespondingReader() - Method in class adams.data.io.output.NestedAdamsExperimentWriter: Returns, if available, the corresponding reader.
getCorrespondingReader() - Method in class adams.data.io.output.SerializedAdamsExperimentWriter: Returns, if available, the corresponding reader.
getCorrespondingReader() - Method in class adams.data.io.output.SVMLightSpreadSheetWriter: Returns, if available, the corresponding reader.
getCorrespondingReader() - Method in class adams.data.io.output.XrffSpreadSheetWriter: Returns, if available, the corresponding reader.
getCorrespondingWriter() - Method in class adams.data.io.input.AbstractAdamsExperimentReader: Returns, if available, the corresponding writer.
getCorrespondingWriter() - Method in class adams.data.io.input.ArffSpreadSheetReader: Returns, if available, the corresponding writer.
getCorrespondingWriter() - Method in class adams.data.io.input.JsonAdamsExperimentReader: Returns, if available, the corresponding writer.
getCorrespondingWriter() - Method in class adams.data.io.input.JSONSpreadSheetReader: Returns, if available, the corresponding writer.
getCorrespondingWriter() - Method in class adams.data.io.input.LibSVMSpreadSheetReader: Returns, if available, the corresponding writer.
getCorrespondingWriter() - Method in class adams.data.io.input.MatlabSpreadSheetReader: Returns, if available, the corresponding writer.
getCorrespondingWriter() - Method in class adams.data.io.input.NestedAdamsExperimentReader: Returns, if available, the corresponding writer.
getCorrespondingWriter() - Method in class adams.data.io.input.SerializedAdamsExperimentReader: Returns, if available, the corresponding writer.
getCorrespondingWriter() - Method in class adams.data.io.input.SVMLightSpreadSheetReader: Returns, if available, the corresponding writer.
getCorrespondingWriter() - Method in class adams.data.io.input.XrffSpreadSheetReader: Returns, if available, the corresponding writer.
getCreateView() - Method in interface adams.data.weka.InstancesViewCreator: Returns whether to create only a view.
getCreateView() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns whether to create only a view.
getCreateView() - Method in class adams.flow.transformer.WekaRandomSplit: Returns whether to create only a view.
getCrossValidationSeed() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the current seed value for cross-validation.
getCrossValidationSeed() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the current seed value for cross-validation.
getCurrent() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog: Returns the current object.
getCurrent() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Returns the current value.
getCurrent() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: Returns the current object.
getCurrent() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel: Returns the current value.
getCurrent() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: Returns the current algorithm in use.
getCurrent() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the current file.
getCurrent() - Method in class adams.gui.wizard.WekaSelectDatasetPage: Returns the current value.
getCurrent() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: Returns the current files.
getCurrentAttributeRange() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the current range of attributes to use.
getCurrentClassIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the currently selected class index.
getCurrentDirectory() - Method in class adams.gui.chooser.DatasetFileChooserPanel: Returns the current directory in use by the file chooser.
getCurrentDirectory() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the current directory in use by the file chooser.
getCurrentDirectory() - Method in class adams.gui.wizard.WekaSelectDatasetPage: Returns the current directory in use by the file chooser.
getCurrentDirectory() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: Returns the current directory in use by the file chooser.
getCurrentFile() - Method in class weka.gui.explorer.ExplorerExt: Returns the current file.
getCurrentFitness() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the currently best fitness.
getCurrentIDIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the currently selected ID index.
getCurrentSortIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the currently selected sort index.
getCustomLoader() - Method in class adams.flow.transformer.WekaFileReader: Returns the custom loader in use.
getCustomLoader() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the custom loader in use.
getCustomLoader() - Method in class weka.filters.unsupervised.instance.AlignDataset: Returns the custom loader to use (if enabled).
getCustomLoader() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the custom loader to use (if enabled).
getCustomPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the custom paintlet.
getCustomPanel(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler: Returns the custom panel of the editor.
getCustomPropsFile() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the custom properties file to use for initializing the database setup instead of WEKA's default one.
getCustomPropsFile() - Method in class adams.flow.source.WekaDatabaseReader: Returns the custom properties file to use for initializing the database setup instead of WEKA's default one.
getCustomSaver() - Method in class adams.flow.sink.WekaFileWriter: Returns the custom saver in use.
getCustomStopMessage() - Method in class adams.flow.source.WekaSelectDataset: Returns the custom message to use when stopping the flow.
getCustomSupplyTextMenuItemCaption() - Method in class adams.flow.sink.WekaInstancesDisplay: Returns the text for the menu item.
getCustomSupplyTextMenuItemCaption() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the text for the menu item.
getCustomTextFileFilter() - Method in class adams.flow.sink.WekaInstancesDisplay: Returns a custom file filter for the file chooser.
getCustomTextFileFilter() - Method in class adams.flow.sink.WekaInstanceViewer: Returns a custom file filter for the file chooser.
getData() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator: Returns the data to use for training and so forth.
getData() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Returns the actual underlying data.
getData() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer: Returns the actual underlying data.
getData() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Returns the currently loaded data.
getData() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: Returns the underlying data.
getData() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns the currently loaded data.
getData() - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource: Returns the currently loaded data.
getData() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Returns the currently loaded data.
getData() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Returns the currently loaded data.
getData() - Method in class adams.gui.visualization.instance.InstanceContainer: Returns the stored instance.
getData() - Method in class adams.gui.visualization.instance.InstanceContainerTableColumnNameGenerator: Returns the name of the column with the actual data in it.
getData() - Method in class adams.gui.visualization.instance.InstanceTable: Returns the underlying Instances object.
getData() - Method in class adams.gui.visualization.instance.InstanceTableModel: Returns the underlying data.
getData() - Method in class adams.ml.data.InstancesHeaderRow: Returns the underlying Instance.
getData() - Method in class adams.ml.data.InstancesView: Returns the underlying Instances.
getData() - Method in class adams.ml.data.InstanceView: Returns the underlying Instance.
getData() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the data in use.
getData() - Method in class weka.classifiers.AbstractSplitGenerator: Returns the original data.
getData() - Method in interface weka.classifiers.SplitGenerator: Returns the original data.
getData() - Method in class weka.core.InstanceGrouping: Returns the underlying data.
getData(Experiment) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Loads the experimental results.
getDatabaseConnection() - Method in class adams.data.instances.AbstractInstanceGenerator: Returns the currently used database connection object, can be null.
getDatabaseConnection() - Method in class adams.flow.transformer.AbstractInstanceGenerator: Returns the database connection to use.
getDatabaseID() - Method in class adams.gui.visualization.instance.InstanceContainer: Returns the database ID.
getDatabaseIDColumnIndex() - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Returns the index of the column with the database ID.
getDataDef() - Method in class adams.opt.genetic.PackDataGeneticAlgorithm
getDataDef() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection
getDataDef() - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm
getDataDef() - Method in class adams.opt.optimise.GeneticAlgorithm
getDataGenerator() - Method in class adams.flow.source.WekaDataGenerator: Returns the data generator in use.
getDataHashcode() - Method in class weka.gui.explorer.ExplorerExt: Returns the hashcode of the current dataset.
getDataPaintlet() - Method in class adams.gui.visualization.instance.InstancePanel: Returns the paintlet for painting the instance.
getDataRowClass() - Method in class adams.ml.data.InstancesView: Returns the class used for rows.
getDataRowType() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet: Returns the type of data row to use.
getDataset() - Method in class adams.flow.transformer.WekaStoreInstance: Returns the name of the dataset in internal storage to append to.
getDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Returns the dataset to index.
getDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Return the currently selected dataset.
getDataset() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the full dataset, can be null if none loaded.
getDataset() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the currently set filename of the dataset for cross-validation.
getDataSet() - Method in class weka.core.converters.SimpleArffLoader: Returns the full dataset.
getDataSet() - Method in class weka.core.converters.SpreadSheetLoader: Return the full data set.
getDataset1() - Method in class adams.tools.CompareDatasets: Returns the first dataset for the comparison.
getDataset2() - Method in class adams.tools.CompareDatasets: Returns the second dataset for the comparison.
getDatasetFormat() - Method in class adams.data.featureconverter.Weka: Returns the class of the dataset that the converter generates.
getDatasetHeader() - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader: Acquires the dataset header.
getDatasetHeader() - Method in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader: Acquires the header.
getDatasetHeader() - Method in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader: Acquires the header.
getDatasetHeader() - Method in class adams.data.instance.Instance: Returns the header of the underlying dataset.
getDatasetInfo() - Method in class adams.ml.model.classification.WekaClassificationModel: Returns information about the dataset used for building the model.
getDatasetInfo() - Method in class adams.ml.model.clustering.WekaClusteringModel: Returns information about the dataset used for building the model.
getDatasetInfo() - Method in class adams.ml.model.regression.WekaRegressionModel: Returns information about the dataset used for building the model.
getDatasetNames() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the list of names to use in attribute renaming in place of the {DATASET} keyword.
getDatasets() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: The datasets in use.
getDataSetups() - Method in class adams.opt.genetic.PackDataGeneticAlgorithm
getDataSetups() - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm
getDataSetups() - Method in class adams.opt.optimise.GeneticAlgorithm
getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Returns the list selection mode to use.
getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab: Returns the list selection mode to use.
getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Returns the list selection mode to use.
getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.DataTab: Returns the list selection mode to use.
getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab: Returns the list selection mode to use.
getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Returns the list selection mode to use.
getDataTableListSelectionMode() - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab: Returns the list selection mode to use.
getDataType() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns what type of data to retrieve from the Instances object.
getDataType() - Method in class adams.flow.transformer.WekaInstancesStatistic: Returns what type of data to retrieve from the Instances object.
getDataWidth() - Method in class adams.gui.visualization.instance.InstanceContainerTableColumnNameGenerator: Returns the width of the data column.
getDateFormat() - Method in class adams.ml.data.InstancesView: Returns the date formatter.
getDateTimeFormat() - Method in class adams.ml.data.InstancesView: Returns the date/time formatter.
getDateTimeMsecFormat() - Method in class adams.ml.data.InstancesView: Returns the date/time msec formatter.
getDBIDName() - Static method in class adams.data.weka.ArffUtils: Returns the name of the attribute containing the database ID.
getDebug() - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Returns whether or not debugging output shouild be printed
getDebug() - Method in class weka.classifiers.meta.LeastMedianSq: Returns whether or not debugging output shouild be printed
getDebug() - Method in class weka.core.converters.SpreadSheetLoader: Gets whether additional debug information is printed.
getDebug() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin: Returns whether to output debugging information.
getDefaultAlgorithm() - Method in class weka.classifiers.functions.PLSWeighted: Returns the default PLS filter.
getDefaultAlgorithm() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the default algorithm.
getDefaultAlgorithm() - Method in class weka.filters.supervised.attribute.PLS: Returns the default algorithm.
getDefaultAlpha() - Method in class weka.filters.supervised.attribute.YGradientEPO: Returns the default algorithm.
getDefaultAlpha() - Method in class weka.filters.supervised.attribute.YGradientGLSW: Returns the default algorithm.
getDefaultAttRegExp() - Method in class weka.filters.unsupervised.attribute.Detrend: Returns the default regular expression for identifying the attributes to process.
getDefaultAttRegExp() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Returns the default regular expression for identifying the attributes to process.
getDefaultAttributeRange() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the default range of attributes to use.
getDefaultAttributeRange() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Returns the default regular expression for identifying the attributes to process.
getDefaultAttributeSelection() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the default attribute selection.
getDefaultAxisX() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot: Returns the setup for the X axis.
getDefaultAxisX() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the setup for the X axis.
getDefaultAxisY() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot: Returns the setup for the Y axis.
getDefaultAxisY() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the setup for the Y axis.
getDefaultBase() - Method in class weka.classifiers.meta.Fallback: Returns the default base classifier.
getDefaultBorder() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns the default border thickness of the table.
getDefaultCaseIndex(Actor, Token) - Method in class adams.flow.condition.bool.WekaClassification: Returns the index of the default case.
getDefaultCellPadding() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns the default cell padding for the table.
getDefaultCellSpacing() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns the default cell spacing for the table.
getDefaultClassAttributes() - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: Returns the default regular expression for the class attributes.
getDefaultClassifier() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the default classifier to use.
getDefaultClassifier() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the default classifier.
getDefaultClassIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the default class index in use.
getDefaultClassname() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the default classname.
getDefaultClassname() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the default classname.
getDefaultClassname() - Method in class adams.core.discovery.genetic.GenericInteger: Returns the default classname.
getDefaultClassname() - Method in class adams.core.discovery.genetic.GenericString: Returns the default classname.
getDefaultClassName() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the name of the default attribute to use as the class attribute for supervised summary filters.
getDefaultCleaner() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Returns the default cleaner.
getDefaultCleaners() - Method in class weka.core.tokenizers.cleaners.MultiCleaner: Returns the default token cleaners.
getDefaultColor() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet: Returns the default color to use when no color information in the report.
getDefaultColorProvider() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Returns the default color provider to use.
getDefaultColorProvider() - Static method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Returns the default color provider to use.
getDefaultColumnFinder() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the default column finder which selects the attributes for summarisation.
getDefaultColumns() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the default size.
getDefaultColumns() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix: The number of PLS components
getDefaultCorrection() - Method in class weka.filters.unsupervised.attribute.Detrend: Returns the default correction scheme.
getDefaultCorrection() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Returns the default correction scheme.
getDefaultCorrection() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Returns the default correction scheme.
getDefaultDatabaseConnection() - Method in class adams.data.instances.AbstractInstanceGenerator: Returns the default database connection.
getDefaultDatabaseConnection() - Method in class adams.gui.visualization.instance.InstancePanel: Returns the default database connection.
getDefaultDefaultClass() - Method in class adams.flow.source.valuedefinition.WekaGOEValueDefinition: Returns the default default class.
getDefaultDetector() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the default detector.
getDefaultDialogTitle() - Method in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceList: Returns the default title to use for dialogs.
getDefaultDialogTitle() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterEntryPanel: Returns the default title to use for dialogs.
getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixAdamsCSV: returns the default of whether column names are prefixed with the index.
getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixMediaWiki: returns the default of whether column names are prefixed with the index.
getDefaultExperiment() - Method in class adams.flow.source.WekaNewExperiment: Returns the default experiment.
getDefaultFallback() - Method in class weka.classifiers.meta.Fallback: Returns the default fallback classifier.
getDefaultFilter() - Method in class weka.classifiers.functions.PLSClassifierWeighted: Returns the default PLS filter.
getDefaultFilter() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings: Returns the default PLS filter.
getDefaultFind() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Returns the default regular expression for finding tokens to clean.
getDefaultFormatExtension() - Method in class adams.data.io.input.AbstractAdamsExperimentReader: Returns the default extension of the format.
getDefaultFormatExtension() - Method in class adams.data.io.output.AbstractAdamsExperimentWriter: Returns the default extension of the format.
getDefaultGenerator() - Method in class adams.flow.transformer.AbstractInstanceGenerator: Returns the default generator.
getDefaultHandler() - Method in class adams.flow.sink.WekaExperimentFileWriter: Returns the default IO handler.
getDefaultHandler() - Method in class adams.flow.transformer.WekaExperimentFileReader: Returns the default IO handler.
getDefaultHeight() - Method in class adams.flow.sink.WekaAttributeSummary: Returns the default height for the dialog.
getDefaultHeight() - Method in class adams.flow.sink.WekaClassifierErrors: Returns the default height for the dialog.
getDefaultHeight() - Method in class adams.flow.sink.WekaCostBenefitAnalysis: Returns the default height for the dialog.
getDefaultHeight() - Method in class adams.flow.sink.WekaCostCurve: Returns the default height for the dialog.
getDefaultHeight() - Method in class adams.flow.sink.WekaInstancesDisplay: Returns the default height for the dialog.
getDefaultHeight() - Method in class adams.flow.sink.WekaInstancesPlot: Returns the default height for the dialog.
getDefaultHeight() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the default height for the dialog.
getDefaultHeight() - Method in class adams.flow.sink.WekaMarginCurve: Returns the default height for the dialog.
getDefaultHeight() - Method in class adams.flow.sink.WekaThresholdCurve: Returns the default height for the dialog.
getDefaultIDIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the default ID index in use.
getDefaultIgnoredAttributes() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Returns the default regular expression for ignored/skipped attributes.
getDefaultInclueAttributes(int) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the default for the specified attribute type.
getDefaultIndex() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Returns the default attribute index.
getDefaultIndex() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Returns the default index.
getDefaultIndex() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns the default attribute index.
getDefaultInitialSetupsProvider() - Method in class adams.opt.genetic.PackDataGeneticAlgorithm: Returns the default initial setups provider.
getDefaultLabel() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Returns the default label index.
getDefaultLabel() - Method in class weka.classifiers.meta.Veto: Returns the default label index.
getDefaultLabelRegExp() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns the default label regular expression.
getDefaultList() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the default list.
getDefaultList() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the default list.
getDefaultList() - Method in class adams.core.discovery.genetic.GenericInteger: Returns the default list.
getDefaultList() - Method in class adams.core.discovery.genetic.GenericString: Returns the default list.
getDefaultList() - Method in class adams.core.discovery.genetic.GPDGamma: Returns the default list.
getDefaultList() - Method in class adams.core.discovery.genetic.GPDNoise: Returns the default list.
getDefaultList() - Method in class adams.core.discovery.genetic.PLSFilterNumComponents: Returns the default list.
getDefaultList() - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints: Returns the default list.
getDefaultLocal() - Method in class weka.classifiers.meta.SocketFacade: Returns the default address of the return address.
getDefaultMainFilter() - Method in class weka.filters.FilteredFilter: Returns the default main filter.
getDefaultMaximum() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the default maximum.
getDefaultMaximum() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the default maximum.
getDefaultMaximum() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the default maximum.
getDefaultMaximum() - Method in class adams.core.discovery.genetic.GenericInteger: Returns the default maximum.
getDefaultMaximum() - Method in class adams.core.discovery.genetic.GPDGamma: Returns the default maximum.
getDefaultMaximum() - Method in class adams.core.discovery.genetic.GPDNoise: Returns the default maximum.
getDefaultMaximum() - Method in class adams.core.discovery.genetic.PLSFilterNumComponents: Returns the default maximum.
getDefaultMaximum() - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints: Returns the default maximum.
getDefaultMaximum() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix: Returns the default maximum.
getDefaultMenuItem() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: Returns the default name for the menu item.
getDefaultMenuItem() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: Returns the default name for the menu item.
getDefaultMenuItem() - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic: Returns the default name for the menu item.
getDefaultMenuItem() - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights: Returns the default name for the menu item.
getDefaultMenuItem() - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset: Returns the default name for the menu item.
getDefaultMinimum() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the default minimum.
getDefaultMinimum() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the default minimum.
getDefaultMinimum() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the default minimum.
getDefaultMinimum() - Method in class adams.core.discovery.genetic.GenericInteger: Returns the default minimum.
getDefaultMinimum() - Method in class adams.core.discovery.genetic.GPDGamma: Returns the default minimum.
getDefaultMinimum() - Method in class adams.core.discovery.genetic.GPDNoise: Returns the default minimum.
getDefaultMinimum() - Method in class adams.core.discovery.genetic.PLSFilterNumComponents: Returns the default minimum.
getDefaultMinimum() - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints: Returns the default minimum.
getDefaultMinimum() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix: Returns the default minimum.
getDefaultMinProbability() - Method in class weka.classifiers.meta.AbstainMinimumProbability: Returns the default minimum probability that the chosen class label must meet.
getDefaultMinProbability() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Returns the default minimum probability.
getDefaultMinSamples() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Returns the default minimum number of samples.
getDefaultN() - Method in class weka.filters.supervised.attribute.YGradientEPO: Returns the default algorithm.
getDefaultNumFolds() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the default number of folds to use in CV.
getDefaultNumPoints() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the default number of points.
getDefaultNumThreads() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the default number of threads to use for cross-validation.
getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaASEvaluator: Returns the default object to use.
getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaASSearch: Returns the default object to use.
getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaClassifier: Returns the default object to use.
getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaClusterer: Returns the default object to use.
getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaDataGenerator: Returns the default object to use.
getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaFilter: Returns the default object to use.
getDefaultObject() - Method in class adams.gui.flow.tree.quickaction.EditWekaStreamableFilter: Returns the default object to use.
getDefaultOutputType() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the default output type to use.
getDefaultOutputType() - Method in class adams.opt.genetic.DarkLord: Returns the default output type to use.
getDefaultOutputType() - Method in class adams.opt.genetic.Hermione: Returns the default output type to use.
getDefaultPackage() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Returns the default package of the types of setups to generate.
getDefaultPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Returns the default paintlet to use.
getDefaultPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the default paintlet to use.
getDefaultParameters() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Returns the default parameters.
getDefaultParameters() - Method in class adams.flow.source.WekaClassifierGenerator: Returns the default parameters.
getDefaultParameters() - Method in class adams.flow.source.WekaClustererGenerator: Returns the default parameters.
getDefaultParameters() - Method in class adams.flow.source.WekaFilterGenerator: Returns the default parameters.
getDefaultPostTokenizer() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Returns the default (post) token tokenizer.
getDefaultPreFilter() - Method in class weka.filters.FilteredFilter: Returns the default pre-filter.
getDefaultPrefix() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the default prefix for the new attributes.
getDefaultPreparation() - Method in class weka.classifiers.meta.SocketFacade: Returns the default data preparation scheme to use.
getDefaultPreprocessingType() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns the default preprocessing type.
getDefaultPreprocessingType() - Method in class adams.data.instancesanalysis.pls.PRM: Returns the default preprocessing type.
getDefaultPreprocessingType() - Method in class adams.data.instancesanalysis.pls.SparsePLS: Returns the default preprocessing type.
getDefaultPreTokenizer() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Returns the default (pre) token tokenizer.
getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixAdamsCSV: returns the default of whether column names or numbers instead are printed.
getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixMediaWiki: returns the default of whether column names or numbers instead are printed.
getDefaultProperty() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the default property.
getDefaultProperty() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the default property.
getDefaultProperty() - Method in class adams.core.discovery.genetic.GenericInteger: Returns the default property.
getDefaultProperty() - Method in class adams.core.discovery.genetic.GenericString: Returns the default property.
getDefaultRange() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the default attribute range.
getDefaultRange() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor: Returns the default range.
getDefaultRangePaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the default paintlet to use for the lower/upper statistics.
getDefaultReader() - Method in class adams.flow.transformer.WekaInstanceFileReader: Returns the default reader to use.
getDefaultReader() - Method in class adams.gui.chooser.AdamsExperimentFileChooser: Returns the default reader.
getDefaultReader() - Method in class adams.gui.chooser.WekaFileChooser: Returns the default reader.
getDefaultRegExp() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the default regular expression for identifying attributes.
getDefaultRegExp() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Returns the default regular expression.
getDefaultRemote() - Method in class weka.classifiers.meta.SocketFacade: Returns the default address of the remote process.
getDefaultReplace() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Returns the default expression for replacing matching tokens with.
getDefaultRowFinder() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the default training data row selector.
getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixAdamsCSV: returns the default width for the row names.
getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixMediaWiki: returns the default width for the row names.
getDefaultRows() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the default size.
getDefaultRows() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix: This is the number of attributes
getDefaultRowSelection() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Returns the default row selection scheme.
getDefaultSampleSize() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Returns the default sample size.
getDefaultSeed() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the default seed value.
getDefaultSelectionProcessor() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Returns the default selection processor.
getDefaultSetup() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Returns the default setup.
getDefaultSetup() - Method in class adams.flow.source.WekaClassifierGenerator: Returns the default setup.
getDefaultSetup() - Method in class adams.flow.source.WekaClustererGenerator: Returns the default setup.
getDefaultSetup() - Method in class adams.flow.source.WekaFilterGenerator: Returns the default setup.
getDefaultSortIndex() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the default sort index in use.
getDefaultSplits() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the default splits.
getDefaultSplits() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the default splits.
getDefaultSplits() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the default splits.
getDefaultSplits() - Method in class adams.core.discovery.genetic.GPDGamma: Returns the default splits.
getDefaultSplits() - Method in class adams.core.discovery.genetic.GPDNoise: Returns the default splits.
getDefaultSplits() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix
getDefaultSummaryFilter() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the default filter to use to summarise the attributes.
getDefaultSuperClass() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Returns the default super class, the same as the type "T" when defining the generics.
getDefaultSuperClass() - Method in class adams.flow.source.valuedefinition.WekaGOEValueDefinition: Returns the default super class.
getDefaultSuperClass() - Method in class adams.flow.source.WekaClassifierGenerator: Returns the default super class, the same as the type "T" when defining the generics.
getDefaultSuperClass() - Method in class adams.flow.source.WekaClustererGenerator: Returns the default super class, the same as the type "T" when defining the generics.
getDefaultSuperClass() - Method in class adams.flow.source.WekaFilterGenerator: Returns the default super class, the same as the type "T" when defining the generics.
getDefaultSupport() - Method in class weka.classifiers.meta.ConsensusOrVote: Returns the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.
getDefaultSupport() - Method in class weka.classifiers.meta.Veto: Returns the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.
getDefaultTimeout() - Method in class weka.classifiers.meta.SocketFacade: The default timeout in milli-second.
getDefaultTitle() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns the default title.
getDefaultTitle() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Returns the default title.
getDefaultTokenizers() - Method in class weka.core.tokenizers.MultiTokenizer: Returns the default token tokenizers.
getDefaultType() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Returns the default regular expression for finding tokens to clean.
getDefaultWaveNoRegExp() - Method in class weka.filters.unsupervised.attribute.Detrend: Returns the default regular expression for extracting the wave numbers.
getDefaultWaveNoRegExp() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Returns the default regular expression for extracting the wave numbers.
getDefaultWidth() - Method in class adams.flow.sink.WekaAttributeSummary: Returns the default width for the dialog.
getDefaultWidth() - Method in class adams.flow.sink.WekaClassifierErrors: Returns the default width for the dialog.
getDefaultWidth() - Method in class adams.flow.sink.WekaCostBenefitAnalysis: Returns the default width for the dialog.
getDefaultWidth() - Method in class adams.flow.sink.WekaCostCurve: Returns the default width for the dialog.
getDefaultWidth() - Method in class adams.flow.sink.WekaInstancesDisplay: Returns the default width for the dialog.
getDefaultWidth() - Method in class adams.flow.sink.WekaInstancesPlot: Returns the default width for the dialog.
getDefaultWidth() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the default width for the dialog.
getDefaultWidth() - Method in class adams.flow.sink.WekaMarginCurve: Returns the default width for the dialog.
getDefaultWidth() - Method in class adams.flow.sink.WekaThresholdCurve: Returns the default width for the dialog.
getDefaultWorkspaceName() - Method in class adams.gui.tools.wekainvestigator.InvestigatorManagerPanel: The default name for a workspace.
getDefaultWorkspaceName() - Method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter: The default name for a workspace.
getDefaultWriter() - Method in class adams.gui.chooser.AdamsExperimentFileChooser: Returns the default writer.
getDefaultWriter() - Method in class adams.gui.chooser.WekaFileChooser: Returns the default writer.
getDefaultWriter() - Method in class weka.experiment.ResultMatrixAdamsCSV: Returns the default writer to use.
getDefaultXRegExp() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the default X regexp.
getDefaultYRegExp() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the default Y regexp.
getDeflationMode() - Method in class adams.data.instancesanalysis.pls.NIPALS: Returns the deflation mode to use.
getDerivativeOrder() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns the order of the derivative.
getDerivativeOrder() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Returns the order of the derivative.
getDesignVersion() - Method in class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors: Get the specific version of Weka the class is designed for.
getDesignVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrors: Get the specific version of Weka the class is designed for.
getDesignVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrorsPlot: Get the specific version of Weka the class is designed for.
getDesignVersion() - Method in class weka.gui.visualize.plugins.SaveGraph: Get the specific version of Weka the class is designed for.
getDesignVersion() - Method in class weka.gui.visualize.plugins.SaveTree: Get the specific version of Weka the class is designed for.
getDesignVersion() - Method in class weka.gui.visualize.plugins.ThresholdCurves: Get the specific version of Weka the class is designed for.
getDetector() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the detector.
getDev() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive
getDialog(Dialog, Dialog.ModalityType) - Static method in class adams.gui.visualization.instance.HistogramFactory: Returns a new dialog for displaying histograms.
getDialog(Frame, boolean) - Static method in class adams.gui.visualization.instance.HistogramFactory: Returns a new dialog for displaying displaying histograms.
getDialogTitle() - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Returns the title for the dialog.
getDiameter() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the diameter of the cross.
getDiffer() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Gets the type of strategy to apply if the two values differ.
getDiffer() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Gets the type of strategy to apply if the two values differ.
getDisabled() - Static method in class adams.gui.goe.WekaEditorsRegistration.AccessiblePluginManager: Returns the disabled plugins.
getDiscardPredictions() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator: Returns whether to discard the predictions in order to preserve memory.
getDiscardPredictions() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns whether to discard the predictions in order to preserve memory.
getDiscardPredictions() - Method in class adams.flow.transformer.WekaTestSetEvaluator: Returns whether to discard the predictions in order to preserve memory.
getDiscardPredictions() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns whether to discard the predictions in order to preserve memory.
getDiscardPredictions() - Method in class adams.multiprocess.WekaCrossValidationJob: Returns whether the predictions are discarded.
getDisplay(InstanceContainer) - Method in class adams.gui.visualization.instance.InstanceContainerDisplayIDGenerator: Returns the display ID for the sequence.
getDisplayID() - Method in class adams.gui.visualization.instance.InstanceContainer: Returns the displayed container's ID.
getDisplayName() - Method in class weka.experiment.ResultMatrixAdamsCSV: returns the name of the output format.
getDisplayName() - Method in class weka.experiment.ResultMatrixMediaWiki: returns the name of the output format.
getDisplayStdDevs() - Method in class weka.clusterers.SAXKMeans: Gets whether standard deviations and nominal count.
getDistanceFunction() - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient: Returns the distance function to use.
getDistanceFunction() - Method in class weka.clusterers.SAXKMeans: returns the distance function currently in use.
getDistances() - Method in class weka.core.neighboursearch.NewNNSearch: Returns the distances of the k nearest neighbours.
getDistributionFormat() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the format for the 'Name' column for the numeric classification.
getDistributionSorting() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the format for the 'Name' column for the numeric classification.
getDominantEigenVector(Matrix) - Static method in class weka.core.matrix.MatrixHelper: determines the dominant eigenvector for the given matrix and returns it
getDontReplaceMissingValues() - Method in class weka.clusterers.SAXKMeans: Gets whether missing values are to be replaced.
getDropAbove() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Returns the threshold of the weights above which to drop instances.
getDropAtMost() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns the maximum percentage of instances to drop.
getDropBelow() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Returns the threshold of the weights below which to drop instances.
getDropBelow() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns the threshold of the normalized weights below which to drop instances.
getDropNonClassYs() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns whether to remove Y attributes from the output that are not the class attribute.
getEditor() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog: Returns the underlying editor.
getEditor() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: Returns the underlying editor.
getEliminateColinearAttributes() - Method in class weka.classifiers.functions.LinearRegressionJ: Get the value of EliminateColinearAttributes.
getEncoding() - Method in class adams.data.io.input.NestedAdamsExperimentReader: Returns the encoding to use.
getEncoding() - Method in class weka.core.converters.SimpleArffLoader: Returns the encoding to use.
getEncoding() - Method in class weka.core.converters.SimpleArffSaver: Returns the encoding to use.
getEnsureEqualValues() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets whether to check all data-sources for a merged attribute have the same value.
getEntryPanel() - Method in class weka.gui.explorer.MultiExplorer: Returns the panel with the explorer panel entries.
getError() - Method in class weka.classifiers.meta.AbstainLeastMedianSq
getError() - Method in class weka.classifiers.meta.LeastMedianSq
getErrorAtPct(int) - Method in class weka.classifiers.meta.AbstainLeastMedianSq: finds the median residual squared for the current regression.
getErrorAtPct(int) - Method in class weka.classifiers.meta.LeastMedianSq: finds the median residual squared for the current regression.
getErrorCalculation() - Method in class adams.flow.transformer.WekaBootstrapping: Returns how to calculate the errors for the percentiles.
getErrorScaler() - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator: Returns the scaling scheme.
getErrorScaler() - Method in class adams.flow.sink.WekaClassifierErrors: Returns the scheme to use for scaling the errors.
getErrorScalers() - Static method in class adams.data.weka.predictions.AbstractErrorScaler: Returns a list with classnames of scalers.
getEta() - Method in class weka.classifiers.trees.XGBoost: Gets the step size shrinkage to use in updates to prevent overfitting.
getEvaluation() - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator: Returns the underlying Evaluation object.
getEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: Returns the stored Evaluation object.
getEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns the stored Evaluation object.
getEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns the stored Evaluation object.
getEvaluation() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the generated (aggregated) evaluation.
getEvaluation() - Method in class adams.multiprocess.WekaCrossValidationJob: Returns the generated evaluation object.
getEvaluation(Token) - Method in class adams.flow.sink.WekaClassifierErrors: Returns the Evaluation object from the token.
getEvaluation(Token) - Method in class adams.flow.sink.WekaCostBenefitAnalysis: Returns the Evaluation object from the token.
getEvaluation(Token) - Method in class adams.flow.sink.WekaCostCurve: Returns the Evaluation object from the token.
getEvaluation(Token) - Method in class adams.flow.sink.WekaMarginCurve: Returns the Evaluation object from the token.
getEvaluation(Token) - Method in class adams.flow.sink.WekaThresholdCurve: Returns the Evaluation object from the token.
getEvaluationPostProcessor() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the post-processing scheme for the evaluation.
getEvaluations() - Static method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation: Returns the available actions.
getEvaluations() - Static method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation: Returns the available actions.
getEvaluations() - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation: Returns the available actions.
getEvaluations() - Static method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation: Returns the available actions.
getEvaluations() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the generated evaluations (if multi-threaded or separated).
getEvaluationType() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the type of evaluation to perform.
getEvaluator() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns the evaluation method in use.
getEvaluator() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Returns the evaluator to use.
getEvaluator() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Returns the stored evaluator object.
getEvaluators() - Static method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Returns a list with classnames of evaluators.
getExactMatch() - Method in class adams.data.conversion.SwapPLS: Returns whether to use the complete command-line for comparison rather than just the class name.
getExample() - Method in class adams.data.weka.WekaAttributeIndex: Returns the example.
getExample() - Method in class adams.data.weka.WekaAttributeRange: Returns the example.
getExample() - Method in class adams.data.weka.WekaLabelIndex: Returns the example.
getExample() - Method in class adams.data.weka.WekaLabelRange: Returns the example.
getExample() - Method in class adams.data.weka.WekaUnorderedAttributeRange: Returns the example.
getExcludeClass() - Method in class weka.core.AbstractHashableInstance: Returns whether the class is excluded from the hashcode computation.
getExcludedAttributes() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the prefix separator string.
getExcludeWeight() - Method in class weka.core.AbstractHashableInstance: Returns whether the weight is excluded from the hashcode computation.
getExperiment() - Method in class adams.flow.source.WekaNewExperiment: Returns the experiment setup.
getExperiment() - Method in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog: Returns the experiment.
getExperiment() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: Returns the stored Evaluation object.
getExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Returns the current experiment.
getExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: Returns the current experiment.
getExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: Returns the current experiment.
getExperiment() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: Returns the current experiment.
getExperimentClass() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractAdamsExperimentIO: Returns the experiment superclass/interface.
getExperimentClass() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO: Returns the experiment superclass/interface.
getExperimentClass() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractWekaExperimentIO: Returns the experiment superclass/interface.
getExperimentClass() - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO: Returns the experiment superclass/interface.
getExperimentFile() - Method in class adams.flow.transformer.WekaExperiment: Returns the file the experiment is stored in.
getExperimentIO() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: Returns the handler for the IO, i.e., loading/saving of experiments.
getExperimentType() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the type of experiment to perform.
getExplorer() - Method in class weka.gui.explorer.ExperimentPanel: returns the parent Explorer frame.
getExplorer() - Method in class weka.gui.explorer.SqlPanel: returns the parent Explorer frame
getExplorerOptions(Explorer) - Static method in class weka.gui.explorer.WorkspaceHelper: Obtains the options from the explorer to be saved in the workspace.
getExplorerPanel() - Method in class weka.gui.explorer.panels.AbstractAdditionalExplorerPanel: Returns the panel to display.
getExplorerPanel() - Method in interface weka.gui.explorer.panels.AdditionalExplorerPanel: Returns the panel to display.
getExplorerPanelHandler() - Method in class weka.gui.explorer.panels.AbstractAdditionalExplorerPanel: Returns the associated panel handler.
getExplorerPanelHandler() - Method in interface weka.gui.explorer.panels.AdditionalExplorerPanel: Returns the associated panel handler.
getExpression() - Method in class weka.classifiers.functions.MathExpressionClassifier: Returns the mathematical expression to evaluate.
getExtensions() - Method in class adams.gui.tools.previewbrowser.InstanceExplorerHandler: Returns the list of extensions (without dot) that this handler can take care of.
getExtensions() - Method in class adams.gui.tools.previewbrowser.WekaDatasetHandler: Returns the list of extensions (without dot) that this handler can take care of.
getFallback() - Method in class weka.classifiers.meta.Fallback: Returns the fallback classifier.
getFastDistanceCalc() - Method in class weka.clusterers.SAXKMeans: Gets whether to use faster distance calculation.
getFavoritesClass() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: The class to use for the favorites (can be array class).
getFavoritesClass() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel: The class to use for the favorites (can be array class).
getFavorZeroes() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns whether 0s are favored over 1s.
getFeatureSelector() - Method in class weka.classifiers.trees.XGBoost: Gets the feature selection and ordering method.
getField() - Method in enum adams.flow.core.EvaluationStatistic: Returns the display string without the "numeric" or "nominal" in parentheses.
getField() - Method in enum adams.flow.core.ExperimentStatistic: Returns the display string without the "numeric" or "nominal" in parentheses.
getFieldName(AbstractField) - Static method in class adams.data.weka.ArffUtils: Returns the name of an attribute for a field.
getFields() - Method in class adams.data.conversion.ReportToWekaInstance: Returns the fields in use.
getFields() - Method in interface adams.data.instances.InstanceGeneratorWithFields: Returns the targets to add.
getFile() - Method in class adams.env.InstanceCompareDefinition: Returns the properties file name (no path) this definition is for.
getFile() - Method in class adams.env.InstanceExplorerDefinition: Returns the properties file name (no path) this definition is for.
getFile() - Method in class adams.env.WekaInvestigatorDefinition: Returns the properties file name (no path) this definition is for.
getFile() - Method in class adams.env.WekaInvestigatorShortcutsDefinition: Returns the properties file name (no path) this definition is for.
getFileChooser() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu: Returns the filechooser to use.
getFileChooser() - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO: Returns the file chooser to use.
getFileChooser() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: Returns the file chooser to use for loading/saving of props files.
getFileChooser() - Method in class weka.gui.explorer.ExplorerExt: Returns the file chooser in use.
getFileChooserParameters() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Returns the file chooser for parameters.
getFileChooserTitle() - Method in class adams.flow.source.WekaSelectDataset: Returns the title for the file chooser dialog.
getFileDescription() - Method in class weka.core.converters.AArffLoader: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.SimpleArffLoader: Get a one line description of the type of file
getFileDescription() - Method in class weka.core.converters.SimpleArffSaver: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.SpreadSheetLoader: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.SpreadSheetSaver: Returns a description of the file type.
getFileExtension() - Method in class weka.core.converters.SimpleArffLoader: Get the file extension used for this type of file
getFileExtension() - Method in class weka.core.converters.SpreadSheetLoader: Get the file extension used for this type of file
getFileExtension() - Method in class weka.core.converters.SpreadSheetSaver: Get the file extension used for this type of file
getFileExtensions() - Method in class weka.core.converters.SimpleArffLoader: Gets all the file extensions used for this type of file
getFileExtensions() - Method in class weka.core.converters.SimpleArffSaver: Gets all the file extensions used for this type of file
getFileExtensions() - Method in class weka.core.converters.SpreadSheetLoader: Gets all the file extensions used for this type of file
getFileExtensions() - Method in class weka.core.converters.SpreadSheetSaver: Gets all the file extensions used for this type of file
getFilename() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the currently selected filename, "" if none selected.
getFiles() - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: Returns the current files.
getFilter() - Method in class adams.data.spreadsheet.filter.WekaFilter: Returns the filter in use.
getFilter() - Method in class adams.data.weka.rowfinder.FilteredIQR: Returns the IQR filter.
getFilter() - Method in class adams.flow.transformer.WekaFilter: Returns the filter in use.
getFilter() - Method in class adams.flow.transformer.WekaStreamFilter: Returns the filter in use.
getFilter() - Method in class weka.classifiers.functions.ClassificationViaPLS: Get the PLS filter.
getFilter() - Method in class weka.classifiers.functions.PLSClassifierWeighted: Get the PLS filter.
getFilter() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter
getFilter() - Method in class weka.core.neighboursearch.FilteredSearch: Gets the filter used.
getFilter() - Method in class weka.filters.unsupervised.attribute.FastWavelet: Get the preprocessing filter.
getFilter(int) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Gets a single filter from the set of available filters.
getFilter(int) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Gets a single filter from the set of available filters.
getFilter(int, int) - Method in class weka.classifiers.meta.VotedImbalance: Gets a filter for a particular index.
getFilter(int, int, boolean) - Method in class weka.classifiers.meta.SubsetEnsemble: Gets a filter for a particular index.
getFilteredData() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob: Returns the filtered data.
getFilters() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Gets the list of possible filters to choose from.
getFilters() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Gets the list of possible filters to choose from.
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.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction: Returns the flow context, if any.
getFlowContext() - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction: Returns the flow context, if any.
getFlowContext() - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction: Returns the flow context, if any.
getFlowContext() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the flow context, if any.
getFlowContext() - Method in class adams.multiprocess.WekaCrossValidationJob: Returns the flow context, if any.
getFlowContext() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Return the flow context, if any.
getFlowContext() - Method in class weka.classifiers.functions.PyroProxy: Returns the flow context, if any.
getFlowFile() - Method in class weka.filters.FlowFilter: Returns the flow to process the data with.
getFold() - Method in class adams.multiprocess.WekaCrossValidationJob: Returns the fold index.
getFoldEvaluations() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns the stored Evaluation objects per fold.
getFoldModels() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns the stored Classifier objects per fold.
getFolds() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator: Returns the number of folds for cross-validation.
getFolds() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the number of folds to use (only CV).
getFolds() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns the number of folds.
getFolds() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the number of folds to use.
getFolds() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Returns the number of folds.
getFolds() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Returns the number of folds.
getFolds() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the number of folds.
getFolds() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the number of folds to generate.
getFolds() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the number of folds.
getFolds() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Returns the number of folds.
getFolds() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: Returns the number of folds.
getFolds() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the number of folds.
getFolds() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Returns the number of cross-validation folds.
getFolds() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the number of folds to use in cross-validation.
getFolds() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the number of folds to use in cross-validation.
getForceCompression() - Method in class weka.core.converters.SimpleArffLoader: Gets whether the file gets interpreted as gzip-compressed ARFF file.
getFormat() - Method in class weka.filters.unsupervised.attribute.StringToDate: Returns the parse format to use.
getFormatDescription() - Method in class adams.data.io.input.AbstractAdamsExperimentReader: Returns a string describing the format (used in the file chooser).
getFormatDescription() - Method in class adams.data.io.input.AbstractWekaSpreadSheetReader: Returns a string describing the format (used in the file chooser).
getFormatDescription() - Method in class adams.data.io.input.InstanceReader: Returns a string describing the format (used in the file chooser).
getFormatDescription() - Method in class adams.data.io.input.JsonAdamsExperimentReader: Returns a string describing the format (used in the file chooser).
getFormatDescription() - Method in class adams.data.io.input.NestedAdamsExperimentReader: Returns a string describing the format (used in the file chooser).
getFormatDescription() - Method in class adams.data.io.input.SerializedAdamsExperimentReader: Returns a string describing the format (used in the file chooser).
getFormatDescription() - Method in class adams.data.io.output.AbstractAdamsExperimentWriter: Returns a string describing the format (used in the file chooser).
getFormatDescription() - Method in class adams.data.io.output.AbstractWekaSpreadSheetWriter: Returns a string describing the format (used in the file chooser).
getFormatDescription() - Method in class adams.data.io.output.JsonAdamsExperimentWriter: Returns a string describing the format (used in the file chooser).
getFormatDescription() - Method in class adams.data.io.output.NestedAdamsExperimentWriter: Returns a string describing the format (used in the file chooser).
getFormatDescription() - Method in class adams.data.io.output.SerializedAdamsExperimentWriter: Returns a string describing the format (used in the file chooser).
getFormatDescription() - Method in class adams.gui.visualization.debug.objectexport.WekaInstancesExporter: Returns a string describing the format (used in the file chooser).
getFormatExtensions() - Method in class adams.data.io.input.AbstractAdamsExperimentReader: Returns the extension(s) of the format.
getFormatExtensions() - Method in class adams.data.io.input.AbstractWekaSpreadSheetReader: Returns the extension(s) of the format.
getFormatExtensions() - Method in class adams.data.io.input.InstanceReader: Returns the extension(s) of the format.
getFormatExtensions() - Method in class adams.data.io.input.JsonAdamsExperimentReader: Returns the extension(s) of the format.
getFormatExtensions() - Method in class adams.data.io.input.NestedAdamsExperimentReader: Returns the extension(s) of the format.
getFormatExtensions() - Method in class adams.data.io.input.SerializedAdamsExperimentReader: Returns the extension(s) of the format.
getFormatExtensions() - Method in class adams.data.io.output.AbstractAdamsExperimentWriter: Returns the extension(s) of the format.
getFormatExtensions() - Method in class adams.data.io.output.AbstractWekaSpreadSheetWriter: Returns the extension(s) of the format.
getFormatExtensions() - Method in class adams.data.io.output.JsonAdamsExperimentWriter: Returns the extension(s) of the format.
getFormatExtensions() - Method in class adams.data.io.output.NestedAdamsExperimentWriter: Returns the extension(s) of the format.
getFormatExtensions() - Method in class adams.data.io.output.SerializedAdamsExperimentWriter: Returns the extension(s) of the format.
getFormatExtensions() - Method in class adams.gui.visualization.debug.objectexport.WekaInstancesExporter: Returns the extension(s) of the format.
getFormula() - Method in class adams.ml.data.DataCellView: Returns the formula.
getFull() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Returns the full dataset if present.
getGamma() - Method in class weka.classifiers.functions.GPD: Returns the gamma for the RBF kernel.
getGamma() - Method in class weka.classifiers.trees.XGBoost: Gets the minimum loss reduction required to make a further partition on a leaf node of the tree.
getGene(int, int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns the value of the specified gene.
getGenerateLine() - Method in class adams.data.baseline.AbstractLinearRegressionBased: Returns whether to return the line as fake data or the corrected data.
getGenerateRules() - Method in class weka.classifiers.trees.m5.M5Base2: get whether rules are being generated rather than a tree
getGenerator() - Method in class adams.flow.transformer.AbstractInstanceGenerator: Returns the generator in use.
getGenerator() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the scheme for generating the folds.
getGenerator() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the scheme for generating the folds.
getGenerator() - Method in class adams.flow.transformer.WekaEnsembleGenerator: Returns the ensemble generator to use.
getGenerator() - Method in class adams.flow.transformer.WekaRandomSplit: Returns the scheme for generating the split.
getGenerator() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the scheme for generating the folds.
getGenerator() - Method in class adams.flow.transformer.WekaSplitGenerator: Returns the scheme for generating the split.
getGenerator() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: Returns the scheme for generating the folds.
getGenerator() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: Returns the scheme for generating the split.
getGenerator() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the generator to use for generating the folds.
getGenerator() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the scheme for generating the folds.
getGenerators() - Static method in class adams.data.instances.AbstractInstanceGenerator: Returns a list with classnames of generators.
getGeneticAlgorithms() - Static method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns a list with classnames of genetic algorithms.
getGlue() - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Returns the glue to use.
getGOEEditor() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: Returns the underlying GOE editor.
getGrid() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Returns the grid size.
getGroup() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the replacement string to use as group (eg '$2').
getGroup() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns the replacement string to use as group (eg '$2').
getGroup() - Method in class adams.gui.visualization.instance.containerlistpopup.SaveAs: The group this customizer belongs to.
getGroup() - Method in class adams.gui.visualization.instance.containerlistpopup.ViewAsTable: The group this customizer belongs to.
getGroup() - Method in class adams.gui.visualization.instance.plotpopup.Adjust: The group this customizer belongs to.
getGroup() - Method in class adams.gui.visualization.instance.plotpopup.Histogram: The group this customizer belongs to.
getGroup() - Method in class adams.gui.visualization.instance.plotpopup.SaveVisible: The group this customizer belongs to.
getGroup() - Method in class adams.gui.visualization.instance.plotpopup.Viewport: The group this customizer belongs to.
getGroup() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the replacement string to use as group (eg '$2').
getGroup() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns the replacement string to use as group (eg '$2').
getGroup() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the replacement string to use as group (eg '$2').
getGroup() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns the replacement string to use as group (eg '$2').
getGroup() - Method in class weka.core.InstanceGrouping: The group expression, i.e., replacement string (eg '$2').
getGroup() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Returns the replacement string to use as group (eg '$2').
getGroups() - Method in class weka.classifiers.MultiLevelSplitGenerator: Returns the groups to generate.
getGrowPolicy() - Method in class weka.classifiers.trees.XGBoost: Gets the way new nodes are added to the tree.
getHandler() - Method in class adams.flow.sink.WekaExperimentFileWriter: Returns the IO handler.
getHandler() - Method in class adams.flow.transformer.WekaExperimentFileReader: Returns the IO handler.
getHandlers() - Method in class adams.opt.genetic.Hermione: Returns the currently set discovery handlers.
getHandlers() - Static method in class weka.gui.explorer.AbstractExplorerPanelHandler: Returns a list with classnames of handlers.
getHandlers() - Static method in class weka.gui.explorer.WorkspaceHelper: Returns all available handlers, with the DefaultHandler being the last one.
getHeader() - Method in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader: Returns the file to load the dataset header from.
getHeader() - Method in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader: Returns the name of the storage value representing the dataset header.
getHeader() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: Returns the stored training set header.
getHeader() - Method in class adams.ml.data.InstancesView: Returns the a spreadsheet with the same header and comments.
getHeaderPopupMenuCustomizer() - Method in class adams.gui.visualization.instances.InstancesTable: Returns the current popup menu customizer (for the header).
getHeaderRow() - Method in class adams.ml.data.InstancesView: Returns the header row.
getHiClassifier() - Method in class weka.classifiers.meta.HighLowSplit
getHiLopoint() - Method in class weka.classifiers.meta.HighLowSplit
getHistogramOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Get the options for the histogram.
getHistory() - Method in class weka.gui.explorer.MultiExplorer: Returns the underlying history panel.
getHitDetector() - Method in class adams.gui.visualization.instance.InstancePanel: Returns the hit detector.
getHoldOutPercentage() - Method in class weka.classifiers.meta.ClassifierCascade: the percentage to use for validation set to determine termination criterion (0-100).
getICA() - Method in class adams.data.instancesanalysis.FastICA: Returns the ICA analysis.
getIconName() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: Returns the file name of the icon.
getIconName() - Method in class adams.gui.menu.AbstractWekaMenuItemDefinition: Returns the file name of the icon.
getIconName() - Method in class adams.gui.menu.AppendDatasets: Returns the file name of the icon.
getIconName() - Method in class adams.gui.menu.BatchFilterDatasets: Returns the file name of the icon.
getIconName() - Method in class adams.gui.menu.BayesNetEditor: Returns the file name of the icon.
getIconName() - Method in class adams.gui.menu.DatasetCompatibility: Returns the file name of the icon.
getIconName() - Method in class adams.gui.menu.InstanceCompare: Returns the file name of the icon.
getIconName() - Method in class adams.gui.menu.InstanceExplorer: Returns the file name of the icon.
getIconName() - Method in class adams.gui.menu.MakeCompatibleDatasets: Returns the file name of the icon.
getIconName() - Method in class adams.gui.menu.MergeDatasets: Returns the file name of the icon.
getIconName() - Method in class adams.gui.menu.WekaInvestigator: Returns the file name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotColumn: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotRow: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.Binning: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.DataSort: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.Histogram: Returns the name of the icon.
getIconName() - Method in interface adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItem: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.JFreeChart: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.SimplePlot: Returns the name of the icon.
getIconName() - Method in class adams.gui.visualization.instances.instancestable.ViewCell: Returns the name of the icon.
getID() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the name of the attribute/field to use as ID in the display.
getID() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Returns the container ID.
getID() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer: Returns the container ID.
getID() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Returns the ID to use for the returned instances.
getID() - Method in class adams.gui.visualization.instance.InstanceContainer: Returns the container's ID.
getID() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Returns the attribute name/index of attribute with IDs.
getID() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the attribute name/index to use for identifying rows.
getIDAttributeName(Instances) - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Returns a unique attribute name for the ID attribute.
getIDName() - Static method in class adams.data.weka.ArffUtils: Returns the name of the attribute containing the ID of the data container.
getIDs(Instances, int) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Retrieves the IDs from the dataset.
getIDTest() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the attribute name/index to use for identifying rows in the test set.
getIgnoreClass() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: Gets whether to ignore the class.
getIgnoredAttributes() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Returns the regular expression for ignored/skipped attributes.
getIncludeAttributes(int) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns whether only numeric attributes should be used.
getIncludeClass() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns whether to include the class attribute in the comparison.
getIncludeClass() - Method in class weka.filters.unsupervised.instance.Sort: Returns whether to include the class attribute in the comparison.
getIncorrect() - Method in class weka.filters.unsupervised.attribute.SpellChecker: Returns the incorrect labels, blank-separated list.
getIncremental() - Method in class adams.flow.source.WekaDatabaseReader: Returns whether to output single Instance objects or just one Instances object.
getIndex() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer: Returns the index.
getIndex() - Method in class adams.data.weka.classattribute.AttributeIndex: Returns the index of the attribute to select.
getIndex() - Method in class adams.data.weka.relationname.AttributeIndex: Returns the index of the attribute to select.
getIndex() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the attribute index to use for grouping.
getIndex() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns the attribute index to use for grouping.
getIndex() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Returns the index of the classifier in the actor's input array.
getIndex() - Method in class adams.flow.transformer.WekaExtractArray: Returns the type of extraction to perform.
getIndex() - Method in class adams.flow.transformer.WekaGetInstanceValue: Returns the 1-based index of the attribuate value to retrieve from the Instance.
getIndex() - Method in class adams.flow.transformer.WekaSetInstanceValue: Returns the 1-based attribute index to set in the Instance.
getIndex() - Method in class adams.flow.transformer.WekaSubsets: Returns the index of the attribute to split on.
getIndex() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Returns the index, generates it if necessary.
getIndex() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the attribute index to use for grouping.
getIndex() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns the attribute index to use for grouping.
getIndex() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the attribute index to use for grouping.
getIndex() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns the attribute index to use for grouping.
getIndex() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Returns the attribute index to use for grouping.
getIndex() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Returns the index of the attribute to convert.
getIndex() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Returns the attribute index to use for grouping.
getIndex() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns the index of the attribute to convert.
getIndices() - Method in class adams.data.instances.InstanceComparator: Returns the indices used for sorting.
getIndices() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Returns the indices of the (actual) selected rows.
getIndices() - Method in class weka.classifiers.MultiLevelSplitGenerator: Returns the attribute indices.
getInitialDirectory() - Method in class adams.flow.source.WekaSelectDataset: Returns the initial directory.
getInitialFiles() - Method in class adams.flow.source.WekaSelectDataset: Returns the initial files.
getInitializationMethod() - Method in class weka.clusterers.SAXKMeans: Get the initialization method to use
getInitializeOnce() - Method in class adams.flow.transformer.WekaFilter: Returns whether the filter gets initialized only with the first batch.
getInitializeOnce() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns whether the internal reorder filter gets initialized only with the first batch.
getInitialSetups() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm
getInitialSetups() - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm
getInitialSetups(T) - Method in class adams.opt.genetic.initialsetups.PackDataInitialSetupsProvider: Provides the initial gene setup.
getInlineValue() - Method in class adams.gui.goe.WekaExperimentFileEditor: Returns the current value.
getInput() - Method in class adams.flow.transformer.WekaDatasetsMerge: Gets the input Instances to merge.
getInputs() - Method in class adams.ml.data.InstancesView: Returns a spreadsheet containing only the input columns, not class columns.
getInputType() - Method in class adams.data.io.input.AbstractWekaSpreadSheetReader: Returns how to read the data, from a file, stream or reader.
getInstance() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer: Returns the stored Instance.
getInstance(Instances, int, String, TIntList) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Returns the instance from the dataset with the specified ID.
getInstanceClass() - Method in class adams.flow.transformer.WekaNewInstance: Returns the class name of the Instance object to create.
getInstanceContainerList() - Method in class adams.gui.visualization.instance.InstanceExplorer: Returns the panel listing the instances.
getInstancePanel() - Method in class adams.gui.visualization.instance.AbstractInstancePaintlet: Returns the instance panel currently in use.
getInstancePanel() - Method in class adams.gui.visualization.instance.InstanceExplorer: Returns the panel for painting the instances.
getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel: Returns the underlying instances.
getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Returns the currently displayed instances.
getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: Returns the currently set data.
getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Returns the underlying data.
getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: Returns the instances currently in use.
getInstances() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: Returns the instances currently in use.
getInstances() - Method in class adams.gui.visualization.instance.InstancePanel: Returns the currently visible instances.
getInstances() - Method in class adams.gui.visualization.instances.InstancesPanel: Returns the currently displayed data.
getInstances() - Method in class adams.gui.visualization.instances.InstancesTable: returns the data
getInstances() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Returns the Instances to use.
getInstances() - Method in class adams.gui.visualization.instances.InstancesTableModel: returns the data
getInstances() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Returns the instances in use by the genetic algorithm.
getInstances() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the currently set dataset for cross-validation.
getInstances() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the currently set dataset for cross-validation.
getInstances(T) - Method in class adams.data.baseline.AbstractLinearRegressionBased: Returns a dataset containing the x and y values.
getInstancesActor() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Returns the callable actor from which to retrieve Instances in case of AbstractDatasetInstanceEvaluator-derived evaluators.
getInstancesHeader() - Method in class adams.ml.model.classification.WekaClassificationModel: Returns the Instances header used for building the model.
getInstancesHeader() - Method in class adams.ml.model.clustering.WekaClusteringModel: Returns the Instances header used for building the model.
getInstancesHeader() - Method in class adams.ml.model.regression.WekaRegressionModel: Returns the Instances header used for building the model.
getInstancesIndices() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Gets ranges of instances selected.
getInstancesValueAt(int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel: returns the double value of the underlying Instances object at the given position, -1 if out of bounds
getInt(int[], int, int) - Method in class adams.opt.optimise.genetic.PackData
getIntercept() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns the intercept of the function.
getInterceptSE() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns the standard error intercept of the function.
getInterval() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns the interval for outputting the Instances objects.
getInterval() - Method in class adams.flow.transformer.WekaStreamEvaluator: Returns the output interval.
getIntervals() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval: Returns the stored intervals.
getInverseTransform() - Method in class weka.filters.unsupervised.attribute.FastWavelet: Gets whether to use the inverse transform.
getInverseTransform() - Method in class weka.filters.unsupervised.attribute.FFT: Returns whether to compute inverse.
getInvert() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities: Returns whether the matching sense of the capabilities is inverted.
getInvert() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns whether to invert the matching sense.
getInvert() - Method in class adams.flow.transformer.WekaRegexToRange: Get invert match?
getInvert() - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens: Returns whether to invert the matching sense, ie keep only the emoticons rather than removing them.
getInvert() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Returns whether the invert the column indices.
getInvert() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Returns whether the invert the row indices.
getInvert() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Get whether selection is inverted.
getInvert() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Get whether selection is inverted.
getInvert() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns whether to invert the matching sense (ie keep rather than remove).
getInvert() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns whether to invert the matching sense.
getInvertMatchingSense() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns whether to invert the matching sense.
getInvertSelection() - Method in class weka.filters.unsupervised.instance.KennardStone: Gets if selection is to be inverted.
getInvertSelection() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Gets if selection is to be inverted.
getIqr() - Method in class adams.data.weka.rowfinder.FilteredIQR: Returns the iqr multiplier.
getItem() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane: Returns the underlying result item.
getItemClass() - Method in class adams.flow.source.WekaSelectDataset: Returns the base class of the items.
getItemClass() - Method in class adams.flow.source.WekaSelectObjects: Returns the based class of the items.
getItemClass() - Method in class adams.flow.transformer.WekaAttributeIterator: Returns the base class of the items.
getItemClass() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor: Returns the base class of the items.
getItemClass() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns the base class of the items.
getItemClass() - Method in class adams.flow.transformer.WekaInstanceFileReader: Returns the base class of the items.
getItemClass() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the base class of the items.
getItemClass() - Method in class adams.flow.transformer.WekaInstancesInfo: Returns the base class of the items.
getItemClass() - Method in class adams.flow.transformer.WekaRandomSplit: Returns the base class of the items.
getItemClass() - Method in class adams.flow.transformer.WekaSplitGenerator: Returns the base class of the items.
getItems(Class) - Static method in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper: Returns a sorted list of popup menu items for the specified superclass.
getIterations() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Gets the iterations use.
getJavaInitializationString() - Method in class adams.gui.goe.WekaExperimentFileEditor: Returns a representation of the current property value as java source.
getJobRunner() - Method in class adams.flow.transformer.WekaExperimentExecution: Returns the jobrunner for the experiment.
getJobRunner() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the jobrunner for the experiment.
getJobRunner() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the JobRunner, if any.
getJobRunnerSetup() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the JobRunnerSetup, if any.
getJobRunnerSetup() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the jobrunner setup in use.
getKeepAttributeNames() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns whether to keep the original attribute names.
getKeepAttributeNames() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Returns whether to keep the original attribute names.
getKeepExisting() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns whether any existing file is kept on first execution.
getKeepNumComponents() - Method in class adams.data.conversion.SwapPLS: Returns whether the 'number of components' of the old filter are retained.
getKeepOnlySingleUniqueID() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns whether to keep only a single instance of the unique ID attribute.
getKeepRelationName() - Method in class adams.flow.transformer.WekaFilter: Returns whether the filter doesn't change the relation name.
getKeepRelationName() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns whether the filter doesn't change the relation name.
getKeepRelationName() - Method in class adams.flow.transformer.WekaStreamFilter: Returns whether the filter doesn't change the relation name.
getKeepSupervisedClass() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets whether to keep the class attribute of the summary attributes in the final dataset.
getKernel() - Method in class adams.data.instancesanalysis.pls.KernelPLS: Sets the kernel to use.
getKernel() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Gets the kernel to use.
getKernel() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Gets the kernel to use.
getKernel() - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Gets the kernel to use.
getKey() - Method in class adams.env.InstanceCompareDefinition: Returns the key this definition is for.
getKey() - Method in class adams.env.InstanceExplorerDefinition: Returns the key this definition is for.
getKey() - Method in class adams.env.WekaInvestigatorDefinition: Returns the key this definition is for.
getKey() - Method in class adams.env.WekaInvestigatorShortcutsDefinition: Returns the key this definition is for.
getKeys() - Method in class adams.flow.source.WekaDatabaseReader: Returns the keys to use for identifying a single row (comma-separated list).
getKeySet() - Method in class adams.opt.optimise.genetic.PackData
getKNN() - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Gets the number of neighbours used for kernel bandwidth setting.
getKNN() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Gets the number of neighbours used for kernel bandwidth setting.
getLabel() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Returns the label index.
getLabel() - Method in class weka.classifiers.meta.Veto: Returns the label index.
getLabelIndex() - Method in class adams.flow.transformer.WekaInstancesInfo: Returns the index of the label to use.
getLabelIndex() - Method in class weka.classifiers.functions.ClassificationViaPLS: Get the label index of the class attribute to get the PLS matrices for.
getLabelMatch() - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Returns the label for the matching rows.
getLabelNonMatch() - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Returns the label for the non-matching rows.
getLabelRegExp() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns the regular expression for matching the labels to remove.
getLabelString() - Method in class weka.classifiers.functions.ClassificationViaPLS: Get the class attribute's label to get the PLS matrices for.
getLambda() - Method in class adams.data.instancesanalysis.pls.DIPLS: Returns the lambda.
getLambda() - Method in class adams.data.instancesanalysis.pls.SparsePLS: Returns the sparsity parameter; determines sparseness.
getLambda() - Method in class adams.data.instancesanalysis.pls.VCPLS: Returns the lambda parameter.
getLambda() - Method in class weka.classifiers.trees.XGBoost: Gets the L2 regularisation term on weights.
getLastError() - Method in class weka.classifiers.AggregateEvaluations: Returns the error that occurred during the last operation.
getLastSetup(Class, boolean, boolean) - Method in class adams.gui.visualization.instances.InstancesTable: Returns any last setup if available.
getLenient() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns whether to tolerate attributes that are missing in the incoming data.
getLimit() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the limit to impose on the axes.
getListType() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: Returns the type of list to generate.
getLoader() - Method in class adams.gui.chooser.DatasetFileChooserPanel: Returns the current loader.
getLoadings() - Method in class adams.data.instancesanalysis.PCA: Returns the loadings.
getLoadings() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns the loadings, if available.
getLoadings() - Method in class adams.data.instancesanalysis.pls.DIPLS: Returns the loadings, if available.
getLoadings() - Method in class adams.data.instancesanalysis.PLS: Returns the loadings.
getLoadings() - Method in class adams.data.instancesanalysis.pls.KernelPLS: Returns the loadings, if available.
getLoadings() - Method in class adams.data.instancesanalysis.pls.NIPALS: Returns the loadings, if available.
getLoadings() - Method in class adams.data.instancesanalysis.pls.OPLS: Returns the loadings, if available.
getLoadings() - Method in class adams.data.instancesanalysis.pls.PLS1: Returns the loadings, if available.
getLoadings() - Method in class adams.data.instancesanalysis.pls.PRM: Returns the loadings, if available.
getLoadings() - Method in class adams.data.instancesanalysis.pls.SIMPLS: Returns the loadings, if available.
getLoadings() - Method in class adams.data.instancesanalysis.pls.SparsePLS: Returns the loadings, if available.
getLoadings() - Method in class adams.data.instancesanalysis.pls.VCPLS: Returns the loadings, if available.
getLoadings() - Method in class weka.classifiers.functions.PLSWeighted: Returns the loadings, if available.
getLoadings() - Method in interface weka.core.GenericPLSMatrixAccess: Returns the loadings, if available.
getLoadings() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the loadings, if available.
getLoadings() - Method in class weka.filters.supervised.attribute.PLS: Returns the loadings, if available.
getLoadingsCalculations() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: returns the maximum number of attributes to use.
getLocal() - Method in class weka.classifiers.meta.SocketFacade: Returns the return address for the remote process to use.
getLocale() - Method in class adams.ml.data.InstancesView: Returns the current locale.
getLocations() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the locations of the data (indices/regular expressions on attribute name).
getLocations() - Method in class adams.flow.transformer.WekaInstancesStatistic: Returns the locations of the data (indices/regular expressions on attribute name).
getLoClassifier() - Method in class weka.classifiers.meta.HighLowSplit
getLog() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns the internal log buffer.
getLogPanel() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: Returns the log panel.
getLoHipoint() - Method in class weka.classifiers.meta.HighLowSplit
getLoHipoint() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier
getLower() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Returns the lower value to output.
getLower() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Returns the lower value to output.
getLower() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Returns the lower value to output.
getLower() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the lower value to output.
getM5RootNode() - Method in class weka.classifiers.trees.m5.M5Base2
getM5RootNode() - Method in class weka.classifiers.trees.m5.Rule2
getMainFilter() - Method in class weka.filters.FilteredFilter: Returns the main filter in use.
getMakeClassLast() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns whether to make the class attribute the last attribute.
getMakeThreadSafe() - Method in class adams.flow.transformer.WekaModelReader: Returns whether to wrap classifier inside a threadsafe ThreadSafeClassifierWrapper wrapper.
getManualClassifier() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns the manual to use instead of obtaining it from the flow.
getManualClassifier() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Returns the manual to use instead of obtaining it from the flow.
getManualMax() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the maximum to use when using manual binning with user-supplied max/max enabled.
getManualMin() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the minimum to use when using manual binning with user-supplied min/max enabled.
getMappedAttributeName(AbstractMerge.SourceAttribute) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the name of the attribute in the merged dataset that the given source attribute maps to.
getMappedAttributeName(AbstractMerge.SourceAttribute) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Gets the name of the attribute in the merged dataset that the given source attribute maps to.
getMarkerExtent() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Returns the current marker extent (which is the width and height of the shape).
getMarkerShape(int) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Determines the shape to paint around the data points, based on the index of the data.
getMaskAsString() - Method in class adams.opt.genetic.DarkLord.DarkLordJob: Returns the "mask" of attributes as range string.
getMatrix() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess: Returns the name of matrix to extract.
getMatrix() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter
getMatrix() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
getMatrix(String) - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns the matrix with the specified name.
getMatrix(String) - Method in class adams.data.instancesanalysis.pls.DIPLS: Returns the matrix with the specified name.
getMatrix(String) - Method in class adams.data.instancesanalysis.pls.KernelPLS: Returns the matrix with the specified name.
getMatrix(String) - Method in class adams.data.instancesanalysis.pls.NIPALS: Returns the matrix with the specified name.
getMatrix(String) - Method in class adams.data.instancesanalysis.pls.OPLS: Returns the matrix with the specified name.
getMatrix(String) - Method in class adams.data.instancesanalysis.pls.PLS1: Returns the matrix with the specified name.
getMatrix(String) - Method in class adams.data.instancesanalysis.pls.PRM: Returns the matrix with the specified name.
getMatrix(String) - Method in class adams.data.instancesanalysis.pls.SIMPLS: Returns the matrix with the specified name.
getMatrix(String) - Method in class adams.data.instancesanalysis.pls.SparsePLS: Returns the matrix with the specified name.
getMatrix(String) - Method in class adams.data.instancesanalysis.pls.VCPLS: Returns the matrix with the specified name.
getMatrix(String) - Method in class weka.classifiers.functions.PLSWeighted: Returns the matrix with the specified name.
getMatrix(String) - Method in interface weka.core.GenericPLSMatrixAccess: Returns the matrix with the specified name.
getMatrix(String) - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the matrix with the specified name.
getMatrix(String) - Method in class weka.filters.supervised.attribute.PLS: Returns the matrix with the specified name.
getMatrix(Classifier) - Method in class adams.flow.transformer.WekaExtractPLSMatrix: Returns the spreadsheet representation of the chosen from the classifier.
getMatrix(Classifier) - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess: Returns the spreadsheet representation of the chosen from the classifier.
getMatrix(GenericPLSMatrixAccess) - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess: Returns the spreadsheet representation of the chosen from the classifier/filter.
getMatrix(PLSMatrixAccess) - Method in class adams.flow.transformer.WekaExtractPLSMatrix: Returns the spreadsheet representation of the chosen from the classifier/filter.
getMatrixNames() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns the all the available matrices.
getMatrixNames() - Method in class adams.data.instancesanalysis.pls.DIPLS: Returns the all the available matrices.
getMatrixNames() - Method in class adams.data.instancesanalysis.pls.KernelPLS: Returns the all the available matrices.
getMatrixNames() - Method in class adams.data.instancesanalysis.pls.NIPALS: Returns the all the available matrices.
getMatrixNames() - Method in class adams.data.instancesanalysis.pls.OPLS: Returns the all the available matrices.
getMatrixNames() - Method in class adams.data.instancesanalysis.pls.PLS1: Returns the all the available matrices.
getMatrixNames() - Method in class adams.data.instancesanalysis.pls.PRM: Returns the all the available matrices.
getMatrixNames() - Method in class adams.data.instancesanalysis.pls.SIMPLS: Returns the all the available matrices.
getMatrixNames() - Method in class adams.data.instancesanalysis.pls.SparsePLS: Returns the all the available matrices.
getMatrixNames() - Method in class adams.data.instancesanalysis.pls.VCPLS: Returns the all the available matrices.
getMatrixNames() - Method in class weka.classifiers.functions.PLSWeighted: Returns the all the available matrices.
getMatrixNames() - Method in interface weka.core.GenericPLSMatrixAccess: Returns the all the available matrices.
getMatrixNames() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the all the available matrices.
getMatrixNames() - Method in class weka.filters.supervised.attribute.PLS: Returns the all the available matrices.
getMatrixType() - Method in class adams.flow.transformer.WekaExtractPLSMatrix: Returns the type of matrix to extract.
getMatrixValues() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Returns the type of values to generate.
getMax() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the maximum number of top-ranked classifiers to forward.
getMax() - Method in class weka.classifiers.trees.RandomModelTrees
getMax() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
getMax() - Method in class weka.filters.unsupervised.instance.Scale: Returns the maximum for the values.
getMaxAttributeNames() - Method in class adams.data.instancesanalysis.PCA: Returns the maximum number of attribute names.
getMaxAttributes() - Method in class adams.data.instancesanalysis.PCA: Returns the maximum attributes.
getMaxBin() - Method in class weka.classifiers.trees.XGBoost: Gets the maximum number of discrete bins to bucket continuous features.
getMaxClassRangePercentage() - Method in class weka.classifiers.meta.MinMaxLimits: Get the percentage of leeway to apply to the upper limit determaxed by the range of the class attribute in the training data.
getMaxDecimalPlaces() - Method in class weka.core.converters.SimpleArffSaver: Returns the maximum number of decimal places to print
getMaxDepth() - Method in class weka.classifiers.trees.XGBoost: Gets the maximum depth of a tree.
getMaxDifference() - Method in class weka.classifiers.meta.AbstainAverage: gets number of samples
getMaxDifference() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: gets number of samples
getMaxDifference() - Method in class weka.classifiers.meta.AbstainVote: gets number of samples
getMaxDisplayItems() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Returns the maximum number of array items to display via toString().
getMaxFactor() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns the upper limit for the multiplication factor for instances.
getMaxHandling() - Method in class weka.classifiers.meta.MinMaxLimits: Get how the upper limit is handled.
getMaximum() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the maximum.
getMaximum() - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns the maximum.
getMaximum() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Returns the maximum.
getMaximumAttributeNames() - Method in class adams.flow.transformer.WekaPrincipalComponents: Gets maximum number of attribute names to use.
getMaximumAttributeNames() - Method in class weka.core.neighboursearch.PCANNSearch: Gets maximum number of attributes to include in transformed attribute names.
getMaximumAttributeNames() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Gets maximum number of attributes to include in transformed attribute names.
getMaximumAttributes() - Method in class adams.flow.transformer.WekaPrincipalComponents: Gets maximum number of PC attributes to retain.
getMaximumAttributes() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Gets maximum number of PC attributes to retain.
getMaximumDeltaStep() - Method in class weka.classifiers.trees.XGBoost: Gets the maximum delta step we allow each leaf output to be.
getMaximumIncluded() - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns whether the maximum is included.
getMaximumIncluded() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Returns whether the maximum is included.
getMaxIter() - Method in class adams.data.instancesanalysis.pls.KernelPLS: Sets the inner NIPALS loop improvement tolerance.
getMaxIter() - Method in class adams.data.instancesanalysis.pls.NIPALS: Returns the NIPALS loop maximum number of iterations.
getMaxIter() - Method in class adams.data.instancesanalysis.pls.PRM: Returns the NIPALS loop maximum number of iterations.
getMaxIter() - Method in class adams.data.instancesanalysis.pls.SparsePLS: Returns the NIPALS loop maximum number of iterations.
getMaxIterations() - Method in class weka.clusterers.SAXKMeans: gets the number of maximum iterations to be executed.
getMaxIterations() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Gets the maximum number of cleansing iterations performed
getMaxIterations() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Gets the maximum number of cleansing iterations performed
getMaxLabels() - Method in class adams.data.conversion.SpreadSheetToWekaInstances: Returns the name of the global actor in use.
getMaxLabels() - Method in class adams.data.spreadsheet.filter.WekaFilter: Returns the name of the global actor in use.
getMaxLeaves() - Method in class weka.classifiers.trees.XGBoost: Gets the maximum number of nodes to be added.
getMaxLevels() - Method in class weka.classifiers.meta.ClassifierCascade: the maximum number of levels in the cascade.
getMaxManual() - Method in class weka.classifiers.meta.MinMaxLimits: Get the manual upper limit.
getMaxNeighbors() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns the maximum number of neighbors to find.
getMaxSize() - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler: Returns the maximum size for the errors.
getMaxTrainTime() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns the maximum number of seconds to perform training.
getMaxVal() - Method in class adams.opt.optimise.genetic.PackDataDef.DataInfo
getMaxVersion() - Method in class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors: Get the maximum version of Weka, exclusive, the class is designed to work with.
getMaxVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrors: Get the maximum version of Weka, exclusive, the class is designed to work with.
getMaxVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrorsPlot: Get the maximum version of Weka, exclusive, the class is designed to work with.
getMaxVersion() - Method in class weka.gui.visualize.plugins.SaveGraph: Get the maximum version of Weka, exclusive, the class is designed to work with.
getMaxVersion() - Method in class weka.gui.visualize.plugins.SaveTree: Get the maximum version of Weka, exclusive, the class is designed to work with.
getMaxVersion() - Method in class weka.gui.visualize.plugins.ThresholdCurves: Get the maximum version of Weka, exclusive, the class is designed to work with.
getMeanStdev(Instance) - Method in class weka.filters.unsupervised.attribute.PAA: Return an array where the 1st value is the mean, and the 2nd the standard deviation of the attribute values.
getMeanStdev(Instance) - Method in class weka.filters.unsupervised.attribute.SAX: Return an array where the 1st value is the mean, and the 2nd the standard deviation of the attribute values.
getMeasure() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the measure used for ranking the classifiers.
getMeasure() - Method in enum adams.flow.transformer.WekaClassifierRanker.Measure: Returns the associated measure.
getMeasure() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Returns the measure for ranking.
getMeasure() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Returns the measure used for evaluating the fitness.
getMeasure() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the current measure for evaluating the fitness.
getMeasure() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the current measure for evaluating the fitness.
getMeasure(String) - Method in class weka.classifiers.trees.m5.M5Base2: Returns the value of the named measure
getMeasuresPrefix() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the prefix for the measure attributes.
getMenuBar() - Method in class adams.gui.tools.DatasetCompatibilityPanel: Creates a menu bar (singleton per panel object).
getMenuBar() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Creates a menu bar (singleton per panel object).
getMenuBar() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Creates a menu bar (singleton per panel object).
getMenuBar() - Method in class adams.gui.visualization.instance.InstanceComparePanel: Creates a menu bar (singleton per panel object).
getMenuBar() - Method in class adams.gui.visualization.instance.InstanceExplorer: Creates a menu bar (singleton per panel object).
getMenuBar() - Method in class weka.gui.explorer.ExplorerExt: Creates a menu bar (singleton per panel object).
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: Returns the name for the menu item.
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: Returns the name for the menu item.
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.AttributeStatistics: Returns the name for the menu item.
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.Binning: Returns the name for the menu item.
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight: Returns the name for the menu item.
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.ColumnStatistic: Returns the name for the menu item.
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.DataSort: Returns the name for the menu item.
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.Histogram: Returns the name for the menu item.
getMenuItem() - Method in interface adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItem: Returns the name for the menu item.
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.JFreeChart: Returns the name for the menu item.
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.RowStatistic: Returns the name for the menu item.
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.SimplePlot: Returns the name for the menu item.
getMenuItem() - Method in class adams.gui.visualization.instances.instancestable.ViewCell: Returns the name for the menu item.
getMenuItemText() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: Returns the (optional) cuistom menu item text.
getMenuItemText() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: Returns the (optional) cuistom menu item text.
getMergedIndex() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Gets the position for the merged attribute.
getMergedIndex() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Gets the position for the merged attribute.
getMergeMethod() - Method in class adams.flow.transformer.WekaDatasetsMerge: Gets the currently-set merge method.
getMessage() - Method in class adams.flow.transformer.WekaChooseAttributes: Returns the message to display to the user (variables get expanded).
getMetaDataColor() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the scheme for extracting the color from the meta-data.
getMetaLevelClassifier() - Method in class weka.classifiers.meta.PartitionedStacking: Returns the meta-level classifier.
getMethodNamePrediction() - Method in class weka.classifiers.functions.PyroProxy: Returns the name of the method to call for predictions.
getMethodNameTrain() - Method in class weka.classifiers.functions.PyroProxy: Returns the name of the method to call for training.
getMetricDescription() - Method in class weka.classifiers.evaluation.Bias: Get a short description of this metric (algorithm, forumulas etc.).
getMetricDescription() - Method in class weka.classifiers.evaluation.Dice: Get a short description of this metric (algorithm, forumulas etc.).
getMetricDescription() - Method in class weka.classifiers.evaluation.MSLE: Get a short description of this metric (algorithm, forumulas etc.).
getMetricDescription() - Method in class weka.classifiers.evaluation.RPD: Get a short description of this metric (algorithm, formulas etc.).
getMetricDescription() - Method in class weka.classifiers.evaluation.RSquared: Get a short description of this metric (algorithm, forumulas etc.).
getMetricDescription() - Method in class weka.classifiers.evaluation.SDR: Get a short description of this metric (algorithm, formulas etc.).
getMetricName() - Method in class weka.classifiers.evaluation.Bias: Get the name of this metric
getMetricName() - Method in class weka.classifiers.evaluation.Dice: Get the name of this metric
getMetricName() - Method in class weka.classifiers.evaluation.MSLE: Get the name of this metric
getMetricName() - Method in class weka.classifiers.evaluation.RPD: Get the name of this metric
getMetricName() - Method in class weka.classifiers.evaluation.RSquared: Get the name of this metric
getMetricName() - Method in class weka.classifiers.evaluation.SDR: Get the name of this metric
getMiddle(double[]) - Method in class weka.core.SAXDistance: Returns value in the middle of the two parameter values.
getMiddle(double[]) - Method in class weka.core.WeightedEuclideanDistance: Returns value in the middle of the two parameter values.
getMiddle(double[]) - Method in class weka.core.WeightedEuclideanDistanceRidge: Returns value in the middle of the two parameter values.
getMin() - Method in class weka.classifiers.trees.RandomRegressionForest: Gets the current leaf threshold.
getMin() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
getMin() - Method in class weka.filters.unsupervised.instance.Scale: Returns the minimum for the values.
getMinChildWeight() - Method in class weka.classifiers.trees.XGBoost: Gets the minimum sum of instance weights (hessian) needed in a child.
getMinClassRangePercentage() - Method in class weka.classifiers.meta.MinMaxLimits: Get the percentage of leeway to apply to the lower limit determined by the range of the class attribute in the training data.
getMinHandling() - Method in class weka.classifiers.meta.MinMaxLimits: Get how the lower limit is handled.
getMinimal() - Method in class weka.attributeSelection.LinearRegressionAttributeEval: Returns whether to be more memory conservative or being able to output the model as string.
getMinimal() - Method in class weka.classifiers.functions.LinearRegressionJ: Returns whether to be more memory conservative or being able to output the model as string.
getMinImprovement() - Method in class weka.classifiers.meta.ClassifierCascade: the minimum improvement between levels that the statistic must improve.
getMinimum() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the minimum.
getMinimum() - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns the minimum.
getMinimum() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Returns the minimum.
getMinimumIncluded() - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns whether the minimum is included.
getMinimumIncluded() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Returns whether the minimum is included.
getMinManual() - Method in class weka.classifiers.meta.MinMaxLimits: Get the manual lower limit.
getMinNumInstances() - Method in class weka.classifiers.trees.m5.M5Base2: Get the minimum number of instances to allow at a leaf node
getMinNumInstances() - Method in class weka.classifiers.trees.m5.Rule2: Get the minimum number of instances to allow at a leaf node
getMinNumInstances() - Method in class weka.classifiers.trees.m5.RuleNode2: Get the minimum number of instances to allow at a leaf node
getMinProbability() - Method in class weka.classifiers.meta.AbstainMinimumProbability: Returns the minimum probability that the chosen class label must meet.
getMinProbability() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Returns the minimum probability for the selected label.
getMinSamples() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Returns the minimum number of samples that are required for calculating IQR stats.
getMinVersion() - Method in class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors: Get the minimum version of Weka, inclusive, the class is designed to work with.
getMinVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrors: Get the minimum version of Weka, inclusive, the class is designed to work with.
getMinVersion() - Method in class weka.gui.visualize.plugins.FixedClassifierErrorsPlot: Get the minimum version of Weka, inclusive, the class is designed to work with.
getMinVersion() - Method in class weka.gui.visualize.plugins.SaveGraph: Get the minimum version of Weka, inclusive, the class is designed to work with.
getMinVersion() - Method in class weka.gui.visualize.plugins.SaveTree: Get the minimum version of Weka, inclusive, the class is designed to work with.
getMinVersion() - Method in class weka.gui.visualize.plugins.ThresholdCurves: Get the minimum version of Weka, inclusive, the class is designed to work with.
getMissing() - Method in class adams.tools.CompareDatasets: Returns the first dataset for the comparison.
getModel() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: Returns the stored model object.
getModel() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns the stored model object.
getModel() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns the stored model object.
getModel() - Method in class adams.gui.visualization.instances.InstancesPanel: Returns the model in use.
getModel() - Method in class weka.classifiers.trees.m5.RuleNode2: Get the linear model at this node
getModel(Report) - Static method in class adams.gui.visualization.instance.InstanceReportFactory: Returns a new model for the given report.
getModelActor() - Method in class adams.flow.condition.bool.WekaClassification: Returns the callable actor to obtain the model from if model file is pointing to a directory.
getModelActor() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the filter source actor.
getModelActor() - Method in class adams.flow.transformer.WekaFilter: Returns the filter source actor.
getModelContainerClass() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the model container class that is supported.
getModelDescription() - Method in class adams.ml.model.classification.WekaClassificationModel: Gets a short string description of the model.
getModelDescription() - Method in class adams.ml.model.clustering.WekaClusteringModel: Gets a short string description of the model.
getModelDescription() - Method in class adams.ml.model.regression.WekaRegressionModel: Gets a short string description of the model.
getModelFile() - Method in class adams.flow.condition.bool.WekaClassification: Returns the file to load the model from.
getModelFile() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the file to load the model from.
getModelFile() - Method in class adams.flow.transformer.WekaFilter: Returns the file to load the model from.
getModelFromContainer(AbstractContainer) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Retrieves the model from the container.
getModelFromContainer(AbstractContainer, MessageCollection) - Method in class adams.flow.core.WekaClassifierModelLoader: Retrieves the model from the container.
getModelFromContainer(AbstractContainer, MessageCollection) - Method in class adams.flow.core.WekaClustererModelLoader: Retrieves the model from the container.
getModelFromContainer(AbstractContainer, MessageCollection) - Method in class adams.flow.core.WekaFilterModelLoader: Retrieves the model from the container.
getModelLoadingType() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the loading type.
getModelLoadingType() - Method in class adams.flow.transformer.WekaFilter: Returns the loading type.
getModelName() - Method in class weka.classifiers.functions.PyroProxy: Returns the name of the model to use.
getModelResetVariable() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the variable to monitor for changes in order to reset the model.
getModelStorage() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the filter storage item.
getModelStorage() - Method in class adams.flow.transformer.WekaFilter: Returns the filter storage item.
getMorphologies() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Returns the morphologies to apply.
getMultiplier() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev: Returns the multiplier for the stdev..
getN() - Method in class weka.core.SAXDistance: Returns the nth point setting.
getN() - Method in class weka.filters.supervised.attribute.YGradientEPO: Returns the number of eigenvectors to keep.
getName() - Method in class adams.data.weka.classattribute.ByExactName: Returns the name in use.
getName() - Method in class adams.data.weka.columnfinder.ByExactName: Returns the name in use.
getName() - Method in class adams.gui.goe.popupmenu.EncloseClassifier: The name used for sorting.
getName() - Method in class adams.gui.goe.popupmenu.EncloseClusterer: The name used for sorting.
getName() - Method in class adams.gui.goe.popupmenu.InvertInstancesColumnFinder: The name used for sorting.
getName() - Method in class adams.gui.goe.popupmenu.InvertInstancesRowFinder: The name used for sorting.
getName() - Method in class adams.gui.goe.popupmenu.PullUpClassifier: The name used for sorting.
getName() - Method in class adams.gui.goe.popupmenu.PullUpClusterer: The name used for sorting.
getName() - Method in class adams.gui.goe.popupmenu.PullUpInstancesColumnFinder: The name used for sorting.
getName() - Method in class adams.gui.goe.popupmenu.PullUpInstancesRowFinder: The name used for sorting.
getName() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: Returns the name of the item.
getName() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Returns the name of the evaluation (displayed in combobox).
getName() - Method in class adams.gui.visualization.instance.containerlistpopup.SaveAs: The name.
getName() - Method in class adams.gui.visualization.instance.containerlistpopup.ViewAsTable: The name.
getName() - Method in class adams.gui.visualization.instance.plotpopup.Adjust: The name.
getName() - Method in class adams.gui.visualization.instance.plotpopup.Histogram: The name.
getName() - Method in class adams.gui.visualization.instance.plotpopup.SaveVisible: The name.
getName() - Method in class adams.gui.visualization.instance.plotpopup.Viewport: The name.
getName() - Method in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer: Returns the name of the column.
getName() - Method in class adams.ml.data.InstancesView: Returns the name of the spreadsheet.
getName() - Method in class adams.opt.optimise.genetic.PackDataDef.DataInfo
getName(Attribute, int) - Method in class adams.data.weka.WekaLabelIndex: Returns the label name at the specified index.
getName(Attribute, int) - Method in class adams.data.weka.WekaLabelRange: Returns the column name at the specified index.
getName(Instances, int) - Method in class adams.data.weka.WekaAttributeIndex: Returns the column name at the specified index.
getName(Instances, int) - Method in class adams.data.weka.WekaAttributeRange: Returns the column name at the specified index.
getName(Instances, int) - Method in class adams.data.weka.WekaUnorderedAttributeRange: Returns the column name at the specified index.
getNameLowerCase() - Method in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer: Returns the name of the column in lowercase.
getNames() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Returns the names to use for the fusion subsets (corresponds to the subsets).
getNameServer() - Method in class weka.classifiers.functions.PyroProxy: Returns the address of the Pyro nameserver.
getNameServer() - Method in interface weka.core.PyroProxyObject: Returns the address of the Pyro nameserver.
getNameSuffix() - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem: Returns the name suffix of the item.
getNative() - Method in class adams.ml.data.DataCellView: Returns the cell as native object, according to its type.
getNearestNeighbourSearchAlgorithm() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Returns the current nearestNeighbourSearch algorithm in use.
getNestedItem(String) - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem: Returns the nested items by its name.
getNewFilter() - Method in class adams.data.conversion.SwapPLS: Returns the new PLS filter to replace with.
getNextInstance(Instances) - Method in class weka.core.converters.SimpleArffLoader: Not supported.
getNextInstance(Instances) - Method in class weka.core.converters.SpreadSheetLoader: SpreadSheetLoader is unable to process a data set incrementally.
getNextSelectedIndex(int[], int) - Method in class adams.data.weka.datasetsplitter.RowSplitter: Gets the next index selected by the row-finder.
getNoAdditionalFieldsPrefix() - Method in interface adams.data.instances.InstanceGeneratorWithAdditionalFields: Returns whether to drop the prefix for the additional fields.
getNoCheck() - Method in class adams.flow.transformer.WekaExperiment: Returns whether to avoid the check at setUp time whether the experiment file is present or not.
getNoise() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Get the value of noise.
getNoise() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Get the value of noise.
getNoise() - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Get the value of noise.
getNoise() - Method in class weka.classifiers.functions.GPD: Get the value of noise.
getNominal() - Method in class weka.filters.unsupervised.attribute.SAX: Gets whether output numeric or nominal values.
getNoReplacement() - Method in class weka.classifiers.meta.VotedImbalance: Gets whether instances are drawn with or without replacement.
getNormaliseType() - Method in class weka.classifiers.trees.XGBoost: Gets the type of normalisation algorithm.
getNormalize() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns whether to normalize the data before generating the histogram.
getNormalPlotOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: get the options for the normal plot.
getNormYWeights() - Method in class adams.data.instancesanalysis.pls.NIPALS: Returns whether to normalize Y weights.
getNoteName(String) - Static method in class adams.data.weka.ArffUtils: Returns the name of an attribute for a note.
getNotes() - Method in class adams.data.instance.Instance: Returns the currently stored notes.
getNotes() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the notes for the experiment.
getNoUpdate() - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Returns whether to suppress the update of the nearest-neighbor search algorithm when making predictions.
getNoUpdate() - Method in class weka.classifiers.lazy.LWLSynchro: Returns whether to suppress the update of the nearest-neighbor search algorithm when making predictions.
getNoUpdate() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter: Returns whether to suppress the update of the nearest-neighbor search algorithm when making predictions.
getNoUpdate() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Returns whether to suppress the update of the nearest-neighbor search algorithm when making predictions.
getNthPoint() - Method in class weka.filters.unsupervised.attribute.DownSample: Returns the nth point setting.
getNumattrs() - Method in class weka.classifiers.meta.Corr
getNumBalanced() - Method in class weka.classifiers.meta.VotedImbalance: Returns the number of balanced datasets to generate (= #classifiers).
getNumberFormat() - Method in class adams.ml.data.InstancesView: Returns the number formatter.
getNumberInSubset() - Method in class weka.filters.unsupervised.instance.KennardStone: Returns the number of rows to select in subset.
getNumberOfParallelTrees() - Method in class weka.classifiers.trees.XGBoost: Gets the number of parallel trees constructed during each iteration.
getNumberOfRounds() - Method in class weka.classifiers.trees.XGBoost: Gets the number of boosting rounds to perform.
getNumBins() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the number of bins to use in manual calculation.
getNumBits() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the number of required bits.
getNumBits(AbstractGeneticDiscoveryHandler[]) - Method in class adams.opt.genetic.Hermione: Get total number of bits for params
getNumBitsForAll(AbstractGeneticDiscoveryHandler[]) - Method in class adams.opt.genetic.Hermione: Get List containing number of bits used for params
getNumChrom() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns the number of chromosomes to use.
getNumClusters() - Method in class weka.clusterers.SAXKMeans: gets the number of clusters to generate.
getNumCoefficients() - Method in class adams.data.instancesanalysis.pls.SIMPLS: returns the number of coefficients of W matrix to keep (rest gets zeroed).
getNumComponents() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: returns the maximum number of attributes to use.
getNumComponents() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: returns the maximum number of attributes to use.
getNumComponents() - Method in class weka.core.neighboursearch.PLSNNSearch
getNumComponents(Object) - Method in class adams.data.conversion.SwapPLS: Retrieves the number of components from the filter.
getNumCycles() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Returns the number of cycles to apply.
getNumDecimals() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the number of decimals to show in the bin description.
getNumDecimals() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Returns the currently set number of decimals.
getNumDecimals() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Returns the number of decimals to use for numeric values.
getNumDecimals() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Returns the number of decimals to use for numeric values.
getNumEvaluationBins() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Returns the number of bins to use during evaluation.
getNumExecutionSlots() - Method in class weka.classifiers.meta.SubsetEnsemble: Get the number of execution slots (threads) to use for building the members of the ensemble.
getNumExecutionSlots() - Method in class weka.classifiers.meta.VotedImbalance: Get the number of execution slots (threads) to use for building the members of the ensemble.
getNumExecutionSlots() - Method in class weka.clusterers.SAXKMeans: Get the degree of parallelism to use.
getNumFolds() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Returns the number of folds.
getNumFolds() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the number of folds.
getNumFolds() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns the number of folds.
getNumFolds() - Method in interface weka.classifiers.CrossValidationFoldGenerator: Returns the number of folds.
getNumFolds() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns the number of folds.
getNumFolds() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the number of folds.
getNumFolds() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the number of folds.
getNumFolds() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns the number of folds.
getNumFolds() - Method in class weka.classifiers.meta.ClassifierCascade: the number of folds for cross-validation.
getNumFolds() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the number of folds to use in CV.
getNumFolds() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Gets the number of cross-validation folds used by the filter.
getNumFolds() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Gets the number of cross-validation folds used by the filter.
getNumGenes() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns the number of genes to use.
getNumInstances() - Method in class weka.classifiers.trees.m5.RuleNode2: Return the number of instances that reach this node.
getNumIterations() - Method in class weka.classifiers.trees.RandomModelTrees: Gets the number of iterations.
getNumIterations() - Method in class weka.classifiers.trees.RandomRegressionForest: Gets the number of iterations
getNumNames(Attribute) - Method in class adams.data.weka.WekaLabelIndex: Returns the number of labels that the attribute has.
getNumNames(Attribute) - Method in class adams.data.weka.WekaLabelRange: Returns the number of columns the dataset has.
getNumNames(Instances) - Method in class adams.data.weka.WekaAttributeIndex: Returns the number of columns the dataset has.
getNumNames(Instances) - Method in class adams.data.weka.WekaAttributeRange: Returns the number of columns the dataset has.
getNumNames(Instances) - Method in class adams.data.weka.WekaUnorderedAttributeRange: Returns the number of columns the dataset has.
getNumPoints() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves: Returns the number of points to generate.
getNumPoints() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the number of points to output.
getNumPoints() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Returns the number of points to the left of a data point.
getNumPointsLeft() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns the number of points to the left of a data point.
getNumPointsRight() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns the number of points to the right of a data point.
getNumRandomFeatures() - Method in class weka.classifiers.meta.SubsetEnsemble: Returns the number of additional random features to use.
getNumRegressions() - Method in class weka.classifiers.meta.AbstainLeastMedianSq: gets number of samples
getNumRegressions() - Method in class weka.classifiers.meta.LeastMedianSq: gets number of samples
getNumRows() - Method in class adams.data.conversion.WekaCapabilitiesToInstances: Returns the number of data rows to generate.
getNumSimplsCoefficients() - Method in class adams.data.instancesanalysis.pls.PRM: Returns the number of SIMPLS coefficients to keep.
getNumSubSamples() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the number of sub-samples to generate.
getNumThreads() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the number of threads in use.
getNumThreads() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the number of threads to use for cross-validation.
getNumThreads() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the number of threads to use for cross-validation.
getNumThreads() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the number of threads to use for cross-validation (only used if no JobRunnerSetup/JobRunner set).
getNumThreads() - Method in class weka.classifiers.meta.ClassifierCascade: the number of threads to use.
getNumThreads() - Method in class weka.classifiers.trees.XGBoost: Gets the number of parallel threads used to run XGBoost.
getNumThreads() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the number of threads to use for cross-validation.
getNumZeroes() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Returns the number of zeroes a row must have at least in order to be removed.
getObject() - Method in class adams.ml.data.DataCellView: Returns the object.
getObjective() - Method in class weka.classifiers.trees.XGBoost: Gets the learning objective.
getOffline() - Method in class adams.data.instances.AbstractInstanceGenerator: Returns whether the generator operates in offline mode.
getOldFilter() - Method in class adams.data.conversion.SwapPLS: Returns the old PLS filter to replace.
getOneDrop() - Method in class weka.classifiers.trees.XGBoost: Sets whether at least one tree is always dropped during the dropout.
getOneMissing() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Gets the type of strategy to apply if one of the values is missing.
getOneMissing() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Gets the type of strategy to apply if one of the values is missing.
getOnlyFirstBatch() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Returns whether to apply row finder during first batch.
getOnTheFly() - Method in class adams.flow.condition.bool.WekaClassification: Returns whether the model file gets built on the fly and might not be present at start up time.
getOnTheFly() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns whether the model file gets built on the fly and might not be present at start up time.
getOnTheFly() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns whether the reference file gets built on the fly and might not be present at start up time.
getOpenFileFilters() - Method in class adams.gui.chooser.AdamsExperimentFileChooser: Returns the file filters for opening files.
getOpenFileFilters() - Method in class adams.gui.chooser.WekaFileChooser: Returns the file filters for opening files.
getOperation() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns the way the buffer operates.
getOptimizer() - Method in class adams.flow.transformer.WekaClassifierOptimizer: Returns the optimizer in use.
getOptional() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns whether the callable sink is optional.
getOptions() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.attributeSelection.LinearRegressionAttributeEval
getOptions() - Method in class weka.classifiers.functions.ClassificationViaPLS: returns the options of the current setup
getOptions() - Method in class weka.classifiers.functions.FakeClassifier: returns the options of the current setup
getOptions() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.GeneticAlgorithm: returns the options of the current setup
getOptions() - Method in class weka.classifiers.functions.GPD: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.LinearRegressionJ: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.MathExpressionClassifier: returns the options of the current setup
getOptions() - Method in class weka.classifiers.functions.PLSClassifierWeighted: returns the options of the current setup
getOptions() - Method in class weka.classifiers.functions.PLSWeighted: returns the options of the current setup
getOptions() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.lazy.LWLSynchro: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.meta.AbstainAttributePercentile: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.AbstainAverage: Gets the current settings of Vote.
getOptions() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Gets the current settings of Vote.
getOptions() - Method in class weka.classifiers.meta.AbstainingCascade: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.AbstainMinimumProbability: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.AbstainVote: Gets the current settings of Vote.
getOptions() - Method in class weka.classifiers.meta.ClassifierCascade: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.meta.Consensus: Gets the current settings of Vote.
getOptions() - Method in class weka.classifiers.meta.ConsensusOrVote: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.Corr: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.Fallback: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.FilteredClassifierExt: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.HighLowSplit: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.InputSmearing: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.LeastMedianSq: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.MinMaxLimits: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.meta.PartitionedStacking: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.SocketFacade: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.meta.SubsetEnsemble: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.meta.SuppressModelOutput: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.Veto: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.meta.VotedImbalance: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.trees.m5.M5Base2: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.trees.M5P2: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.trees.RandomModelTrees: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.trees.RandomRegressionForest: Gets the current settings of the Classifier.
getOptions() - Method in class weka.clusterers.SAXKMeans: Gets the current settings of SimpleKMeans.
getOptions() - Method in class weka.core.AbstractSimpleOptionHandler: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.core.converters.SimpleArffLoader: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.core.converters.SimpleArffSaver: returns the options of the current setup
getOptions() - Method in class weka.core.converters.SpreadSheetLoader: Gets the setting
getOptions() - Method in class weka.core.converters.SpreadSheetSaver: returns the options of the current setup
getOptions() - Method in class weka.core.neighboursearch.FilteredSearch
getOptions() - Method in class weka.core.neighboursearch.NewNNSearch: Gets the current settings.
getOptions() - Method in class weka.core.neighboursearch.PCANNSearch
getOptions() - Method in class weka.core.neighboursearch.PLSNNSearch
getOptions() - Method in class weka.core.SAXDistance: Gets the current settings of the filter.
getOptions() - Method in class weka.core.tokenizers.cleaners.AbstractTokenCleaner: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.core.tokenizers.cleaners.MultiCleaner: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.core.tokenizers.MultiTokenizer: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.core.WeightedEuclideanDistanceRidge: Gets the current settings of the classifier.
getOptions() - Method in class weka.experiment.ResultMatrixMediaWiki: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.filters.FilteredFilter: Gets the current settings of the classifier.
getOptions() - Method in class weka.filters.FlowFilter: returns the options of the current setup.
getOptions() - Method in class weka.filters.SerializedFilter: returns the options of the current setup.
getOptions() - Method in class weka.filters.supervised.attribute.MultiPLS: returns the options of the current setup
getOptions() - Method in class weka.filters.supervised.attribute.PLS: returns the options of the current setup
getOptions() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.filters.supervised.attribute.YGradientEPO: returns the options of the current setup
getOptions() - Method in class weka.filters.supervised.attribute.YGradientGLSW: returns the options of the current setup
getOptions() - Method in class weka.filters.supervised.instance.RemoveOutliers: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Gets the current settings of the classifier.
getOptions() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.AnyToString: Gets the current settings of the Classifier.
getOptions() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: returns the options of the current setup
getOptions() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: returns the options of the current setup.
getOptions() - Method in class weka.filters.unsupervised.attribute.Detrend: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.filters.unsupervised.attribute.DownSample: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.filters.unsupervised.attribute.FastWavelet: returns the options of the current setup.
getOptions() - Method in class weka.filters.unsupervised.attribute.FFT: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.InputSmearing: Gets the current settings of the Classifier.
getOptions() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.LogTransform: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: returns the options of the current setup.
getOptions() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: returns the options of the current setup.
getOptions() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Gets the current settings of the Classifier.
getOptions() - Method in class weka.filters.unsupervised.attribute.PAA: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.SAX: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.SetMissingValue: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.filters.unsupervised.attribute.SpellChecker: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.StringToDate: Gets the current settings of the Classifier.
getOptions() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Gets the current settings of the classifier.
getOptions() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Gets the current settings of the classifier.
getOptions() - Method in class weka.filters.unsupervised.instance.AlignDataset: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Gets the current settings of the classifier.
getOptions() - Method in class weka.filters.unsupervised.instance.KeepRange: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.KennardStone: Gets the current settings of the classifier.
getOptions() - Method in class weka.filters.unsupervised.instance.LatestRecords: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Gets the current settings of the classifier.
getOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor: Gets the current settings of the classifier.
getOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Gets the current settings of the classifier.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: returns the options of the current setup.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.Scale: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.Sort: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.SortOnAttribute: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Gets the current settings of the filter.
getOptions(Object) - Method in class adams.core.option.WekaCommandLineHandler: Returns the commandline options (without classname) of the specified object.
getOriginalIndices() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns the stored original indices.
getOriginalIndices() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the original indices.
getOtherParameters() - Method in class weka.classifiers.trees.XGBoost: Gets any other XGBoost parameters the user has set.
getOutput() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Returns the prediction output generator in use.
getOutput() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput: Returns the output generator in use.
getOutput() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the prediction output generator in use.
getOutputAdditionalStats() - Method in class weka.attributeSelection.LinearRegressionAttributeEval: Get whether to output additional statistics (such as std.
getOutputAdditionalStats() - Method in class weka.classifiers.functions.LinearRegressionJ: Get whether to output additional statistics (such as std.
getOutputAdditionalStats() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Get whether to output additional statistics (such as std.
getOutputArray() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Returns whether to output an array or a sequence of classifier setups.
getOutputBestSetup() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns whether to output the best setup for optimizers like GridSearch and MultiSearch.
getOutputBestSetup() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Returns whether the best setup is output in case of optimizers like GridSearch/MultiSearch.
getOutputBuffer() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the output buffer.
getOutputContainer() - Method in class adams.flow.transformer.WekaFilter: Returns whether to output a container with the filter alongside the filtered data or just the filtered data.
getOutputDirectory() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the currently set directory for the generated ARFF files.
getOutputDirectory() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the currently set directory for the generated ARFF files.
getOutputDistribution() - Method in class adams.flow.transformer.wekaclusterer.AddCluster: Returns whether to output the cluster distribution instead of the cluster index.
getOutputFile() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the file to store the experiment in.
getOutputFile() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Get output file.
getOutputFile() - Method in class adams.tools.CompareDatasets: Returns the first dataset for the comparison.
getOutputFormat() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns the output format.
getOutputFormat() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: Returns the type of output format to generate.
getOutputFormat() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the output format in use for generating the output.
getOutputFormat() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns the current output format.
getOutputFormat() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the output format in use for generating the output.
getOutputGenerator() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem: Returns the output generator.
getOutputGenerator() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane: Returns the underlying output generator.
getOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Returns the current output generators.
getOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Returns the current output generators.
getOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Returns the current output generators.
getOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Returns the current output generators.
getOutputGenerators() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Returns the current output generators.
getOutputHeader() - Method in class adams.data.instances.AbstractInstanceGenerator: Returns the current header.
getOutputHeader() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns whether to output the header of the result matrix as well.
getOutputHeader() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns whether to output the header of the result matrix as well.
getOutputIndices() - Method in class adams.flow.transformer.WekaAttributeIterator: Returns whether to output 1-based indices of matches instead of the names.
getOutputInstance() - Method in class adams.flow.transformer.WekaClassifying: Returns whether Instance objects are output instead of PredictionContainer ones.
getOutputModel() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Returns whether to output the clusterer model as well.
getOutputModel() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator: Returns whether to output the clusterer model as well.
getOutputName() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the name to use for the merged dataset.
getOutputName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel: Returns the name to display in the GUI.
getOutputName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel: Returns the name to display in the GUI.
getOutputName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel: Returns the name to display in the GUI.
getOutputName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel: Returns the name to display in the GUI.
getOutputName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel: Returns the name to display in the GUI.
getOutputOnlyModel() - Method in class adams.flow.transformer.AbstractWekaModelReader: Returns whether only the model is output instead of the container.
getOutputPrefix() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns the current output prefix.
getOutputPrefixType() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the type of prefix to use for the output.
getOutputRelationName() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns whether the relation name is output as well.
getOutputs() - Method in class adams.ml.data.InstancesView: Returns a spreadsheet containing only output columns, i.e., the class columns.
getOutputType() - Method in class adams.data.io.output.AbstractWekaSpreadSheetWriter: Returns how the data is written.
getOutputType() - Method in class adams.flow.transformer.WekaFileReader: Returns how to output the data.
getOutputType() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the type of output to generate.
getOverlays() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the overlays to use in the plot.
getOverride() - Method in class adams.flow.transformer.WekaClassSelector: Returns whether any existing class index will be overriden or not.
getOverrideJobRunner() - Method in class adams.flow.transformer.WekaExperimentExecution: Returns whether to override the jobrunner of the experiment.
getOwner() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot: Returns the current owner.
getOwner() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Returns the owner.
getOwner() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Returns the owner.
getOwner() - Method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem: Returns the owner.
getOwner() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob: Returns the owner.
getOwner() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob: Returns the owner.
getOwner() - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource: Returns the owner of this source.
getOwner() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Returns the owner of this tab.
getOwner() - Method in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane: Returns the owner.
getOwner() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Returns the owner.
getOwner() - Method in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel: Returns the experimenter this panel belongs to.
getOwner() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel: Returns the setup panel this option panel belongs to.
getOwner() - Method in class adams.gui.visualization.instance.InstanceContainerManager: Returns the owning panel.
getOwner() - Method in class adams.gui.visualization.instance.InstancePointHitDetector: Returns the owner.
getOwner() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: Returns the owning panel.
getOwner() - Method in class adams.ml.data.DataCellView: Returns the row this cell belongs to.
getOwner() - Method in class adams.ml.data.InstanceView: Returns the spreadsheet this row belongs to.
getOwner() - Method in class adams.opt.optimise.GeneticAlgorithm.GAJob: Returns the owner.
getPackages() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: Returns the packages to output.
getPadding() - Method in class weka.filters.unsupervised.attribute.FastWavelet: Gets the type of Padding to use.
getPaintlet() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the paintlet in use.
getPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Returns the paintlet to use for the plot.
getPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the paintlet to use.
getPaintMoment() - Method in class adams.gui.visualization.instance.AbstractInstancePaintlet: Returns when this paintlet is to be executed.
getPanel() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Returns a panel with options to display.
getPanel() - Static method in class adams.gui.visualization.instance.HistogramFactory: Returns an instance of a new panel for displaying histograms.
getPanel(Report) - Static method in class adams.gui.visualization.instance.InstanceReportFactory: Returns a new panel for the given report.
getPanel(String) - Method in class weka.gui.explorer.MultiExplorer: Returns the panel with the specified name.
getPanel(List<ReportContainer>) - Static method in class adams.gui.visualization.instance.InstanceReportFactory: Returns a new table for the given reports.
getPanelEvaluator() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Returns the panel with the evaluator.
getPanelForReports(List) - Static method in class adams.gui.visualization.instance.InstanceReportFactory: Returns a new table for the given reports.
getPanelGOE() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Returns the panel with the algorithm.
getPanelGOE() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Returns the panel with the algorithm.
getPanelGOE() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Returns the panel with the algorithm.
getPanelLeft() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Returns the left panel.
getPanelLeft() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Returns the left panel.
getPanelLeft() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Returns the left panel.
getPanelLeft() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Returns the left panel.
getPanelLeft() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Returns the left panel.
getPanelRight() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Returns the right panel.
getPanelRight() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Returns the right panel.
getPanelRight() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Returns the right panel.
getPanelRight() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Returns the right panel.
getPanelRight() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Returns the right panel.
getPanelRight() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Returns the panel on the right (for the analysis display).
getPanels() - Static method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel: Returns a list with classnames of panels.
getPanels() - Static method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: Returns a list with classnames of panels.
getPanels() - Static method in class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel: Returns a list with classnames of panels.
getPanels() - Static method in class weka.gui.explorer.panels.AbstractAdditionalExplorerPanel: Returns a list with classnames of panels.
getPanelSearch() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Returns the panel with the search.
getParameterPanel() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: Returns the underlying property sheet panel.
getParameters() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Returns the setup parameters.
getParentComponentActor() - Method in class adams.flow.source.WekaSelectDataset: Returns the (optional) callable actor to use as parent component instead of the flow panel.
getParser() - Method in class weka.classifiers.functions.MathExpressionClassifier: Returns the parser to use.
getPassword() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the database password.
getPassword() - Method in class adams.flow.source.WekaDatabaseReader: Returns the database password.
getPct() - Method in class weka.classifiers.meta.AbstainLeastMedianSq
getPct() - Method in class weka.classifiers.meta.LeastMedianSq
getPercent() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst: Returns the percentage to remove.
getPercentage() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns the split percentage.
getPercentage() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Returns the split percentage.
getPercentage() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the percentage (0-1).
getPercentage() - Method in class adams.flow.transformer.WekaRandomSplit: Returns the percentage (0-1).
getPercentage() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: Returns the split percentage.
getPercentage() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Returns the split percentage.
getPercentage() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Returns the split percentage.
getPercentage() - Method in class weka.classifiers.DefaultRandomSplitGenerator: Returns the split percentage.
getPercentage() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns the split percentage.
getPercentage() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns the split percentage.
getPercentage() - Method in interface weka.classifiers.RandomSplitGenerator: Returns the split percentage.
getPercentile() - Method in class weka.classifiers.meta.AbstainAttributePercentile
getPercentiles() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the percentiles to calculate for the errors.
getPerformance() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: The generated performance.
getPerformTraining() - Method in class weka.classifiers.functions.PyroProxy: Returns whether to train the model as well.
getPlotData() - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator: Assembles and returns the plot.
getPlotInstances() - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator: Returns the generated dataset that is plotted.
getPlotName() - Method in class adams.flow.transformer.WekaAccumulatedError: Returns the current plot name.
getPLS() - Method in class weka.classifiers.trees.RandomRegressionForest: Gets the current number of PLS components to generate.
getPLS1bHat() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns the PLS1 b "hat" matrix.
getPLS1bHat() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings: Returns the PLS1 b "hat" matrix.
getPLS1bHat() - Method in interface weka.core.PLSMatrixAccess: Returns the PLS1 b "hat" matrix.
getPLS1bHat() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings: Returns the PLS1 b "hat" matrix.
getPLS1P() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns the PLS1 P matrix.
getPLS1P() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings: Returns the PLS1 P matrix.
getPLS1P() - Method in interface weka.core.PLSMatrixAccess: Returns the PLS1 P matrix.
getPLS1P() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings: Returns the PLS1 P matrix.
getPLS1RegVector() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns the reg vector.
getPLS1RegVector() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings: Returns the reg vector.
getPLS1RegVector() - Method in interface weka.core.PLSMatrixAccess: Returns the reg vector.
getPLS1RegVector() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings: Returns the reg vector.
getPLS1W() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns the PLS1 W matrix.
getPLS1W() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings: Returns the PLS1 W matrix.
getPLS1W() - Method in interface weka.core.PLSMatrixAccess: Returns the PLS1 W matrix.
getPLS1W() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings: Returns the PLS1 W matrix.
getPlugins() - Static method in class adams.gui.goe.WekaEditorsRegistration.AccessiblePluginManager: Returns the plugins.
getPolynomialOrder() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns the polynominal order.
getPolynomialOrder() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Returns the polynominal order.
getPopupMenu() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Generates the right-click popup menu.
getPopupMenu() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel: Generates the right-click popup menu.
getPopupMenu() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Creates and returns the popup menu.
getPostProcessor() - Method in class adams.flow.transformer.WekaClustererPostProcessor: Returns the post-processor in use.
getPostProcessor() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor: Returns the post-processor in use.
getPostProcessor() - Method in class adams.flow.transformer.WekaTrainClusterer: Returns the post-processor in use.
getPostProcessors() - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor: Returns the distance function to use.
getPostProcessors() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor: Returns the post-processors in use.
getPostTokenizer() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Returns the tokenizer to use for the final tokenization (after cleaning).
getPredicted() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the column with the predicted values.
getPredicted() - Method in class weka.classifiers.functions.FromPredictions: Returns the column with the predicted values.
getPredictedIndex() - Method in class weka.classifiers.functions.FromPredictions: Returns the predicted 0-based index.
getPredictedMax() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the upper limit in use for the predicted values.
getPredictedMin() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the lower limit in use for the predicted values.
getPrediction() - Method in class adams.flow.transformer.WekaAccumulatedError.SortablePrediction: Returns the stored prediction.
getPredictions() - Method in class weka.classifiers.AggregateEvaluations: Returns all the currently stored predictions.
getPredictions() - Method in class weka.classifiers.functions.FromPredictions: Returns the predictions that were loaded.
getPredictionsFile() - Method in class weka.classifiers.functions.FromPredictions: Returns the file with the predictions.
getPredictionType() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns the type of prediction to perform.
getPredictMax() - Method in class weka.classifiers.functions.FakeClassifier: Returns the maximum value to predict.
getPredictMin() - Method in class weka.classifiers.functions.FakeClassifier: Returns the minimum value to predict.
getPredictor() - Method in class weka.classifiers.meta.Consensus: Returns the index of the classifier for making the actual predictions.
getPredictor() - Method in class weka.classifiers.trees.XGBoost: Gets the type of predictor algorithm to use.
getPredictWait() - Method in class weka.classifiers.functions.FakeClassifier: Returns the time in msec to wait when calling classifyInstance.
getPreferJobRunner() - Method in class adams.flow.transformer.WekaFilter: Returns whether to offload processing to a JobRunner instance if available.
getPreferJobRunner() - Method in class adams.flow.transformer.WekaTestSetEvaluator: Returns whether to offload processing to a JobRunner instance if available.
getPreferJobRunner() - Method in class adams.flow.transformer.WekaTrainAssociator: Returns whether to offload processing to a JobRunner instance if available.
getPreferJobRunner() - Method in class adams.flow.transformer.WekaTrainClassifier: Returns whether to offload processing to a JobRunner instance if available.
getPreferJobRunner() - Method in class adams.flow.transformer.WekaTrainClusterer: Returns whether to offload processing to a JobRunner instance if available.
getPreferJobRunner() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator: Returns whether to offload processing to a JobRunner instance if available.
getPreFilter() - Method in class adams.data.weka.rowfinder.FilteredIQR: Returns the pre filter.
getPreFilter() - Method in class weka.filters.FilteredFilter: Returns the pre-filter in use.
getPreFilter() - Method in class weka.filters.unsupervised.instance.KennardStone: Returns the pre-filter to apply to the data to perform the search on.
getPrefix() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the optional prefix string.
getPrefix() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the prefix for the new attributes.
getPrefixDatasetsWithIndex() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns whether to prefix the datasets with the index.
getPrefixDatasetsWithIndex() - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ExperimentWithCustomizableRelationNames: Returns whether to prefix the datasets with the index.
getPrefixDatasetsWithIndex() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Returns whether to use the filename as relation name.
getPrefixDatasetsWithIndex() - Method in class weka.experiment.ExtExperiment: Returns whether to prefix the datasets with the index.
getPrefixes() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Gets the list of prefixes to use.
getPrefixes() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Gets the list of prefixes to use.
getPrefixSeparator() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the prefix separator string.
getPreparation() - Method in class weka.classifiers.meta.SocketFacade: Returns the data preparation scheme to use.
getPreprocessing() - Method in class weka.core.neighboursearch.PLSNNSearch: Gets the type of preprocessing to use
getPreprocessingType() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns the type of preprocessing to perform.
getPreprocessingType() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Returns the type of preprocessing to perform.
getPreSelectedIndices(Instances) - Method in class adams.flow.transformer.WekaChooseAttributes: Returns the pre-selected indices.
getPreserveIDColumn() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets whether the first non-summary attribute should be treated as an ID and moved to the first attribute position.
getPreserveInstancesOrder() - Method in class weka.clusterers.SAXKMeans: Gets whether order of instances must be preserved.
getPreserveOrder() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns whether to preserve the order.
getPreserveOrder() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Returns whether to preserve the order.
getPreserveOrder() - Method in class adams.flow.transformer.WekaRandomSplit: Returns whether to preserve order and suppress randomization.
getPreserveOrder() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: Returns whether to preserve the order.
getPreserveOrder() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Returns whether to preserve the order.
getPreserveOrder() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Returns whether to preserve the order.
getPreserveOrder() - Method in class weka.classifiers.DefaultRandomSplitGenerator: Returns whether to preserve the order.
getPreserveOrder() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns whether to preserve the order.
getPreserveOrder() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns whether to preserve the order.
getPreserveOrder() - Method in interface weka.classifiers.RandomSplitGenerator: Returns whether to preserve the order.
getPreTokenizer() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Returns the tokenizer to use for the initial tokenization (before cleaning).
getProbability() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer: Returns the probability.
getProcessor() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor: Returns the processor for the incoming classifier arrays.
getProcessType() - Method in class weka.classifiers.trees.XGBoost: Gets the type of boosting process to run.
getProperties() - Static method in class adams.gui.goe.WekaEditorsRegistration.AccessibleGenericObjectEditor: Returns the editor properties.
getProperties() - Static method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Returns the properties that define the editor.
getProperties() - Static method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns the properties that define the investigator.
getProperties() - Static method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Returns the properties that define the editor.
getProperties() - Static method in class adams.gui.visualization.instance.InstanceComparePanel: Returns the properties that define the editor.
getProperties() - Static method in class adams.gui.visualization.instance.InstanceExplorer: Returns the properties that define the editor.
getProperties() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: Returns the content of the page (ie parameters) as properties.
getProperties() - Method in class adams.gui.wizard.WekaSelectDatasetPage: Returns the content of the page (ie parameters) as properties.
getProperties() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: Returns the content of the page (ie parameters) as properties.
getProperty() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the property to manage.
getProperty() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the property to manage.
getProperty() - Method in class adams.core.discovery.genetic.GenericInteger: Returns the property to manage.
getProperty() - Method in class adams.core.discovery.genetic.GenericString: Returns the property to manage.
getPropertyDescriptor() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the property descriptor for the handled property.
getPropertyDescriptor() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the property descriptor for the handled property.
getPropertyDescriptor() - Method in class adams.core.discovery.genetic.GenericInteger: Returns the property descriptor for the handled property.
getPropertyDescriptor() - Method in class adams.core.discovery.genetic.GenericString: Returns the property descriptor for the handled property.
getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaASEvaluator: Returns the property name to look for.
getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaASSearch: Returns the property name to look for.
getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaClassifier: Returns the property name to look for.
getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaClusterer: Returns the property name to look for.
getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaDataGenerator: Returns the property name to look for.
getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaFilter: Returns the property name to look for.
getPropertyName() - Method in class adams.gui.flow.tree.quickaction.EditWekaStreamableFilter: Returns the property name to look for.
getQuery() - Method in class adams.flow.source.WekaDatabaseReader: Returns the query to execute.
getQuickInfo() - Method in class adams.data.conversion.MapToWekaInstance: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.data.conversion.SwapPLS: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.data.spreadsheet.filter.WekaFilter: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities: Returns the quick info string to be displayed in the flow editor.
getQuickInfo() - Method in class adams.flow.condition.bool.WekaClassification: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.sink.WekaAttributeSummary: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.sink.WekaClassifierErrors: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.sink.WekaCostCurve: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.sink.WekaExperimentFileWriter: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.sink.WekaFileWriter: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.sink.WekaInstancesPlot: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.sink.WekaThresholdCurve: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.WekaAssociatorSetup: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.WekaClassifierSetup: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.WekaClustererSetup: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.WekaDatabaseReader: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.WekaDataGenerator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.WekaNewExperiment: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.WekaNewInstances: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.WekaPackageManagerAction: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.source.WekaSelectDataset: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.standalone.WekaPackageManagerAction: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.AbstractInstanceGenerator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.AbstractWekaModelReader: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaAccumulatedError: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaAttributeIterator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaBootstrapping: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaChooseAttributes: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaClassifierInfo: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaClassSelector: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaClustererInfo: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaClustererPostProcessor: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaDatasetsMerge: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaDatasetSplit: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaEnsembleGenerator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaEvaluationInfo: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaEvaluationValues: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaExperiment: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaExperimentExecution: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaExperimentFileReader: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaExtractArray: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaExtractPLSMatrix: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaFileReader: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaFilter: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaGetInstancesValue: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaGetInstanceValue: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaInstancesInfo: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaInstancesStatistic: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaModelReader: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaNewInstance: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaPackageManagerAction: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaPrincipalComponents
getQuickInfo() - Method in class adams.flow.transformer.WekaRandomSplit: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaRegexToRange: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaRenameRelation: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Returns a quick info about the object, which can be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaSetInstancesValue: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaSetInstanceValue: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaSplitGenerator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaStoreInstance: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaStreamEvaluator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaStreamFilter: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaSubsets: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaTestSetEvaluator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaTextDirectoryReader: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaTrainAssociator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaTrainClassifier: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaTrainClusterer: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator: Returns a quick info about the actor, which will be displayed in the GUI.
getQuickInfo() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator: Returns a quick info about the actor, which will be displayed in the GUI.
getRandom() - Method in class weka.classifiers.functions.FakeClassifier: Returns the random number generator to use.
getRandomize() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Returns whether to randomize the data.
getRandomize() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns whether to randomize the data.
getRandomize() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns whether to randomize the data.
getRandomize() - Method in interface weka.classifiers.CrossValidationFoldGenerator: Returns whether to randomize the data.
getRandomize() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns whether to randomize the data.
getRandomize() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns whether to randomize the data.
getRandomize() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns whether to randomize the data.
getRandomize() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns whether to randomize the data.
getRandomize() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Returns whether to randomize the data.
getRandomize() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns whether to include the class attribute in the comparison.
getRandomSeed() - Method in class weka.classifiers.meta.AbstainLeastMedianSq: get the seed for the random number generator
getRandomSeed() - Method in class weka.classifiers.meta.LeastMedianSq: get the seed for the random number generator
getRange() - Method in class adams.flow.sink.WekaAttributeSummary: Returns the range of attributes to visualize.
getRange() - Method in class adams.flow.transformer.WekaAttributeIterator: Returns the range of attributes to operate on.
getRange() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Returns the range of attributes to use.
getRange() - Method in class weka.filters.unsupervised.attribute.AnyToString: Returns the attribute range to use.
getRange() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the attribute range.
getRange() - Method in class weka.filters.unsupervised.attribute.StringToDate: Returns the first attribute range to use (regular expression on attribute names).
getRange() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor: Returns the attribute range to work on.
getRange(int) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Gets a single Range from the set of available Ranges.
getRange(SelectOptionPanel) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Turns the selected attributes into a range string.
getRange1() - Method in class adams.tools.CompareDatasets: Returns the range of attributes of the first dataset.
getRange2() - Method in class adams.tools.CompareDatasets: Returns the range of attributes of the second dataset.
getRangePaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the paintlet to use for the lower/upper statistics.
getRanges() - Method in class adams.data.weka.rowfinder.ByNumericRange: Returns the intervals.
getRanges() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange: Returns the ranges to include.
getRanges() - Method in class weka.classifiers.meta.PartitionedStacking: Returns the attribute ranges for the base-classifiers.
getRanges() - Method in class weka.filters.unsupervised.attribute.detrend.RangeBased: Returns the wave number ranges.
getRanges() - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased: Returns the wave number ranges.
getRanges() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Gets the list of possible Ranges to choose from.
getRateDrop() - Method in class weka.classifiers.trees.XGBoost: Gets the dropout rate (a fraction of previous trees to drop during the dropout).
getReader() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Returns the spreadsheet reader to use.
getReader() - Method in class weka.classifiers.functions.FromPredictions: Returns the spreadsheet reader to use.
getReader() - Method in class weka.core.converters.SpreadSheetLoader: Returns the spreadsheet reader in use.
getReaderClass() - Method in class adams.gui.chooser.AdamsExperimentFileChooser: Returns the reader superclass for the GOE.
getReaderClass() - Method in class adams.gui.chooser.WekaFileChooser: Returns the reader superclass for the GOE.
getReaderForFile(File) - Method in class adams.gui.chooser.AdamsExperimentFileChooser: Returns the reader for the specified file.
getReaderForFile(File) - Method in class adams.gui.chooser.WekaFileChooser: Returns the reader for the specified file.
getReaders() - Static method in class adams.data.io.input.AbstractAdamsExperimentReader: Returns a list with classes of readers.
getReal() - Method in class weka.filters.unsupervised.attribute.FFT: Returns whether to return real or imaginary part.
getReduceNumberOfDistanceCalcsViaCanopies() - Method in class weka.clusterers.SAXKMeans: Get whether to use canopies to reduce the number of distance computations required
getReferenceActor() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the callable actor to obtain the reference dataset from if reference file is pointing to a directory.
getReferenceDataset() - Method in class weka.filters.unsupervised.instance.AlignDataset: Returns the file containing the reference dataset.
getReferenceError() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference: Returns the absolute value of the reference error.
getReferenceFile() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the file to load the reference dataset from.
getReferenceSize() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference: Returns the size for the reference error.
getRegex() - Method in class adams.flow.transformer.WekaRegexToRange: Returns the regular expression for attribute matching.
getRegexName() - Method in class adams.flow.transformer.WekaClassSelector: Returns the regular expression for selecting the attributes.
getRegExp() - Method in class adams.data.weka.classattribute.ByName: Returns the regular expression to use for locating the class attribute.
getRegExp() - Method in class adams.data.weka.columnfinder.ByName: Returns the regular expression in use.
getRegExp() - Method in class adams.data.weka.rowfinder.ByLabel: Returns the regular expression in use.
getRegExp() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
getRegExp() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
getRegExp() - Method in class adams.flow.transformer.WekaAttributeIterator: Returns the regular expression for the name.
getRegExp() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns the regular expression to match the strings against.
getRegExp() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
getRegExp() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
getRegExp() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
getRegExp() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
getRegExp() - Method in class weka.core.InstanceGrouping: Returns the regular expression in use (eg '(.*)-([0-9]+)-(.*)').
getRegExp() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the regular expression for identifying attributes.
getRegExp() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Gets the list of regular expressions.
getRegExp() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Returns the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
getRegExp(int) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Gets a single BaseRegExp from the set of available expressions.
getRegExps() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Returns the regular expression to apply to the attribute names for identifying the fusion subsets (incl class).
getRegExps() - Method in class weka.classifiers.MultiLevelSplitGenerator: Returns the regular expressions to use for extracting the groups.
getRegressionTree() - Method in class weka.classifiers.trees.m5.Rule2: Get the value of regressionTree.
getRegressionTree() - Method in class weka.classifiers.trees.m5.RuleNode2: Get the value of regressionTree.
getRegVector() - Method in class weka.filters.supervised.attribute.PLSFilterExtended
getRelationName() - Method in class adams.flow.source.WekaNewInstances: Returns the name of the relation.
getRelationName() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the pattern used for renaming the relation.
getRelationName() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns the relation name template.
getRelationName() - Method in interface weka.classifiers.CrossValidationFoldGenerator: Returns the relation name template.
getRelationName() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns the relation name template.
getRelationName() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the relation name template.
getRelationName() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the relation name template.
getRelationName() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns the relation name template.
getRelationName() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Returns the relation name template.
getRelationNameHeuristic() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns the current relation name heuristic.
getRelativeWidths() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Returns whether the calculated widths are divided by the class value.
getRemote() - Method in class weka.classifiers.meta.SocketFacade: Returns the address of the remote process.
getRemoteObjectName() - Method in class weka.classifiers.functions.PyroProxy: Returns the name of the remote object to use.
getRemoteObjectName() - Method in interface weka.core.PyroProxyObject: Returns the name of the remote object to use.
getRemove() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns whether to remove if not all present
getRemoveAsString() - Method in class adams.opt.genetic.DarkLord.DarkLordJob: Generates a range string of attributes to keep (= one has to use the inverse matching sense with the Remove filter).
getRemoveAsString(int[]) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection: Generates a range string of attributes to keep (= one has to use the inverse matching sense with the Remove filter).
getRemoveAttributeIndices() - Method in class weka.classifiers.meta.FilteredClassifierExt: Returns the attributes indices that are removed before applying the actual filter.
getRemoveChars() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Gets the characters to remove from start/end of the generated name.
getRemoveChars() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Gets the characters to remove from start/end of the generated name.
getRemoveTrain() - Method in class weka.classifiers.meta.AbstainAttributePercentile
getRemoveUnused() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Gets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.
getRemoveUnused() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Gets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.
getReplace() - Method in class adams.flow.transformer.WekaRenameRelation: Returns the replacement string.
getReplace() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Returns the expression to use for assembling the numeric part.
getReplaceMissing() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Gets whether missing values are replace.
getReplaceMissing() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Gets whether missing values are replaced.
getReport() - Method in class adams.data.instance.Instance: Returns the report.
getResetResults() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns whether to clear the results before starting the experiment.
getResetResults() - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ResettableExperiment: Returns whether to clear the results before starting the experiment.
getResetResults() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Returns whether to reset the results.
getResources() - Static method in class adams.gui.goe.WekaEditorsRegistration.AccessiblePluginManager: Returns the resources.
getResult() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog: Returns whether the dialog got cancelled or approved.
getResult() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: Returns whether the dialog got cancelled or approved.
getResult(String) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns a value from the cache.
getResult(String) - Method in class adams.opt.optimise.GeneticAlgorithm: Returns a value from the cache.
getResultFile() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the file to store the experimental results in.
getResultFormat() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the data format the results are stored in.
getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel: Returns the configured ResultListener.
getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel: Returns the configured ResultListener.
getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel: Returns the configured ResultListener.
getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel: Returns the configured ResultListener.
getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel: Returns the configured ResultListener.
getResultListener() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel: Returns the configured ResultListener.
getResultMatrix() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Returns the result matrix.
getResults() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel: Returns the currently set results.
getResults() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel: Returns the current set results.
getResultsHandler() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the results handler to use.
getResultsName() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel: Returns the name to display in the GUI.
getResultsName() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel: Returns the name to display in the GUI.
getResultsName() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel: Returns the name to display in the GUI.
getResultType() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: Returns whether the dialog got cancelled or approved.
getRetainStringValues() - Method in class weka.core.converters.AArffLoader.AArffReader: Returns whether to retain string values.
getReverse() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns whether to reverse the sorting.
getReverse() - Method in class weka.classifiers.AggregateEvaluations: Returns whether to reverse the sorting.
getRevision() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.FakeClassifier: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive
getRevision() - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.GeneticAlgorithm: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.GPD: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.LinearRegressionJ: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.MathExpressionClassifier: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.PLSClassifierWeighted: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.PLSWeighted: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.SimpleLinearRegressionIntervalEstimator: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.LWLIntervalEstimator: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.LWLSynchro: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter: Returns the revision string.
getRevision() - Method in class weka.classifiers.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.AlignDataset: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.DatasetCleaner: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.KeepRange: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.LatestRecords: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RowNorm: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.Scale: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.Sort: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.SortOnAttribute: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns the revision string.
getRidge() - Method in class adams.data.baseline.AbstractLinearRegressionBased: Returns the ridge parameter.
getRidge() - Method in class weka.attributeSelection.LinearRegressionAttributeEval: Get the value of Ridge.
getRidge() - Method in class weka.classifiers.functions.LinearRegressionJ: Get the value of Ridge.
getRidge() - Method in class weka.classifiers.trees.RandomModelTrees
getRidge() - Method in class weka.core.WeightedEuclideanDistanceRidge: Get the value of Ridge.
getRow() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the list of fields that identify a row.
getRow() - Method in class adams.flow.transformer.WekaGetInstancesValue: Returns the 1-based index of the row.
getRow() - Method in class adams.flow.transformer.WekaSetInstancesValue: Returns the 1-based index of the row.
getRow() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the list of fields that identify a row.
getRow(int) - Method in class adams.ml.data.InstancesView: Returns the row at the specified index.
getRow(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Returns the Instance for the row.
getRow(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Returns the row to display.
getRow(String) - Method in class adams.ml.data.InstancesView: Returns the row associated with the given row key, null if not found.
getRowAttribute1() - Method in class adams.tools.CompareDatasets: Returns the index of the attribute used for identifying rows to compare against each other (first dataset).
getRowAttribute2() - Method in class adams.tools.CompareDatasets: Returns the index of the attribute used for identifying rows to compare against each other (second dataset).
getRowCount() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: The number of datasets loaded.
getRowCount() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel: Gets the number of attributes.
getRowCount() - Method in class adams.gui.visualization.instance.InstanceTableModel: Returns the number of rows.
getRowCount() - Method in class adams.gui.visualization.instances.InstancesTableModel: returns the number of rows in the model
getRowCount() - Method in class adams.ml.data.InstancesView: Returns the number of rows currently stored.
getRowFinder() - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder: Returns the row finder in use.
getRowFinder() - Method in class adams.data.weka.datasetsplitter.RowSplitter: Gets the row-finder to use to select rows for the first dataset.
getRowFinder() - Method in class adams.data.weka.rowfinder.AbstractFilteredRowFinder: Returns the row finder in use.
getRowFinder() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the training data row selector.
getRowFinder() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Returns the row finder used by the filter.
getRowFinder() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Returns the row finder scheme.
getRowFinderEnabled() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Returns whether to use the row finder.
getRowFinders() - Static method in class adams.data.weka.rowfinder.AbstractRowFinder: Returns a list with classnames of row finders.
getRowFormat() - Method in class adams.data.featureconverter.Weka: Returns the class of the row that the converter generates.
getRowID(int) - Method in class adams.tools.CompareDatasets: Returns either the ID for the row, either the row index of the actual row attribute ID for that position.
getRowIndex() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Returns the currently selected.
getRowIndex(String) - Method in class adams.ml.data.InstancesView: Returns the row index of the specified row.
getRowKey(int) - Method in class adams.ml.data.InstancesView: Returns the row key at the specified index.
getRowRange() - Method in class weka.filters.unsupervised.instance.KeepRange: Returns the unordered range of rows to keep.
getRows() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the size.
getRows() - Method in class adams.data.weka.rowfinder.Constant: Gets the constant set of rows to find.
getRows() - Method in class adams.gui.event.WekaInvestigatorDataEvent: The affected rows.
getRows() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Returns a list of row IDs.
getRows() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Returns a list of row IDs.
getRows() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
getRowSelection() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Returns the row selection scheme in use.
getRowSetEnumeration() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Allows specific merge methods to specify the order in which rows are placed into the merged dataset, and which rows from the source datasets are used for the source data.
getRowSetEnumeration() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Allows specific merge methods to specify the order in which rows are placed into the merged dataset, and which rows from the source datasets are used for the source data.
getRowSetEnumeration() - Method in class adams.flow.transformer.wekadatasetsmerge.Simple: Allows specific merge methods to specify the order in which rows are placed into the merged dataset, and which rows from the source datasets are used for the source data.
getRunEvaluations() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns the stored Evaluation objects per run.
getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: Returns the stored run information.
getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics: Returns whether the run information is output as well.
getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Returns the stored run information.
getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Returns whether the run information is output as well.
getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns the stored run information.
getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics: Returns whether the run information is output as well.
getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns the stored run information.
getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns whether the run information is output as well.
getRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: Returns the stored run information.
getRunModels() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns the stored Classifier objects per run.
getRunOriginalIndices() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns the stored original indices per run.
getRuns() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the number of runs to perform.
getRuns() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the number of runs to perform.
getRuns() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the number of runs.
getSampleSize() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Returns the sample size to use.
getSampleType() - Method in class weka.classifiers.trees.XGBoost: Gets the type of sampling algorithm.
getSaveFileFilters() - Method in class adams.gui.chooser.AdamsExperimentFileChooser: Returns the file filters for writing files.
getSaveFileFilters() - Method in class adams.gui.chooser.WekaFileChooser: Returns the file filters for writing files.
getSaveInstances() - Method in class weka.classifiers.trees.M5P2: Get whether instance data is being save.
getSaver() - Method in class adams.gui.chooser.DatasetFileChooserPanel: Returns the current saver.
getScale() - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive
getScalePositiveWeights() - Method in class weka.classifiers.trees.XGBoost: Gets the positive-weights scale factor.
getScaler() - Method in class adams.data.weka.predictions.AutoScaler: Returns the scaler for numeric data.
getScores() - Method in class adams.data.instancesanalysis.PCA: Returns the scores.
getScores() - Method in class adams.data.instancesanalysis.PLS: Returns the scores.
getScriptingEngine() - Method in class adams.gui.visualization.instance.InstancePanel: Returns the current scripting engine, can be null.
getSearch() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns the evaluation method in use.
getSearch() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns the search algorithm.
getSearch() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Returns the stored search object.
getSearchAlgorithm() - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Returns the current nearestNeighbourSearch algorithm in use.
getSearchPanel() - Method in class adams.gui.visualization.instances.InstancesPanel: Returns the underlying search panel.
getSecondAttribute() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Gets the name of the second attribute.
getSecondAttributeRange() - Method in class adams.gui.InstanceCompare: Returns the second attribute range.
getSecondAttributeRange() - Method in class adams.gui.visualization.instance.InstanceComparePanel: Returns the second attribute range.
getSecondCrossValidationSeed() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Returns the current seed value for cross-validation (second evaluation).
getSecondDataset() - Method in class adams.gui.InstanceCompare: Returns the second dataset.
getSecondDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel: Returns the second dataset.
getSecondFitness() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob: Returns the fitness (second evaluation).
getSecondFolds() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob: Returns the number of cross-validation folds (second evaluation).
getSecondFolds() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Returns the number of folds to use in cross-validation (second evaluation).
getSecondRange() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Returns the second attribute range to use (regular expression on attribute names).
getSecondResult(String) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Returns a value from the cache (second evaluation).
getSecondRowIndex() - Method in class adams.gui.InstanceCompare: Returns the second row index.
getSecondRowIndex() - Method in class adams.gui.visualization.instance.InstanceComparePanel: Returns the second row index.
getSecondSeed() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob: Returns the cross-validation seed (second evaluation).
getSeed() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator: Returns the seed value for cross-validation.
getSeed() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Returns the seed value.
getSeed() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the seed value.
getSeed() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns the seed value.
getSeed() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Returns the seed value.
getSeed() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns the seed value.
getSeed() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the seed value.
getSeed() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the seed value.
getSeed() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Returns the seed value.
getSeed() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Returns the seed value.
getSeed() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the seed value.
getSeed() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the seed value.
getSeed() - Method in class adams.flow.transformer.WekaRandomSplit: Returns the seed value.
getSeed() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the seed value.
getSeed() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Returns the cross-validation seed.
getSeed() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns the current seed value.
getSeed() - Method in class weka.classifiers.AbstractSplitGenerator: Returns the seed value.
getSeed() - Method in class weka.classifiers.functions.FakeClassifier: Returns the seed value for the random values.
getSeed() - Method in class weka.classifiers.trees.XGBoost: Gets the random number seed.
getSeed() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the seed value.
getSeed() - Method in class weka.filters.unsupervised.attribute.InputSmearing: Gets the seed for the random number generations
getSeed() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Gets the seed for the random number generations
getSeed() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Gets the seed for the random number generations
getSelectedAttributes() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Gets an array containing the indices of all selected (ie checked) attributes.
getSelectedClassifier() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns the specified base classifier.
getSelectedColumn(int[], int) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter: Gets the column number of the selected column at the given index.
getSelectedData() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Returns the currently selected data containers.
getSelectedData() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Returns the currently selected data containers.
getSelectedDatabaseID(int) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Returns the database ID of the currently selected item.
getSelectedDatabaseIDs(int) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Returns the database IDs of the currently selected items.
getSelectedRows() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Returns the currently selected data containers.
getSelectedRows() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Returns the selected rows.
getSelectedRows() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Returns the currently selected data containers.
getSelectedRows() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Gets an array containing the indices of all selected rows.
getSelectedTag() - Method in enum adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType: Returns the corresponding Vote selected tag.
getSelectionModel() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Gets the selection model used by the table.
getSelectionProcessor() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Returns the selection processor scheme in use.
getSendToClasses() - Method in class adams.flow.sink.WekaInstancesDisplay: Returns the classes that the supporter generates.
getSendToClasses() - Method in class adams.gui.tools.DatasetCompatibilityPanel: Returns the classes that the supporter generates.
getSendToClasses() - Method in class adams.gui.visualization.instance.InstanceExplorer: Returns the classes that the supporter generates.
getSendToClasses() - Method in class adams.gui.visualization.instances.InstancesTable: Returns the classes that the supporter generates.
getSendToClasses() - Method in class weka.gui.explorer.ExplorerExt: Returns the classes that the supporter generates.
getSendToItem(Class[]) - Method in class adams.flow.sink.WekaInstancesDisplay: Returns the object to send.
getSendToItem(Class[]) - Method in class adams.gui.tools.DatasetCompatibilityPanel: Returns the object to send.
getSendToItem(Class[]) - Method in class adams.gui.visualization.instance.InstanceExplorer: Returns the object to send.
getSendToItem(Class[]) - Method in class adams.gui.visualization.instances.InstancesTable: Returns the object to send.
getSendToItem(Class[]) - Method in class weka.gui.explorer.ExplorerExt: Returns the object to send.
getSeparateFolds() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns whether to separate the folds, an Evaluation object per fold.
getSequenceManager() - Method in class adams.gui.visualization.instance.InstancePanel: Returns the current container manager.
getSerialized() - Method in class weka.filters.SerializedFilter: Returns the serialized filter file.
getServer() - Method in class weka.classifiers.meta.SocketFacade: Returns the server socket, instantiates it if necessary.
getSetup() - Method in class adams.flow.source.WekaClassifierGenerator: Returns the base classifier.
getSetup() - Method in class adams.flow.source.WekaClustererGenerator: Returns the base clusterer.
getSetup() - Method in class adams.flow.source.WekaFilterGenerator: Returns the base clusterer.
getSetup() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Returns the property in the incoming properties that contains the commandline of the genetic algorithm.
getSetup() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: Returns the genetic algorithm setup to use.
getSetup() - Method in class adams.gui.menu.DarkLord: Returns the genetic algorithm setup to use.
getSetup() - Method in class adams.gui.menu.Hermione: Returns the genetic algorithm setup to use.
getSetupDialog(Dialog, Dialog.ModalityType) - Static method in class adams.gui.visualization.instance.HistogramFactory: Returns an instance of a setup dialog for displaying histograms.
getSetupDialog(Frame, boolean) - Static method in class adams.gui.visualization.instance.HistogramFactory: Returns an instance of a setup dialog for displaying histograms.
getSetupName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: Returns the name for this setup panel.
getSetupName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: Returns the name for this setup panel.
getSetupName() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: Returns the name for this setup panel.
getSetups() - Static method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup: Returns the available actions.
getSetupUpload() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the scheme for uploading the currently best job setup.
getSharedStringsTable() - Method in class adams.ml.data.InstancesView: Returns the table for shared strings.
getShortcutProperties() - Static method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns the properties that define the shortcuts.
getShowAboutBox() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage.CustomPropertySheetPanel: Returns whether the about box is displayed.
getShowAttributeIndex() - Method in class adams.gui.visualization.instances.InstancesTableModel: Returns whether to display the attribute index in the header.
getShowAttributeWeights() - Method in class adams.gui.visualization.instances.InstancesTable: Returns whether to display attribute weights.
getShowAttributeWeights() - Method in class adams.gui.visualization.instances.InstancesTableModel: Returns whether to display attribute weights.
getShowDistribution() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns whether to show the class distribution as well.
getShowDistribution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Returns whether to show the class distribution as well.
getShowError() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns whether to show the error as well.
getShowError() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Returns whether to show the error as well.
getShowProbability() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns whether to show the probability as well.
getShowProbability() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Returns whether to show the probability as well.
getShowWeight() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns whether to show the weight as well.
getShowWeight() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Returns whether to show the weight as well.
getShowWeightsColumn() - Method in class adams.gui.visualization.instances.InstancesTable: Returns whether to display a weights column.
getShowWeightsColumn() - Method in class adams.gui.visualization.instances.InstancesTableModel: Returns whether to display a weights column.
getShowZeroInstancesAsUnknown() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel: Get whether to show zero instances as unknown (i.e.
getSidePanel() - Method in class adams.gui.visualization.instance.InstanceExplorer: Returns the side panel.
getSignificance() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the current significance level (0-1).
getSignificance() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the current significance level (0-1).
getSilent() - Method in class weka.classifiers.MultiLevelSplitGenerator: Returns whether to suppress error messages.
getSimpleAttributeNames() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Get whether to just number the attributes rather than compiling names.
getSimplsB() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns the SIMPLS B matrix.
getSimplsB() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings: Returns the SIMPLS B matrix.
getSimplsB() - Method in interface weka.core.PLSMatrixAccess: Returns the SIMPLS B matrix.
getSimplsB() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings: Returns the SIMPLS B matrix.
getSimplsW() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns the SIMPLS W matrix.
getSimplsW() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings: Returns the SIMPLS W matrix.
getSimplsW() - Method in interface weka.core.PLSMatrixAccess: Returns the SIMPLS W matrix.
getSimplsW() - Method in class weka.filters.supervised.attribute.PLSFilterWithLoadings: Returns the SIMPLS W matrix.
getSize() - Method in class adams.data.weka.predictions.FixedSizeErrorScaler: Returns the size for the errors.
getSizeLimit() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns the threshold of the normalized weights below which to drop instances.
getSkipBuild() - Method in class adams.flow.transformer.WekaTrainClassifier: Returns whether to skip the buildClassifier call for incremental classifiers.
getSkipDrop() - Method in class weka.classifiers.trees.XGBoost: Gets the probability of skipping the dropout procedure during a boosting iteration.
getSkipHistory() - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Returns whether history panels are skipped.
getSkipIdentical() - Method in class weka.core.neighboursearch.NewNNSearch: Gets whether if identical instances are skipped from the neighbourhood.
getSkipNominal() - Method in class adams.data.instancesanalysis.PCA: Returns whether to skip NOMINAL attributes from the PCA process by turning them into STRING attributes.
getSkipTrain() - Method in class weka.classifiers.meta.SocketFacade: Returns whether to skip training, eg when using a pre-built model.
getSlope() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns the slope of the function.
getSlopeSE() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns the standard error of slope of the function.
getSmoothing() - Method in class weka.classifiers.trees.m5.Rule2: Get whether or not smoothing has been turned on
getSortAttributeNames() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns whether to sort the attribute names.
getSortAttributes() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTable: Returns whether to sort the attributes alphabetically for the dropdown list.
getSortAttributes() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableWithButtons: Returns whether to sort the attributes alphabetically for the dropdown list.
getSortDefinitionPanel() - Method in class adams.gui.event.InstancesSortSetupEvent: Returns the SortDefinitionPanel that was added/removed.
getSortLabels() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns whether to store the labels with the specified comparator.
getSortLabels() - Method in class weka.classifiers.AggregateEvaluations: Returns whether to store the labels with the specified comparator.
getSortPanel() - Method in class adams.gui.event.InstancesSortSetupEvent: Returns the SortPanel that triggered the event
getSource() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute: Gets the actual source attribute from the source datasets.
getSource() - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer: Returns the source of the data item.
getSource() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer: Returns the source of the data item.
getSource() - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer: Returns the source of the data item.
getSource() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer: Returns the source of the data item.
getSource() - Method in class adams.gui.tools.wekainvestigator.data.MemoryContainer: Returns the source of the data item.
getSource() - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer: Returns the source of the data item.
getSource() - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer: Returns the source of the data item.
getSourceCodeClass() - Method in class adams.flow.transformer.WekaClassifierInfo: Returns the class name for the generated source code.
getSources() - Method in class adams.data.instancesanalysis.FastICA: Returns the sources.
getSparseFormat() - Method in class adams.flow.source.WekaDatabaseReader: Returns whether data is output in sparse format.
getSplitPercentage() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the split percentage (only train/test splits).
getSplitpoint() - Method in class weka.classifiers.meta.HighLowSplit
getSplitpoint() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier
getSplits() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the minimum.
getSplits() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
getSplitter() - Method in class adams.flow.transformer.WekaDatasetSplit: Gets the splitter to use.
getSpreadSheet() - Method in class adams.ml.data.DataCellView: Returns the spreadsheet this cell belongs to.
getSpreadSheetType() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet: Returns the type of spreadsheet to use.
getSpreadSheetWriter() - Method in class weka.core.converters.SpreadSheetSaver: Returns the spreadsheet writer in use.
getSquaredError() - Method in class weka.clusterers.SAXKMeans: Gets the squared error for all clusters.
getStandardDeviation(Instance) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Gives the variance of the prediction at the given instance
getStandardDeviation(Instance) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Gives standard deviation of the prediction at the given instance.
getStandardDeviation(Instance) - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Gives the variance of the prediction at the given instance
getStartPage() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: Returns the start page for the wizard.
getStartPage() - Method in class adams.gui.menu.DarkLord: Returns the start page for the wizard.
getStartPage() - Method in class adams.gui.menu.Hermione: Returns the start page for the wizard.
getStartPoints(AbstractGeneticDiscoveryHandler[]) - Method in class adams.opt.genetic.Hermione: Get List of start positions in bit string
getState(InstancesTable, MouseEvent, TableRowRange) - Static method in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper: Determines the state of the table.
getStatistic() - Method in class adams.flow.transformer.WekaInstancesStatistic: Returns the statistic in use.
getStatistic() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Returns the statistic to output.
getStatistic() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Returns the statistic to output.
getStatistic() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Returns the statistic to output.
getStatistic() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the statistic to output.
getStatistic() - Method in class weka.classifiers.meta.ClassifierCascade: the statistic to use for termination.
getStatistic(String) - Method in class weka.classifiers.evaluation.Bias: Get the value of the named statistic
getStatistic(String) - Method in class weka.classifiers.evaluation.Dice: Get the value of the named statistic - for the first class label.
getStatistic(String) - Method in class weka.classifiers.evaluation.MSLE: Get the value of the named statistic
getStatistic(String) - Method in class weka.classifiers.evaluation.RPD: Get the value of the named statistic
getStatistic(String) - Method in class weka.classifiers.evaluation.RSquared: Get the value of the named statistic
getStatistic(String) - Method in class weka.classifiers.evaluation.SDR: Get the value of the named statistic
getStatistic(String, int) - Method in class weka.classifiers.evaluation.Dice: Get the value of the named statistic for the given class index.
getStatisticNames() - Method in class weka.classifiers.evaluation.Bias: Get a list of the names of the statistics that this metrics computes.
getStatisticNames() - Method in class weka.classifiers.evaluation.Dice: Get a list of the names of the statistics that this metrics computes.
getStatisticNames() - Method in class weka.classifiers.evaluation.MSLE: Get a list of the names of the statistics that this metrics computes.
getStatisticNames() - Method in class weka.classifiers.evaluation.RPD: Get a list of the names of the statistics that this metrics computes.
getStatisticNames() - Method in class weka.classifiers.evaluation.RSquared: Get a list of the names of the statistics that this metrics computes.
getStatisticNames() - Method in class weka.classifiers.evaluation.SDR: Get a list of the names of the statistics that this metrics computes.
getStatistics() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Returns the statistics to output.
getStatistics() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Returns the statistics to output.
getStatisticValue() - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Returns the value to extract.
getStatisticValues() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the values to extract.
getStatisticValues() - Method in class adams.flow.transformer.WekaEvaluationValues: Returns the values to extract.
getStatusMessageHandler() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the current status message handler in use.
getStatusMessageHandler() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns the status message handler for outputting notifications.
getStatusMessageHandler() - Method in class adams.multiprocess.WekaCrossValidationJob: Returns the status message handler.
getStdDev() - Method in class weka.classifiers.meta.InputSmearing: Gets the multiplier for the standard deviation to use for input smearing.
getStdDev() - Method in class weka.filters.unsupervised.attribute.InputSmearing: Gets the multiplier for the standard deviation to use for input smearing.
getStopFlowIfCanceled() - Method in class adams.flow.source.WekaSelectDataset: Returns whether to stop the flow if dialog canceled.
getStopMode() - Method in class adams.flow.source.WekaSelectDataset: Returns the stop mode.
getStorage() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns the data storage item.
getStorageName() - Method in class adams.data.conversion.MapToWekaInstance: Returns the name of the stored Instances object to use as template.
getStorageName() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Returns the name for the data in the internal storage.
getStoreFilename() - Method in class adams.flow.transformer.WekaTextDirectoryReader: Returns whether the filename gets stored in extra attribute.
getStratify() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Returns whether to stratify the data (in case of nominal class).
getStratify() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns whether to stratify the data (in case of nominal class).
getStratify() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns whether to stratify the data (in case of nominal class).
getStratify() - Method in interface weka.classifiers.CrossValidationFoldGenerator: Returns whether to stratify the data (in case of nominal class).
getStratify() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns whether to stratify the data (in case of nominal class).
getStratify() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns whether to stratify the data (in case of nominal class).
getStratify() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns whether to stratify the data (in case of nominal class).
getStratify() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns whether to stratify the data (in case of nominal class).
getStrict() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns whether to enforce uniqueness in IDs.
getStructure() - Method in class weka.core.converters.AArffLoader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.SimpleArffLoader: Returns the structure of the dataset.
getStructure() - Method in class weka.core.converters.SpreadSheetLoader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure(Instances, String, TIntList) - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Returns the dataset structure.
getSubsampleRatio() - Method in class weka.classifiers.trees.XGBoost: Gets the sub-sample ratio of the training instances.
getSubset() - Method in class weka.classifiers.meta.Corr
getSubset(Instances) - Method in class weka.classifiers.meta.Corr
getSummaryFilter() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the filter to use to summarise the attributes.
getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaASEvaluator: The abstract superclass to use.
getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaASSearch: The abstract superclass to use.
getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaClassifier: The abstract superclass to use.
getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaClusterer: The abstract superclass to use.
getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaDataGenerator: The abstract superclass to use.
getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaFilter: The abstract superclass to use.
getSuperclass() - Method in class adams.gui.flow.tree.quickaction.EditWekaStreamableFilter: The abstract superclass to use.
getSupplementaryData() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns the stored Supplementary object.
getSupplementaryName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns the stored Supplementary name.
getSuppliedPrefix() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the prefix to use in case of OutputPrefixType.SUPPLIED.
getSuppliedReferenceDataset() - Method in class weka.filters.unsupervised.instance.AlignDataset: Returns the manually set reference dataset instead of loading one from disk.
getSuppliedTestSet() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the manually set test set instead of loading one from disk.
getSupport() - Method in class weka.classifiers.meta.ConsensusOrVote: Returns the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.
getSupport() - Method in class weka.classifiers.meta.Veto: Returns the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.
getSupportedFileExtensions(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractAdamsExperimentIO: Returns the supported file extensions.
getSupportedFileExtensions(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO: Returns the supported file extensions.
getSupportedFileExtensions(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractWekaExperimentIO: Returns the supported file extensions.
getSuppressModelOutput() - Method in class weka.classifiers.meta.AbstainingCascade: Returns whether to output the model with the toString() method or not.
getSuppressModelOutput() - Method in class weka.classifiers.meta.ConsensusOrVote: Returns whether to output the model with the toString() method or not.
getSuppressModelOutput() - Method in class weka.classifiers.meta.SuppressModelOutput: Returns whether to output the model with the toString() method or not.
getSuppressModelOutput() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Returns whether to output the model with the toString() method or not.
getSuppressModelOutput() - Method in class weka.classifiers.meta.Veto: Returns whether to output the model with the toString() method or not.
getSuppressModelOutput() - Method in class weka.classifiers.meta.VotedImbalance: Returns whether to output the model with the toString() method or not.
getSuppressModelOutput() - Method in interface weka.core.ModelOutputHandler: Returns whether to output the model with the toString() method or not.
getSwapAxes() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns whether to swap the axes.
getSwapRowsAndColumns() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns whether to swap rows and columns.
getSwapRowsAndColumns() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns whether to swap rows and columns.
getTabbedPane() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns the underlying tabbed pane.
getTabbedPane() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: The tabbed pane for the results.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.DataTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.LogTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab: Returns the icon name for the tab icon.
getTabIcon() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel: Returns the icon to use in the tabbed pane.
getTabIcon() - Method in class adams.gui.tools.wekamultiexperimenter.LogPanel: Returns the icon to use in the tabbed pane.
getTabIcon() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: Returns the icon to use in the tabbed pane.
getTable() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Returns the table.
getTable() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Returns the table.
getTable() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Returns the table.
getTable() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Returns the table.
getTable() - Method in class adams.gui.visualization.instances.InstancesPanel: Returns the underlying table.
getTable(Report) - Static method in class adams.gui.visualization.instance.InstanceReportFactory: Returns a new table for the given report.
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class adams.gui.visualization.instances.AttributeValueCellRenderer: Returns the default table cell renderer.
getTableEpilog() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns the epilog for a table.
getTableModel() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Get the table model in use (or null if no instances have been set yet).
getTableModelClass() - Method in class adams.gui.visualization.instance.InstanceTable: Returns the class of the table model that the models need to be derived from.
getTableName() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the table name to store the data in.
getTableProlog() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns the prolog of a table.
getTabTitle() - Method in class weka.gui.explorer.ExperimentPanel: Returns the title for the tab in the Explorer.
getTabTitle() - Method in class weka.gui.explorer.SqlPanel: Returns the title for the tab in the Explorer
getTabTitleToolTip() - Method in class weka.gui.explorer.ExperimentPanel: Returns the tooltip for the tab in the Explorer.
getTabTitleToolTip() - Method in class weka.gui.explorer.SqlPanel: Returns the tooltip for the tab in the Explorer
getTarget() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: Returns the current object.
getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.DIPLS: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.KernelPLS: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.NIPALS: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.OPLS: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.PLS1: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.PRM: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.SIMPLS: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.SparsePLS: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class adams.data.instancesanalysis.pls.VCPLS: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.GPD: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.AbstainVote: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.ClassificationViaRegressionD: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.InputSmearing: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.trees.m5.M5Base2: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.trees.XGBoost: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.clusterers.SAXKMeans
getTechnicalInformation() - Method in class weka.core.SAXDistance: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.WeightedEuclideanDistance: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.WeightedEuclideanDistanceRidge: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.supervised.attribute.PLS: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.FastWavelet: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.FFT: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.InputSmearing: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTemplate() - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels: Returns the MultipleClassifiersCombiner template to use.
getTemplate() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels: Returns the Vote template to use.
getTemplate() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: Returns the stored template object.
getTemplate() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds: Returns the Vote template to use.
getTemplate() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns the stored template object.
getTemplate() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns the stored template object.
getTemplate() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: Returns the stored template object.
getTest() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the name of the callable actor to obtain the test set.
getTest() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: The test data.
getTest() - Method in class adams.multiprocess.WekaCrossValidationJob: Returns the test set.
getTestAttributes() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the range of attributes from the test to add to the output.
getTestBase() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the index of the test base.
getTestBase() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the index of the test base.
getTestData() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns the (optional) storage item that contains the test data; cross-validation is performed if not present.
getTester() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the Tester in use.
getTester() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the Tester in use.
getTester() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Returns the tester.
getTester(Instances) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Sets up the testing algorithm and returns it.
getTestingUpdateInterval() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Returns the interval to use for outputting progress info during testing.
getTestInstances() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Returns the test instances in use by the genetic algorithm.
getTestInstances() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the currently set test set (if null, cross-validation is used).
getTestset() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Returns the name of the callable clusterer in use.
getTestset() - Method in class adams.flow.transformer.WekaTestSetEvaluator: Returns the name of the callable classifier in use.
getTestSet() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the file containing the test set to remove from the data passing through the filter.
getTestSplitName() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns the name of the split to use for testing.
getTestSplitName() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Returns the name of the split to use for testing, ie generating predictions.
getThreshold() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator: Returns the threshold.
getThreshold() - Method in class adams.tools.CompareDatasets: Returns the threshold for the correlation coefficient.
getThreshold() - Method in class weka.classifiers.meta.ClassifierCascade: the threshold for the statistic for termination.
getThreshold() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Gets the threshold for the max error when predicting a numeric class.
getThreshold() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Gets the threshold for the max error when predicting a numeric class.
getThresholdCheck() - Method in class weka.classifiers.meta.ClassifierCascade: whether to go below or above the threshold.
getThresholds() - Method in class weka.classifiers.meta.VotedImbalance: Returns the pairs of threshold/number of resampled models.
getTimeFormat() - Method in class adams.ml.data.InstancesView: Returns the time formatter.
getTimeMsecFormat() - Method in class adams.ml.data.InstancesView: Returns the time/msec formatter.
getTimeout() - Method in class weka.classifiers.meta.SocketFacade: Returns the timeout in milli-second to wait for new connections.
getTimestampPrefix() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Return the timestamp prefix for logs.
getTimeZone() - Method in class adams.ml.data.InstancesView: Returns the currently used timezone.
getTipText() - Method in class adams.core.base.AttributeTypeList: Returns a tool tip for the GUI editor (ignored if null is returned).
getTitle() - Method in class adams.gui.application.WekaExperimenterPreferencesPanel: The title of the preferences.
getTitle() - Method in class adams.gui.application.WekaExplorerPreferencesPanel: The title of the preferences.
getTitle() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel: The title of the preferences.
getTitle() - Method in class adams.gui.application.WekaPluginManagerExtensions: The title of the initialization.
getTitle() - Method in class adams.gui.application.WekaSystemProperties: The title of the initialization.
getTitle() - Method in class adams.gui.menu.AppendDatasets: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.ArffViewer: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.BatchFilterDatasets: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.BayesNetEditor: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.BoundaryVisualizer: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.CostCurve: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.DarkLord: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.DatasetCompatibility: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.Experimenter: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.Explorer: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.GraphVisualizer: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.Hermione: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.InstanceCompare: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.InstanceExplorer: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.InstancesPlot: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.MakeCompatibleDatasets: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.MarginCurve: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.MergeDatasets: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.MultiExplorer: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.PackageManager: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.PlotAttributeVsAttribute: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.ROC: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.SqlViewer: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.TreeVisualizer: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.WekaCommandToCode: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.WekaInvestigator: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.WekaMultiExperimenter: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.WekaSimpleCLI: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.menu.Workbench: Returns the title of the window (and text of menuitem).
getTitle() - Method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem: The menu item title.
getTitle() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob: Returns the title of the job.
getTitle() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob: Returns the title of the job.
getTitle() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputGenerator: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Returns the title of this 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.repeated.Predictions: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsFitted: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsPredictor: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.RunInformation: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeVisualizer: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ClusterAssignments: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.GraphSource: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.LegacyTreeVisualizer: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ModelOutput: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.RunInformation: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.DataTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.RunInformation: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: The title to use for the tab.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.LogTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Returns the title of this table.
getTitle() - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab: Returns the title of this table.
getTitle() - Method in class weka.gui.explorer.ExplorerExt: Returns the base title in use by the title generator.
getTitleClassDetails() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the title to use for the class details.
getTitleGenerator() - Method in class weka.gui.explorer.ExplorerExt: Returns the title generator in use.
getTitleMatrix() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the title to use for the confusion matrix.
getTitleNameColumn() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the title of the "Name" column, i.e., the first column.
getTitleSummary() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the title to use for the summary.
getTitleValueColumn() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the title of the "Value" column, i.e., the first column.
getTokenizers() - Method in class weka.core.tokenizers.MultiTokenizer: Returns the tokenizers to use.
getTol() - Method in class adams.data.instancesanalysis.pls.KernelPLS: Sets the inner NIPALS loop maximum number of iterations.
getTol() - Method in class adams.data.instancesanalysis.pls.NIPALS: Returns the inner NIPALS loop improvement tolerance.
getTol() - Method in class adams.data.instancesanalysis.pls.PRM: Returns the inner NIPALS loop improvement tolerance.
getTol() - Method in class adams.data.instancesanalysis.pls.SparsePLS: Returns the inner NIPALS loop improvement tolerance.
getTolerateHeaderChanges() - Method in class adams.data.instances.AbstractInstanceGenerator: Returns whether to tolerate header changes and merely re-generating the header instead of throwing an exception.
getToolTipsEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Returns whether to show tool tips.
getToolTipsEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Returns whether to show tool tips.
getToolTipsEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Returns whether to show tool tips.
getToolTipsEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Returns whether to show tool tips.
getToolTipsEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Returns whether to show tool tips.
getToolTipText(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Returns "<nominal value> [<nominal value count>]" if displaying a bar plot and mouse is on some bar.
getTopK() - Method in class weka.classifiers.trees.XGBoost: Gets the number of top features to select when using the greedy or thrifty feature selector.
getTrain() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the name of the callable actor to obtain the training set.
getTrain() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: The training data.
getTrain() - Method in class adams.multiprocess.WekaCrossValidationJob: Returns the training set.
getTrain() - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Returns the training data in use.
getTrainingSet(int) - Method in class weka.classifiers.meta.InputSmearing: Returns a training set for a particular iteration.
getTrainingSet(int, int) - Method in class weka.classifiers.meta.SubsetEnsemble: Gets a training set for a particular index.
getTrainingSet(int, int) - Method in class weka.classifiers.meta.VotedImbalance: Gets a training set for a particular index.
getTrainSplitName() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns the name of the split to use for training.
getTrainSplitName() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Returns the name of the split to use for training.
getTransformedInstances() - Method in class weka.core.neighboursearch.TransformNNSearch
getTreeMethod() - Method in class weka.classifiers.trees.XGBoost: Gets the tree construction algorithm used in XGBoost.
getTrials() - Method in class weka.classifiers.trees.RandomModelTrees
getTurnOffAbstaining() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: Returns whether abstaining of the base classifier is turned off.
getTweedieVariancePower() - Method in class weka.classifiers.trees.XGBoost: Gets the parameter that controls the variance of the Tweedie distribution.
getType() - Method in class adams.flow.transformer.WekaClassifierInfo: Returns the type of information to generate.
getType() - Method in enum adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType: Returns the corresponding Vote type.
getType() - Method in class adams.flow.transformer.WekaClustererInfo: Returns the type of information to generate.
getType() - Method in class adams.flow.transformer.WekaEvaluationInfo: Returns the type of information to generate.
getType() - Method in class adams.flow.transformer.WekaExtractArray: Returns the type of extraction to perform.
getType() - Method in class adams.flow.transformer.WekaInstancesInfo: Returns the type of information to generate.
getType() - Method in class adams.gui.event.InstancesSortSetupEvent: Returns the event type.
getType() - Method in class adams.gui.event.WekaInvestigatorDataEvent: Returns the type.
getType() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Returns the conversion type to use.
getType(int) - Method in class adams.gui.visualization.instances.InstancesTableModel: returns the TYPE of the attribute at the given position
getType(int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel: returns the TYPE of the attribute at the given position
getUndo() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Returns the current undo manager.
getUndo() - Method in class adams.gui.visualization.instance.InstancePanel: Returns the current undo manager, can be null.
getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Returns the data to store in the undo.
getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.DatabaseContainer: Returns the data to store in the undo.
getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer: Returns the data to store in the undo.
getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer: Returns the data to store in the undo.
getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer: Returns the data to store in the undo.
getUndoData() - Method in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer: Returns the data to store in the undo.
getUndoHandler() - Method in class adams.gui.visualization.instances.InstancesTable: Returns the undo handler in use.
getUndoHandler() - Method in class adams.gui.visualization.instances.InstancesTableModel: Returns the undo handler in use.
getUniqueID() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Gets the name of the unique ID attribute that the merge is joining on.
getUniqueID() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the attribute (string/numeric) to use for uniquely identifying rows.
getUnpruned() - Method in class weka.classifiers.trees.m5.M5Base2: Get whether unpruned tree/rules are being generated
getUnpruned() - Method in class weka.classifiers.trees.m5.Rule2: Get whether unpruned tree/rules are being generated
getUnselectedColumns(int[], int) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter: Creates an int[] which contains the unselected columns.
getUnset() - Method in class adams.flow.transformer.WekaClassSelector: Returns whether to unset the class attribute.
getUpdateContainerColor() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet: Returns whether to update the container's color with the color determined by this paintlet.
getUpdateHeader() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns whether to remove the labels also from the attribute definition.
getUpdateInterval() - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater: Returns the number of tokens after which the display is being updated.
getUpdater() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the updater in use.
getUpdater() - Method in class weka.classifiers.trees.XGBoost: Gets the choice of algorithm to fit the linear model.
getUpdateRelationName() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns whether to update the relation name with the new class attribute.
getUpdateWait() - Method in class weka.classifiers.functions.FakeClassifier: Returns the time in msec to wait when calling updateClassifier.
getUpper() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Returns the upper value to output.
getUpper() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Returns the upper value to output.
getUpper() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Returns the upper value to output.
getUpper() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the upper value to output.
getURL() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the query to execute.
getURL() - Method in class adams.flow.source.WekaDatabaseReader: Returns the query to execute.
getUseAbsoluteError() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns whether to use an absolute error (ie no direction).
getUseAbsoluteError() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Returns whether to use an absolute error (ie no direction).
getUseColumnNamesAsClassLabels() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns whether to use the names of the class distribution columns as labels in the fake evaluation.
getUseCustomLoader() - Method in class adams.flow.transformer.WekaFileReader: Returns whether a custom loader is used or not.
getUseCustomLoader() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns whether a custom loader is used or not.
getUseCustomLoader() - Method in class weka.filters.unsupervised.instance.AlignDataset: Returns whether to use a custom loader or automatic loading.
getUseCustomLoader() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns whether to use a custom loader or automatic loading.
getUseCustomPaintlet() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns whether to use the custom paintlet.
getUseCustomSaver() - Method in class adams.flow.sink.WekaFileWriter: Returns whether a custom saver is used or not.
getUseError() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns whether to use the error for the cross size.
getUseFilename() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns whether to use the filename (w/o path) instead of the relationname.
getUseFilename() - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ExperimentWithCustomizableRelationNames: Returns whether to use the filename (w/o path) instead of the relationname.
getUseFilename() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Returns whether to use the filename as relation name.
getUseFilename() - Method in class weka.experiment.ExtExperiment: Returns whether to use the filename (w/o path) instead of the relationname.
getUseFixedMinMax() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns whether to use user-supplied min/max for bin calculation rather than obtain min/max from data.
getUseMedian() - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters: Returns whether to use the median instead of the mean.
getUseModelResetVariable() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the whether to use a variable to monitor for changes in order to reset the model.
getUseOriginalIndices() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns whether to align with original data (requires: WekaEvaluationContainer as input and original indices in container).
getUseOuterWindow() - Method in class adams.flow.source.WekaSelectDataset: Returns whether to use the outer window as parent.
getUsePrefix() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns whether to use prefixes.
getUseProbabilities() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Returns whether to use probabilities instead of 0 and 1 for the counts.
getUser() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the database user.
getUser() - Method in class adams.flow.source.WekaDatabaseReader: Returns the database user.
getUseRelationNameAsFilename() - Method in class adams.flow.sink.WekaFileWriter: Returns whether the relation name is used as filename.
getUseRelationNameAsFilename() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns whether the relation name is used as filename.
getUseRelationNameAsTable() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns whether to output single Instance objects or just one Instances object.
getUserMode() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.AppendDatasets: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.ArffViewer: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.BatchFilterDatasets: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.BayesNetEditor: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.BoundaryVisualizer: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.CostCurve: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.DatasetCompatibility: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.Experimenter: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.Explorer: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.GraphVisualizer: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.InstanceCompare: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.InstanceExplorer: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.InstancesPlot: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.MakeCompatibleDatasets: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.MarginCurve: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.MergeDatasets: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.MultiExplorer: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.PackageManager: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.PlotAttributeVsAttribute: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.ROC: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.SqlViewer: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.TreeVisualizer: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.WekaCommandToCode: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.WekaInvestigator: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.WekaMultiExperimenter: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.WekaSimpleCLI: Returns the user mode, which determines visibility as well.
getUserMode() - Method in class adams.gui.menu.Workbench: Returns the user mode, which determines visibility as well.
getUseRowAttribute() - Method in class adams.tools.CompareDatasets: Returns whether to use the row attribute or the order in the datasets for matching up the rows.
getUseSaveDialog() - Method in class adams.gui.wizard.WekaSelectDatasetPage: Returns whether the save or open dialog is used.
getUseSecondEvaluation() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob: Returns the whether to use second evaluation.
getUseSecondEvaluation() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Returns whether to use the second evaluation.
getUseThread() - Method in class adams.gui.menu.PlotAttributeVsAttribute: Whether to use a simple runnable for launching or a separate thread.
getUseTree() - Method in class weka.classifiers.trees.m5.Rule2: get whether an m5 tree is being used rather than rules
getUseUnsmoothed() - Method in class weka.classifiers.trees.m5.M5Base2: Get whether or not smoothing is being used
getUseViews() - Method in interface adams.data.weka.InstancesViewSupporter: Returns whether to use views.
getUseViews() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns whether to use views instead of dataset copies, in order to conserve memory.
getUseViews() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns whether to use views instead of dataset copies, in order to conserve memory.
getUseViews() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns whether to use views instead of dataset copies, in order to conserve memory.
getUseViews() - Method in class weka.classifiers.AbstractSplitGenerator: Returns whether to use views.
getValue() - Method in class adams.flow.transformer.WekaSetInstancesValue: Returns the value to set in the report.
getValue() - Method in class adams.flow.transformer.WekaSetInstanceValue: Returns the value to set in the report.
getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the integer value from the property container.
getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the double value from the property container.
getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the float value from the property container.
getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GenericInteger: Returns the double value from the property container.
getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GenericString: Returns the string value from the property container.
getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GPDGamma: Returns the double value from the property container.
getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.GPDNoise: Returns the double value from the property container.
getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.PLSFilterNumComponents: Returns the integer value from the property container.
getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints: Returns the integer value from the property container.
getValue(PropertyPath.PropertyContainer) - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix: Returns the matrix value from the property container.
getValue(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler: Returns the value currently being edited.
getValue(Map, String, Object) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Returns the specified default value if the map doesn't contain a value for the specified key.
getValue(Evaluation, EvaluationStatistic, int) - Static method in class adams.flow.core.EvaluationHelper: Returns a statistical value from the evaluation object.
getValue(Instance, int) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the value of the specified attribute from the given Instance.
getValueAt(int, int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: Returns the value at the specified position.
getValueAt(int, int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel: Gets a table cell
getValueAt(int, int) - Method in class adams.gui.visualization.instance.InstanceTableModel: Returns the value at the given position.
getValueAt(int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel: returns the value for the cell at columnindex and rowIndex
getValueEnsureEqual(int[], List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the value of the mapped attribute, ensuring that all possible sources either provide a missing value or the same value as each other.
getValueFirstAvailable(int[], List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the first encountered source value for a merged attribute.
getVariableName() - Method in class adams.flow.template.InstanceDumperVariable: Returns the variable name to generate the sub-flow for.
getVariableName() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns the name of the variable to monitor.
getVariableName() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns the name of the variable to monitor.
getVariance() - Method in class adams.data.instancesanalysis.PCA: Returns the variance.
getVariance() - Method in class weka.classifiers.meta.AbstainLeastMedianSq
getVarianceCovered() - Method in class adams.flow.transformer.WekaPrincipalComponents: Gets the proportion of total variance to account for when retaining principal components.
getVarianceCovered() - Method in class weka.core.neighboursearch.PCANNSearch: Gets the proportion of total variance to account for when retaining principal components.
getVarianceCovered() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Gets the proportion of total variance to account for when retaining principal components.
getVector(Matrix, int) - Static method in class weka.core.matrix.MatrixHelper: returns the (column) vector of the matrix at the specified index
getVerbosity() - Method in class weka.classifiers.trees.XGBoost: Gets the verbosity level.
getVersusFitOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Get the options for the vsfit plot.
getVersusOrderOptions() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Get the options for the vsorder plot.
getVisible(int) - Method in class adams.gui.visualization.instance.InstanceContainerManager: Returns the nth visible container.
getVisibleIndices() - Method in class adams.gui.visualization.instance.InstanceContainerManager: Returns the indices of all visible containers.
getVisualizeMenuItem(String, String) - Method in class weka.gui.visualize.plugins.SaveGraph: Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the graph in XML BIF format.
getVisualizeMenuItem(String, String) - Method in class weka.gui.visualize.plugins.SaveTree: Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the tree in GraphViz's dotty format.
getVisualizeMenuItem(ArrayList<Prediction>, Attribute) - Method in class weka.gui.visualize.plugins.ThresholdCurves: Get a JMenu or JMenuItem which contain action listeners that perform the visualization, using some but not necessarily all of the data.
getVisualizeMenuItem(Instances) - Method in class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors: Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the classifier errors.
getVisualizeMenuItem(Instances) - Method in class weka.gui.visualize.plugins.FixedClassifierErrors: Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the classifier errors.
getVisualizeMenuItem(Instances) - Method in class weka.gui.visualize.plugins.FixedClassifierErrorsPlot: Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the classifier errors.
getVotingType() - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs: Returns the type of voting in use.
getWaitForJobs() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns whether to wait for jobs to finish when terminating.
getWaveNoRegExp() - Method in class weka.filters.unsupervised.attribute.Detrend: Returns the regular expression used for extracting the wave number from the attribute name (using the first group).
getWaveNoRegExp() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Returns the regular expression used for extracting the wave number from the attribute name (using the first group).
getWeight() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the (optional) column with the instance weight values.
getWeight() - Method in class weka.classifiers.functions.FromPredictions: Returns the column with the weight values.
getWeightIndex() - Method in class weka.classifiers.functions.FromPredictions: Returns the weight 0-based index.
getWeightingKernel() - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Gets the kernel weighting method to use.
getWeightingKernel() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Gets the kernel weighting method to use.
getWeights() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Returns the optional property in the incoming properties for the initial weights to use.
getWeights(OptData) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection
getWindows() - Method in class weka.filters.unsupervised.attribute.PAA: Returns the nth point setting.
getWindows() - Method in class weka.filters.unsupervised.attribute.SAX: Returns the nth point setting.
getWithReplacement() - Method in class adams.flow.transformer.WekaBootstrapping: Returns whether to draw predictions using replacement.
getWriter() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Returns the spreadsheet writer to use.
getWriterClass() - Method in class adams.gui.chooser.AdamsExperimentFileChooser: Returns the writer superclass for the GOE.
getWriterClass() - Method in class adams.gui.chooser.WekaFileChooser: Returns the writer superclass for the GOE.
getWriterForFile(File) - Method in class adams.gui.chooser.AdamsExperimentFileChooser: Returns the writer for the specified file.
getWriterForFile(File) - Method in class adams.gui.chooser.WekaFileChooser: Returns the writer for the specified file.
getWriters() - Static method in class adams.data.io.output.AbstractAdamsExperimentWriter: Returns a list with classes of writers.
getX() - Method in class adams.data.instance.InstancePoint: Returns the X value.
getX(Instance) - Static method in class weka.core.matrix.MatrixHelper: returns the data minus the class column as matrix
getX(Instances) - Static method in class weka.core.matrix.MatrixHelper: returns the data minus the class column as matrix
getX(Instances) - Method in class weka.filters.supervised.attribute.PLSFilterExtended: Override superclass method in order to deal with multiple y
getXRegExp() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the regular expression to identify the X attributes.
getxWeights() - Method in class weka.filters.supervised.attribute.PLSFilterExtended
getY() - Method in class adams.data.instance.InstancePoint: Returns the Y value.
getY(Instance) - Static method in class weka.core.matrix.MatrixHelper: returns the data class column as matrix
getY(Instances) - Static method in class weka.core.matrix.MatrixHelper: returns the data class column as matrix
getY(Instances) - Method in class weka.filters.supervised.attribute.PLSFilterExtended: Override superclass method in order to deal with multiple y
getY(Instances, int[]) - Static method in class weka.core.matrix.MatrixHelper: returns the data class columns as matrix
getYRegExp() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the regular expression to identify the Y attributes.
getZoomOverview() - Method in class adams.flow.sink.WekaInstanceViewer: Returns whether the zoom overview gets displayed.
getZoomOverviewPanel() - Method in class adams.gui.visualization.instance.InstancePanel: Returns the zoom overview panel.
globalInfo() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns a string describing the object.
globalInfo() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns a string describing the object.
globalInfo() - Method in class adams.core.discovery.genetic.GenericInteger: Returns a string describing the object.
globalInfo() - Method in class adams.core.discovery.genetic.GenericString: Returns a string describing the object.
globalInfo() - Method in class adams.core.discovery.genetic.GPDGamma: Returns a string describing the object.
globalInfo() - Method in class adams.core.discovery.genetic.GPDNoise: Returns a string describing the object.
globalInfo() - Method in class adams.core.discovery.genetic.PLSFilterNumComponents: Returns a string describing the object.
globalInfo() - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints: Returns a string describing the object.
globalInfo() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix: Returns a string describing the object.
globalInfo() - Method in class adams.core.management.WekaHomeEnvironmentModifier: Returns a string describing the object.
globalInfo() - Method in class adams.core.management.WekaPackagesClassPathAugmenter: Returns a string describing the object.
globalInfo() - Method in class adams.data.baseline.AbstractLinearRegressionBased: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.AdamsInstanceToWekaInstance: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.MapToWekaInstance: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.ReportToWekaInstance: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.SpreadSheetToWekaInstances: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.SwapPLS: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaCapabilitiesToInstances: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaCapabilitiesToSpreadSheet: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaCommandToCode: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaDrawableToString: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaEvaluationToCostCurve: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaEvaluationToMarginCurve: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaInstanceToAdamsInstance: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaInstanceToMap: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaPackageToMap: Returns a string describing the object.
globalInfo() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns a string describing the object.
globalInfo() - Method in class adams.data.featureconverter.Weka: Returns a string describing the object.
globalInfo() - Method in class adams.data.indexedsplits.InstancesIndexedSplitsRunsCompatibility: Returns a string describing the object.
globalInfo() - Method in class adams.data.instancesanalysis.FastICA: Returns a string describing the object.
globalInfo() - Method in class adams.data.instancesanalysis.PCA: Returns a string describing the object.
globalInfo() - Method in class adams.data.instancesanalysis.pls.DIPLS: Returns a string describing the object.
globalInfo() - Method in class adams.data.instancesanalysis.PLS: Returns a string describing the object.
globalInfo() - Method in class adams.data.instancesanalysis.pls.KernelPLS: Returns a string describing the object.
globalInfo() - Method in class adams.data.instancesanalysis.pls.NIPALS: Returns a string describing the object.
globalInfo() - Method in class adams.data.instancesanalysis.pls.OPLS: Returns a string describing the object.
globalInfo() - Method in class adams.data.instancesanalysis.pls.PLS1: Returns a string describing this class.
globalInfo() - Method in class adams.data.instancesanalysis.pls.PRM: Returns a string describing the object.
globalInfo() - Method in class adams.data.instancesanalysis.pls.SIMPLS: Returns a string describing this class.
globalInfo() - Method in class adams.data.instancesanalysis.pls.SparsePLS: Returns a string describing the object.
globalInfo() - Method in class adams.data.instancesanalysis.pls.VCPLS: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.input.ArffSpreadSheetReader: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.input.InstanceReader: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.input.JsonAdamsExperimentReader: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.input.JSONSpreadSheetReader: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.input.LibSVMSpreadSheetReader: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.input.MatlabSpreadSheetReader: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.input.NestedAdamsExperimentReader: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.input.SerializedAdamsExperimentReader: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.input.SVMLightSpreadSheetReader: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.input.XrffSpreadSheetReader: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.output.ArffSpreadSheetWriter: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.output.JsonAdamsExperimentWriter: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.output.JSONSpreadSheetWriter: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.output.LibSVMSpreadSheetWriter: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.output.MatlabSpreadSheetWriter: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.output.NestedAdamsExperimentWriter: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.output.SerializedAdamsExperimentWriter: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.output.SVMLightSpreadSheetWriter: Returns a string describing the object.
globalInfo() - Method in class adams.data.io.output.XrffSpreadSheetWriter: Returns a string describing the object.
globalInfo() - Method in class adams.data.spreadsheet.filter.WekaFilter: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.classattribute.AttributeIndex: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.classattribute.ByExactName: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.classattribute.ByName: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.classattribute.LastAttribute: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.classattribute.NoClassAttribute: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.columnfinder.AllFinder: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.columnfinder.ByExactName: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.columnfinder.ByName: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.columnfinder.Class: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.columnfinder.Constant: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.columnfinder.Invert: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.columnfinder.MultiColumnFinder: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.columnfinder.NullFinder: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.datasetsplitter.ColumnSplitter: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.datasetsplitter.RowSplitter: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.evaluator.PassThrough: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.predictions.AutoScaler: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.predictions.FixedSizeErrorScaler: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.predictions.RoundErrorScaler: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.relationname.AttributeIndex: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.relationname.ClassAttribute: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.relationname.FileName: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.relationname.NoChange: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.rowfinder.AllFinder: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.rowfinder.ByLabel: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.rowfinder.ByNumericRange: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.rowfinder.Constant: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.rowfinder.FilteredIQR: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.rowfinder.Invert: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.rowfinder.MultiRowFinder: Returns a string describing the object.
globalInfo() - Method in class adams.data.weka.rowfinder.NullFinder: Returns a string describing the object.
globalInfo() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Returns a string describing the object.
globalInfo() - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor: Returns a string describing the object.
globalInfo() - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor: Returns a string describing the object.
globalInfo() - Method in class adams.flow.condition.bool.AdamsInstanceCapabilities: Returns a string describing the object.
globalInfo() - Method in class adams.flow.condition.bool.WekaCapabilities: Returns a string describing the object.
globalInfo() - Method in class adams.flow.condition.bool.WekaClassification: Returns a string describing the object.
globalInfo() - Method in class adams.flow.core.WekaClassifierModelLoader: Returns a string describing the object.
globalInfo() - Method in class adams.flow.core.WekaClustererModelLoader: Returns a string describing the object.
globalInfo() - Method in class adams.flow.core.WekaFilterModelLoader: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaAttributeSummary: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaClassifierErrors: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaCostBenefitAnalysis: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaCostCurve: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaExperimentFileWriter: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaFileWriter: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaGraphVisualizer: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaInstancesDisplay: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaInstancesPlot: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaInstanceViewer: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaMarginCurve: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaModelWriter: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaThresholdCurve: Returns a string describing the object.
globalInfo() - Method in class adams.flow.sink.WekaTreeVisualizer: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.valuedefinition.WekaGOEValueDefinition: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaAssociatorSetup: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaClassifierGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaClassifierSetup: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaClustererGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaClustererSetup: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaDatabaseReader: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaDataGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaFilterGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaNewExperiment: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaNewInstances: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaPackageManagerAction: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaSelectDataset: Returns a string describing the object.
globalInfo() - Method in class adams.flow.source.WekaSelectObjects: Returns a string describing the object.
globalInfo() - Method in class adams.flow.standalone.WekaPackageManagerAction: Returns a string describing the object.
globalInfo() - Method in class adams.flow.standalone.wekapackagemanageraction.RefreshCache: Returns a string describing the object.
globalInfo() - Method in class adams.flow.template.InstanceDumperVariable: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.AbstractInstanceGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaAccumulatedError: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaAggregateEvaluations: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaAttributeIterator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaAttributeSelectionSummary: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaBootstrapping: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaChooseAttributes: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaClassifierInfo: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaClassifierOptimizer: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.PassThrough: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaClassifying: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaClassSelector: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaClusterAssignments: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaclusterer.AddCluster: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaclusterer.ClusterCounts: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaclusterer.ClusterStatistics: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaclusterer.PassThrough: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaClustererInfo: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaClustererPostProcessor: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaClusterEvaluationSummary: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaClustering: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaDatasetsMerge: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekadatasetsmerge.Simple: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaDatasetSplit: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaEnsembleGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaEvaluationInfo: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.PassThrough: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaEvaluationValues: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaExperiment: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaExperimentExecution: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaExperimentFileReader: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaExtractArray: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaExtractPLSMatrix: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaFileReader: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaFilter: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaGetCapabilities: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaGetInstancesValue: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaGetInstanceValue: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaInstanceFileReader: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaInstancesAppend: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaInstancesInfo: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaInstancesStatistic: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaModelReader: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaNewInstance: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaPackageManagerAction: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromFile: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallFromURL: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.InstallPackage: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaPredictionsToInstances: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaPredictionsToSpreadSheet: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaPrincipalComponents: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaRandomSplit: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaRegexToRange: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaRelationName: Deprecated.

Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaRenameRelation: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaSetInstancesValue: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaSetInstanceValue: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaSplitGenerator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaStoreInstance: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaStreamEvaluator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaStreamFilter: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaSubsets: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaTestSetEvaluator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaTextDirectoryReader: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaTrainAssociator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaTrainClassifier: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaTrainClusterer: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator: Returns a string describing the object.
globalInfo() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.previewbrowser.GraphSource: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.previewbrowser.GraphVisualizer: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.previewbrowser.InstanceExplorerHandler: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.previewbrowser.InterQuartileRangeViewer: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.previewbrowser.TreeVisualizer: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.previewbrowser.WekaDatasetHandler: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.ModelOutput: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.Rules: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.output.RunInformation: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.ReducedData: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.RunInformation: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.Null: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.Simple: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.GraphSource: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyClassifierErrors: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyGraphVisualizer: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyMarginCurve: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyTreeVisualizer: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ModelOutput: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsFitted: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsPredictor: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.RunInformation: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeVisualizer: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ClusterAssignments: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.GraphSource: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.LegacyTreeVisualizer: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.ModelOutput: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.RunInformation: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.RunInformation: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultAdamsExperimentIO: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultWekaExperimentIO: Returns a string describing the object.
globalInfo() - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instance.InstancePointHitDetector: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.AttributeStatistics: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.Binning: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.ColumnStatistic: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.DataSort: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.Histogram: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.JFreeChart: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.RowStatistic: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.SimplePlot: Returns a string describing the object.
globalInfo() - Method in class adams.gui.visualization.instances.instancestable.ViewCell: Returns a string describing the object.
globalInfo() - Method in class adams.ml.model.classification.WekaClassifier: Returns a string describing the object.
globalInfo() - Method in class adams.ml.model.clustering.WekaClusterer: Returns a string describing the object.
globalInfo() - Method in class adams.ml.model.regression.WekaRegressor: Returns a string describing the object.
globalInfo() - Method in class adams.opt.genetic.DarkLord: Returns a string describing the object.
globalInfo() - Method in class adams.opt.genetic.Hermione: Returns a string describing the object.
globalInfo() - Method in class adams.opt.genetic.initialsetups.PackDataInitialSetupsProvider: Returns a string describing the object.
globalInfo() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction
globalInfo() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AttributeSelection
globalInfo() - Method in class adams.opt.optimise.GeneticAlgorithm: Returns a string describing the object.
globalInfo() - Method in class adams.tools.CompareDatasets: Returns a string describing the object.
globalInfo() - Method in class weka.attributeSelection.LinearRegressionAttributeEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.PLS1AttributeEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.SIMPLSAttributeEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Returns a string describing the object.
globalInfo() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns a string describing the object.
globalInfo() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Returns a string describing the object.
globalInfo() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns a string describing the object.
globalInfo() - Method in class weka.classifiers.DefaultRandomSplitGenerator: Returns a string describing the object.
globalInfo() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.FakeClassifier: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.FromPredictions: Returns a string describing the object.
globalInfo() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.GeneticAlgorithm: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.GPD: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.LinearRegressionJ: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.MathExpressionClassifier: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.PLSClassifierWeighted: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.PLSWeighted: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.PyroProxy: Returns a string describing classifier.
globalInfo() - Method in class weka.classifiers.functions.SimpleLinearRegressionIntervalEstimator: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns a string describing the object.
globalInfo() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns a string describing the object.
globalInfo() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns a string describing the object.
globalInfo() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns a string describing the object.
globalInfo() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns a string describing the object.
globalInfo() - Method in class weka.classifiers.lazy.AbstainingLWL: Returns a string describing classifier.
globalInfo() - Method in class weka.classifiers.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.AlignDataset: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.instance.DatasetCleaner: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.KeepRange: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.KennardStone: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.instance.LatestRecords: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin: Returns a string describing the processor.
globalInfo() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.Average: Returns a string describing the processor.
globalInfo() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.PassThrough: Returns a string describing the processor.
globalInfo() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Returns a string describing the row selection scheme.
globalInfo() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.IndividualRows: Returns a string describing the row selection scheme.
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.RowNorm: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.Scale: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.instance.Sort: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.SortOnAttribute: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns a string describing this classifier.
glueTipText() - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Returns the tip text for this property.
GPD - Class in weka.classifiers.functions: Implements Gaussian Processes for regression without hyperparameter-tuning, with an inline RBF kernel.
For more information see

David J.C.
GPD() - Constructor for class weka.classifiers.functions.GPD
GPDGamma - Class in adams.core.discovery.genetic: GPD gamma handler.
GPDGamma() - Constructor for class adams.core.discovery.genetic.GPDGamma
GPDNoise - Class in adams.core.discovery.genetic: GPD noise handler.
GPDNoise() - Constructor for class adams.core.discovery.genetic.GPDNoise
GPU - weka.classifiers.trees.XGBoost.Predictor
GPU_EXACT - weka.classifiers.trees.XGBoost.TreeMethod
GPU_HIST - weka.classifiers.trees.XGBoost.TreeMethod
graph() - Method in class weka.classifiers.trees.M5P2: Return a dot style String describing the tree.
graph(StringBuffer) - Method in class weka.classifiers.trees.m5.RuleNode2: Assign a unique identifier to each node in the tree and then calls graphTree
GRAPH - adams.flow.transformer.WekaClassifierInfo.InfoType: graph (if available).
GRAPH - adams.flow.transformer.WekaClustererInfo.InfoType: graph (if available).
GraphHelper - Class in adams.gui.tools.wekainvestigator.output: Helper class for graphs.
GraphHelper() - Constructor for class adams.gui.tools.wekainvestigator.output.GraphHelper
GraphSource - Class in adams.gui.tools.previewbrowser: Displays the source of a weka.core.Drawable graph.
GraphSource - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Displays the source code of the graph (dot or XML BIF).
GraphSource - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output: Displays the source code of the graph (dot or XML BIF).
GraphSource() - Constructor for class adams.gui.tools.previewbrowser.GraphSource
GraphSource() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.GraphSource
GraphSource() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.GraphSource
graphTree(StringBuffer) - Method in class weka.classifiers.trees.m5.RuleNode2: Return a dotty style string describing the tree
graphType() - Method in class weka.classifiers.trees.M5P2: Returns the type of graph this classifier represents.
GraphVisualizer - Class in adams.gui.menu: Displays data in the graph visualizer.
GraphVisualizer - Class in adams.gui.tools.previewbrowser: Displays BayesNet graphs.
GraphVisualizer() - Constructor for class adams.gui.menu.GraphVisualizer: Initializes the menu item with no owner.
GraphVisualizer() - Constructor for class adams.gui.tools.previewbrowser.GraphVisualizer
GraphVisualizer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.GraphVisualizer: Initializes the menu item.
GREEDY - weka.classifiers.trees.XGBoost.FeatureSelector
gridTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Returns the tip text for this property.
GROUP - Static variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression
GroupedBinnedNumericClassCrossValidationFoldGenerator - Class in weka.classifiers: Helper class for generating cross-validation folds.
GroupedBinnedNumericClassCrossValidationFoldGenerator() - Constructor for class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Initializes the generator.
GroupedBinnedNumericClassCrossValidationFoldGenerator(Instances, int, long, boolean) - Constructor for class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Initializes the generator.
GroupedBinnedNumericClassCrossValidationFoldGenerator(Instances, int, long, boolean, boolean, String) - Constructor for class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Initializes the generator.
GroupedBinnedNumericClassRandomSplitGenerator - Class in weka.classifiers: Generates random splits of datasets with numeric classes using a binning algorithm.
GroupedBinnedNumericClassRandomSplitGenerator() - Constructor for class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Initializes the generator.
GroupedBinnedNumericClassRandomSplitGenerator(Instances, double) - Constructor for class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Initializes the generator.
GroupedBinnedNumericClassRandomSplitGenerator(Instances, long, double) - Constructor for class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Initializes the generator.
GroupedBinnedNumericClassRandomSplitGenerator(Instances, long, double, boolean) - Constructor for class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Initializes the generator.
GroupedClassValueBinValueExtractor() - Constructor for class adams.data.binning.BinnableInstances.GroupedClassValueBinValueExtractor
GroupedCrossValidationFoldGenerator - Class in weka.classifiers: Helper class for generating cross-validation folds.
GroupedCrossValidationFoldGenerator() - Constructor for class weka.classifiers.GroupedCrossValidationFoldGenerator: Initializes the generator.
GroupedCrossValidationFoldGenerator(Instances, int, long, boolean, boolean, WekaAttributeIndex, BaseRegExp, String) - Constructor for class weka.classifiers.GroupedCrossValidationFoldGenerator: Initializes the generator.
GroupedCrossValidationFoldGeneratorUsingNumericClassValues - Class in weka.classifiers: Helper class for generating cross-validation folds.
Uses the string representation of the numeric class values as grouping.
GroupedCrossValidationFoldGeneratorUsingNumericClassValues() - Constructor for class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Initializes the generator.
GroupedCrossValidationFoldGeneratorUsingNumericClassValues(Instances, int, long, boolean) - Constructor for class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Initializes the generator.
GroupedRandomSplitGenerator - Class in weka.classifiers: Generates random splits of datasets, making sure that groups of instances stay together (identified via a regexp).
GroupedRandomSplitGenerator() - Constructor for class weka.classifiers.GroupedRandomSplitGenerator: Initializes the generator.
GroupedRandomSplitGenerator(Instances, long, double, boolean, WekaAttributeIndex, BaseRegExp, String) - Constructor for class weka.classifiers.GroupedRandomSplitGenerator: Initializes the generator.
GroupExpression - Class in weka.filters.unsupervised.instance.multirowprocessor.selection: Identifies groups in strings using regular expressions.
GroupExpression() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression
groups() - Method in class weka.core.InstanceGrouping: Returns the groups.
groupsTipText() - Method in class weka.classifiers.MultiLevelSplitGenerator: Returns the tip text for this property.
groupTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the tip text for this property.
groupTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns the tip text for this property.
groupTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
groupTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns the tip text for this property.
groupTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the tip text for this property.
groupTipText() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns the tip text for this property.
groupTipText() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Returns the tip text for this property.
growPolicyTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the growPolicy option.
GUI - adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption

H

handleException(String, Throwable) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Logs the error and returns a compiled error string.
handlersTipText() - Method in class adams.opt.genetic.Hermione: Returns the tip text for this property.
handlerTipText() - Method in class adams.flow.sink.WekaExperimentFileWriter: Returns the tip text for this property.
handlerTipText() - Method in class adams.flow.transformer.WekaExperimentFileReader: Returns the tip text for this property.
handles(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.AbstractWekaRepeatedCrossValidationOutput: Checks whether the cross-validation results can be processed.
handles(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Checks whether the cross-validation results can be processed.
handles(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Checks whether the cross-validation results can be processed.
handles(WekaEvaluationContainer[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Checks whether the cross-validation results can be processed.
handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.EncloseClassifier: Customizes the GOE popup menu.
handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.EncloseClusterer: Customizes the GOE popup menu.
handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.InvertInstancesColumnFinder: Customizes the GOE popup menu.
handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.InvertInstancesRowFinder: Customizes the GOE popup menu.
handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpClassifier: Customizes the GOE popup menu.
handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpClusterer: Customizes the GOE popup menu.
handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpInstancesColumnFinder: Customizes the GOE popup menu.
handles(GenericObjectEditorPopupMenu, PropertyEditor, JComponent) - Method in class adams.gui.goe.popupmenu.PullUpInstancesRowFinder: Customizes the GOE popup menu.
handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.containerlistpopup.SaveAs: Checks whether this action can handle the panel.
handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.containerlistpopup.ViewAsTable: Checks whether this action can handle the panel.
handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Adjust: Checks whether this action can handle the panel.
handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Histogram: Checks whether this action can handle the panel.
handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.SaveVisible: Checks whether this action can handle the panel.
handles(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Viewport: Checks whether this action can handle the panel.
handles(Class) - Method in class adams.core.option.WekaCommandLineHandler: Checks whether the given class can be processed.
handles(Class) - Method in class adams.flow.core.WekaPropertyValueConverter: Checks whether this converter handles the particular class.
handles(Class) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler: Checks whether the given class can be processed.
handles(Class) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator: Returns whether this class is handled by this generator.
handles(Class) - Method in class adams.gui.visualization.debug.inspectionhandler.WekaEvaluation: Checks whether the handler can handle the specified class.
handles(Class) - Method in class adams.gui.visualization.debug.inspectionhandler.WekaInstances: Checks whether the handler can handle the specified class.
handles(Class) - Method in class adams.gui.visualization.debug.objectexport.WekaInstancesExporter: Checks whether the exporter can handle the specified class.
handles(Class) - Method in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer: Checks whether the renderer can handle the specified class.
handles(Object) - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Checks whether this object is handled by this discovery handler.
handles(Object) - Method in class adams.core.discovery.genetic.GenericFloatResolution: Checks whether this object is handled by this discovery handler.
handles(Object) - Method in class adams.core.discovery.genetic.GenericInteger: Checks whether this object is handled by this discovery handler.
handles(Object) - Method in class adams.core.discovery.genetic.GenericString: Checks whether this object is handled by this discovery handler.
handles(Object) - Method in class adams.core.discovery.genetic.GPDGamma: Checks whether this object is handled by this discovery handler.
handles(Object) - Method in class adams.core.discovery.genetic.GPDNoise: Checks whether this object is handled by this discovery handler.
handles(Object) - Method in class adams.core.discovery.genetic.PLSFilterNumComponents: Checks whether this object is handled by this discovery handler.
handles(Object) - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints: Checks whether this object is handled by this discovery handler.
handles(Object) - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix: Checks whether this object is handled by this discovery handler.
handles(Object) - Method in class adams.gui.tools.previewbrowser.GraphSource: Returns whether viewer handles this object.
handles(Object) - Method in class adams.gui.tools.previewbrowser.GraphVisualizer: Returns whether viewer handles this object.
handles(Object) - Method in class adams.gui.tools.previewbrowser.InterQuartileRangeViewer: Returns whether viewer handles this object.
handles(Object) - Method in class adams.gui.tools.previewbrowser.TreeVisualizer: Returns whether viewer handles this object.
handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Checks whether this handler can process the given panel.
handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AssociationsHandler: Checks whether this handler can process the given panel.
handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AttributeSelectionHandler: Checks whether this handler can process the given panel.
handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ClassifierHandler: Checks whether this handler can process the given panel.
handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ClustererHandler: Checks whether this handler can process the given panel.
handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.DefaultHandler: Checks whether this handler can process the given panel.
handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ExperimentHandler: Checks whether this handler can process the given panel.
handles(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.PreprocessHandler: Checks whether this handler can process the given panel.
handlesExperiment(AbstractExperiment) - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: Checks whether the experiment can be handled.
handlesExperiment(Object) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Checks whether the experiment can be handled.
handlesExperiment(T) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: Checks whether the experiment can be handled.
handlesExperiment(Experiment) - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: Checks whether the experiment can be handled.
handlesResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel: Returns whether this panel handles the specified ResultListener.
handlesResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel: Returns whether this panel handles the specified ResultListener.
handlesResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel: Returns whether this panel handles the specified ResultListener.
handlesResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel: Returns whether this panel handles the specified ResultListener.
handlesResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel: Returns whether this panel handles the specified ResultListener.
handlesResults(Instances) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel: Checks whether the results can be handled at all.
handlesResults(Instances) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Checks whether the results can be handled at all.
handlesResults(Instances) - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel: Checks whether the results can be handled at all.
handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.AttributeStatistics: Checks whether the row range can be handled.
handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.Binning: Checks whether the row range can be handled.
handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.ChangeAttributeWeight: Checks whether the row range can be handled.
handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.ColumnStatistic: Checks whether the row range can be handled.
handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.DataSort: Checks whether the row range can be handled.
handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.Histogram: Checks whether the row range can be handled.
handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart: Checks whether the row range can be handled.
handlesRowRange(TableRowRange) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot: Checks whether the row range can be handled.
hasAdditionalAttributes() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns whether additional attributes data is present.
hasAttributeIndex() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Checks whether an attribute index has been set.
hasCallableActor() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Checks whether a reference to the callable actor is currently available.
hasCell(int) - Method in class adams.ml.data.InstancesHeaderRow: Returns whether the row alread contains the cell at the specified location.
hasCell(int) - Method in class adams.ml.data.InstanceView: Returns whether the row alread contains the cell at the specified location.
hasCell(int, int) - Method in class adams.ml.data.InstancesView: Checks whether the cell with the given indices already exists.
hasCell(String) - Method in class adams.ml.data.InstancesHeaderRow: Returns whether the row alread contains the cell with the given key.
hasCell(String) - Method in class adams.ml.data.InstanceView: Returns whether the row alread contains the cell with the given key.
hasChanged(DataContainer) - Method in class adams.gui.tools.wekainvestigator.datatable.action.Revert: Checks whether the container got changed or the source has changed.
hasClassifyTab() - Method in class weka.gui.explorer.ExplorerExt: Returns whether the classify tab is present.
hasClusterTab() - Method in class weka.gui.explorer.ExplorerExt: Returns whether the cluster tab is present.
hasCustomPanel(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler: Checks whether the editor supplies its own panel.
hasDataChanged(List<String>, ComboBoxModel<String>) - Static method in class adams.gui.tools.wekainvestigator.evaluation.DatasetHelper: Checks whether the data has changed and the model needs updating.
hasDataChanged(List<String>, ComboBoxModel<String>) - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Checks whether the data has changed and the model needs updating.
hasDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Checks whether an existing file has been set.
hasDatasetHeader() - Method in class adams.data.instance.Instance: Returns whether a header of a dataset is available.
hasEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: Returns whether an Evaluation object is present.
hasEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns whether an Evaluation object is present.
hasEvaluation() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns whether an Evaluation object is present.
hasExperiment() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: Returns whether an Evaluation object is present.
hasFoldEvaluations() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns whether Evaluation objects per fold are present.
hasFoldModels() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns whether Classifier objects per fold are present.
hasFull() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Checks whether a full dataset is present.
hasGraph(Drawable) - Static method in class adams.gui.tools.wekainvestigator.output.GraphHelper: Checks whether an actual graph is available.
HashableInstanceUsingString - Class in weka.core: TODO: what this class does
HashableInstanceUsingString(Instance) - Constructor for class weka.core.HashableInstanceUsingString: Initializes the wrapper.
HashableInstanceUsingSum - Class in weka.core: Computes the hashcode as sum of the internal double values.
HashableInstanceUsingSum(Instance) - Constructor for class weka.core.HashableInstanceUsingSum: Initializes the wrapper.
hashCode() - Method in class adams.gui.visualization.instance.InstanceContainer: Returns the hashcode of the instance.
hashCode() - Method in class weka.core.AbstractHashableInstance: Returns the hashcode of this Instance, computes it if neccessary.
hasHeader() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: Returns whether an training set header is present.
hasLastError() - Method in class weka.classifiers.AggregateEvaluations: Returns whether an error was encountered during the last operation.
hasLoadings() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class adams.data.instancesanalysis.pls.DIPLS: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class adams.data.instancesanalysis.pls.KernelPLS: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class adams.data.instancesanalysis.pls.NIPALS: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class adams.data.instancesanalysis.pls.OPLS: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class adams.data.instancesanalysis.pls.PLS1: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class adams.data.instancesanalysis.pls.PRM: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class adams.data.instancesanalysis.pls.SIMPLS: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class adams.data.instancesanalysis.pls.SparsePLS: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class adams.data.instancesanalysis.pls.VCPLS: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class weka.classifiers.functions.PLSWeighted: Whether the algorithm supports return of loadings.
hasLoadings() - Method in interface weka.core.GenericPLSMatrixAccess: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class weka.filters.supervised.attribute.MultiPLS: Whether the algorithm supports return of loadings.
hasLoadings() - Method in class weka.filters.supervised.attribute.PLS: Whether the algorithm supports return of loadings.
hasMissingValue() - Method in class weka.core.AbstractHashableInstance: Tests whether an instance has a missing value.
hasModel() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: Returns whether an model object is present.
hasModel() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns whether an model object is present.
hasModel() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns whether an model object is present.
hasMoreData() - Method in class adams.data.io.input.InstanceReader: Returns whether there is more data available.
hasMoreElements() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID.UniqueIDEnumeration
hasMoreElements() - Method in class adams.flow.transformer.wekadatasetsmerge.Simple.SimpleRowSetIterator
hasMoreElements() - Method in class weka.core.tokenizers.MultiTokenizer: Tests if this enumeration contains more elements.
hasMoreElements() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Tests if this enumeration contains more elements.
hasMoreZeroes(BitSet, BitSet) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: return if a has more zeroes than b.
hasName() - Method in class adams.ml.data.InstancesView: Returns whether the spreadsheet has a name.
hasNestedItems() - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem: Returns whether nested items are present.
hasNext() - Method in class weka.classifiers.AbstractSplitGenerator: Returns true if the iteration has more elements.
hasNext() - Method in interface weka.classifiers.SplitGenerator: Returns true if the iteration has more elements.
hasOriginalIndices() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns whether the original indices are present.
hasPendingOutput() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Checks whether there is pending output to be collected after executing the flow item.
hasPendingOutput() - Method in class adams.flow.source.WekaDatabaseReader: Checks whether there is pending output to be collected after executing the flow item.
hasPendingOutput() - Method in class adams.flow.transformer.WekaAccumulatedError: Checks whether there is pending output to be collected after executing the flow item.
hasPendingOutput() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Checks whether there is pending output to be collected after executing the flow item.
hasPendingOutput() - Method in class adams.flow.transformer.WekaFileReader: Checks whether there is pending output to be collected after executing the flow item.
hasPendingOutput() - Method in class adams.flow.transformer.WekaInstanceBuffer: Checks whether there is pending output to be collected after executing the flow item.
hasPendingOutput() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Checks whether there is pending output to be collected after executing the flow item.
hasPendingOutput() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Checks whether there is pending output to be collected after executing the flow item.
hasPendingOutput() - Method in class adams.flow.transformer.WekaSubsets: Checks whether there is pending output to be collected after executing the flow item.
hasPredictionsAvailable(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Checks whether any predictions are available from the selected items.
hasReadOnlyTable() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Returns whether a readonly table is used.
hasReadOnlyTable() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: Returns whether a readonly table is used.
hasReadOnlyTable() - Method in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab: Returns whether a readonly table is used.
hasReadOnlyTable() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Returns whether a readonly table is used.
hasReadOnlyTable() - Method in class adams.gui.tools.wekainvestigator.tab.MatrixTab: Returns whether a readonly table is used.
hasRegistered() - Method in class adams.gui.goe.WekaEditorsRegistration: Returns whether registration already occurred.
hasReport() - Method in class adams.data.instance.Instance: Checks whether a report is present.
hasResults() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel: Checks whether there are any results available.
hasRow(int) - Method in class adams.ml.data.InstancesView: Returns whether the spreadsheet already contains the row with the given index.
hasRow(String) - Method in class adams.ml.data.InstancesView: Returns whether the spreadsheet already contains the row with the given key.
hasRunEvaluations() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns whether Evaluation objects per run are present.
hasRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: Returns whether run information is present.
hasRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Returns whether run information is present.
hasRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns whether run information is present.
hasRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns whether run information is present.
hasRunInformation() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: Returns whether run information is present.
hasRunModels() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns whether Classifier objects per run are present.
hasRunOriginalIndices() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns whether the original indices per run are present.
hasSendToItem(Class[]) - Method in class adams.gui.tools.DatasetCompatibilityPanel: Checks whether something to send is available.
hasSendToItem(Class[]) - Method in class adams.gui.visualization.instance.InstanceExplorer: Checks whether something to send is available.
hasSendToItem(Class[]) - Method in class adams.gui.visualization.instances.InstancesTable: Checks whether something to send is available.
hasSendToItem(Class[]) - Method in class weka.gui.explorer.ExplorerExt: Checks whether something to send is available.
hasSourceChanged() - Method in class adams.gui.tools.wekainvestigator.data.FileContainer: Returns true if the source has changed.
hasSourceChanged() - Method in interface adams.gui.tools.wekainvestigator.data.MonitoringDataContainer: Returns true if the source has changed.
hasSupplementaryData() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns whether an Supplementary object is present.
hasSupplementaryName() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns whether a name for the Supplementary object is present.
hasValue() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Checks whether the value of text field is different from the default value, i.e., a proper value.
HEADER - adams.flow.transformer.WekaEvaluationInfo.InfoType
HEADER - adams.flow.transformer.WekaFileReader.OutputType: only the header.
HEADER - adams.flow.transformer.WekaInstancesInfo.InfoType: the header (as string).
headerTipText() - Method in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader: Returns the tip text for this property.
headerTipText() - Method in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader: Returns the tip text for this property.
Hermione - Class in adams.gui.menu: For optimizing datasets (parameter selection) using genetic algorithm.
Hermione - Class in adams.opt.genetic: Hermione.
Hermione() - Constructor for class adams.gui.menu.Hermione: Initializes the menu item with no owner.
Hermione() - Constructor for class adams.opt.genetic.Hermione
Hermione(AbstractApplicationFrame) - Constructor for class adams.gui.menu.Hermione: Initializes the menu item.
Hermione.HermioneJob - Class in adams.opt.genetic: A job class specific to Hermione.
HermioneJob(Hermione, int, int[], Instances, Instances) - Constructor for class adams.opt.genetic.Hermione.HermioneJob: Initializes the job.
hiClassifierTipText() - Method in class weka.classifiers.meta.HighLowSplit
hide(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, List<InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Viewport: Allows the user to hide the instances.
hideButtons(Container) - Method in class weka.gui.explorer.ExplorerExt: Hides the buttons of the preprocess panel.
hideOthers(DataContainerPanelWithContainerList<Instance, InstanceContainerManager, InstanceContainer>, List<InstanceContainer>) - Method in class adams.gui.visualization.instance.plotpopup.Viewport: Allows the user to hide all other instances.
HighLowSplit - Class in weka.classifiers.meta: Uses base classifier to get guess, then get prediction from either lo/hi classifier

Valid options are:
HighLowSplit() - Constructor for class weka.classifiers.meta.HighLowSplit
HighLowSplitSingleClassifier - Class in weka.classifiers.meta: Uses base classifier to get guess, then get prediction from either lo/hi classifier

Valid options are:
HighLowSplitSingleClassifier() - Constructor for class weka.classifiers.meta.HighLowSplitSingleClassifier
hiLopointTipText() - Method in class weka.classifiers.meta.HighLowSplit
HINGE_LOSS_FOR_BINARY_CLASSIFICATION - weka.classifiers.trees.XGBoost.Objective
HIST - weka.classifiers.trees.XGBoost.TreeMethod
HistCalc() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel.HistCalc
Histogram - Class in adams.gui.visualization.instance.plotpopup: Generates histograms from the visible containers.
Histogram - Class in adams.gui.visualization.instances.instancestable: Allows to generate a histogram from a column or row.
Histogram() - Constructor for class adams.gui.visualization.instance.plotpopup.Histogram
Histogram() - Constructor for class adams.gui.visualization.instances.instancestable.Histogram
HistogramFactory - Class in adams.gui.visualization.instance: A factory for histogram related objects.
HistogramFactory() - Constructor for class adams.gui.visualization.instance.HistogramFactory
HistogramFactory.Dialog - Class in adams.gui.visualization.instance: Dialog for displaying histograms generated from instances.
HistogramFactory.Panel - Class in adams.gui.visualization.instance: A panel for displaying a histogram based on the GC data of a instance.
HistogramFactory.SetupDialog - Class in adams.gui.visualization.instance: A dialog that queries the user about parameters for displaying histograms.
histogramOptionsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Tip text for the histogram options property.
HISTORY - adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption
historyEntrySelected(AbstractNamedHistoryPanel.HistoryEntrySelectionEvent) - Method in class weka.gui.explorer.MultiExplorer: Gets called whenever a history entry gets selected.
HistoryPanel(AssociateTab) - Constructor for class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Initializes the history.
HistoryPanel(AttributeSelectionTab) - Constructor for class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Initializes the history.
HistoryPanel(ClassifyTab) - Constructor for class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Initializes the history.
HistoryPanel(ClusterTab) - Constructor for class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Initializes the history.
HistoryPanel(ExperimentTab) - Constructor for class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Initializes the history.
HistoryPanel(DefaultAnalysisPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel.HistoryPanel: Initializes the history.
HOLDOUT_PERCENTAGE - Static variable in class weka.classifiers.meta.ClassifierCascade
holdOutPercentageTipText() - Method in class weka.classifiers.meta.ClassifierCascade: Returns the tip text for this property.

I

ICATipText() - Method in class adams.data.instancesanalysis.FastICA: Returns the tip text for this property.
IDTestTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the tip text for this property.
IDTipText() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the tip text for this property.
IDTipText() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Returns the tip text for this property.
IDTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the tip text for this property.
ignoreClassTipText() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: Returns the tip text for this property.
IGNORED_ATTRIBUTES - Static variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp
ignoredAttributesTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Returns the tip text for this property.
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.functions.PyroProxy: Returns true if this BatchPredictor can generate batch predictions in an efficient manner.
includeClassTipText() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns the tip text for this property.
includeClassTipText() - Method in class weka.filters.unsupervised.instance.Sort: Returns the tip text for this property.
incorrectTipText() - Method in class weka.filters.unsupervised.attribute.SpellChecker: Returns the tip text for this property.
incProgress() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Increments and updates the progress.
INCREMENTAL - adams.flow.transformer.WekaFileReader.OutputType: row by row.
incrementalTipText() - Method in class adams.flow.source.WekaDatabaseReader: Returns the tip text for this property.
IndependentComponentsTab - Class in adams.gui.tools.wekainvestigator.tab: Visualizes the ICA components/sources and ICA space calculated from the selected dataset.
IndependentComponentsTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab
index() - Method in class adams.ml.data.DataCellView: Returns the column this cell is in.
index(int) - Method in class weka.core.AbstractHashableInstance: Returns the index of the attribute stored at the given position in the sparse representation.
INDEX - Static variable in class weka.filters.unsupervised.attribute.NominalToNumeric
INDEX - Static variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression
INDEX - Static variable in class weka.filters.unsupervised.instance.RemoveWithLabels
IndexedSplitsRunsEvaluation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation: Performs the evaluation according to the provided indexed splits.
IndexedSplitsRunsEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation
indexOf(Cell) - Method in class adams.ml.data.InstancesHeaderRow: Returns the column this particular cell is in (must belong to this row!).
indexOf(Cell) - Method in class adams.ml.data.InstanceView: Returns the column this particular cell is in (must belong to this row!).
indexOf(String) - Method in class adams.gui.visualization.instance.InstanceContainerManager: Determines the index of the sequence with the specified ID.
indexOfColumn(String) - Method in class adams.ml.data.InstancesView: Returns the index of the column using the specified name.
indexOfDataset(List<DataContainer>, String) - Static method in class adams.gui.tools.wekainvestigator.evaluation.DatasetHelper: Determines the index of the old dataset name in the current dataset model.
indexOfUnescaped(String, char, int) - Method in class weka.core.converters.SimpleArffLoader: Finds the index of an unescaped (ie not preceded by backslash) character starting with the provided starting position.
indexTipText() - Method in class adams.data.weka.classattribute.AttributeIndex: Returns the tip text for this property.
indexTipText() - Method in class adams.data.weka.relationname.AttributeIndex: Returns the tip text for this property.
indexTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the tip text for this property.
indexTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns the tip text for this property.
indexTipText() - Method in class adams.flow.transformer.WekaExtractArray: Returns the tip text for this property.
indexTipText() - Method in class adams.flow.transformer.WekaGetInstanceValue: Returns the tip text for this property.
indexTipText() - Method in class adams.flow.transformer.WekaSetInstanceValue: Returns the tip text for this property.
indexTipText() - Method in class adams.flow.transformer.WekaSubsets: Returns the tip text for this property.
indexTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
indexTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns the tip text for this property.
indexTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the tip text for this property.
indexTipText() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns the tip text for this property.
indexTipText() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Returns the tip text for this property.
indexTipText() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Returns the tip text for this property.
indexTipText() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Returns the tip text for this property.
indexTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns the tip text for this property.
indicesTipText() - Method in class weka.classifiers.MultiLevelSplitGenerator: Returns the tip text for this property.
IndividualRows - Class in weka.filters.unsupervised.instance.multirowprocessor.selection: Just selects each row by itself.
IndividualRows() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.selection.IndividualRows
INFO - weka.classifiers.trees.XGBoost.Verbosity
init() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction
init(int) - Method in class adams.opt.genetic.PackDataGeneticAlgorithm
init(int) - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm
init(int, int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Initializes the algorithm.
init(Associator) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.AbstractAssociatorEvaluation: Initializes the result item.
init(Associator) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: Initializes the result item.
init(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.AbstractAttributeSelectionEvaluation: Initializes the result item.
init(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: Initializes the result item.
init(ASEvaluation, ASSearch) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Initializes the result item.
init(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Initializes the result item.
init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.AbstractClustererEvaluation: Initializes the result item.
init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: Initializes the result item.
init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Initializes the result item.
init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: Initializes the result item.
init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Initializes the result item.
init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: Initializes the result item.
init(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: Initializes the result item.
initActions() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Initializes the actions.
initActualFilter(Instances) - Method in class adams.flow.transformer.WekaFilter: Initializes the actual filter to use.
initExecute() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Initializes the experiment.
initFilters(boolean, Class[]) - Static method in class adams.gui.chooser.AdamsExperimentFileChooser: initializes the filters.
initFilters(boolean, Class[]) - Static method in class adams.gui.chooser.WekaFileChooser: initializes the SpreadSheetFileExtensionFilters.
initForDisplay() - Method in class adams.gui.goe.WekaExperimentFileEditor: Initializes the display of the value.
initGUI() - Method in class adams.gui.application.WekaExperimenterPreferencesPanel
initGUI() - Method in class adams.gui.application.WekaExplorerPreferencesPanel
initGUI() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel
initGUI() - Method in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog: Sets up the GUI components.
initGUI() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog: For initializing the GUI.
initGUI() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: For initializing the GUI.
initGUI() - Method in class adams.gui.InstanceCompare: Initializes the widgets.
initGUI() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.DatasetCompatibilityPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.weka.AbstractPanelWithFile: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.weka.AppendDatasetsPanel: For initializing the GUI.
initGUI() - Method in class adams.gui.tools.weka.BatchFilterDatasetsPanel: For initializing the GUI.
initGUI() - Method in class adams.gui.tools.weka.CostCurvePanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTable: Initializes some GUI-related things.
initGUI() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Initializes the panel.
initGUI() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.LogTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.StatisticsTable: Initializes the table.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: For initializing the GUI.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel: For initializing the GUI.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: For initializing the GUI.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.LogPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.tools.WekaOptionsConversionPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.visualization.instance.InstanceComparePanel: Initializes the widgets.
initGUI() - Method in class adams.gui.visualization.instance.InstanceExplorer: Initializes the widgets.
initGUI() - Method in class adams.gui.visualization.instance.InstancePanel: Initializes the GUI.
initGUI() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Initializes the GUI elements.
initGUI() - Method in class adams.gui.visualization.instances.InstancesPanel: Initializes the members.
initGUI() - Method in class adams.gui.visualization.instances.InstancesTable: Initializes the widget.
initGUI() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Initializes the widgets.
initGUI() - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Sets up the GUI components.
initGUI() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: Initializes the widets.
initGUI() - Method in class adams.gui.wizard.WekaSelectDatasetPage: Initializes the widets.
initGUI() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: Initializes the widets.
initGUI() - Method in class weka.gui.explorer.ExplorerExt: Initializes the widgets.
initGUI() - Method in class weka.gui.explorer.MultiExplorer: For initializing the GUI.
initGUI() - Method in class weka.gui.explorer.SqlPanel: initializes the GUI
initGUI(JComponent, boolean) - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel: Initializes the panel with the specified component.
initGUI(JComponent, boolean) - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel: Initializes the panel with the specified component.
initGUI(JComponent, boolean, boolean) - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel: Initializes the panel with the specified component.
initHelp() - Method in class adams.flow.container.WekaAssociatorContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaAttributeSelectionContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaClusterEvaluationContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaClusteringContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaEvaluationContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaExperimentContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaFilterContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaGeneticAlgorithmContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaGeneticAlgorithmInitializationContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaModelContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaNearestNeighborSearchContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaPredictionContainer: Initializes the help strings.
initHelp() - Method in class adams.flow.container.WekaTrainTestSetContainer: Initializes the help strings.
initialDirectoryTipText() - Method in class adams.flow.source.WekaSelectDataset: Returns the tip text for this property.
initialFilesTipText() - Method in class adams.flow.source.WekaSelectDataset: Returns the tip text for this property.
initialiseW(Instances) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter
initialiseW(Instances) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
initialiseWeights() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter
initialiseWeights() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
initializationMethodTipText() - Method in class weka.clusterers.SAXKMeans: Returns the tip text for this property.
initialize() - Method in class adams.data.conversion.WekaEvaluationToCostCurve: Initializes the members.
initialize() - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve: Initializes the members.
initialize() - Method in class adams.data.instances.AbstractInstanceGenerator: Initializes the members.
initialize() - Method in class adams.data.io.input.AbstractWekaSpreadSheetReader: Initializes the members.
initialize() - Method in class adams.data.io.output.AbstractWekaSpreadSheetWriter: Initializes the members.
initialize() - Method in class adams.data.weka.rowfinder.FilteredIQR: Initializes the members.
initialize() - Method in class adams.flow.core.WekaPropertyValueConverter: Initializes member variables.
initialize() - Method in class adams.flow.sink.WekaCostCurve: Initializes the members.
initialize() - Method in class adams.flow.sink.WekaThresholdCurve: Initializes the members.
initialize() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Initializes the members.
initialize() - Method in class adams.flow.source.WekaNewInstances: Initializes the members.
initialize() - Method in class adams.flow.source.WekaSelectDataset: Initializes the members.
initialize() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel
initialize() - Method in class adams.flow.transformer.WekaChooseAttributes: Initializes the members.
initialize() - Method in class adams.flow.transformer.WekaClassifierRanker: Initializes the members.
initialize() - Method in class adams.flow.transformer.WekaClassSelector: Initializes the members.
initialize() - Method in class adams.flow.transformer.WekaExtractArray: Initializes the member variables.
initialize() - Method in class adams.flow.transformer.WekaFilter: Initializes the members.
initialize() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Initializes the members.
initialize() - Method in class adams.flow.transformer.WekaGetInstancesValue: Initializes the members.
initialize() - Method in class adams.flow.transformer.WekaGetInstanceValue: Initializes the members.
initialize() - Method in class adams.flow.transformer.WekaInstanceDumper: Initializes the members.
initialize() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Initializes the members.
initialize() - Method in class adams.flow.transformer.WekaSetInstancesValue: Initializes the members.
initialize() - Method in class adams.flow.transformer.WekaSetInstanceValue: Initializes the members.
initialize() - Method in class adams.flow.transformer.WekaSubsets: Initializes the members.
initialize() - Method in class adams.gui.chooser.DatasetFileChooserPanel: Initializes the members.
initialize() - Method in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog: Initializes its members.
initialize() - Method in class adams.gui.goe.WekaGenericArrayEditorDialog: For initializing members.
initialize() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Initializes the members.
initialize() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: For initializing members.
initialize() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel: Initializes the members.
initialize() - Method in class adams.gui.InstanceCompare: For initializing members.
initialize() - Method in class adams.gui.menu.AbstractParameterHandlingWekaMenuItemDefinition: Initializes the members.
initialize() - Method in class adams.gui.menu.BoundaryVisualizer: Initializes members.
initialize() - Method in class adams.gui.menu.CostCurve: Initializes members.
initialize() - Method in class adams.gui.menu.GraphVisualizer: Initializes members.
initialize() - Method in class adams.gui.menu.InstancesPlot: Initializes members.
initialize() - Method in class adams.gui.menu.MarginCurve: Initializes members.
initialize() - Method in class adams.gui.menu.ROC: Initializes members.
initialize() - Method in class adams.gui.menu.TreeVisualizer: Initializes members.
initialize() - Method in class adams.gui.tools.DatasetCompatibilityPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Save: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Initializes the widgets.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Initializes the widgets.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Initializes the widgets.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.DataTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab: Initializes the members.
initialize() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel: For initializing members.
initialize() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: For initializing members.
initialize() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: For initializing members.
initialize() - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: Initializes the members.
initialize() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel: Initializes the members.
initialize() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Initializes the indexer, if necessary.
initialize() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Initializes the members.
initialize() - Method in class adams.gui.visualization.instance.InstanceComparePanel: Initializes the members.
initialize() - Method in class adams.gui.visualization.instance.InstanceContainer: Initializes members.
initialize() - Method in class adams.gui.visualization.instance.InstanceContainerModel: Initializes the members.
initialize() - Method in class adams.gui.visualization.instance.InstanceExplorer: Initializes the members.
initialize() - Method in class adams.gui.visualization.instance.InstancePanel: Initializes the members.
initialize() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Initializes the members.
initialize() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Initializes the members.
initialize() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: Initializes the members.
initialize() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Initializes the members.
initialize() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Initializes the members.
initialize() - Method in class adams.opt.optimise.GeneticAlgorithm: Initializes the members.
initialize() - Method in class adams.tools.CompareDatasets: Initializes the members.
initialize() - Method in class weka.classifiers.AbstractSplitGenerator: Initializes the members.
initialize() - Method in class weka.classifiers.AggregateEvaluations: Initializes the members.
initialize() - Method in class weka.classifiers.MultiLevelSplitGenerator: Initializes the members.
initialize() - Method in class weka.core.InstanceGrouping: Initializes the grouping.
initialize() - Method in class weka.core.SAXDistance: initializes the ranges and the attributes being used.
initialize() - Method in class weka.core.WeightedEuclideanDistance: initializes the ranges and the attributes being used.
initialize() - Method in class weka.core.WeightedEuclideanDistanceRidge: initializes the ranges and the attributes being used.
initialize() - Method in class weka.gui.explorer.ExplorerEntryPanel: Initializes the members.
initialize() - Method in class weka.gui.explorer.ExplorerExt: Initializes the members.
initialize() - Method in class weka.gui.explorer.MultiExplorer
initialize(PyroProxy, Instances) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Converts the instance into a different format.
initializeConverters(File) - Method in class adams.gui.chooser.DatasetFileChooserPanel: Initializes the converters.
initializeDialog() - Method in class adams.flow.source.WekaSelectObjects: Initializes the interactive dialog with the
initializeIterator() - Method in class weka.classifiers.AbstractSplitGenerator: Initializes the iterator, randomizes the data if required.
initializeIterator() - Method in interface weka.classifiers.SplitGenerator: Initializes the iterator (gets implicitly called, when calling next()).
initializeOnceTipText() - Method in class adams.flow.transformer.WekaFilter: Returns the tip text for this property.
initializeOnceTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the tip text for this property.
initialSortNewTableModel() - Method in class adams.gui.visualization.instance.InstanceTable: Returns the initial setting of whether to sort new models.
initialUseOptimalColumnWidths() - Method in class adams.gui.visualization.instance.InstanceTable: Returns the initial setting of whether to set optimal column widths.
initLookup() - Method in class adams.tools.CompareDatasets: Initializes the lookup table of indices for the second dataset, if necessary.
initOutputBuffer() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Initializes the output buffer.
initOutputBuffer() - Method in class adams.multiprocess.WekaCrossValidationExecution: Initializes the output buffer.
initProgress() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Initializes progress.
initResults() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Initializes the results.
initServer() - Method in class weka.classifiers.meta.SocketFacade: Initializes the server socket if necessary.
input(Instance) - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Input an instance for filtering.
InputSmearing - Class in weka.classifiers.meta: Extended version of weka.classifiers.meta.Bagging, which allows input smearing of numeric attributes.
Class for bagging a classifier to reduce variance.
InputSmearing - Class in weka.filters.unsupervised.attribute
InputSmearing() - Constructor for class weka.classifiers.meta.InputSmearing
InputSmearing() - Constructor for class weka.filters.unsupervised.attribute.InputSmearing
insertAttributeAt(int) - Method in class weka.core.AbstractHashableInstance: Inserts an attribute at the given position (0 to numAttributes()).
insertAttributeAt(Attribute, int) - Method in class weka.core.InstancesView: Inserts an attribute at the given position (0 to numAttributes()) and sets all values to be missing.
insertColumn(int, String) - Method in class adams.ml.data.InstancesView: Inserts a column at the specified location.
insertColumn(int, String, String) - Method in class adams.ml.data.InstancesView: Inserts a column at the specified location.
insertColumn(int, String, String, boolean) - Method in class adams.ml.data.InstancesView: Inserts a column at the specified location.
insertInstance(int) - Method in class adams.gui.visualization.instances.InstancesTableModel
insertInstance(int, boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel
insertRow(int) - Method in class adams.ml.data.InstancesView: Inserts a row at the specified location.
insertUpdate(DocumentEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationDocumentListener
inspect(Object) - Method in class adams.gui.visualization.debug.inspectionhandler.WekaEvaluation: Returns further inspection values.
inspect(Object) - Method in class adams.gui.visualization.debug.inspectionhandler.WekaInstances: Returns further inspection values.
INSTALLED - adams.flow.source.wekapackagemanageraction.ListPackages.ListType
InstallFromFile - Class in adams.flow.transformer.wekapackagemanageraction: Action that installs packages from files.
InstallFromFile() - Constructor for class adams.flow.transformer.wekapackagemanageraction.InstallFromFile
InstallFromURL - Class in adams.flow.transformer.wekapackagemanageraction: Action that installs packages from URLs.
InstallFromURL() - Constructor for class adams.flow.transformer.wekapackagemanageraction.InstallFromURL
installLinearModels() - Method in class weka.classifiers.trees.m5.RuleNode2: Traverses the tree and installs linear models at each node.
InstallOfficial - Class in adams.flow.transformer.wekapackagemanageraction: Action that installs official packages via their name and (optional) version.
InstallOfficial() - Constructor for class adams.flow.transformer.wekapackagemanageraction.InstallOfficial
InstallPackage - Class in adams.flow.transformer.wekapackagemanageraction: Action that installs the incoming package.
InstallPackage() - Constructor for class adams.flow.transformer.wekapackagemanageraction.InstallPackage
installSmoothedModels() - Method in class weka.classifiers.trees.m5.RuleNode2
instance(int) - Method in class weka.core.InstancesView: Returns the instance at the given position.
Instance - Class in adams.data.instance: Stores values from weka.core.Instance objects, with X being the attribute index (integer) and Y being the internal value (double).
Instance() - Constructor for class adams.data.instance.Instance: Initializes the sequence.
INSTANCE_TO_INSTANCES - adams.flow.transformer.WekaInstanceBuffer.Operation: Instance -> Instances.
instanceClassTipText() - Method in class adams.flow.transformer.WekaNewInstance: Returns the tip text for this property.
InstanceComparator - Class in adams.data.instances: For comparing instance objects.
InstanceComparator(int[]) - Constructor for class adams.data.instances.InstanceComparator: Initializes the comparator.
InstanceComparator(int[], boolean[]) - Constructor for class adams.data.instances.InstanceComparator: Initializes the comparator.
InstanceCompare - Class in adams.gui: Stand-alone version of the Instance Compare utility.
InstanceCompare - Class in adams.gui.menu: For comparing two datasets visually.
InstanceCompare() - Constructor for class adams.gui.InstanceCompare
InstanceCompare() - Constructor for class adams.gui.menu.InstanceCompare: Initializes the menu item with no owner.
InstanceCompare(AbstractApplicationFrame) - Constructor for class adams.gui.menu.InstanceCompare: Initializes the menu item.
InstanceCompareDefinition - Class in adams.env: Definition for the InstanceCompare props file.
InstanceCompareDefinition() - Constructor for class adams.env.InstanceCompareDefinition
InstanceComparePanel - Class in adams.gui.visualization.instance: A tool for comparing two datasets visually.
InstanceComparePanel() - Constructor for class adams.gui.visualization.instance.InstanceComparePanel
InstanceComparePanel.DatasetIndexer - Class in adams.gui.visualization.instance: Helper class for indexing the rows of a dataset.
InstanceComparePanel.DatasetPanel - Class in adams.gui.visualization.instance: Specialized panel for loading dataset and setting various parameters.
InstanceContainer - Class in adams.gui.visualization.instance: A container class for a weka.core.Instance wrapped in a weka.core.Instance.
InstanceContainer(InstanceContainerManager, Instance) - Constructor for class adams.gui.visualization.instance.InstanceContainer: Initializes the container.
InstanceContainerDisplayIDGenerator - Class in adams.gui.visualization.instance: Class for generating display IDs for Instance objects (based on weka.core.Instance objects).
InstanceContainerDisplayIDGenerator() - Constructor for class adams.gui.visualization.instance.InstanceContainerDisplayIDGenerator
InstanceContainerList - Class in adams.gui.visualization.instance: A panel that lists Instances in a JTable.
InstanceContainerList() - Constructor for class adams.gui.visualization.instance.InstanceContainerList
InstanceContainerManager - Class in adams.gui.visualization.instance: A handler for the Instance containers.
InstanceContainerManager(ContainerListManager<InstanceContainerManager>) - Constructor for class adams.gui.visualization.instance.InstanceContainerManager: Initializes the manager.
InstanceContainerModel - Class in adams.gui.visualization.instance: A model for displaying the currently loaded Instance objects.
InstanceContainerModel(ContainerListManager<InstanceContainerManager>) - Constructor for class adams.gui.visualization.instance.InstanceContainerModel: Initializes the model.
InstanceContainerModel(InstanceContainerManager) - Constructor for class adams.gui.visualization.instance.InstanceContainerModel: Initializes the model.
InstanceContainerTableColumnNameGenerator - Class in adams.gui.visualization.instance: Abstract class for generating the column names of a table.
InstanceContainerTableColumnNameGenerator() - Constructor for class adams.gui.visualization.instance.InstanceContainerTableColumnNameGenerator
InstanceDumperVariable - Class in adams.flow.template: Generates a sub-flow that sets a variable for the adams.flow.transformer.WekaInstanceDumper transformer's outputPrefix property using a prefix based on the full flow name.
InstanceDumperVariable() - Constructor for class adams.flow.template.InstanceDumperVariable
InstanceExplorer - Class in adams.gui.menu: For displaying and filtering instances.
InstanceExplorer - Class in adams.gui.visualization.instance: A panel for exploring Instances visually.
InstanceExplorer() - Constructor for class adams.gui.menu.InstanceExplorer: Initializes the menu item with no owner.
InstanceExplorer() - Constructor for class adams.gui.visualization.instance.InstanceExplorer
InstanceExplorer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.InstanceExplorer: Initializes the menu item.
InstanceExplorerDefinition - Class in adams.env: Definition for the InstanceExplorer props file.
InstanceExplorerDefinition() - Constructor for class adams.env.InstanceExplorerDefinition
InstanceExplorerHandler - Class in adams.gui.tools.previewbrowser: Displays the following WEKA dataset types in the Instance Explorer: csv,arff,arff.gz,xrff,xrff.gz

Valid options are:
InstanceExplorerHandler() - Constructor for class adams.gui.tools.previewbrowser.InstanceExplorerHandler
InstanceGeneratorWithAdditionalFields - Interface in adams.data.instances: Generators with additional fields.
InstanceGeneratorWithFields - Interface in adams.data.instances: Generators with fields.
InstanceGrouping - Class in weka.core: Groups rows in a dataset using a regular expression on a nominal or string attribute.
InstanceGrouping(Instances, WekaAttributeIndex, BaseRegExp, String) - Constructor for class weka.core.InstanceGrouping: Initializes the object.
InstanceLinePaintlet - Class in adams.gui.visualization.instance: Paintlet for generating a line plot for Instance objects.
InstanceLinePaintlet() - Constructor for class adams.gui.visualization.instance.InstanceLinePaintlet
InstanceLinePaintlet.MarkerShape - Enum in adams.gui.visualization.instance: Enum for the marker shape to plot around the data points.
InstanceNode(int, Double) - Constructor for class weka.core.neighboursearch.NewNNSearch.InstanceNode
InstancePanel - Class in adams.gui.visualization.instance: A panel for displaying instances.
InstancePanel() - Constructor for class adams.gui.visualization.instance.InstancePanel: Initializes the panel.
InstancePanel(String) - Constructor for class adams.gui.visualization.instance.InstancePanel: Initializes the panel.
InstancePoint - Class in adams.data.instance: A 2-dimensional point (X: attribute index, Y: internal value).
InstancePoint() - Constructor for class adams.data.instance.InstancePoint: Initializes the point with no points and no ID.
InstancePoint(Integer, Double) - Constructor for class adams.data.instance.InstancePoint: Initializes the point with no ID.
InstancePointComparator - Class in adams.data.instance: A comparator for InstancePoint objects.
InstancePointComparator() - Constructor for class adams.data.instance.InstancePointComparator: The default constructor uses comparison by X in ascending manner.
InstancePointComparator(boolean, boolean) - Constructor for class adams.data.instance.InstancePointComparator: This constructor initializes the comparator either with comparison by X or by Y.
InstancePointHitDetector - Class in adams.gui.visualization.instance: Detects selections of instance points in the instance panel.
InstancePointHitDetector(InstancePanel) - Constructor for class adams.gui.visualization.instance.InstancePointHitDetector: Initializes the hit detector.
InstanceReader - Class in adams.data.io.input: Reads WEKA datasets in various formats.
InstanceReader() - Constructor for class adams.data.io.input.InstanceReader
InstanceReportFactory - Class in adams.gui.visualization.instance: A factory for GUI components for Instance-related reports.
InstanceReportFactory() - Constructor for class adams.gui.visualization.instance.InstanceReportFactory
InstanceReportFactory.Panel - Class in adams.gui.visualization.instance: A specialized panel that displays reports.
InstanceReportFactory.Table - Class in adams.gui.visualization.instance: A specialized table for displaying a Report.
INSTANCES_TO_INSTANCE - adams.flow.transformer.WekaInstanceBuffer.Operation: Instances -> Instance.
instancesActorTipText() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Returns the tip text for this property.
InstancesColumnComboBox - Class in adams.gui.visualization.instances: ComboBox that lists the attribute names of the associated Instances in alphabetical order and when the user selects one, ensures that this column is visible.
InstancesColumnComboBox(InstancesTable) - Constructor for class adams.gui.visualization.instances.InstancesColumnComboBox: Initializes the combobox.
InstancesColumnComboBox.ColumnContainer - Class in adams.gui.visualization.instances: Container for storing column name and
InstancesCrossValidationFoldGenerator - Class in adams.flow.transformer.indexedsplitsrunsgenerator: Split generator that generates folds for cross-validation for Instances objects.
InstancesCrossValidationFoldGenerator() - Constructor for class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator
InstancesGroupedCrossValidationFoldGenerator - Class in adams.flow.transformer.indexedsplitsrunsgenerator: Split generator that generates folds for cross-validation for Instances objects.
InstancesGroupedCrossValidationFoldGenerator() - Constructor for class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator
InstancesGroupedRandomSplitGenerator - Class in adams.flow.transformer.indexedsplitsrunsgenerator: Random split generator that works on Instances objects (groups instances).
InstancesGroupedRandomSplitGenerator() - Constructor for class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator
InstancesHeaderRow - Class in adams.ml.data: Header row for an Instances object.
InstancesHeaderRow(InstancesView) - Constructor for class adams.ml.data.InstancesHeaderRow: Initializes the header row.
InstancesIndexedSplitsRunsCompatibility - Class in adams.data.indexedsplits: Performs compatibility tests between indexed splits configurations and Weka Instances objects.
InstancesIndexedSplitsRunsCompatibility() - Constructor for class adams.data.indexedsplits.InstancesIndexedSplitsRunsCompatibility
InstancesIndexedSplitsRunsEvaluation - Class in adams.flow.transformer.indexedsplitsrunsevaluation: Evaluates the specified classifier on the indexed splits runs applied to the incoming data.
InstancesIndexedSplitsRunsEvaluation() - Constructor for class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation
InstancesIndexedSplitsRunsGenerator - Interface in adams.flow.transformer.indexedsplitsrunsgenerator: Indicator interface for generators that process Instances objects.
InstancesIndexedSplitsRunsPredictions - Class in adams.flow.transformer.indexedsplitsrunspredictions: Trains the referenced classifier on the training splits and generates predictions for the test splits.
InstancesIndexedSplitsRunsPredictions() - Constructor for class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions
instancesIndicesTipText() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Returns the tip text for this property.
InstancesPanel - Class in adams.gui.visualization.instances: Panel displaying an Instances table.
InstancesPanel() - Constructor for class adams.gui.visualization.instances.InstancesPanel
InstancesPlot - Class in adams.gui.menu: Displays plot of Instances.
InstancesPlot() - Constructor for class adams.gui.menu.InstancesPlot: Initializes the menu item with no owner.
InstancesPlot(AbstractApplicationFrame) - Constructor for class adams.gui.menu.InstancesPlot: Initializes the menu item.
InstancesRandomSplitGenerator - Class in adams.flow.transformer.indexedsplitsrunsgenerator: Random split generator that works on Instances objects.
InstancesRandomSplitGenerator() - Constructor for class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator
InstancesSortDefinitionPanel - Class in adams.gui.visualization.instances.instancestable: Represents a single sorting definition.
InstancesSortDefinitionPanel(InstancesSortPanel) - Constructor for class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: Initializes the definition panel.
InstancesSortPanel - Class in adams.gui.visualization.instances.instancestable: Panel that allows users to sort instances over an arbitrary number of columns.
InstancesSortPanel() - Constructor for class adams.gui.visualization.instances.instancestable.InstancesSortPanel
InstancesSortSetupEvent - Class in adams.gui.event: Event that gets sent when the InstancesSortPanel setup changes.
InstancesSortSetupEvent(InstancesSortPanel, InstancesSortDefinitionPanel, InstancesSortSetupEvent.EventType) - Constructor for class adams.gui.event.InstancesSortSetupEvent: Initializes the event.
InstancesSortSetupEvent.EventType - Enum in adams.gui.event: The type of event.
InstancesSortSetupListener - Interface in adams.gui.event: Interface for listeners that react to changes in a sort setup of a InstancesSortPanel.
InstancesSummaryPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab: This panel just displays relation name, number of instances, and number of attributes.
InstancesSummaryPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel: Creates the instances panel with no initial instances.
InstancesTable - Class in adams.gui.visualization.instances: Table for displaying Instances objects.
InstancesTable(InstancesTableModel) - Constructor for class adams.gui.visualization.instances.InstancesTable: Initializes the table with the model.
InstancesTable(Instances) - Constructor for class adams.gui.visualization.instances.InstancesTable: Initializes the table with the data.
InstancesTableModel - Class in adams.gui.visualization.instances: The model for the Instances.
InstancesTableModel() - Constructor for class adams.gui.visualization.instances.InstancesTableModel: performs some initialization
InstancesTableModel(Instances) - Constructor for class adams.gui.visualization.instances.InstancesTableModel: initializes the model with the given data
InstancesTablePopupMenuItem - Interface in adams.gui.visualization.instances.instancestable: Ancestor for menu items of popups for the InstancesTable.
InstancesTablePopupMenuItemHelper - Class in adams.gui.visualization.instances.instancestable: Helper class for constructing popup menus for the InstancesTable.
InstancesTablePopupMenuItemHelper() - Constructor for class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper
InstancesTablePopupMenuItemHelper.TableState - Class in adams.gui.visualization.instances.instancestable: Container object for the table state used by the popup menu items.
instancesToDMatrix(Instance[]) - Method in class weka.classifiers.trees.XGBoost: Converts a WEKA dataset into a DMatrix (the input type expected by XGBoost).
InstancesView - Class in adams.ml.data: Provides a view of an Instances object.
InstancesView - Class in weka.core: Presents a view of an Instances object.
InstancesView() - Constructor for class adams.ml.data.InstancesView: Initializes the view with a dummy dataset.
InstancesView(Instances) - Constructor for class adams.ml.data.InstancesView: Initializes the view.
InstancesView(Instances, int[]) - Constructor for class weka.core.InstancesView: Initializes the dataset.
InstancesView(Instances, int, int) - Constructor for class weka.core.InstancesView: Initializes the dataset.
InstancesViewCreator - Interface in adams.data.weka: Interface for classes that generate Weka Instances views.
InstancesViewSupporter - Interface in adams.data.weka: Interface for classes that support Weka Instances views.
InstanceTab - Class in adams.gui.tools.wekainvestigator.tab: Visualizes the selected dataset like the instance explorer.
InstanceTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.InstanceTab
InstanceTable - Class in adams.gui.visualization.instance: A specialized table for displaying an Instances object.
InstanceTable(Instances) - Constructor for class adams.gui.visualization.instance.InstanceTable: Initializes the table.
InstanceTableModel - Class in adams.gui.visualization.instance: A generic table model for displaying weka.core.Instances objects.
InstanceTableModel(Instances) - Constructor for class adams.gui.visualization.instance.InstanceTableModel: Initializes the model.
instanceToRow(Instance) - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor: Converts a single Instance into a JSON array (excluding class).
instanceToRow(Instance, BaseString) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Converts a single Instance into a JSON array.
InstanceUtils - Class in adams.data.instance: Utility class for instances.
InstanceUtils() - Constructor for class adams.data.instance.InstanceUtils
InstanceView - Class in adams.ml.data: Wrapper around an Instance object.
InstanceView(InstancesView, Instance) - Constructor for class adams.ml.data.InstanceView: Initializes the row view.
InstanceZoomOverviewPaintlet - Class in adams.gui.visualization.instance: Highlights the current zoom in the instance panel.
InstanceZoomOverviewPaintlet() - Constructor for class adams.gui.visualization.instance.InstanceZoomOverviewPaintlet
InstanceZoomOverviewPanel - Class in adams.gui.visualization.instance: Panel that shows the zoom in the TIC panel as overlay.
InstanceZoomOverviewPanel() - Constructor for class adams.gui.visualization.instance.InstanceZoomOverviewPanel
intArrayToString(int[]) - Method in class adams.opt.genetic.Hermione: Int array of bits to string.
INTERNAL_REPRESENTATION - weka.filters.unsupervised.attribute.NominalToNumeric.ConversionType
interpolate(double, int, double, int, double) - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns interpolated value.
interpretePosition(Instances, String) - Method in class adams.data.instances.AbstractInstanceGenerator: Interpretes the position string based on the given dataset.
InterquartileRangeSamp - Class in weka.filters.unsupervised.attribute: A sampling filter for detecting outliers and extreme values based on interquartile ranges.
InterquartileRangeSamp() - Constructor for class weka.filters.unsupervised.attribute.InterquartileRangeSamp
InterquartileRangeSamp.IQRs - Class in weka.filters.unsupervised.attribute: Container class for the IQR values.
InterQuartileRangeViewer - Class in adams.gui.tools.previewbrowser: Displays internal values of the InterquartileRange filter.
InterQuartileRangeViewer() - Constructor for class adams.gui.tools.previewbrowser.InterQuartileRangeViewer
INTERSECT - adams.data.weka.columnfinder.MultiColumnFinder.Combination: intersect/and.
INTERSECT - adams.data.weka.rowfinder.MultiRowFinder.Combination: intersect/and.
IntervalEstimatorBased - Class in adams.data.weka.evaluator: Uses a classifier that produces confidence intervals.
IntervalEstimatorBased() - Constructor for class adams.data.weka.evaluator.IntervalEstimatorBased
IntervalEstimatorBased.SortedInterval - Class in adams.data.weka.evaluator: Helper class for sorting the confidence intervals.
intervalTipText() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns the tip text for this property.
intervalTipText() - Method in class adams.flow.transformer.WekaStreamEvaluator: Returns the tip text for this property.
invalidateHashCode() - Method in class weka.core.AbstractHashableInstance: Invalidates the hash code.
invalidateName() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: Invalidates the name.
inverse(Instances) - Method in class weka.filters.unsupervised.attribute.FastWavelet: Renames the attributes when using the inverse transform.
inverseTransformTipText() - Method in class weka.filters.unsupervised.attribute.FastWavelet: Returns the tip text for this property.
inverseTransformTipText() - Method in class weka.filters.unsupervised.attribute.FFT: Returns the tip text for this property.
Invert - Class in adams.data.weka.columnfinder: Inverts the selected columns of the provided sub-column-filter.
Invert - Class in adams.data.weka.rowfinder: Inverts the selected rows of the provided sub-row-filter.
Invert() - Constructor for class adams.data.weka.columnfinder.Invert
Invert() - Constructor for class adams.data.weka.rowfinder.Invert
INVERT - Static variable in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens
INVERT - Static variable in class weka.filters.unsupervised.instance.RemoveWithLabels
INVERT_SELECTION - Static variable in class weka.filters.unsupervised.instance.KennardStone
InvertInstancesColumnFinder - Class in adams.gui.goe.popupmenu: Encloses a Instances ColumnFinder in Invert.
InvertInstancesColumnFinder() - Constructor for class adams.gui.goe.popupmenu.InvertInstancesColumnFinder
InvertInstancesRowFinder - Class in adams.gui.goe.popupmenu: Encloses a Instances RowFinder in Invert.
InvertInstancesRowFinder() - Constructor for class adams.gui.goe.popupmenu.InvertInstancesRowFinder
invertMatchingSenseTipText() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the tip text for this property.
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.KennardStone: Returns the tip text for this property.
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Returns the tip text for this property.
invertTipText() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities: Returns the tip text for this property.
invertTipText() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns the tip text for this property.
invertTipText() - Method in class adams.flow.transformer.WekaRegexToRange: Returns the tip text for this property.
invertTipText() - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens: Returns the tip text for this property.
invertTipText() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Returns the tip text for this property.
invertTipText() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Returns the tip text for this property.
invertTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Returns the tip text for this property
invertTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Returns the tip text for this property
invertTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the tip text for this property.
invertTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns the tip text for this property.
InvestigatorAsNewDataset - Class in adams.gui.visualization.instances.instancestable: Allows the user to add the selected rows as new dataset in the Investigator.
InvestigatorAsNewDataset() - Constructor for class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset
InvestigatorJob - Class in adams.gui.tools.wekainvestigator.job: For running jobs in the InvestigatorPanel.
InvestigatorJob(InvestigatorPanel, String) - Constructor for class adams.gui.tools.wekainvestigator.job.InvestigatorJob: Initializes the job.
InvestigatorManagerPanel - Class in adams.gui.tools.wekainvestigator: Manages multiple sessions of the Investigator.
InvestigatorManagerPanel() - Constructor for class adams.gui.tools.wekainvestigator.InvestigatorManagerPanel
InvestigatorPanel - Class in adams.gui.tools.wekainvestigator: The main panel for the Investigator.
InvestigatorPanel() - Constructor for class adams.gui.tools.wekainvestigator.InvestigatorPanel
InvestigatorTabbedPane - Class in adams.gui.tools.wekainvestigator.tab: Tabbed pane for managing the tabs of the Investigator.
InvestigatorTabbedPane(InvestigatorPanel) - Constructor for class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane: Initializes the tabbed pane.
InvestigatorTabJob - Class in adams.gui.tools.wekainvestigator.job: For running jobs in a AbstractInvestigatorTab.
InvestigatorTabJob(AbstractInvestigatorTab, String) - Constructor for class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob: Initializes the job.
InvestigatorTabRunnableJob - Class in adams.gui.tools.wekainvestigator.job: For executing Runnable's in a AbstractInvestigatorTab.
InvestigatorTabRunnableJob(AbstractInvestigatorTab, Runnable) - Constructor for class adams.gui.tools.wekainvestigator.job.InvestigatorTabRunnableJob: Initializes the job.
InvestigatorWorkspaceHelper - Class in adams.gui.tools.wekainvestigator: Helper class for Weka Investigator workspaces.
InvestigatorWorkspaceHelper() - Constructor for class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper
InvestigatorWorkspaceList - Class in adams.gui.tools.wekainvestigator: Lists the sessions.
InvestigatorWorkspaceList() - Constructor for class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceList
IQRs(double, double, double, double) - Constructor for class weka.filters.unsupervised.attribute.InterquartileRangeSamp.IQRs
iqrTipText() - Method in class adams.data.weka.rowfinder.FilteredIQR: Returns the tip text for this property.
IR_PRECISION - adams.flow.core.EvaluationStatistic
IR_PRECISION - adams.flow.core.ExperimentStatistic
IR_RECALL - adams.flow.core.EvaluationStatistic
IR_RECALL - adams.flow.core.ExperimentStatistic
isAbstaining(Instance) - Method in class weka.classifiers.meta.ConsensusOrVote: Determines whether to abstain from the prediction.
isAntiAliasingEnabled() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns whether anti-aliasing is used.
isAntiAliasingEnabled() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Returns whether anti-aliasing is used.
isAntiAliasingEnabled() - Method in class adams.gui.visualization.instance.InstancePanel: Returns whether anti-aliasing is used.
isAntiAliasingEnabled() - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet: Returns whether anti-aliasing is used.
isAnyClassAttribute(List<AbstractMerge.SourceAttribute>) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Checks if any of the source attributes in the given list is a class attribute.
isAnyDateType() - Method in class adams.ml.data.DataCellView: Checks whether the cell represents a date, time or date/time value.
isAscending() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: Returns whether ascending or descending is used.
isAvailable() - Method in class adams.data.io.input.AbstractAdamsExperimentReader: Returns whether the reader is actually available.
isAvailable() - Method in class adams.data.io.output.AbstractAdamsExperimentWriter: Returns whether the writer is actually available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotColumn: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotRow: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.Binning: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.Histogram: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItem: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart: Returns whether the menu item is available.
isAvailable(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot: Returns whether the menu item is available.
isBoolean() - Method in class adams.ml.data.DataCellView: Checks whether the cell represents a boolean value.
isBusy() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Returns whether the tab is busy.
isBusy() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns whether the tab is busy.
isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Returns whether the tab is busy.
isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Returns whether the tab is busy.
isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Returns whether the tab is busy.
isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Returns whether the tab is busy.
isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Returns whether the tab is busy.
isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Returns whether the tab is busy.
isBusy() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Returns whether the tab is busy.
isButtonPanelVisible() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: Returns the visibility state of the buttons panel (load/save).
isCellEditable(int, int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: Returns whether a cell is editable.
isCellEditable(int, int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.StatisticsTable: returns always false, since it's just information for the user
isCellEditable(int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel: returns true if the cell at rowindex and columnindexis editable
isClassAttribute(int) - Method in class adams.ml.data.InstancesView: Returns whether the specified column is a class attribute.
isClassAttribute(int, int) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Whether the given attribute is a class attribute.
isClassAttribute(AbstractMerge.SourceAttribute) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Checks if the given source attribute is a class attribute.
isClassAttribute(String) - Method in class adams.ml.data.InstancesView: Returns whether the specified column is a class attribute.
isClassAttributeByName(String) - Method in class adams.ml.data.InstancesView: Returns whether the specified column is a class attribute.
isClassFirst() - Method in class weka.experiment.ExtExperiment: Returns whether the class is the first attribute.
isClassIndex(int) - Method in class adams.gui.visualization.instances.InstancesTableModel: checks whether the column represents the class or not
isColumnFinderTrained() - Method in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder: Checks whether the column finder has been trained.
isColumnFinderTrained() - Method in interface adams.data.weka.columnfinder.TrainableColumnFinder: Checks whether the column finder has been trained.
isCompatible(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Checks whether the selected datasets are compatible.
isCompatible(Dataset) - Method in class adams.ml.model.classification.WekaClassificationModel: Checks whether the dataset is compatible with the model.
isCompatible(Dataset) - Method in class adams.ml.model.clustering.WekaClusteringModel: Checks whether the dataset is compatible with the model.
isCompatible(Dataset) - Method in class adams.ml.model.regression.WekaRegressionModel: Checks whether the dataset is compatible with the model.
isCompatible(Object, IndexedSplitsRuns) - Method in class adams.data.indexedsplits.InstancesIndexedSplitsRunsCompatibility: Checks whether the data is compatible with the indexed splits.
isCompatible(Instance) - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader: Checks the instance against the header, whether they are compatible.
isComplete(int[]) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Checks whether the number of rows located in the current results are complete.
isComplete(int[]) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: Checks whether the number of rows located in the current results are complete.
isContentType(int, Cell.ContentType) - Method in class adams.ml.data.InstancesView: Checks whether the given column is of the specific content type or not.
isCrossValidation() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Returns whether cross-valiation was used.
isDataLoaded() - Method in class weka.gui.explorer.ExplorerExt: Checks whether data is currently loaded.
isDate() - Method in class adams.ml.data.DataCellView: Checks whether the cell represents a date value.
isDateLenient() - Method in class adams.ml.data.InstancesView: Returns whether the parsing of dates is lenient or not.
isDateTime() - Method in class adams.ml.data.DataCellView: Checks whether the cell represents a date/time value.
isDateTimeLenient() - Method in class adams.ml.data.InstancesView: Returns whether the parsing of date/times is lenient or not.
isDateTimeMsec() - Method in class adams.ml.data.DataCellView: Checks whether the cell represents a date/time with msec value.
isDateTimeMsecLenient() - Method in class adams.ml.data.InstancesView: Returns whether the parsing of date/time msecs is lenient or not.
isDottyTree(String) - Static method in class adams.gui.tools.wekainvestigator.output.GraphHelper: Simple check whether the string represents a dotty tree.
isDottyTree(Drawable) - Static method in class adams.gui.tools.wekainvestigator.output.GraphHelper: Simple check whether the drawble generates a dotty tree.
isDouble() - Method in class adams.ml.data.DataCellView: Returns whether the content represents a double number.
isExecuting() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Returns whether an experiment is currently being executed.
isFirstDefinition(InstancesSortDefinitionPanel) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Checks whether the panel is the first one.
isFormula() - Method in class adams.ml.data.DataCellView: Returns whether the content represents a formula.
isGOEEditor() - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: Returns whether the underlying editor is GenericObjectEditor.
isHit(MouseEvent) - Method in class adams.gui.visualization.instance.InstancePointHitDetector: Checks for a hit.
isHtml(Class) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator: Returns whether the generated help is HTML or plain text.
isInitialized() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns whether the scheme has been initialized.
isInlineEditingAvailable() - Method in class adams.gui.goe.WekaExperimentFileEditor: Checks whether inline editing is available.
isInlineValueValid(String) - Method in class adams.gui.goe.WekaExperimentFileEditor: Checks whether the value id valid.
isInteractive() - Method in class adams.flow.template.InstanceDumperVariable: Whether the flow generated is an interactive one.
isLastDefinition(InstancesSortDefinitionPanel) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Checks whether the panel is the last one.
isLeaf() - Method in class weka.classifiers.trees.m5.RuleNode2: Return true if this node is a leaf
isLong() - Method in class adams.ml.data.DataCellView: Returns whether the content represents a long number.
isMarkersDisabled() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Returns whether marker shapes are disabled.
isMatch(InstanceContainer, String, boolean) - Method in class adams.gui.visualization.instance.InstanceContainerManager: Returns whether the container matches the current search.
isMissing() - Method in class adams.ml.data.DataCellView: Checks whether the cell contains a missing value.
isMissing(int) - Method in class weka.core.AbstractHashableInstance: Tests if a specific value is "missing".
isMissing(Attribute) - Method in class weka.core.AbstractHashableInstance: Tests if a specific value is "missing".
isMissingAt(int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel: checks whether the value at the given position is missing
isMissingSparse(int) - Method in class weka.core.AbstractHashableInstance: Tests if a specific value is "missing" in the sparse representation.
isModified() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Checks whether the data has been modified.
isModified() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer: Checks whether the data has been modified.
isModified() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: Returns whether the setup has been modified.
isNoCleanUp() - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList: Returns whether to suppress automatic clean ups.
isNonInteractive() - Method in class adams.flow.source.WekaSelectDataset: Returns whether interactiveness is enabled/disabled.
isNonInteractive() - Method in class adams.flow.transformer.WekaChooseAttributes: Returns whether interactiveness is enabled/disabled.
isNotificationEnabled() - Method in class adams.gui.visualization.instances.InstancesTableModel: returns whether the notification of changes is enabled
isNumeric() - Method in class adams.ml.data.DataCellView: Checks whether the stored string is numeric.
isNumeric(int) - Method in class adams.ml.data.InstancesView: Checks whether the given column is numeric or not.
isNumeric(int, boolean) - Method in class adams.ml.data.InstancesView: Checks whether the given column is numeric or not.
isObject() - Method in class adams.ml.data.DataCellView: Returns whether the content represents an object.
isOfficial(String) - Static method in class weka.core.WekaPackageUtils: Checks whether the package is an official one.
isOfficial(Package) - Static method in class weka.core.WekaPackageUtils: Checks whether the package is an official one.
isOnlyNominal() - Method in enum adams.flow.core.EvaluationStatistic: Returns whether the statistic applies to nominal attributes only.
isOnlyNumeric() - Method in enum adams.flow.core.EvaluationStatistic: Returns whether the statistic applies to numeric attributes only.
isOutside(Instance, int, double, double) - Static method in class weka.classifiers.RangeCheckHelper: Performs a check for the given instance, whether it exceeds the range.
isPaused() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns whether the object is currently paused.
isPaused() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns whether the object is currently paused.
isPerClass() - Method in enum adams.flow.core.EvaluationStatistic: Returns whether the statistic is a per-class one.
isPerClassLabel() - Method in enum adams.opt.genetic.Measure: Returns whether the measure is per class label.
isPLSFilter(Filter) - Method in class adams.data.conversion.SwapPLS: Checks whether the filter is an actual PLS filter.
isPreSelection() - Method in class adams.flow.transformer.WekaChooseAttributes: Returns the regular expression to pre-select attributes for the dialog.
isReadOnly() - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: Returns whether the model is readonly.
isReadOnly() - Method in class adams.gui.visualization.instances.InstancesTable: returns whether the model is read-only
isReadOnly() - Method in class adams.gui.visualization.instances.InstancesTableModel: returns whether the model is read-only
isRemoveUsed() - Method in class weka.classifiers.meta.FilteredClassifierExt: Returns whether the Remove filter is used at all.
isRequired(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Checks whether the classifier/dataset combination is required.
isRowFinderTrained() - Method in class adams.data.weka.rowfinder.AbstractTrainableRowFinder: Checks whether the row finder has been trained.
isRowFinderTrained() - Method in interface adams.data.weka.rowfinder.TrainableRowFinder: Checks whether the row finder has been trained.
isRunning() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Whether the experiment is still running.
isRunning() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns whether the algorithm is still running.
isSearchMatch(SearchParameters, int) - Method in class adams.gui.visualization.instance.InstanceTableModel: Tests whether the search matches the specified row.
isSecondBetterFitness(double) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Checks whether the fitness is better (second evaluation).
isSidePanelVisible() - Method in class adams.gui.visualization.instance.InstanceExplorer: Returns whether the side panel is visible or not.
isSingleThreaded() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns whether the execution was single-threaded (after WekaCrossValidationExecution.execute()).
isSingleton() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.AppendDatasets: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.ArffViewer: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.BatchFilterDatasets: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.BayesNetEditor: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.BoundaryVisualizer: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.CostCurve: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.DatasetCompatibility: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.Experimenter: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.Explorer: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.GraphVisualizer: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.InstanceCompare: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.InstanceExplorer: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.InstancesPlot: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.MakeCompatibleDatasets: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.MarginCurve: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.MergeDatasets: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.MultiExplorer: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.PackageManager: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.PlotAttributeVsAttribute: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.ROC: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.SqlViewer: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.TreeVisualizer: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.WekaCommandToCode: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.WekaInvestigator: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.WekaMultiExperimenter: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.WekaSimpleCLI: Whether the panel can only be displayed once.
isSingleton() - Method in class adams.gui.menu.Workbench: Whether the panel can only be displayed once.
isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Whether the execution has been stopped.
isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Whether the execution has been stopped.
isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Whether the execution has been stopped.
isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Whether the execution has been stopped.
isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Whether the execution has been stopped.
isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Whether the execution has been stopped.
isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Whether the execution has been stopped.
isStopped() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup: Whether the execution has been stopped.
isStopped() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns whether the experiment has been stopped.
isStopped() - Method in class adams.multiprocess.WekaCrossValidationExecution: Returns whether the execution has been stopped.
isStopped() - Method in class weka.classifiers.evaluation.StoppableEvaluation: Whether the execution has been stopped.
isStopped() - Method in class weka.classifiers.MultiLevelSplitGenerator: Whether the execution has been stopped.
isStopped() - Method in class weka.classifiers.StoppableClassifier: Whether the execution has been stopped.
isStopped() - Method in class weka.classifiers.StoppableEvaluation: Whether the execution has been stopped.
isStopped() - Method in class weka.classifiers.StoppableRandomizableClassifier: Whether the execution has been stopped.
isStopped() - Method in class weka.classifiers.StoppableSingleClassifierEnhancer: Whether the execution has been stopped.
isString() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Returns whether the sort index is nominal/string or numeric.
isString() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Returns whether the index values are nominal/string or numeric.
isTime() - Method in class adams.ml.data.DataCellView: Checks whether the cell represents a time value.
isTimeLenient() - Method in class adams.ml.data.InstancesView: Returns whether the parsing of times is lenient or not.
isTimeMsec() - Method in class adams.ml.data.DataCellView: Checks whether the cell represents a time/msec value.
isTimeMsecLenient() - Method in class adams.ml.data.InstancesView: Returns whether the parsing of times/msec is lenient or not.
isUndoEnabled() - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList: Returns whether undo is enabled.
isUndoEnabled() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Returns whether undo is enabled.
isUndoEnabled() - Method in class adams.gui.visualization.instances.InstancesTable: returns whether undo support is enabled
isUndoEnabled() - Method in class adams.gui.visualization.instances.InstancesTableModel: returns whether undo support is enabled
isUndoSupported() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Returns whether an Undo manager is currently available.
isUndoSupported() - Method in class adams.gui.visualization.instance.InstancePanel: Returns whether an Undo manager is currently available.
isUniqueIDName(String) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Whether the given attribute name is the name of the unique ID attribute.
isUsingStorage() - Method in class adams.data.conversion.MapToWekaInstance: Returns whether storage items are being used.
isUsingStorage() - Method in class adams.flow.transformer.WekaFilter: Returns whether storage items are being used.
isUsingStorage() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Returns whether storage items are being used.
isUsingStorage() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns whether storage items are being used.
isUsingY() - Method in class adams.data.instance.InstancePointComparator: Returns whether Y or X number is used for ordering.
isValid() - Method in class adams.flow.container.WekaAttributeSelectionContainer: Checks whether the setup of the container is valid.
isValid() - Method in class adams.flow.container.WekaClusterEvaluationContainer: Checks whether the setup of the container is valid.
isValid() - Method in class adams.flow.container.WekaClusteringContainer: Checks whether the setup of the container is valid.
isValid() - Method in class adams.flow.container.WekaEvaluationContainer: Checks whether the setup of the container is valid.
isValid() - Method in class adams.flow.container.WekaExperimentContainer: Checks whether the setup of the container is valid.
isValid() - Method in class adams.flow.container.WekaFilterContainer: Checks whether the setup of the container is valid.
isValid() - Method in class adams.flow.container.WekaGeneticAlgorithmContainer: Checks whether the setup of the container is valid.
isValid() - Method in class adams.flow.container.WekaGeneticAlgorithmInitializationContainer: Checks whether the setup of the container is valid.
isValid() - Method in class adams.flow.container.WekaModelContainer: Checks whether the setup of the container is valid.
isValid() - Method in class adams.flow.container.WekaNearestNeighborSearchContainer: Checks whether the setup of the container is valid.
isValid() - Method in class adams.flow.container.WekaPredictionContainer: Checks whether the setup of the container is valid.
isValid() - Method in class adams.flow.container.WekaTrainTestSetContainer: Checks whether the setup of the container is valid.
isValid(String) - Method in class adams.core.base.AttributeTypeList: Checks whether the string value is a valid presentation for this class.
isValid(Instances) - Method in enum adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure: Checks whether the data can be used with this measure.
isValid(Instances, String) - Method in enum adams.opt.genetic.Measure: Checks whether the data can be used with this measure.
isValidDataIndex(BaseComboBox) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Checks whether the combobox selection index is a valid dataset index.
isValidSetup() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Checks whether the setup is valid, i.e., no name used twice, at least one sorting definition.
isVisible() - Method in class adams.gui.visualization.instance.InstanceContainer: Returns whether the instance is visible.
isVisible(int) - Method in class adams.gui.visualization.instance.InstanceContainerManager: Returns whether the container at the specified position is visible.
isZoomOverviewPanelVisible() - Method in class adams.gui.visualization.instance.InstanceExplorer: Returns whether the zoom overview panel is visible or not.
isZoomOverviewPanelVisible() - Method in class adams.gui.visualization.instance.InstancePanel: Returns whether the zoom overview panel is visible or not.
iterationsTipText() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns the tip text for this property.

J

jamaToWeka(Matrix) - Static method in class adams.data.instancesanalysis.pls.MatrixHelper: Turns a Jama matrix into a Weka one.
JdbcOutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka: Stores the results in a JDBC database.
JdbcOutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel
JFreeChart - Class in adams.gui.visualization.instances.instancestable: Allows to perform a simple plot of a column or row.
JFreeChart() - Constructor for class adams.gui.visualization.instances.instancestable.JFreeChart
jobRunnerTipText() - Method in class adams.flow.transformer.WekaExperimentExecution: Returns the tip text for this property.
jobRunnerTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the tip text for this property.
JOIN - adams.data.weka.columnfinder.MultiColumnFinder.Combination: join/merge/or.
JOIN - adams.data.weka.rowfinder.MultiRowFinder.Combination: join/merge/or.
JoinAttributes - Class in weka.filters.unsupervised.attribute: A simple filter that joins several attributes into a single STRING one, with a user defined string acting as 'glue'.
JoinAttributes() - Constructor for class weka.filters.unsupervised.attribute.JoinAttributes
JoinOnID - Class in adams.flow.transformer.wekadatasetsmerge: Joins the datasets by concatenating rows that share a unique ID.
JoinOnID() - Constructor for class adams.flow.transformer.wekadatasetsmerge.JoinOnID
JoinOnID.UniqueIDEnumeration - Class in adams.flow.transformer.wekadatasetsmerge: Enumeration class that returns the rows from the source datasets joined on the unique ID attribute.
joinOptions(String[]) - Method in class adams.core.option.WekaCommandLineHandler: Turns the option array back into a commandline.
JsonAdamsExperimentReader - Class in adams.data.io.input: Reads ADAMS Experiments in JSON format.
JsonAdamsExperimentReader() - Constructor for class adams.data.io.input.JsonAdamsExperimentReader
JsonAdamsExperimentWriter - Class in adams.data.io.output: Writes ADAMS experiments in JSON format.
JsonAdamsExperimentWriter() - Constructor for class adams.data.io.output.JsonAdamsExperimentWriter
JSONSpreadSheetReader - Class in adams.data.io.input: Reads WEKA datasets in JSON format and turns them into spreadsheets.
JSONSpreadSheetReader() - Constructor for class adams.data.io.input.JSONSpreadSheetReader
JSONSpreadSheetWriter - Class in adams.data.io.output: Writes a spreadsheet in JSON file format.
JSONSpreadSheetWriter() - Constructor for class adams.data.io.output.JSONSpreadSheetWriter

K

KAPPA - adams.flow.transformer.WekaClassifierRanker.Measure: evaluation via: Kappa statistic.
KAPPA - adams.opt.genetic.Measure: Kappa.
KAPPA_STATISTIC - adams.flow.core.EvaluationStatistic
KAPPA_STATISTIC - adams.flow.core.ExperimentStatistic
KB_INFORMATION - adams.flow.core.EvaluationStatistic
KB_INFORMATION - adams.flow.core.ExperimentStatistic
KB_MEAN_INFORMATION - adams.flow.core.EvaluationStatistic
KB_MEAN_INFORMATION - adams.flow.core.ExperimentStatistic
KB_RELATIVE_INFORMATION - adams.flow.core.EvaluationStatistic
KB_RELATIVE_INFORMATION - adams.flow.core.ExperimentStatistic
keepAttributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns the tip text for this property.
keepAttributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Returns the tip text for this property.
keepExistingTipText() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns the tip text for this property.
keepIndices(Instances) - Method in class weka.classifiers.meta.Corr
keepIndicesBasedOnCorrelation(Instances) - Method in class weka.classifiers.meta.Corr
keepNumComponentsTipText() - Method in class adams.data.conversion.SwapPLS: Returns the tip text for this property.
keepOnlySingleUniqueIDTipText() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the tip text for this property.
KeepRange - Class in weka.filters.unsupervised.instance: Keeps only the range of rows, in the order specified.
KeepRange() - Constructor for class weka.filters.unsupervised.instance.KeepRange
keepRelationNameTipText() - Method in class adams.flow.transformer.WekaFilter: Returns the tip text for this property.
keepRelationNameTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the tip text for this property.
keepRelationNameTipText() - Method in class adams.flow.transformer.WekaStreamFilter: Returns the tip text for this property.
keepSupervisedClassTipText() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the tip-text for the keep-supervised-class option.
KennardStone - Class in weka.filters.unsupervised.instance: Applies the Kennard-Stone algorithm to the dataset.
Each row has the pre-filter (eg PLS) applied before performing the search.
KennardStone() - Constructor for class weka.filters.unsupervised.instance.KennardStone
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.RepeatedCrossValidation
KEY_ADDITIONAL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet
KEY_ADDITIONAL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit
KEY_ADDITIONAL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet
KEY_ADDITIONALATTRIBUTES - Static variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab
KEY_ADDITIONALATTRIBUTES - Static variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab
KEY_ADDITIONALATTRIBUTES - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab
KEY_ALGORITHM - Static variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab
KEY_ANTIALIASING - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab
KEY_ATTRIBUTES - Static variable in class adams.gui.visualization.instances.instancestable.ArrayStatistic
KEY_ATTRIBUTES - Static variable in class adams.gui.visualization.instances.instancestable.Histogram
KEY_BATCHFILTER - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab
KEY_BINNING - Static variable in class adams.gui.visualization.instances.instancestable.Binning
KEY_CLASS_INDEX - Static variable in class weka.gui.explorer.AttributeSelectionHandler
KEY_CLASS_INDEX - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_CLASS_INDEX - Static variable in class weka.gui.explorer.ClustererHandler
KEY_CLASS_INDEX - Static variable in class weka.gui.explorer.ExperimentHandler
KEY_CLASSATTRIBUTE - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper
KEY_CLASSDISTRIBUTION - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions
KEY_CLASSIFIER - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab
KEY_CLASSIFIER - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab
KEY_CLUSTERER - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab
KEY_CLUSTERER - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab
KEY_COLOR - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab
KEY_COLORPROVIDER - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab
KEY_COLUMNS - Static variable in class adams.gui.visualization.instances.instancestable.Binning
KEY_COLUMNS - Static variable in class adams.gui.visualization.instances.instancestable.JFreeChart
KEY_COLUMNS - Static variable in class adams.gui.visualization.instances.instancestable.SimplePlot
KEY_COST_SENSITIVE_EVALUATION - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_CV_FOLDS - Static variable in class weka.gui.explorer.AttributeSelectionHandler
KEY_CV_FOLDS - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_DATA - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab
KEY_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab
KEY_DATASET - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel
KEY_DATATABLE_HEIGHT - Static variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable
KEY_DATATABLE_SELECTEDROWS - Static variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable
KEY_DISCARDPREDICTIONS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
KEY_DISCARDPREDICTIONS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel
KEY_DISCARDPREDICTIONS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet
KEY_DISCARDPREDICTIONS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit
KEY_DISCARDPREDICTIONS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet
KEY_ERROR_PLOT_POINT_SIZE - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_EVALUATION - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab
KEY_EVALUATION - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab
KEY_EVALUATION - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab
KEY_EVALUATION - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab
KEY_EVALUATION - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab
KEY_EVALUATION - Static variable in class weka.gui.explorer.ExperimentHandler
KEY_EVALUATION_METRICS - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_EVALUATION_PREFIX - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab
KEY_EVALUATION_PREFIX - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab
KEY_EVALUATION_PREFIX - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab
KEY_EVALUATION_PREFIX - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab
KEY_EVALUATION_PREFIX - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab
KEY_EVALUATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab
KEY_FILE - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions
KEY_FILE - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation
KEY_FILE - Static variable in class adams.gui.wizard.WekaSelectDatasetPage: key in the properties that contains the file name.
KEY_FILES - Static variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: key in the properties that contains the file name.
KEY_FILTER - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab
KEY_FINALMODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
KEY_FINALMODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation
KEY_FIRST_ATTRANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.CompareTab
KEY_FIRST_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.CompareTab
KEY_FOLD - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane
KEY_FOLD - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel
KEY_FOLDS - Static variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation
KEY_FOLDS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
KEY_FOLDS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation
KEY_FOLDS - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation
KEY_FOLDS - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup
KEY_FOLDS - Static variable in class weka.gui.explorer.ExperimentHandler
KEY_GENERATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
KEY_GENERATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation
KEY_GENERATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit
KEY_GENERATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup
KEY_GENERATOR - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup
KEY_HISTOGRAM - Static variable in class adams.gui.visualization.instances.instancestable.Histogram
KEY_HISTORY - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab
KEY_HISTORY - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab
KEY_HISTORY - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab
KEY_HISTORY - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab
KEY_HISTORY - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab
KEY_ICA - Static variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab
KEY_ID - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab
KEY_IDS - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab
KEY_IGNORED_ATTRIBUTES - Static variable in class weka.gui.explorer.ClustererHandler
KEY_JOBRUNNER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
KEY_JOBRUNNER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation
KEY_JOBRUNNER - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup
KEY_JOBRUNNER - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup
KEY_KEEPNAME - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab
KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab
KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab
KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab
KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab
KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab
KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab
KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab
KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab
KEY_LEFTPANELWIDTH - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab
KEY_LENIENT - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation
KEY_LOG - Static variable in class adams.gui.tools.wekainvestigator.tab.LogTab
KEY_MARKERS - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab
KEY_MAXATTRIBUTENAMES - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab
KEY_MAXATTRIBUTES - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab
KEY_MODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel
KEY_MODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel
KEY_MODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel
KEY_MODEL - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel
KEY_OUTPUT_CONFUSION_MATRIX - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_OUTPUT_ENTROPY - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_OUTPUT_MODEL - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_OUTPUT_PER_CLASS - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_OUTPUT_PREDICTIONS - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_OUTPUT_SOURCE_CODE - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_OUTPUTGENERATORS - Static variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the key for the output generators.
KEY_OUTPUTGENERATORS - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the key for the output generators.
KEY_OUTPUTGENERATORS - Static variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the key for the output generators.
KEY_OUTPUTGENERATORS - Static variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the key for the output generators.
KEY_OUTPUTGENERATORS - Static variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the key for the output generators.
KEY_PERCENTAGE - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit
KEY_PERCENTAGE - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit
KEY_PERCENTAGE - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup
KEY_PERCENTAGE_SPLIT - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_PERCENTAGE_SPLIT - Static variable in class weka.gui.explorer.ClustererHandler
KEY_PERFOLDOUTPUT - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
KEY_PLOT - Static variable in class adams.gui.visualization.instances.instancestable.JFreeChart
KEY_PLOT - Static variable in class adams.gui.visualization.instances.instancestable.SimplePlot
KEY_PREDICTED - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions
KEY_PRESERVE_ORDER - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_PRESERVEORDER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel
KEY_PRESERVEORDER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit
KEY_PRESERVEORDER - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel
KEY_PRESERVEORDER - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit
KEY_QUERY - Static variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: the key for the query.
KEY_RANDOM_SEED - Static variable in class weka.gui.explorer.AttributeSelectionHandler
KEY_RANDOM_SEED - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_RANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab
KEY_RANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab
KEY_RANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab
KEY_RANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab
KEY_READER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions
KEY_READER - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation
KEY_RELATIONNAME - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper
KEY_REPLACE - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab
KEY_RUN - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel
KEY_RUNS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation
KEY_RUNS - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup
KEY_RUNS - Static variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup
KEY_RUNS - Static variable in class weka.gui.explorer.ExperimentHandler
KEY_SCHEME - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel
KEY_SCHEME_OPTIONS - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel
KEY_SCHEME_VERSION_ID - Static variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel
KEY_SEARCH - Static variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab
KEY_SECOND_ATTRANGE - Static variable in class adams.gui.tools.wekainvestigator.tab.CompareTab
KEY_SECOND_DATASET - Static variable in class adams.gui.tools.wekainvestigator.tab.CompareTab
KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation
KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel
KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit
KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel
KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation
KEY_SEED - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit
KEY_SERIALIZE - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab
KEY_SERIALIZE_FILE - Static variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab
KEY_SKIPNOMINAL - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab
KEY_STATISTIC - Static variable in class adams.gui.visualization.instances.instancestable.ArrayStatistic
KEY_STORE_CLUSTERS - Static variable in class weka.gui.explorer.ClustererHandler
KEY_STORE_PREDICTIONS - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_TABS - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper
KEY_TEST - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet
KEY_TEST - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet
KEY_TEST - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet
KEY_TEST - Static variable in class weka.gui.explorer.AttributeSelectionHandler
KEY_TEST - Static variable in class weka.gui.explorer.ClassifierHandler
KEY_TEST - Static variable in class weka.gui.explorer.ClustererHandler
KEY_TESTSPLIT - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation
KEY_TRAIN - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet
KEY_TRAIN - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet
KEY_TRAIN - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet
KEY_TRAINSPLIT - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation
KEY_UNDOENABLED - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper
KEY_USEVIEWS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation
KEY_USEVIEWS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit
KEY_USEVIEWS - Static variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit
KEY_VALIDATE - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet
KEY_VARIANCE - Static variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab
KEY_WEIGHT - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions
keysTipText() - Method in class adams.flow.source.WekaDatabaseReader: Returns the tip text for this property.
KEYWORD_ATTRIBUTE - Static variable in class weka.core.converters.SimpleArffLoader
KEYWORD_DATA - Static variable in class weka.core.converters.SimpleArffLoader
KEYWORD_RELATION - Static variable in class weka.core.converters.SimpleArffLoader
KMEANS_PLUS_PLUS - Static variable in class weka.clusterers.SAXKMeans
kMeansPlusPlusInit(Instances) - Method in class weka.clusterers.SAXKMeans: Initialize using the k-means++ method
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.FilteredSearch: Returns k nearest instances in the current neighbourhood to the supplied instance.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.NewNNSearch: Returns k nearest instances in the current neighbourhood to the supplied instance.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.PCANNSearch: Returns k nearest instances in the current neighbourhood to the supplied instance.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.PLSNNSearch: Returns k nearest instances in the current neighbourhood to the supplied instance.
KNNTipText() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Returns the tip text for this property.

L

LABEL - Static variable in class weka.classifiers.meta.ThresholdedBinaryClassification
LABEL - Static variable in class weka.classifiers.meta.Veto
LABEL_COUNT - adams.flow.transformer.WekaInstancesInfo.InfoType: the number of instances with the specified class label (selected attribute, only nominal).
LABEL_COUNTS - adams.flow.transformer.WekaInstancesInfo.InfoType: the counts per label (selected attribute, only nominal).
LABEL_DISTRIBUTION - adams.flow.transformer.WekaInstancesInfo.InfoType: the distribution (percentages, 0-1) per label (selected attribute, only nominal).
LABEL_FALSE - Static variable in class adams.data.instances.AbstractInstanceGenerator: the "false" label for boolean data types.
LABEL_MATCH - Static variable in class weka.filters.unsupervised.instance.DatasetLabeler: the default label for a "match".
LABEL_NONMATCH - Static variable in class weka.filters.unsupervised.instance.DatasetLabeler: the default label for a "non-match".
LABEL_REGEXP - Static variable in class weka.filters.unsupervised.instance.RemoveWithLabels
LABEL_TRUE - Static variable in class adams.data.instances.AbstractInstanceGenerator: the "true" label for boolean data types.
labelIndexTipText() - Method in class adams.flow.transformer.WekaInstancesInfo: Returns the tip text for this property.
labelIndexTipText() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns the tip text for this property.
labelMatchTipText() - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Returns the tip text for this property.
labelNonMatchTipText() - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Returns the tip text for this property.
labelRegExpTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns the tip text for this property.
LABELS - adams.flow.transformer.WekaInstancesInfo.InfoType: the labels (selected attribute, only nominal).
labelStringTipText() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns the tip text for this property.
labelTipText() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Returns the tip text for this property.
labelTipText() - Method in class weka.classifiers.meta.Veto: Returns the tip text for this property.
LAMBDAMART_MAXIMISE_MAP - weka.classifiers.trees.XGBoost.Objective
LAMBDAMART_MAXIMISE_NDCG - weka.classifiers.trees.XGBoost.Objective
LAMBDAMART_PAIRWISE_RANKING - weka.classifiers.trees.XGBoost.Objective
lambdaTipText() - Method in class adams.data.instancesanalysis.pls.DIPLS: Returns the tip text for this property
lambdaTipText() - Method in class adams.data.instancesanalysis.pls.SparsePLS: Returns the tip text for this property
lambdaTipText() - Method in class adams.data.instancesanalysis.pls.VCPLS: Returns the tip text for this property
lambdaTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the lambda option.
LastAttribute - Class in adams.data.weka.classattribute: Simply chooses the last attribute as class attribute.
LastAttribute() - Constructor for class adams.data.weka.classattribute.LastAttribute
lastInstance() - Method in class weka.core.InstancesView: Returns the last instance in the set.
lastUpdated() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Returns the timestamp the data was last updated.
lastUpdated() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer: Returns the timestamp the data was last updated.
LatestRecords - Class in weka.filters.unsupervised.instance: Retains the latest database records.
LatestRecords() - Constructor for class weka.filters.unsupervised.instance.LatestRecords
launch() - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.AppendDatasets: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.ArffViewer: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.BatchFilterDatasets: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.BayesNetEditor: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.BoundaryVisualizer: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.CostCurve: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.DatasetCompatibility: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.Experimenter: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.Explorer: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.GraphVisualizer: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.InstanceCompare: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.InstanceExplorer: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.InstancesPlot: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.MakeCompatibleDatasets: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.MarginCurve: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.MergeDatasets: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.MultiExplorer: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.PackageManager: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.PlotAttributeVsAttribute: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.ROC: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.SqlViewer: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.TreeVisualizer: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.WekaCommandToCode: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.WekaInvestigator: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.WekaMultiExperimenter: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.WekaSimpleCLI: Launches the functionality of the menu item.
launch() - Method in class adams.gui.menu.Workbench: Launches the functionality of the menu item.
launchAssignToClusters(Instances, int[]) - Method in class weka.clusterers.SAXKMeans: Launch the tasks that assign instances to clusters
launchMoveCentroids(Instances[]) - Method in class weka.clusterers.SAXKMeans: Launch the move centroids tasks
LeanMultiScheme - Class in weka.classifiers.meta: Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data.
LeanMultiScheme() - Constructor for class weka.classifiers.meta.LeanMultiScheme
LeastMedianSq - Class in weka.classifiers.meta: Finds the base classifier with the best least median squared error.
LeastMedianSq() - Constructor for class weka.classifiers.meta.LeastMedianSq
LeaveOneOutByValueGenerator - Class in weka.classifiers: Generates train/test split pairs using the unique values from the specified attribute.
LeaveOneOutByValueGenerator() - Constructor for class weka.classifiers.LeaveOneOutByValueGenerator: Initializes the generator.
LeaveOneOutByValueGenerator(Instances, long, boolean, WekaAttributeIndex) - Constructor for class weka.classifiers.LeaveOneOutByValueGenerator: Initializes the generator.
LEFT - Static variable in class weka.classifiers.trees.m5.Rule2
leftNode() - Method in class weka.classifiers.trees.m5.RuleNode2: Get the left child of this node
LegacyClassifierErrors - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Generates classifier errors plot (legacy Weka output).
LegacyClassifierErrors() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyClassifierErrors
LegacyCostBenefitAnalysis - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Generates cost benefit analysis (legacy Weka output).
LegacyCostBenefitAnalysis() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis
LegacyCostCurve - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Generates cost curve (legacy Weka output).
LegacyCostCurve() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve
LegacyGraphVisualizer - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Displays the graph that the model generated (legacy Weka output).
LegacyGraphVisualizer() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyGraphVisualizer
LegacyMarginCurve - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Generates margin curve (legacy Weka output).
LegacyMarginCurve() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyMarginCurve
LegacyThresholdCurve - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Generates margin curve (legacy Weka output).
LegacyThresholdCurve() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve
LegacyTreeVisualizer - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Displays the tree that the model generated (legacy Weka output).
LegacyTreeVisualizer - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output: Displays the tree that the model generated (legacy Weka output).
LegacyTreeVisualizer() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyTreeVisualizer
LegacyTreeVisualizer() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.LegacyTreeVisualizer
lenientTipText() - Method in class adams.data.indexedsplits.InstancesIndexedSplitsRunsCompatibility: Returns the tip text for this property.
lenientTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the tip text for this property.
LibSVMSpreadSheetReader - Class in adams.data.io.input: Reads WEKA datasets in LibSVM format and turns them into spreadsheets.
LibSVMSpreadSheetReader() - Constructor for class adams.data.io.input.LibSVMSpreadSheetReader
LibSVMSpreadSheetWriter - Class in adams.data.io.output: Writes a spreadsheet in LibSVM file format.
LibSVMSpreadSheetWriter() - Constructor for class adams.data.io.output.LibSVMSpreadSheetWriter
LIFT - adams.flow.sink.WekaThresholdCurve.AttributeName
limitTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
LINEAR_REGRESSION - weka.classifiers.trees.XGBoost.Objective
LinearRegressionAttributeEval - Class in weka.attributeSelection: Uses the coefficients of LinearRegressionJ to determine the importance of the attributes (attribute selection turned off, no elimination of collinear attributes).
LinearRegressionAttributeEval() - Constructor for class weka.attributeSelection.LinearRegressionAttributeEval
LinearRegressionJ - Class in weka.classifiers.functions: Class for using linear regression for prediction.
LinearRegressionJ() - Constructor for class weka.classifiers.functions.LinearRegressionJ
listCapabilities(Capabilities) - Method in class adams.gui.help.WekaOptionHandlerHelpGenerator: returns a comma-separated list of all the capabilities.
listOptions() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Returns an enumeration of all the available options..
listOptions() - Method in class weka.attributeSelection.LinearRegressionAttributeEval
listOptions() - Method in class weka.classifiers.functions.ClassificationViaPLS: Gets an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.FakeClassifier: Gets an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.GeneticAlgorithm: Gets an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.GPD: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.LinearRegressionJ: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.MathExpressionClassifier: Gets an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.PLSClassifierWeighted: Gets an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.PLSWeighted: Gets an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.lazy.LWLSynchro: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AbstainAttributePercentile: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AbstainAverage: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AbstainingCascade: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AbstainMinimumProbability: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AbstainVote: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.ClassifierCascade: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.Consensus: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.ConsensusOrVote: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.Corr: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.Fallback: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.FilteredClassifierExt: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.HighLowSplit: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.InputSmearing: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.LeastMedianSq: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.MinMaxLimits: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.PartitionedStacking: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.SocketFacade: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.SubsetEnsemble: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.SuppressModelOutput: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.Veto: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.VotedImbalance: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.m5.M5Base2: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.trees.M5P2: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.trees.RandomModelTrees: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.RandomRegressionForest: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.SAXKMeans: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.AbstractSimpleOptionHandler: Returns an enumeration of all the available options..
listOptions() - Method in class weka.core.converters.SimpleArffLoader: Returns an enumeration of all the available options..
listOptions() - Method in class weka.core.converters.SimpleArffSaver: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.SpreadSheetLoader: Lists the available options
listOptions() - Method in class weka.core.converters.SpreadSheetSaver: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.FilteredSearch
listOptions() - Method in class weka.core.neighboursearch.NewNNSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.PCANNSearch
listOptions() - Method in class weka.core.neighboursearch.PLSNNSearch
listOptions() - Method in class weka.core.SAXDistance: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.tokenizers.cleaners.AbstractTokenCleaner: Returns an enumeration of all the available options..
listOptions() - Method in class weka.core.tokenizers.cleaners.MultiCleaner: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.tokenizers.MultiTokenizer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.WeightedEuclideanDistanceRidge: Returns an enumeration describing the available options.
listOptions() - Method in class weka.experiment.ResultMatrixMediaWiki: Returns an enumeration of all the available options..
listOptions() - Method in class weka.filters.FilteredFilter: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.FlowFilter: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.SerializedFilter: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.MultiPLS: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.PLS: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.YGradientEPO: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.YGradientGLSW: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AnyToString: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Detrend: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.DownSample: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.FastWavelet: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.FFT: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.InputSmearing: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.LogTransform: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.PAA: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.SAX: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.SetMissingValue: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.SpellChecker: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.StringToDate: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.AlignDataset: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.KeepRange: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.KennardStone: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.LatestRecords: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin: Returns an enumeration of all the available options..
listOptions() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.Scale: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.Sort: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.SortOnAttribute: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns an enumeration describing the available options.
listOrArray(Object) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: If the object should be a list of strings instead of an array of strings, then it gets converted accordingly.
ListPackages - Class in adams.flow.source.wekapackagemanageraction: Lists the packages.
ListPackages() - Constructor for class adams.flow.source.wekapackagemanageraction.ListPackages
ListPackages.ListType - Enum in adams.flow.source.wekapackagemanageraction: The type of list to generate.
ListPackages.OutputFormat - Enum in adams.flow.source.wekapackagemanageraction: How to output the packages.
listTypeTipText() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: Returns the tip text for this property.
load(File) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO: Loads an experiment.
load(File) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultAdamsExperimentIO: Loads an experiment.
load(File) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultWekaExperimentIO: Loads an experiment.
load(File) - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO: Loads an experiment.
load(File) - Method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter: Loads the specified file in a new panel.
load(File) - Method in class weka.gui.explorer.MultiExplorer: Loads the specified file in a new panel.
load(File[]) - Method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter: Loads the specified files in new panels.
load(File[]) - Method in class weka.gui.explorer.MultiExplorer: Loads the specified files in new panels.
loadClassifier() - Method in class weka.gui.explorer.ExplorerExt: Loads a classifier in the classify tab.
loadClusterer() - Method in class weka.gui.explorer.ExplorerExt: Loads a clusterer in the cluster tab.
loadData(Instances, List<InstanceContainer>) - Method in class adams.gui.visualization.instance.InstanceExplorer: Loads the given data into the container manager.
loadDataFromDatabase() - Method in class adams.gui.visualization.instance.InstanceExplorer: pops up SQL Viewer for SQL statement.
loadDataFromDisk() - Method in class adams.gui.visualization.instance.InstanceExplorer: pops up file dialog for loading dataset form disk.
loadDataFromDisk(File) - Method in class adams.gui.visualization.instance.InstanceExplorer: pops up file dialog for loading dataset form disk.
loadDataset() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Loads the dataset, if possible.
loadDataset(int) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Loads the dataset.
LoadDatasetDialog - Class in adams.gui.visualization.instance: A dialog for loading datasets from disk.
LoadDatasetDialog(Dialog) - Constructor for class adams.gui.visualization.instance.LoadDatasetDialog: Creates a modal dialog.
LoadDatasetDialog(Dialog, String) - Constructor for class adams.gui.visualization.instance.LoadDatasetDialog: Creates a modal dialog.
LoadDatasetDialog(Frame) - Constructor for class adams.gui.visualization.instance.LoadDatasetDialog: Creates a modal dialog.
LoadDatasetDialog(Frame, String) - Constructor for class adams.gui.visualization.instance.LoadDatasetDialog: Creates a modal dialog.
loadFile(boolean) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Loads the file and displays the IDs.
loadFromDatabase() - Method in class weka.gui.explorer.ExplorerExt: Lets the user load data from a database.
loadFromURL() - Method in class weka.gui.explorer.ExplorerExt: Lets the user load data from a URL.
loadingsCalculationsTipText() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Returns the tip text for this property
loadModel() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Attempts to load the model and (if available) the header.
loadModel() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Attempts to load the model and (if available) the header.
loadPackageDirectory(File) - Method in class adams.core.management.WekaPackagesClassPathAugmenter: Processes a package directory.
loadParameters() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Prompts the user to select a yaml file to load the parameters for this tab from.
loadProperties() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: Loads properties from a file, prompts the user to select props file.
loadReferenceDataset() - Method in class weka.filters.unsupervised.instance.AlignDataset: Loads the reference dataset from disk or returns the manually supplied one.
loadResults() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner: Examines the supplied experiment to determine the results destination and attempts to load the results.
loadResults() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractWekaExperimentRunner: Examines the supplied experiment to determine the results destination and attempts to load the results.
loadTestSet() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Loads the test set from disk or returns the manually supplied one.
localTipText() - Method in class weka.classifiers.meta.SocketFacade: Returns the tip text for this property.
locateMethod(String) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Locates the method with the specified name (method is expected to take no parameters).
locateRows(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the rows for the classifier/dataset combination.
locationsTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the tip text for this property.
locationsTipText() - Method in class adams.flow.transformer.WekaInstancesStatistic: Returns the tip text for this property.
loClassifierTipText() - Method in class weka.classifiers.meta.HighLowSplit
log(String) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Displays the message.
log(String, Throwable) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Displays the error.
logAndShowMessage(String) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Logs the error message and shows it in the status bar.
LogClassRegressor - Class in weka.classifiers.meta: Takes log of the class attribute in the data.
LogClassRegressor() - Constructor for class weka.classifiers.meta.LogClassRegressor
logDensity(Instance, double) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Returns natural logarithm of density estimate for given value based on given instance.
logError(String, String) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Logs the error message and also displays an error dialog.
logError(String, String) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel: Logs the error message and also displays an error dialog.
logError(String, Throwable) - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: Logs the exception.
logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Logs the exception and also displays an error dialog.
logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource: Logs the exception and also displays an error dialog.
logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Logs the exception and also displays an error dialog.
logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Logs the exception and also displays an error dialog.
logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Logs the exception and also displays an error dialog.
logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Logs the exception and also displays an error dialog.
logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Logs the exception and also displays an error dialog.
logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Logs the exception and also displays an error dialog.
logError(String, Throwable, String) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Logs the exception and also displays an error dialog.
logError(String, Throwable, String) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Logs the error message and also displays an error dialog.
logError(Throwable, String) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Logs the exception and also displays an error dialog.
LOGISTIC_REGRESSION - weka.classifiers.trees.XGBoost.Objective
LOGISTIC_REGRESSION_FOR_BINARY_CLASSIFICATION - weka.classifiers.trees.XGBoost.Objective
LOGIT_RAW_REGRESSION_FOR_BINARY_CLASSIFICATION - weka.classifiers.trees.XGBoost.Objective
logMessage(String) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Logs the message.
logMessage(String) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel: Logs the message.
logMessage(Throwable) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Logs the exception with no dialog.
LogPanel - Class in adams.gui.tools.wekamultiexperimenter: The log panel.
LogPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.LogPanel
LogTab - Class in adams.gui.tools.wekainvestigator.tab: Just displays the log messages.
LogTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.LogTab
LogTargetRegressor - Class in weka.classifiers.meta: Takes logs of all numeric attributes in the data.
LogTargetRegressor() - Constructor for class weka.classifiers.meta.LogTargetRegressor
LogTransform - Class in weka.filters.unsupervised.attribute: Transforms all numeric attributes in the specified range using a log-transform.
The class attribute is omitted.
If a value less or equal to zero is encountered, a missing value is output.
LogTransform() - Constructor for class weka.filters.unsupervised.attribute.LogTransform
loHipointTipText() - Method in class weka.classifiers.meta.HighLowSplit
loHipointTipText() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier
LOSSGUIDE - weka.classifiers.trees.XGBoost.GrowPolicy
LowerStatistic - Enum in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated: Enumeration of lower bound statistics to compute.
lowerTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Returns the tip text for this property.
lowerTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Returns the tip text for this property.
lowerTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Returns the tip text for this property.
lowerTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the tip text for this property.
LWLContainer() - Constructor for class weka.classifiers.lazy.LWLDatasetBuilder.LWLContainer
LWLDatasetBuilder - Class in weka.classifiers.lazy: Class for building LWL-style weighted datasets.
LWLDatasetBuilder() - Constructor for class weka.classifiers.lazy.LWLDatasetBuilder
LWLDatasetBuilder.LWLContainer - Class in weka.classifiers.lazy: the container with the weighted dataset, distances, indices.
LWLIntervalEstimator - Class in weka.classifiers.lazy: Locally weighted learning.
LWLIntervalEstimator() - Constructor for class weka.classifiers.lazy.LWLIntervalEstimator
LWLSynchro - Class in weka.classifiers.lazy: Locally weighted learning.
LWLSynchro() - Constructor for class weka.classifiers.lazy.LWLSynchro: Initializes the classifier.
LWLSynchroPrefilter - Class in weka.classifiers.lazy: Locally weighted learning.
LWLSynchroPrefilter() - Constructor for class weka.classifiers.lazy.LWLSynchroPrefilter: Initializes the classifier.

M

m_Aborted - Variable in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: whether the user cancelled the experiment.
m_Absolute - Variable in class weka.filters.unsupervised.attribute.CorrelationMatrix: whether to return the absolute correlations.
m_AcceptListener - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the listener waiting for the user to accept the input.
m_AccumulatdError - Variable in class adams.flow.transformer.WekaAccumulatedError: the accumulated error so far.
m_Action - Variable in class adams.flow.source.WekaPackageManagerAction: the action to execute.
m_Action - Variable in class adams.flow.standalone.WekaPackageManagerAction: the action to execute.
m_Action - Variable in class adams.flow.transformer.WekaPackageManagerAction: the action to execute.
m_ActionFileClassAttribute - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for selecting the class attribute heuristic.
m_ActionFileClear - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for clearing all datasets.
m_ActionFileClose - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for closing the investigator.
m_ActionFileOpen - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for loading a dataset.
m_ActionFileRelationName - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for selecting the relation name heuristic.
m_ActionFileStopJob - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for stopping a job.
m_Actions - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: the available actions.
m_Actions - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the available actions.
m_ActionTabCloseAllTabs - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for closing all tabs.
m_ActionTabCloseTab - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for closing a tab.
m_ActionTabCopyTab - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for copying a tab.
m_ActionTabLoadParameters - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for loading parameters for a tab.
m_ActionTabSaveParameters - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for saving parmeters of a tab.
m_ActionTabUndoCloseTab - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the action for undoing closed a tab.
m_Actual - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions: the column with the actual values.
m_Actual - Variable in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure: the collected actual.
m_Actual - Variable in class weka.classifiers.functions.FromPredictions: the column with the actual values.
m_ActualAlgorithm - Variable in class adams.flow.transformer.WekaGeneticAlgorithm: the actual algorithm in use.
m_ActualAssociator - Variable in class adams.flow.transformer.WekaTrainAssociator: the actual weka associator.
m_ActualBase - Variable in class weka.classifiers.meta.Fallback: the actual base classifier.
m_ActualCapabilities - Variable in class adams.flow.condition.bool.AbstractAttributeCapabilities: the capabilities object to use.
m_ActualClass - Variable in class adams.core.discovery.genetic.GenericDoubleResolution: the actual class.
m_ActualClass - Variable in class adams.core.discovery.genetic.GenericFloatResolution: the actual class.
m_ActualClass - Variable in class adams.core.discovery.genetic.GenericInteger: the actual class.
m_ActualClass - Variable in class adams.core.discovery.genetic.GenericString: the actual class.
m_ActualClusterer - Variable in class adams.flow.transformer.WekaTrainClusterer: the weka clusterer.
m_ActualFallback - Variable in class weka.classifiers.meta.Fallback: the actual fallback classifier.
m_ActualFilter - Variable in class adams.data.spreadsheet.filter.WekaFilter: the actual filter in use.
m_ActualFilter - Variable in class adams.data.weka.rowfinder.FilteredIQR: the actual IQR filter.
m_ActualFilter - Variable in class adams.flow.transformer.WekaFilter: the actual filter used.
m_ActualFilter - Variable in class weka.classifiers.functions.PLSClassifierWeighted: the actual filter to use
m_ActualFilter - Variable in class weka.filters.SerializedFilter: the actual filter.
m_ActualFilter - Variable in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: the actual filter used internally for filtering the data.
m_ActualFolds - Variable in class adams.multiprocess.WekaCrossValidationExecution: the actual folds used.
m_ActualGenerator - Variable in class adams.flow.transformer.WekaCrossValidationSplit: the actual fold generator.
m_ActualGenerator - Variable in class adams.flow.transformer.WekaRandomSplit: the currently active generator.
m_ActualGenerator - Variable in class adams.flow.transformer.WekaSplitGenerator: the currently active generator.
m_ActualIndex - Variable in class weka.classifiers.functions.FromPredictions: the actual column index.
m_ActualJobRunner - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: JobRunner for the classifier/dataset combinations.
m_ActualJobRunner - Variable in class adams.multiprocess.WekaCrossValidationExecution: the runner in use.
m_ActualLabel - Variable in class weka.classifiers.meta.ThresholdedBinaryClassification: the index of the label to check.
m_ActualLabel - Variable in class weka.classifiers.meta.Veto: the index of the label to check.
m_ActualMax - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: the maximum to use for the actual values (pos inf = no restriction).
m_ActualMin - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: the minimum to use for the actual values (neg inf = no restriction).
m_ActualNumBalanced - Variable in class weka.classifiers.meta.VotedImbalance: the actual number of balanced datasets to generate.
m_ActualNumFolds - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator: the actual number of folds.
m_ActualNumFolds - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: the actual number of folds.
m_ActualNumFolds - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: the actual number of folds.
m_ActualNumThreads - Variable in class adams.multiprocess.WekaCrossValidationExecution: the actual number of threads to use.
m_ActualReferenceDataset - Variable in class weka.filters.unsupervised.instance.AlignDataset: the actual reference dataset in use.
m_ActualSearch - Variable in class adams.flow.transformer.WekaNearestNeighborSearch: the actual neighboorhood search in use.
m_ActualSearch - Variable in class weka.classifiers.lazy.LWLDatasetBuilder: The actual nearest neighbour search algorithm to use.
m_ActualSupport - Variable in class weka.classifiers.meta.ConsensusOrVote: the actual number of classifiers that need to support the label.
m_ActualSupport - Variable in class weka.classifiers.meta.Veto: the actual number of classifiers that need to support the label.
m_ActualTrain - Variable in class weka.classifiers.lazy.LWLDatasetBuilder: The actual training instances used for classification.
m_AddAttributeInformation - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: whether to added attribute information to the meta-data as well.
m_AddClassification - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: whether to add the numeric classification to the output.
m_AddClassificationLabel - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: whether to add the classification label to the output (nominal classes only).
m_AddDatabaseID - Variable in class adams.data.instances.AbstractInstanceGenerator: whether to add the database ID.
m_AddDatasetInformation - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: whether to added basic dataset information to the meta-data as well.
m_AddDistribution - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: whether to add the distribution to the output (nominal classes only).
m_AddFilter - Variable in class weka.filters.unsupervised.instance.DatasetLabeler: the filter for adding the label attribute.
m_addId - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter
m_AddID - Variable in class weka.classifiers.lazy.LWLDatasetBuilder: for adding the ID to trace the instances.
m_AddIndex - Variable in class adams.flow.transformer.WekaInstancesMerge: whether to add the index to the prefix.
m_Additional - Variable in class weka.classifiers.functions.FromPredictions: the additional columns in the spreadsheet to add to the plot containers.
m_AdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: additional attributes.
m_AdditionalHandlers - Static variable in class weka.gui.explorer.WorkspaceHelper: the additional associations between Explorer.ExplorerPanel and AbstractExplorerPanelHandler.
m_AdditionalIndices - Variable in class weka.classifiers.functions.FromPredictions: the additional column indices.
m_AddLabelIndex - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer: whether to prefix the labels with a 1-based index (only nominal classes).
m_AddLabelIndex - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: whether to prefix the labels with a 1-based index (only nominal classes).
m_AddOne - Variable in class weka.filters.unsupervised.attribute.LogTransform: If true output nominal, false output numeric .
m_AdjustToVisibleData - Variable in class adams.gui.visualization.instance.InstancePanel: whether to adjust to visible data or not.
m_Aggregated - Variable in class weka.classifiers.AggregateEvaluations: the aggregated evaluation.
m_Algorithm - Variable in class adams.data.instancesanalysis.PLS: the algorithm to use.
m_Algorithm - Variable in class adams.flow.transformer.WekaGeneticAlgorithm: whether to check the header.
m_Algorithm - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: the binning algorithm.
m_Algorithm - Variable in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: the binning algorithm.
m_Algorithm - Variable in class weka.classifiers.functions.GeneticAlgorithm: the genetic algorithm.
m_Algorithm - Variable in class weka.classifiers.functions.PLSWeighted: the PLS algorithm
m_Algorithm - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: the binning algorithm.
m_Algorithm - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: the binning algorithm.
m_Algorithm - Variable in class weka.filters.supervised.attribute.MultiPLS: the PLS algorithm.
m_Algorithm - Variable in class weka.filters.supervised.attribute.PLS: the PLS algorithm.
m_Algorithm - Variable in class weka.filters.supervised.attribute.YGradientEPO: the EPO algorithm.
m_Algorithm - Variable in class weka.filters.supervised.attribute.YGradientGLSW: the GLSW algorithm.
m_Algorithm - Variable in class weka.filters.unsupervised.attribute.FastWavelet: the type of algorithm.
m_Algorithms - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: the algorithms to evaluate.
m_Alin - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: The parameters of the linear transforamtion realized by the filter on the class attribute
m_Alin - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: The parameters of the linear transformation realized by the filter on the class attribute
m_Alin - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: The parameters of the linear transforamtion realized by the filter on the class attribute
m_Alin - Variable in class weka.classifiers.functions.GPD: The parameters of the linear transforamtion realized by the filter on the class attribute
m_allEqualWeights - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: Do all instances have the same weight
m_Alpha - Variable in class weka.classifiers.trees.XGBoost: L1 regularisation term on weights.
m_Alpha - Variable in class weka.filters.supervised.attribute.YGradientEPO: Alpha parameter.
m_Alpha - Variable in class weka.filters.supervised.attribute.YGradientGLSW: Alpha parameter.
m_AlreadRegistered - Static variable in class adams.gui.goe.WekaEditorsRegistration
m_AlwaysShowMarkers - Variable in class adams.gui.visualization.instance.InstanceLinePaintlet: whether to show markers all the time.
m_AlwaysUseContainer - Variable in class adams.flow.transformer.AbstractWekaClassifierEvaluator: whether to always use a container.
m_Amount - Variable in class weka.filters.unsupervised.instance.LatestRecords: the amount to keep (less than 1: percentage, otherwise absolute number).
m_AntiAliasingEnabled - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: whether anti-aliasing is enabled.
m_AntiAliasingEnabled - Variable in class adams.gui.visualization.instance.InstanceLinePaintlet: whether anti-aliasing is enabled.
m_AntiAliasingEnabled - Variable in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet: whether anti-aliasing is enabled.
m_ArrayEditor - Variable in class adams.flow.source.WekaSelectObjects: the dialog for selecting the objects.
m_as - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: This holds the attribute stats of the current attribute on display.
m_asCache - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Cache of attribute stats info for the current data set
m_Ascending - Variable in class adams.data.instances.InstanceComparator: whether to sort ascending or descending.
m_Assignments - Variable in class weka.clusterers.SAXKMeans: Assignments obtained.
m_Associator - Variable in class adams.flow.source.WekaAssociatorSetup: the weka associator.
m_Associator - Variable in class adams.flow.transformer.WekaTrainAssociator: the name of the callable weka associator.
m_Associator - Variable in class adams.flow.transformer.WekaTrainAssociator.TrainJob: the associator to train.
m_AttIndex - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric: the attribute index.
m_AttIndices - Variable in class weka.filters.unsupervised.attribute.Detrend: the determined indices.
m_AttIndices - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: the determined indices.
m_AttIndices - Variable in class weka.filters.unsupervised.attribute.SimpleDetrend: the determined indices.
m_AttIndicesSet - Variable in class weka.filters.unsupervised.attribute.Detrend: the determined indices (as set).
m_AttIndicesSet - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: the determined indices (as set).
m_attnum - Variable in class weka.classifiers.meta.AbstainAttributePercentile
m_AttRange - Variable in class weka.filters.unsupervised.instance.KennardStone: the range of attributes to apply to.
m_AttRegExp - Variable in class weka.filters.unsupervised.attribute.Detrend: the range of attributes to work on.
m_AttRegExp - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: the range of attributes to work on.
m_attribIndex - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: This holds the index of the current attribute on display and should be set through setAttribute(int idx).
m_attribute - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: The chosen attribute
m_AttributeFilter - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Filter for removing class attribute, nominal attributes with 0 or 1 value.
m_attributeIndex - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: The index of the chosen attribute
m_AttributeIndex - Variable in class adams.data.weka.rowfinder.ByLabel: the attribute index to work on.
m_AttributeIndex - Variable in class adams.data.weka.rowfinder.ByNumericRange: the attribute index to work on.
m_AttributeIndex - Variable in class adams.data.weka.rowfinder.ByNumericValue: the attribute index to work on.
m_AttributeIndex - Variable in class adams.flow.transformer.WekaInstancesInfo: the index of the attribute to get the information for.
m_AttributeIndex - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: the attribute to index.
m_AttributeIndex - Variable in class weka.filters.unsupervised.attribute.SpellChecker: the index of the attribute to work on.
m_AttributeIndex - Variable in class weka.filters.unsupervised.instance.SortOnAttribute: the index of the attribute to sort on.
m_AttributeName - Variable in class adams.flow.transformer.WekaGetInstanceValue: the name of the attribute to get the value from the Instance.
m_AttributeName - Variable in class adams.flow.transformer.WekaInstanceEvaluator: the attribute name of the evaluation object.
m_AttributeName - Variable in class weka.filters.unsupervised.instance.DatasetLabeler: the name of the attribute name to add.
m_AttributeName - Variable in class weka.filters.unsupervised.instance.LatestRecords: the name of the attribute that holds the numeric database ID.
m_AttributeNameLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel: Displays the name of the relation
m_AttributeNames - Variable in class adams.flow.source.WekaNewInstances: the comma-separated list of attribute names.
m_AttributeNames - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes: the attribute names.
m_AttributePrefix - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis: the prefix to use for the generated attributes.
m_AttributeRange - Variable in class adams.data.instancesanalysis.FastICA: the range of attributes to work.
m_AttributeRange - Variable in class adams.data.instancesanalysis.PCA: the range of attributes to work.
m_AttributeRange - Variable in class adams.data.instancesanalysis.PLS: the range of attributes to work.
m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.CorrelationMatrix: the range of attributes to work on.
m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.InputSmearing: the range of the attributes to work on.
m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.JoinAttributes: the range of the attributes to work on.
m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.LogTransform: the range of attributes to log-transform.
m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.SetMissingValue: the range of attributes to set to missing.
m_AttributeRange - Variable in class weka.filters.unsupervised.attribute.SimpleDetrend: the range of attributes to work on.
m_AttributeRenameFindRegexs - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: The regexs to use to find attributes that require renaming.
m_AttributeRenameFormatStrings - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: The format strings specifying how to rename attributes.
m_Attributes - Variable in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: the range of attributes to plot.
m_Attributes - Variable in class weka.filters.unsupervised.attribute.EquiDistance: the indices of the identified attributes.
m_AttributeSelection - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: the attsel object.
m_AttributeSelection - Variable in class weka.classifiers.functions.LinearRegressionJ: The current attribute selection method
m_AttributeSelection - Variable in class weka.filters.unsupervised.attribute.EquiDistance: how to select the attributes.
m_AttributeStats - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: Cached stats on the attributes we've summarized so far
m_AttributesToProcess - Variable in class adams.flow.transformer.WekaMultiLabelSplitter: the indices of the class attributes still to process.
m_AttributeTypeLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel: Displays the type of attribute
m_AttributeTypes - Variable in class adams.flow.source.WekaNewInstances: the comma-separated list of attribute types.
m_AttributeX - Variable in class adams.flow.sink.WekaInstancesPlot: the attribute on the X axis.
m_AttributeX - Variable in class adams.flow.sink.WekaThresholdCurve: the attribute on the X axis.
m_AttributeX - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: the attribute on the X axis.
m_AttributeY - Variable in class adams.flow.sink.WekaInstancesPlot: the attribute on the Y axis.
m_AttributeY - Variable in class adams.flow.sink.WekaThresholdCurve: the attribute on the Y axis.
m_AttributeY - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: the attribute on the Y axis.
m_AttType - Variable in class adams.flow.transformer.WekaInstancesMerge: the attribute type of the ID attribute.
m_AttValues - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp
m_Augmentations - Variable in class adams.core.management.WekaPackagesClassPathAugmenter: for storing the augmentations.
m_AutoKeyGeneration - Variable in class adams.flow.sink.WekaDatabaseWriter: whether to automatically generate a primary key.
m_Average - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: the calculated averages.
m_AverageSpacing - Variable in class weka.filters.unsupervised.attribute.EquiDistance: the average spacing.
m_AverageWidth - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval: the average width.
m_avg_target - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: The training data.
m_avg_target - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: The training data.
m_avg_target - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: The training data.
m_avg_target - Variable in class weka.classifiers.functions.GPD: The training data.
m_AxisX - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: the options for the X axis.
m_AxisY - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: the options for the Y axis.
m_B - Variable in class adams.data.instancesanalysis.pls.SIMPLS: the B matrix (used for prediction)
m_b_hat - Variable in class adams.data.instancesanalysis.pls.PLS1: the b-hat vector
m_BackupModel - Variable in class weka.classifiers.meta.SubsetEnsemble: The backup classifier, in case no ensemble could be constructed at prediction time.
m_BackupModel - Variable in class weka.classifiers.meta.VotedImbalance: The backup classifier, in case no ensemble could be constructed at prediction time.
m_barRange - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Contains the range of each bar in a histogram.
m_Base - Variable in class adams.data.instancesanalysis.pls.OPLS: the base PLS algorithm.
m_Base - Variable in class weka.classifiers.meta.Fallback: the base classifier.
m_BaseScore - Variable in class weka.classifiers.trees.XGBoost: Global bias.
m_BatchSize - Variable in class weka.classifiers.functions.PyroProxy: the batch size.
m_bestClassifier - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_bestClassifier - Variable in class weka.classifiers.meta.LeastMedianSq
m_BestClassifier - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: the best classifier.
m_bestMedian - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_bestMedian - Variable in class weka.classifiers.meta.LeastMedianSq
m_BestRange - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: stores the best range of attribtues.
m_Bias - Variable in class weka.classifiers.meta.VotedImbalance: the bias for the dataset balancing (0 = distribution in input data -- 1 = uniform distribution).
m_BinCalculation - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges: how to calculate the number of bins.
m_BinnableGroups - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: the collapsed data.
m_BinnableGroups - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: the collapsed data.
m_bins - Variable in class weka.core.SAXDistance: number of gaussian bins.
m_bins - Variable in class weka.filters.unsupervised.attribute.SAX: number of gaussian bins.
m_BinWidth - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges: the bin width - used for some calculations.
m_bits - Variable in class adams.opt.optimise.genetic.PackDataDef.DataInfo
m_bits - Variable in class adams.opt.optimise.GeneticAlgorithm
m_BitsPerGene - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the bits per gene to use.
m_BitString - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
m_Blin - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive
m_Blin - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights
m_Blin - Variable in class weka.classifiers.functions.GaussianProcessesWeighted
m_Blin - Variable in class weka.classifiers.functions.GPD
m_Booster - Variable in class weka.classifiers.trees.XGBoost: The trained model.
m_BoosterType - Variable in class weka.classifiers.trees.XGBoost: The type of booster to use.
m_Border - Variable in class weka.experiment.ResultMatrixMediaWiki: the size of the border.
m_BorderTitle - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: the border title.
m_bps - Variable in class weka.filters.unsupervised.attribute.SAX: breakpoints.
m_Buffer - Variable in class adams.flow.transformer.WekaInstanceBuffer: the currently buffered data.
m_Buffer - Variable in class adams.flow.transformer.WekaInstanceDumper: the buffer.
m_BufferSize - Variable in class adams.flow.transformer.WekaInstanceDumper: the size of the buffer.
m_BuildWait - Variable in class weka.classifiers.functions.FakeClassifier: the build wait time in msec.
m_Built - Variable in class weka.classifiers.meta.AbstainingCascade: whether the models got built.
m_ButtonAction - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: the action button.
m_ButtonActivate - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: the button for activating a dataset.
m_ButtonAdd - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: the button for adding classifiers.
m_ButtonAdd - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: the button for adding files.
m_ButtonAdd - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: the button for a new sort definition.
m_ButtonAdd - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: the button for bringing up the filechooser.
m_ButtonAdd - Variable in class weka.gui.explorer.MultiExplorer: the button for adding a panel.
m_ButtonAll - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: to select all attributes
m_ButtonAnalyze - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the analyze button.
m_ButtonCancel - Variable in class adams.gui.goe.WekaExperimentFileEditor: the Cancel button.
m_ButtonCancel - Variable in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog: the Cancel button.
m_ButtonClear - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: the clear button.
m_ButtonClear - Variable in class adams.gui.tools.wekamultiexperimenter.LogPanel: the button for clearing the log.
m_ButtonClose - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the Close button.
m_ButtonCodeOutputCopy - Variable in class adams.gui.tools.WekaOptionsConversionPanel: the button for copying the code output.
m_ButtonCodeOutputPaste - Variable in class adams.gui.tools.WekaOptionsConversionPanel: the button for pasting the code output.
m_ButtonConvert - Variable in class adams.gui.tools.WekaOptionsConversionPanel: the button initiating the conversion.
m_ButtonCopy - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel: the copy button.
m_ButtonCopy - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel: the copy button.
m_ButtonCopy - Variable in class weka.gui.explorer.MultiExplorer: the button for copying a panel.
m_ButtonCredentials - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel: the button for bringing up the dialog for the user credentials.
m_ButtonData - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the button for comparing the data.
m_ButtonDataGo - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the button for displaying the instances.
m_ButtonDisplay - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: the button for displaying the dataset.
m_ButtonDown - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: the down button.
m_ButtonDown - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: the button for moving classifiers down.
m_ButtonDown - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: the button for moving files down.
m_ButtonEdit - Variable in class adams.gui.goe.WekaExperimentFileEditor: the button to bring up the dialog for editing the experiment.
m_ButtonEdit - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: the button for editing a classifier.
m_ButtonEdit - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: the button for changing files.
m_ButtonEdit - Variable in class weka.gui.explorer.ExplorerExt: the edit button of the preprocess panel.
m_ButtonExecute - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: the execute button.
m_ButtonHelp - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: the help button.
m_ButtonHistory - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: the button for the history.
m_ButtonInputCopy - Variable in class adams.gui.tools.WekaOptionsConversionPanel: the button for copying the input.
m_ButtonInputPaste - Variable in class adams.gui.tools.WekaOptionsConversionPanel: the button for pasting the input.
m_ButtonInvert - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: to invert the current selection
m_ButtonLoad - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the Load button.
m_ButtonLoad - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage: the load props button.
m_ButtonLoad - Variable in class weka.gui.explorer.SqlPanel: the Load button
m_ButtonMoveDown - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: the move down button.
m_ButtonMoveDown - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: the button for moving the selected files down.
m_ButtonMoveUp - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: the move up button.
m_ButtonMoveUp - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: the button for moving the selected files up.
m_ButtonNone - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: to deselect all attributes
m_ButtonOK - Variable in class adams.gui.goe.WekaExperimentFileEditor: the OK button.
m_ButtonOK - Variable in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog: the OK button.
m_ButtonOutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the button for editing the output generators.
m_ButtonOutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the button for editing the output generators.
m_ButtonOutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the button for editing the output generators.
m_ButtonOutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the button for editing the output generators.
m_ButtonOutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the button for editing the output generators.
m_ButtonOutputGeneratorsFavorites - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the button for the output generator favorites.
m_ButtonOutputGeneratorsFavorites - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the button for the output generator favorites.
m_ButtonOutputGeneratorsFavorites - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the button for the output generator favorites.
m_ButtonOutputGeneratorsFavorites - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the button for the output generator favorites.
m_ButtonOutputGeneratorsFavorites - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the button for the output generator favorites.
m_ButtonPattern - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: for entering a regular expression for selection
m_ButtonReload - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the button for reloading an existing file.
m_ButtonRemove - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: the button for removing a dataset.
m_ButtonRemove - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: the button for removing classifiers.
m_ButtonRemove - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: the button for removing files.
m_ButtonRemove - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: the remove button.
m_ButtonRemove - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: the button for removing the selected files.
m_ButtonRemove - Variable in class weka.gui.explorer.MultiExplorer: the button for removing a panel.
m_ButtonRemoveAll - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: the button for removing all classifiers.
m_ButtonRemoveAll - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: the button for removing all files.
m_ButtonRemoveAll - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: the button for removing all files.
m_ButtonReset - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: the button for resetting the definitions.
m_ButtonSave - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: the save button.
m_ButtonSave - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: the save button.
m_ButtonSave - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel: the save button.
m_ButtonSave - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel: the save button.
m_ButtonSave - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage: the save props button.
m_ButtonSelectedAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the button for copying the selected attributes range.
m_ButtonSelectedAttributesAction - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: button for removing checked attributes.
m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the start button.
m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the start button.
m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the start button.
m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the start button.
m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the start button.
m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the button to start PCA.
m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the button to start PLS.
m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the button for starting the filtering.
m_ButtonStart - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the button to start PCA.
m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the stop button.
m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the stop button.
m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the stop button.
m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the stop button.
m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the stop button.
m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the button to stop PCA.
m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the button to stop PLS.
m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the button for stop the filtering.
m_ButtonStop - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the button to stop PCA.
m_ButtonStructure - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the button for comparing the structure.
m_ButtonTextGo - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the button for displaying the instances.
m_ButtonUndo - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: the button for undoing changes.
m_ButtonUndo - Variable in class weka.gui.explorer.ExplorerExt: the undo button of the preprocess panel.
m_ButtonUp - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: the up button.
m_ButtonUp - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: the button for moving classifiers up.
m_ButtonUp - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: the button for moving files up.
m_ButtonVisualize - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the button for visualizing.
m_ButtonWorkspace - Variable in class weka.gui.explorer.MultiExplorer: the button for managing the workspaces.
m_C - Variable in class adams.data.instancesanalysis.pls.PRM: Tuning parameter.
m_C - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: The covariance matrix.
m_CallableActor - Variable in class adams.flow.source.WekaSelectDataset: the callable actor.
m_CallableActor - Variable in class adams.flow.transformer.WekaGeneticAlgorithm: the callable actor.
m_CallableName - Variable in class adams.flow.transformer.WekaGeneticAlgorithm: the callable name.
m_CanAbstain - Variable in class weka.classifiers.lazy.AbstainingLWL: whether the base classifier can abstain.
m_CanAbstain - Variable in class weka.classifiers.meta.AbstainingClassifierWrapper: whether the base classifier can abstain.
m_CanAbstain - Variable in class weka.classifiers.meta.FilteredClassifierExt: whether the base classifier can abstain.
m_CanAbstain - Variable in class weka.classifiers.meta.MinMaxLimits: whether the base classifier can abstain.
m_CanAbstain - Variable in class weka.classifiers.meta.ThreadSafeClassifierWrapper: whether the base classifier can abstain.
m_CancelListener - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the listener waiting for the user to cancel the dialog.
m_canopyClusters - Variable in class weka.clusterers.SAXKMeans: The canopy clusterer (if being used)
m_Capabilities - Variable in class adams.flow.condition.bool.AbstractAttributeCapabilities: the class index.
m_Cascade - Variable in class weka.classifiers.meta.ClassifierCascade: the cascade.
m_CellPadding - Variable in class weka.experiment.ResultMatrixMediaWiki: the cell padding.
m_CellPopupMenuCustomizer - Variable in class adams.gui.visualization.instances.InstancesTable: the customizer for the table cells popup menu.
m_CellRenderingCustomizer - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: for highlighting the cells in the table.
m_CellSpacing - Variable in class weka.experiment.ResultMatrixMediaWiki: the cell spacing.
m_centerFilter - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Filter for centering the data
m_centroidCanopyAssignments - Variable in class weka.clusterers.SAXKMeans: Canopies that each centroid falls into (determined by T1 radius)
m_CEPanel - Variable in class weka.gui.explorer.ExperimentPanel: The panel showing the current classifier selection.
m_ChangeListeners - Variable in class adams.gui.goe.WekaGenericObjectEditorPopupMenu: listeners that get notified when the user changes the setup.
m_ChangeListeners - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: the change listeners.
m_ChangeListeners - Variable in class adams.gui.visualization.instances.InstancesTable: the listeners for changes.
m_CharSet - Variable in class adams.flow.transformer.WekaTextDirectoryReader: the character set.
m_CheckBoxAntiAliasing - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: whether to use anti-aliasing.
m_CheckBoxBatchFilter - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the checkbox for batch-filtering.
m_CheckBoxCustomSplitGenerator - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: whether to use a custom split generator.
m_CheckBoxDiscardPredictions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: whether to discard the predictions.
m_CheckBoxDiscardPredictions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: whether to discard the predictions.
m_CheckBoxDiscardPredictions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: whether to discard the predictions.
m_CheckBoxDiscardPredictions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: whether to discard the predictions.
m_CheckBoxDiscardPredictions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: whether to discard the predictions.
m_CheckBoxFinalModel - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: whether to produce a final model.
m_CheckBoxIncludeDateAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: whether to include date attributes.
m_CheckBoxIncludeNominalAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: whether to include numeric nominal.
m_CheckBoxIncludeNumericAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: whether to include numeric attributes.
m_CheckBoxIncludeRelationalAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: whether to include relational attributes.
m_CheckBoxIncludeStringAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: whether to include string attributes.
m_CheckBoxKeepName - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the whether to keep the relation name.
m_CheckBoxLenient - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: whether to be lenient with checks.
m_CheckBoxMarkers - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: whether to use markers.
m_CheckBoxPerFoldOutput - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: whether to use separate evaluations per fold.
m_CheckBoxPreserveOrder - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: whether to preserve the order.
m_CheckBoxPreserveOrder - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: whether to preserve the order.
m_CheckBoxPreserveOrder - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: whether to preserve the order.
m_CheckBoxPreserveOrder - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: whether to preserve the order.
m_CheckBoxPreserveOrder - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: whether to preserve the order.
m_CheckBoxReplace - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the checkbox to replace the datasets.
m_CheckBoxSerialize - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the whether to serialize the filter to a file.
m_CheckBoxSkipNominal - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: whether to skip nominal attributes.
m_CheckBoxSwapRowsColumns - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: for swapping rows/columns.
m_CheckBoxUseViews - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: whether to use views.
m_CheckBoxUseViews - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: whether to use views.
m_CheckBoxUseViews - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: whether to use views.
m_CheckHeader - Variable in class adams.flow.transformer.WekaInstanceBuffer: whether to check the header.
m_CheckHeader - Variable in class adams.flow.transformer.WekaInstanceDumper: whether to check the header.
m_checksTurnedOff - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a numeric class.
m_checksTurnedOff - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a numeric class.
m_checksTurnedOff - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a numeric class.
m_checksTurnedOff - Variable in class weka.classifiers.functions.GPD: Turn off all checks and conversions? Turning them off assumes that data is purely numeric, doesn't contain any missing values, and has a numeric class.
m_checksTurnedOff - Variable in class weka.classifiers.functions.LinearRegressionJ: Turn off all checks and conversions?
m_ClassAttName - Variable in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: the class attribute name.
m_ClassAttribute - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: how to determine the class attribute.
m_ClassAttributeHeuristic - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the heuristic for selecting the class attribute.
m_ClassAttributeIndices - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: the class attribute indices.
m_ClassAttributes - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: the regular expression for identifying class attributes (besides an explicitly set one).
m_ClassAttributes - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: The set of class attributes for the given datasets.
m_ClassAttributes - Variable in class adams.flow.transformer.WekaMultiLabelSplitter: the indices of the class attributes.
m_ClassCombo - Variable in class weka.gui.explorer.ExperimentPanel: Lets the user select the class column.
m_ClassDetails - Variable in class adams.flow.transformer.WekaEvaluationSummary: whether to print the class details as well.
m_ClassDetails - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: whether to print the class details as well.
m_ClassDistribution - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions: the columns with the class distributions.
m_ClassDistribution - Variable in class weka.classifiers.functions.FromPredictions: the class distribution columns (if any).
m_ClassDistributionIndices - Variable in class weka.classifiers.functions.FromPredictions: the class distribution column indices.
m_ClassFilters - Variable in class weka.classifiers.meta.ClassificationViaRegressionD: The filters used to transform the class.
m_ClassFinder - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: The column finder for selecting class attributes.
m_ClassificationEntry - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: the entry to use for the numeric classification in the spreadsheet.
m_ClassificationLabelEntry - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: the entry to use for the classification label in the spreadsheet.
m_Classifier - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased: the IntervalEstimator to use.
m_Classifier - Variable in class adams.flow.source.WekaClassifierSetup: the weka classifier.
m_Classifier - Variable in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator: the name of the callable weka classifier.
m_Classifier - Variable in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: the name of the callable weka classifier.
m_Classifier - Variable in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: the name of the callable weka classifier.
m_Classifier - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: the classifier to evaluate.
m_Classifier - Variable in class adams.flow.transformer.WekaStreamEvaluator: the classifier to use.
m_Classifier - Variable in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob: the classifier to evaluate.
m_Classifier - Variable in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob: the classifier to train.
m_Classifier - Variable in class adams.flow.transformer.WekaTrainClassifier: the name of the callable weka classifier.
m_Classifier - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: the classifier to train.
m_Classifier - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: the classifier.
m_Classifier - Variable in class adams.ml.model.classification.WekaClassifier: the weka classifier to use.
m_Classifier - Variable in class adams.ml.model.regression.WekaRegressor: the weka classifier to use.
m_Classifier - Variable in class adams.multiprocess.WekaCrossValidationExecution: the classifier to evaluate.
m_Classifier - Variable in class adams.multiprocess.WekaCrossValidationJob: the classifier to evaluate.
m_Classifier - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the classifier to use.
m_Classifier - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: the classifier to use if no serialized model is given.
m_Classifier - Variable in class weka.filters.supervised.instance.RemoveOutliers: the classifier to use for evaluation.
m_ClassifierEditor - Variable in class weka.gui.explorer.ExperimentPanel: Lets the user configure the classifier.
m_Classifiers - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: the classifiers to evaluate.
m_Classifiers - Variable in class adams.multiprocess.WekaCrossValidationExecution: the separate classifiers.
m_Classifiers - Variable in class weka.classifiers.meta.ClassificationViaRegressionD: The classifiers.
m_Classifiers - Variable in class weka.classifiers.meta.SubsetEnsemble: the actual classifiers in use.
m_Classifiers - Variable in class weka.classifiers.meta.VotedImbalance: the actual classifiers in use.
m_ClassifierWeights - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
m_ClassifierWeights_string - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
m_classIndex - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Contains the current class index.
m_classIndex - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: The class index from the training data
m_classIndex - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: The class index from the training data
m_classIndex - Variable in class weka.classifiers.functions.GPD: The class index from the training data
m_classIndex - Variable in class weka.classifiers.meta.Corr
m_classIndex - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: The attribute to treat as the class for purposes of cleansing.
m_classIndex - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: The attribute to treat as the class for purposes of cleansing.
m_ClassIndex - Variable in class adams.flow.sink.WekaCostBenefitAnalysis: the index of the class label.
m_ClassIndex - Variable in class adams.flow.source.WekaNewInstances: the index for the class attribute, if any.
m_ClassIndex - Variable in class adams.flow.transformer.WekaBootstrapping: the index of the class label.
m_ClassIndex - Variable in class adams.flow.transformer.WekaClassSelector: the class index.
m_ClassIndex - Variable in class adams.flow.transformer.WekaEvaluationValuePicker: the index of the class label.
m_ClassIndex - Variable in class adams.flow.transformer.WekaEvaluationValues: the range of the class labels.
m_ClassIndex - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: the index of the class label.
m_ClassIndex - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis: the index of the class label.
m_ClassIndex - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: the index of the class label.
m_ClassIndex - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the class index.
m_ClassIndex - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: the class index.
m_ClassIndex - Variable in class weka.classifiers.functions.LinearRegressionJ: The index of the class attribute
m_ClassIndex - Variable in class weka.classifiers.meta.ClassifierCascade: the class index.
m_ClassIndex - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Class index.
m_ClassLabel - Variable in class adams.flow.transformer.WekaClassifierRanker: the class label (in case of class-specific measures).
m_ClassLabel - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: the class label index.
m_ClassLabelIndex - Variable in class adams.data.conversion.WekaEvaluationToCostCurve: the class label index.
m_ClassLabelIndex - Variable in class adams.data.conversion.WekaEvaluationToThresholdCurve: the class label index.
m_ClassLabelIndex - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: the class label index.
m_ClassLabelIndex - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: the class label index for per-class stats.
m_ClassLabelIndex - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: the class label index.
m_ClassLabelIndex - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the label index.
m_ClassLabelRange - Variable in class adams.flow.sink.WekaCostCurve: the class label range.
m_ClassLabelRange - Variable in class adams.flow.sink.WekaThresholdCurve: the class label indices.
m_ClassLabelRange - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve: the class label range.
m_ClassLabelRange - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: the class label indices.
m_ClassLabels - Variable in class weka.classifiers.AggregateEvaluations: the optional class labels.
m_ClassMean - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: the class mean.
m_ClassMean - Variable in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS: the class mean.
m_ClassMean - Variable in class weka.classifiers.functions.LinearRegressionJ: The mean of the class attribute
m_classMeanForMissing - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: The class mean for missing values
m_Classname - Variable in class adams.core.discovery.genetic.GenericDoubleResolution: the class name.
m_Classname - Variable in class adams.core.discovery.genetic.GenericFloatResolution: the class name.
m_Classname - Variable in class adams.core.discovery.genetic.GenericInteger: the class name.
m_Classname - Variable in class adams.core.discovery.genetic.GenericString: the class name.
m_Classname - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode: the classname to use.
m_ClassName - Variable in class adams.flow.source.WekaNewInstances: the name for the class attribute, if any.
m_ClassName - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: The class-attribute for supervised attribute filters.
m_ClassStdDev - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: the class stddev.
m_ClassStdDev - Variable in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS: the class stddev.
m_ClassStdDev - Variable in class weka.classifiers.functions.LinearRegressionJ: The standard deviations of the class attribute
m_ClassType - Variable in class adams.gui.goe.WekaGenericObjectEditorPanel: the class type.
m_Cleaner - Variable in class weka.core.tokenizers.PreCleanedTokenizer: the cleaner to use.
m_Cleaners - Variable in class weka.core.tokenizers.cleaners.MultiCleaner: the cleaners to use.
m_cleansingClassifier - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: The classifier used to do the cleansing
m_cleansingClassifier - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: The classifier used to do the cleansing
m_ClearBuffer - Variable in class adams.flow.transformer.WekaInstanceBuffer: whether to clear the buffer once it has been forwarded.
m_ClearBufferRequired - Variable in class adams.flow.transformer.WekaInstanceBuffer: whether variable triggered clear of buffer.
m_CloseParent - Variable in class adams.gui.tools.weka.AppendDatasetsPanel: whether to close parent.
m_CloseParent - Variable in class adams.gui.tools.weka.BatchFilterDatasetsPanel: whether to close parent.
m_ClusterCentroids - Variable in class weka.clusterers.SAXKMeans: holds the cluster centroids.
m_Clusterer - Variable in class adams.flow.source.WekaClustererSetup: the weka clusterer.
m_Clusterer - Variable in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator: the name of the callable weka clusterer.
m_Clusterer - Variable in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob: the clusterer to train.
m_Clusterer - Variable in class adams.flow.transformer.WekaTrainClusterer: the name of the callable weka clusterer.
m_Clusterer - Variable in class adams.ml.model.clustering.WekaClusterer: the weka classifier to use.
m_ClusterMissingCounts - Variable in class weka.clusterers.SAXKMeans
m_ClusterNominalCounts - Variable in class weka.clusterers.SAXKMeans: For each cluster, holds the frequency counts for the values of each nominal attribute.
m_ClusterSizes - Variable in class weka.clusterers.SAXKMeans: The number of instances in each cluster.
m_ClusterStdDevs - Variable in class weka.clusterers.SAXKMeans: Holds the standard deviations of the numeric attributes in each cluster.
m_Coefficients - Variable in class weka.classifiers.functions.LinearRegressionJ: Array for storing coefficients of linear regression.
m_Coefficients - Variable in class weka.core.WeightedEuclideanDistance: Array for storing coefficients of linear regression.
m_Coefficients - Variable in class weka.core.WeightedEuclideanDistanceRidge: Array for storing coefficients of linear regression.
m_Coefficients - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay: the calculated coefficients.
m_Coefficients - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay2: the calculated coefficients.
m_coeffs - Variable in class weka.classifiers.meta.Corr
m_ColIndex - Variable in class adams.ml.data.DataCellView: the column index.
m_ColName - Variable in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: the column with the name.
m_ColName - Variable in class adams.flow.transformer.wekapackagemanageraction.Uninstall: the column with the name.
m_Color - Variable in class adams.gui.visualization.instance.InstanceContainer: the associated color.
m_colorAttrib - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: This stores and lets the user select a class attribute.
m_ColorField - Variable in class adams.gui.visualization.instance.ReportColorInstancePaintlet: the report field to get the color from.
m_colorList - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Contains discrete colours for colouring of subbars of histograms and bar plots when the class attribute is set and is nominal
m_ColorProvider - Variable in class adams.flow.sink.WekaInstanceViewer: the color provider to use.
m_ColorProvider - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: the color provider to use.
m_ColorProvider - Static variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: the color provider.
m_ColorProvider - Variable in class adams.gui.visualization.instance.InstanceContainerManager: the color provider for managing the colors.
m_Column - Variable in class adams.flow.transformer.WekaExperimentEvaluation: the column (= classifiers).
m_Column - Variable in class adams.flow.transformer.WekaGetInstancesValue: the column index.
m_Column - Variable in class adams.flow.transformer.WekaSetInstancesValue: the column to update.
m_Column - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: the column (= classifiers).
m_Column - Variable in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer: the column index.
m_ColumnComboBox - Variable in class adams.gui.visualization.instances.InstancesPanel: for listing the column names.
m_ColumnFinder - Variable in class adams.data.weka.columnfinder.AbstractFilteredColumnFinder: the ColumnFinder to apply.
m_ColumnFinder - Variable in class adams.data.weka.datasetsplitter.ColumnSplitter: Column-finder for selecting which attributes go in which dataset.
m_ColumnFinder - Variable in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: The classifier template used to do the classification.
m_ColumnFinder - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: The column-finder which selects the attributes to summarise.
m_ColumnFinderTrained - Variable in class adams.data.weka.columnfinder.RowFilteredColumnFinder: whether the column finder was trained on the subset.
m_ColumnNames - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: the column names.
m_Columns - Variable in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: num columns
m_Columns - Variable in class adams.data.weka.columnfinder.Constant: The set of columns to find.
m_Columns - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
m_ColumnSampleByLevel - Variable in class weka.classifiers.trees.XGBoost: Subsample ratio of columns for each level.
m_ColumnSampleByNode - Variable in class weka.classifiers.trees.XGBoost: Subsample ratio of columns for each node (split).
m_ColumnSampleByTree - Variable in class weka.classifiers.trees.XGBoost: Subsample ratio of columns when constructing each tree.
m_ColumnSplitter - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Column-splitter for separating attributes to be summarised.
m_ColVersion - Variable in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: the column with the version.
m_Combination - Variable in class adams.data.weka.columnfinder.MultiColumnFinder: how the indices are combined.
m_Combination - Variable in class adams.data.weka.rowfinder.MultiRowFinder: how the indices are combined.
m_Combination - Variable in class weka.classifiers.meta.ClassifierCascade: how to combine the statistics.
m_CombinationRule - Variable in class weka.classifiers.meta.AbstainVote: Combination Rule variable
m_CombinationRule - Variable in class weka.classifiers.meta.SubsetEnsemble: Combination Rule variable.
m_CombinationRule - Variable in class weka.classifiers.meta.VotedImbalance: Combination Rule variable.
m_ComboBoxClass - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: the class attribute.
m_ComboBoxClass - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the class index.
m_ComboBoxClassificationRegression - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: classification or regression.
m_ComboBoxClassModel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the class index model.
m_ComboBoxColor - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the attribute to use for color.
m_ComboBoxData - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the combobox with all the datasets.
m_ComboBoxDataActions - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the combobox with all the actions.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the datasets.
m_ComboBoxDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the datasets.
m_ComboBoxEvaluation - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: the type of evaluation.
m_ComboBoxEvaluation - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: the type of evaluation.
m_ComboBoxEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the combobox with the available evaluations.
m_ComboBoxEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the combobox with the available evaluations.
m_ComboBoxEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the combobox with the available evaluations.
m_ComboBoxEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the combobox with the available evaluations.
m_ComboBoxFirstDataset - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the first dataset.
m_ComboBoxFirstID - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the ID attribute in the first dataset to use for comparing the data.
m_ComboBoxID - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the ID.
m_ComboBoxID - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the ID index.
m_ComboBoxIDModel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the ID index model.
m_ComboBoxMetric - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the combobox with the metric to evaluate.
m_ComboBoxNames - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: the combobox with column names.
m_ComboBoxOrder - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: how to traverse.
m_ComboBoxOutput - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel: the combobox listing all the output types.
m_ComboBoxPanels - Variable in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel: the combobox with all available panels.
m_ComboBoxResults - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the combobox with the results panels.
m_ComboBoxRowAttribute - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: the combobox with the attribute names.
m_ComboBoxRowAttributeModel - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: the underlying model for the comboxbox.
m_ComboBoxSecondDataset - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the second dataset.
m_ComboBoxSecondID - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the ID attribute in the second dataset to use for comparing the data.
m_ComboBoxSetups - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the combobox with the available setups.
m_ComboBoxSorting - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the sorting index.
m_ComboBoxSorting - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: the type of sorting.
m_ComboBoxSortingModel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the soriting index model.
m_ComboBoxTest - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: the test set.
m_ComboBoxTest - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: the test set.
m_ComboBoxTest - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: the test set.
m_ComboBoxTest - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: the test set.
m_ComboBoxTextActions - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the combobox with all the actions.
m_ComboBoxTextInstances - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the combobox with all the instances.
m_ComboBoxTrain - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: the train set.
m_ComboBoxTrain - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: the train set.
m_ComboBoxTrain - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: the train set.
m_ComboBoxTrain - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: the train set.
m_ComboBoxValidate - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: the validate set.
m_CommandLineHandler - Variable in class adams.flow.core.WekaPropertyValueConverter: the commandline handler to use.
m_CommandLineHandler - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: for handling commandlines.
m_Comment - Variable in class adams.flow.transformer.WekaClusterEvaluationSummary: an optional comment to output.
m_Comment - Variable in class adams.flow.transformer.WekaEvaluationSummary: an optional comment to output.
m_Communication - Variable in class weka.classifiers.functions.PyroProxy: the instance converter to use.
m_Comparator - Static variable in class adams.data.instance.Instance: the default comparator.
m_Comparator - Static variable in class adams.data.instance.InstanceUtils: comparator for finding X values.
m_Comparator - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions: the comparator to use.
m_Comparator - Variable in class weka.classifiers.AggregateEvaluations: the comparator to use.
m_ComparisonField - Variable in class adams.flow.transformer.WekaExperimentEvaluation: the comparison field.
m_ComparisonField - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: the comparison field.
m_completed - Variable in class weka.clusterers.SAXKMeans
m_Completed - Variable in class weka.classifiers.meta.SubsetEnsemble: The number of classifiers completed so far
m_Completed - Variable in class weka.classifiers.meta.VotedImbalance: The number of classifiers completed so far
m_CompleteRowsOnly - Variable in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Whether or not to skip IDs that don't exist in all source datasets.
m_ComplexityStatistics - Variable in class adams.flow.transformer.WekaEvaluationSummary: whether to print the complexity statistics as well.
m_ComplexityStatistics - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: whether to print the complexity statistics as well.
m_Component - Variable in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel: the actual component.
m_Component - Variable in class adams.gui.tools.wekainvestigator.output.TableContentPanel: the actual component.
m_Component - Variable in class adams.gui.tools.wekainvestigator.output.TextualContentPanel: the actual component.
m_ComponentRange - Variable in class weka.attributeSelection.AbstractPLSAttributeEval: for user defined range of components used.
m_Components - Variable in class adams.data.instancesanalysis.FastICA: the components.
m_ConfidenceLevel - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased: the confidence level.
m_Configured - Variable in class adams.flow.transformer.WekaGeneticAlgorithm: whether the callable actor has been configured.
m_ConfusionMatrix - Variable in class adams.flow.transformer.WekaEvaluationSummary: whether to print the confusion matrix as well.
m_ConfusionMatrix - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: whether to print the confusion matrix as well.
m_Container - Variable in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob: the model container.
m_Container - Variable in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob: the generated model container.
m_Containers - Variable in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: the generated containers.
m_Containers - Variable in class weka.classifiers.MultiLevelSplitGenerator: the list of generated containers.
m_Conversion - Variable in class weka.core.converters.SpreadSheetLoader: the conversion to use.
m_Converter - Variable in class adams.data.conversion.WekaCommandToCode: the converter to use.
m_CoordinatesPaintlet - Variable in class adams.gui.visualization.instance.InstancePanel: paintlet for drawing the X-axis.
m_Correct - Variable in class weka.filters.unsupervised.attribute.SpellChecker: the correct spelling for the labels.
m_Correction - Variable in class weka.filters.unsupervised.attribute.Detrend: the correction to use.
m_Correction - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: the correction to use.
m_Correction - Variable in class weka.filters.unsupervised.attribute.SimpleDetrend: the correction to use.
m_Correlation - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Correlation matrix for the original data.
m_CostBenefitPanel - Variable in class adams.flow.sink.WekaCostBenefitAnalysis: the panel.
m_Counter - Variable in class adams.flow.transformer.WekaInstanceDumper: the counter for the filenames.
m_Counter - Variable in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: the counter for the X value of the containers.
m_CoverVariance - Variable in class adams.flow.transformer.WekaPrincipalComponents: the variance to cover.
m_CoverVariance - Variable in class weka.core.neighboursearch.PCANNSearch: the amount of varaince to cover in the original data when retaining the best n PC's.
m_CoverVariance - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: the amount of varaince to cover in the original data when retaining the best n PC's.
m_CreateView - Variable in class adams.flow.transformer.WekaCrossValidationSplit: whether to create a view only.
m_CreateView - Variable in class adams.flow.transformer.WekaRandomSplit: whether to create a view only.
m_CrossValidation - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator: for performing cross-validation.
m_CrossValidation - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: for performing cross-validation.
m_CrossValidation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: performs the actual evaluation.
m_CrossValidation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: performs the actual evaluation.
m_CrossValidation - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment.CrossValidationExperimentJob: for executing the cross-validation.
m_CrossValidationSeed - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the cross-validation seed.
m_CrossValidationSeed - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: the cross-validation seed.
m_cs - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_Current - Variable in class adams.flow.transformer.WekaStreamEvaluator: the current counter of instances.
m_Current - Variable in class adams.gui.goe.WekaGenericArrayEditorDialog: the current object.
m_Current - Variable in class adams.gui.goe.WekaGenericArrayEditorPanel: the current value.
m_Current - Variable in class adams.gui.goe.WekaGenericObjectEditorDialog: the current object.
m_Current - Variable in class adams.gui.goe.WekaGenericObjectEditorPanel: the current object.
m_Current - Variable in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard: the current algorithm.
m_CurrentAssociator - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the current associator.
m_CurrentBoxPlot - Variable in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab: the current boxplot.
m_currentClassifier - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_currentClassifier - Variable in class weka.classifiers.meta.LeastMedianSq
m_CurrentClassifier - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the current classifier.
m_CurrentClassifier - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the current classifier.
m_CurrentClassifier - Variable in class weka.classifiers.evaluation.StoppableEvaluation: the current classifier that is being evaluated.
m_CurrentClusterer - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the current clusterer.
m_CurrentEvaluation - Variable in class adams.flow.transformer.WekaTestSetEvaluator: the current evaluation.
m_CurrentEvaluation - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator: the current evaluation.
m_CurrentEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the current evaluation.
m_CurrentEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the current evaluation.
m_CurrentEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the current evaluation.
m_CurrentEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the current evaluation.
m_CurrentEvaluation - Variable in class adams.multiprocess.WekaCrossValidationExecution: the evaluation currently being run.
m_CurrentEvaluator - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the current evaluator.
m_CurrentFile - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the current file.
m_CurrentFile - Variable in class weka.gui.explorer.ExplorerExt: the current file.
m_CurrentFiles - Variable in class adams.gui.tools.DatasetCompatibilityPanel: the selected files.
m_CurrentFilter - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the current filter.
m_CurrentFold - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: the current fold.
m_CurrentFold - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator: the current fold.
m_CurrentFold - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: the current fold.
m_CurrentFold - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: the current fold.
m_CurrentFold - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: the current fold.
m_CurrentLoader - Variable in class adams.gui.tools.DatasetCompatibilityPanel: the current loader.
m_CurrentPair - Variable in class weka.classifiers.LeaveOneOutByValueGenerator: the current train/test pair to generate.
m_CurrentPanel - Variable in class adams.gui.tools.wekainvestigator.tab.DataTab: the currently displayed panel.
m_CurrentPanel - Variable in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab: the currently displayed panel.
m_CurrentSearch - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the current search.
m_CurrentSetup - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the current p.
m_CustomLoader - Variable in class adams.flow.transformer.WekaFileReader: the custom loader.
m_CustomLoader - Variable in class adams.flow.transformer.WekaReorderAttributesToReference: the custom loader.
m_CustomLoader - Variable in class weka.filters.unsupervised.instance.AlignDataset: the file loader to use for loading the reference data.
m_CustomLoader - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances: the file loader to use for loading the test set.
m_CustomPaintlet - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: the custom paintlet.
m_CustomPropsFile - Variable in class adams.flow.sink.WekaDatabaseWriter: a custom properties file to use instead of default one.
m_CustomPropsFile - Variable in class adams.flow.source.WekaDatabaseReader: a custom properties file to use instead of default one.
m_CustomSaver - Variable in class adams.flow.sink.WekaFileWriter: the custom saver.
m_CustomStopMessage - Variable in class adams.flow.source.WekaSelectDataset: the custom stop message to use if flow gets stopped due to cancelation.
m_CVR - Variable in class weka.classifiers.functions.ClassificationViaPLS: the ClassificationViaRegression used internally.
m_data - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: This holds the current set of instances
m_data - Variable in class adams.opt.optimise.genetic.PackData
m_data - Variable in class weka.classifiers.functions.GPD
m_data - Variable in class weka.classifiers.trees.RandomModelTrees
m_Data - Variable in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator: the data set to use for training and other bits.
m_Data - Variable in class adams.flow.source.WekaDatabaseReader: the full data.
m_Data - Variable in class adams.flow.transformer.WekaFilter.BatchFilterJob: the data to use for training.
m_Data - Variable in class adams.flow.transformer.WekaTrainAssociator.TrainJob: the data to use for training.
m_Data - Variable in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob: the data to use for training.
m_Data - Variable in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob: the data to use for training.
m_Data - Variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: the underlying data.
m_Data - Variable in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: the underlying data.
m_Data - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the data loaded.
m_Data - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: the dataset.
m_Data - Variable in class adams.gui.visualization.instance.InstanceTableModel: the underlying data.
m_Data - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: the instances that forms the basis for the sorting.
m_Data - Variable in class adams.gui.visualization.instances.InstancesTableModel: the data
m_Data - Variable in class adams.ml.data.InstancesHeaderRow: the underlying data.
m_Data - Variable in class adams.ml.data.InstancesView: the underlying data.
m_Data - Variable in class adams.ml.data.InstanceView: the underlying data.
m_Data - Variable in class adams.multiprocess.WekaCrossValidationExecution: the data to evaluate on.
m_Data - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: the data to use.
m_Data - Variable in class weka.classifiers.AbstractSplitGenerator: the original dataset.
m_Data - Variable in class weka.classifiers.meta.AbstainAttributePercentile
m_Data - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_Data - Variable in class weka.classifiers.meta.LeastMedianSq
m_Data - Variable in class weka.classifiers.meta.SubsetEnsemble: For holding the original training set temporarily.
m_Data - Variable in class weka.classifiers.meta.VotedImbalance: For holding the original training set temporarily.
m_Data - Variable in class weka.classifiers.trees.RandomRegressionForest: the original header
m_Data - Variable in class weka.core.AbstractHashableInstance: the wrapped instance.
m_Data - Variable in class weka.core.converters.SimpleArffLoader: the currently loaded data.
m_Data - Variable in class weka.core.converters.SpreadSheetLoader: the actual data.
m_Data - Variable in class weka.core.InstanceGrouping: the original data.
m_Data1 - Variable in class adams.tools.CompareDatasets: the current dataset 1.
m_Data2 - Variable in class adams.tools.CompareDatasets: the current dataset 2.
m_DatabaseConnection - Variable in class adams.data.instances.AbstractInstanceGenerator: the database connection.
m_DataGenerated - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: whether data was generated.
m_DataGenerator - Variable in class adams.flow.source.WekaDataGenerator: the filter to apply.
m_dataPointCanopyAssignments - Variable in class weka.clusterers.SAXKMeans: Canopies that each training instance falls into (determined by T1 radius)
m_DataRowType - Variable in class adams.data.conversion.WekaInstancesToSpreadSheet: the data row type to use.
m_Dataset - Variable in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader: the header to match against.
m_Dataset - Variable in class adams.flow.transformer.WekaMultiLabelSplitter: the dataset to process.
m_Dataset - Variable in class adams.flow.transformer.WekaStoreInstance: the dataset to append to.
m_Dataset - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: the dataset in use.
m_Dataset - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: the dataset in use.
m_Dataset - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: the underlying dataset.
m_Dataset - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: the filename of the data to use for cross-validation.
m_Dataset - Variable in class weka.core.InstancesView: the underlying dataset.
m_Dataset1 - Variable in class adams.tools.CompareDatasets: the first dataset.
m_Dataset2 - Variable in class adams.tools.CompareDatasets: the second dataset.
m_DatasetFileChooser - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: the file chooser for models.
m_DatasetHeader - Variable in class adams.data.instance.Instance: a reference to the dataset the data was obtained from.
m_DatasetInfo - Variable in class adams.ml.model.classification.WekaClassificationModel: the dataset info.
m_DatasetInfo - Variable in class adams.ml.model.clustering.WekaClusteringModel: the dataset info.
m_DatasetInfo - Variable in class adams.ml.model.regression.WekaRegressionModel: the dataset info.
m_DatasetNames - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: The name of each dataset to use in attribute renaming.
m_Datasets - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: The source datasets we are merging.
m_Datasets - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: the datasets to evaluate.
m_DatasetTmpFile - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: the dataset's tmp file.
m_DatasetTmpFile - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: the dataset's tmp file.
m_DataType - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges: the type of data to get from the Instances object (rows or columns).
m_DataType - Variable in class adams.flow.transformer.WekaInstancesStatistic: the type of data to get from the Instances object (rows or columns).
m_DateFormat - Variable in class adams.flow.transformer.WekaInstancesInfo: for formatting dates.
m_debug - Variable in class weka.classifiers.meta.AbstainAttributePercentile
m_debug - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_debug - Variable in class weka.classifiers.meta.LeastMedianSq
m_Debug - Variable in class weka.core.converters.SpreadSheetLoader: whether to print some debug information
m_Debug - Variable in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin: whether to output debugging information.
m_Default - Variable in class adams.gui.goe.WekaGenericArrayEditorPanel: the default value.
m_DefaultAttributeRange - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the default range.
m_DefaultClassIndex - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the default class index.
m_DefaultColor - Variable in class adams.gui.visualization.instance.ReportColorInstancePaintlet: the default color to use if no color found in report.
m_defaultColors - Static variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: default colour list
m_DefaultDataTableHeight - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: the default data table height.
m_DefaultIDIndex - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the default ID index.
m_DefaultIncludeDateAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the default for date attributes.
m_DefaultIncludeNominalAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the default for nominal attributes.
m_DefaultIncludeNumericAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the default for numeric attributes.
m_DefaultIncludeRelationalAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the default for relational attributes.
m_DefaultIncludeStringAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the default for string attributes.
m_DefaultSortIndex - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the default sort index.
m_DeflationMode - Variable in class adams.data.instancesanalysis.pls.NIPALS: X and Y deflation Mode
m_delta - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: Gaussian Noise Value.
m_delta - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: Gaussian Noise Value.
m_delta - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: Gaussian Noise Value.
m_delta - Variable in class weka.classifiers.functions.GPD: Gaussian Noise Value.
m_deltaClass - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: Gaussian Noise Value for class.
m_deltaSquared - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: The squared noise value.
m_DerivativeOrder - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay: the order of the derivative.
m_DerivativeOrder - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay2: the order of the derivative.
m_Detector - Variable in class weka.filters.supervised.instance.RemoveOutliers: the outlier detector to use.
m_df - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Degrees of freedom, used in statistical calculations
m_Dialog - Variable in class adams.flow.source.WekaSelectObjects: the dialog for selecting the objects.
m_Dialog - Variable in class adams.gui.goe.WekaGenericArrayEditorPanel: the dialog for displaying the editor.
m_Dialog - Variable in class adams.gui.goe.WekaGenericObjectEditorPanel: the dialog for displaying the editor.
m_Dialog - Variable in class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns: the dialog for exporting.
m_DialogColorProvider - Variable in class adams.gui.visualization.instance.InstanceExplorer: the dialog for selecting the color provider.
m_DialogPaintlet - Variable in class adams.gui.visualization.instance.InstanceExplorer: the dialog for selecting the paintlet.
m_Diameter - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: the diameter of the cross.
m_Differ - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes: how to handle differing values.
m_Differ - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: how to handle differing values.
m_DIPLS - Variable in class adams.data.instancesanalysis.pls.DIPLS: the actual algorithm.
m_DiscardPredictions - Variable in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator: whether to discard predictions.
m_DiscardPredictions - Variable in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: whether to discard predictions.
m_DiscardPredictions - Variable in class adams.flow.transformer.WekaTestSetEvaluator: whether to discard predictions.
m_DiscardPredictions - Variable in class adams.multiprocess.WekaCrossValidationExecution: whether to discard predictions.
m_DiscardPredictions - Variable in class adams.multiprocess.WekaCrossValidationJob: whether to discard the predictions.
m_displayCurrentAttribute - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel
m_displayStdDevs - Variable in class weka.clusterers.SAXKMeans: Display standard deviations for numeric atts.
m_DistanceFunction - Variable in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient: the distance function to use.
m_DistanceFunction - Variable in class weka.clusterers.SAXKMeans: the distance function used.
m_Distances - Variable in class weka.core.neighboursearch.NewNNSearch: Array holding the distances of the nearest neighbours.
m_DistinctLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel: Displays the number of distinct values
m_distMatrix - Variable in class weka.core.SAXDistance
m_DistributionFormat - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: the format to use for the distribution entries in the spreadsheet.
m_DistributionSorting - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: the type of sorting to apply to the distribution array (if applicable).
m_doneCurrentAttribute - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel
m_dontReplaceMissing - Variable in class weka.clusterers.SAXKMeans: Replace missing values globally?
m_DropAbove - Variable in class weka.filters.unsupervised.instance.RemoveWithWeights: the threshold of weight above which to drop instances.
m_DropAtMost - Variable in class weka.filters.unsupervised.instance.WeightsBasedResample: the maximum percentage (0-1) of instances to drop.
m_DropBelow - Variable in class weka.filters.unsupervised.instance.RemoveWithWeights: the threshold of weight below which to drop instances.
m_DropBelow - Variable in class weka.filters.unsupervised.instance.WeightsBasedResample: the threshold of weight below which to drop instances.
m_DropNonClassYs - Variable in class weka.filters.supervised.attribute.MultiPLS: whether to keep Ys that are not the class or not.
m_Editor - Variable in class adams.gui.goe.WekaGenericArrayEditorDialog: the underlying editor.
m_Editor - Variable in class adams.gui.goe.WekaGenericObjectEditorDialog: the underlying editor.
m_Editor - Variable in class adams.gui.goe.WekaGenericObjectEditorPanel: the generic object editor.
m_Eigenvalues - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Eigenvalues for the corresponding eigenvectors.
m_Eigenvectors - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Will hold the unordered linear transformations of the (normalized) original data.
m_EliminateColinearAttributes - Variable in class weka.classifiers.functions.LinearRegressionJ: Try to eliminate correlated attributes?
m_Encoding - Variable in class adams.data.io.input.NestedAdamsExperimentReader: the encoding to use.
m_Encoding - Variable in class weka.core.converters.SimpleArffLoader: the encoding to use.
m_Encoding - Variable in class weka.core.converters.SimpleArffSaver: the encoding to use.
m_Ensemble - Variable in class weka.classifiers.meta.VotedImbalance: the vote classifier in use.
m_EnsureEqualValues - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Whether to check attributes with multiple sources for equal values among those sources.
m_ErrorCalculation - Variable in class adams.flow.transformer.WekaBootstrapping: the error calculation.
m_ErrorScaler - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator: the scaler scheme to use.
m_ErrorScaler - Variable in class adams.flow.sink.WekaClassifierErrors: The scheme for scaling the errors.
m_errPct - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_errPct - Variable in class weka.classifiers.meta.LeastMedianSq
m_Eta - Variable in class weka.classifiers.trees.XGBoost: The eta value (learning rate).
m_EvalCombo - Variable in class weka.gui.explorer.ExperimentPanel: The type of evaluation: cross-validation or random split.
m_Evaluation - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator: the underlying Evaluation object.
m_Evaluation - Variable in class adams.flow.transformer.WekaAggregateEvaluations: the current evaluation state.
m_Evaluation - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: the current evaluation.
m_Evaluation - Variable in class adams.flow.transformer.WekaStreamEvaluator: the evaluation to use.
m_Evaluation - Variable in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob: the evaluation object to use.
m_Evaluation - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: the evaluation object to use.
m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: the evaluation object.
m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: the current evaluation.
m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: the current evaluation.
m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: the current evaluation.
m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: the current evaluation.
m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: the evaluation object.
m_Evaluation - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: the evaluation object.
m_Evaluation - Variable in class adams.multiprocess.WekaCrossValidationExecution: the (aggregated) evaluation.
m_Evaluation - Variable in class adams.multiprocess.WekaCrossValidationJob: the evaluation.
m_EvaluationError - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: for storing evaluating errors.
m_EvaluationPostProcessor - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the postprocessor for the evaluation.
m_Evaluations - Variable in class adams.multiprocess.WekaCrossValidationExecution: the separate evaluations.
m_EvaluationType - Variable in class adams.flow.sink.WekaExperimentGenerator: the type of evaluation.
m_Evaluator - Variable in class adams.flow.transformer.WekaAttributeSelection: the evaluation.
m_Evaluator - Variable in class adams.flow.transformer.WekaInstanceEvaluator: the evaluator to use.
m_Evaluator - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: the evaluation algorithm.
m_ExactMatch - Variable in class adams.data.conversion.SwapPLS: whether to use an exact match (incl options) or just the class name.
m_ExcludeClass - Variable in class weka.core.AbstractHashableInstance: whether to exclude the class from the hashcode.
m_ExcludedAttributes - Variable in class adams.flow.transformer.WekaInstancesMerge: regular expression for excluding attributes from the datasets.
m_ExcludeWeight - Variable in class weka.core.AbstractHashableInstance: whether to exclude the weight from the hashcode.
m_executionSlots - Variable in class weka.clusterers.SAXKMeans: Number of threads to run
m_executorPool - Variable in class weka.clusterers.SAXKMeans: For parallel execution mode
m_ExecutorPool - Variable in class weka.classifiers.meta.SubsetEnsemble: Pool of threads to train models with
m_ExecutorPool - Variable in class weka.classifiers.meta.VotedImbalance: Pool of threads to train models with
m_Exp - Variable in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: the copy of the experiment.
m_Experiment - Variable in class adams.flow.source.WekaNewExperiment: the experiment.
m_Experiment - Variable in class adams.flow.transformer.WekaExperimentExecution: the current experiment.
m_Experiment - Variable in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog: the current experiment.
m_Experiment - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: the experiment container.
m_Experiment - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: the experiment.
m_Experiment - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: the experiment.
m_ExperimentFile - Variable in class adams.flow.transformer.WekaExperiment: the experiment file.
m_ExperimentIO - Variable in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: the handler for loading/saving experiments.
m_ExperimentType - Variable in class adams.flow.sink.WekaExperimentGenerator: the type of experiment.
m_Explorer - Variable in class weka.gui.explorer.ExperimentPanel: the parent frame.
m_Explorer - Variable in class weka.gui.explorer.SqlPanel: the parent frame
m_Expression - Variable in class weka.classifiers.functions.MathExpressionClassifier: the expression.
m_failed - Variable in class weka.clusterers.SAXKMeans
m_Failed - Variable in class weka.classifiers.meta.SubsetEnsemble: The number of classifiers that experienced a failure of some sort during construction.
m_Failed - Variable in class weka.classifiers.meta.VotedImbalance: The number of classifiers that experienced a failure of some sort during construction.
m_Fallback - Variable in class weka.classifiers.meta.Fallback: the fallback classifier.
m_FallBack - Variable in class weka.classifiers.functions.GPD: the fallback model.
m_FastDistanceCalc - Variable in class weka.clusterers.SAXKMeans: whether to use fast calculation of distances (using a cut-off).
m_FavorZeroes - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: whether to favor 0s instead of 1s.
m_FeatureSelector - Variable in class weka.classifiers.trees.XGBoost: Feature selection and ordering method.
m_ff - Variable in class adams.opt.optimise.GeneticAlgorithm.GAJob: fitness function.
m_Fields - Variable in class adams.data.conversion.ReportToWekaInstance: the fields to turn into an instance.
m_FileChooser - Variable in class adams.gui.chooser.DatasetFileChooserPanel: the filechooser for selecting the dataset.
m_FileChooser - Variable in class adams.gui.menu.BoundaryVisualizer: filechooser for BoundaryVisualizers.
m_FileChooser - Variable in class adams.gui.menu.CostCurve: filechooser for ROCs.
m_FileChooser - Variable in class adams.gui.menu.GraphVisualizer: filechooser for GraphVisualizers.
m_FileChooser - Variable in class adams.gui.menu.InstancesPlot: filechooser for Plots.
m_FileChooser - Variable in class adams.gui.menu.MarginCurve: filechooser for ROCs.
m_FileChooser - Variable in class adams.gui.menu.ROC: filechooser for ROCs.
m_FileChooser - Variable in class adams.gui.menu.TreeVisualizer: filechooser for TreeVisualizers.
m_FileChooser - Variable in class adams.gui.tools.DatasetCompatibilityPanel: the filechooser for selecting the datasets.
m_FileChooser - Variable in class adams.gui.tools.wekainvestigator.datatable.action.Save: the file chooser for exporting.
m_FileChooser - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the filechooser for datasets.
m_FileChooser - Variable in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu: the filechooser.
m_FileChooser - Variable in class adams.gui.tools.wekainvestigator.source.SpreadSheet: the filechooser.
m_FileChooser - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel: the filechooser for saving the output.
m_FileChooser - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel: the filechooser for saving the output.
m_FileChooser - Variable in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO: the filechooser for experiments.
m_FileChooser - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: the file chooser for selecting files.
m_FileChooser - Variable in class adams.gui.visualization.instance.InstancePanel: the file chooser for saving a specific sequence.
m_FileChooser - Variable in class adams.gui.visualization.instances.InstancesTable: the filechooser for exporting data.
m_FileChooser - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage: the filechooser for loading/saving properties.
m_FileChooser - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: the filechooser for selecting the files.
m_FileChooser - Variable in class weka.gui.explorer.ExplorerExt: The file chooser for selecting data files
m_FileChooserIDs - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the file saver for storing the IDs.
m_FileChooserParameters - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: the file chooser.
m_FileChooserResults - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the filechooser for loading/saving results.
m_FileChooserTitle - Variable in class adams.flow.source.WekaSelectDataset: the title of the file chooser dialog.
m_FilePanel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: for selecting the dataset file.
m_FileSerialize - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the file to serialize the trained filter to.
m_Filter - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: for centering the data
m_Filter - Variable in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS: for centering the data
m_Filter - Variable in class adams.data.spreadsheet.filter.WekaFilter: the filter to use.
m_Filter - Variable in class adams.data.weka.rowfinder.FilteredIQR: the IQR filter.
m_Filter - Variable in class adams.flow.transformer.WekaFilter.BatchFilterJob: the filter to use.
m_Filter - Variable in class adams.flow.transformer.WekaFilter: the filter to apply.
m_Filter - Variable in class adams.flow.transformer.WekaInstanceEvaluator: the filter that is used for generating the new data format.
m_Filter - Variable in class adams.flow.transformer.WekaStreamFilter: the filter to apply.
m_Filter - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: The filter used to standardize/normalize all values.
m_Filter - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: The filter used to standardize/normalize all values.
m_Filter - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: The filter used to standardize/normalize all values.
m_Filter - Variable in class weka.classifiers.functions.GPD: The filter used to standardize/normalize all values.
m_Filter - Variable in class weka.classifiers.functions.PLSClassifierWeighted: the PLS filter
m_Filter - Variable in class weka.classifiers.functions.PLSWeighted: the actual filter to use
m_Filter - Variable in class weka.core.neighboursearch.FilteredSearch: The filter
m_Filter - Variable in class weka.filters.unsupervised.attribute.FastWavelet: an optional filter for preprocessing of the data.
m_filtered - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter
m_FilteredData - Variable in class adams.flow.transformer.WekaFilter.BatchFilterJob: the filtered data.
m_Filters - Variable in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: The filters.
m_Filters - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: The filters.
m_filterType - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: Whether to normalize/standardize/neither
m_filterType - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: Whether to normalize/standardize/neither
m_filterType - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: Whether to normalize/standardize/neither
m_filterType - Variable in class weka.classifiers.functions.GPD: Whether to normalize/standardize/neither
m_FinalModel - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator: whether to create a final model.
m_Find - Variable in class adams.flow.transformer.WekaRenameRelation: the string to find.
m_Find - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric: the regular expression to use.
m_Finders - Variable in class adams.data.weka.columnfinder.MultiColumnFinder: the column finders to use.
m_Finders - Variable in class adams.data.weka.rowfinder.MultiRowFinder: the row finders to use.
m_First - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis: the positions of the first range.
m_FirstAdd - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: whether this is the first time a dataset gets added.
m_FirstAttribute - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: the name of the first attribute.
m_FirstAttributeRange - Variable in class adams.gui.InstanceCompare: the first attribute range to use.
m_FirstAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the first set of attributes.
m_firstBatchFinished - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Have we processed the first batch (i.e.
m_firstBatchFinished - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Have we processed the first batch (i.e.
m_FirstData - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the first dataset.
m_FirstFile - Variable in class adams.gui.InstanceCompare: the first file to compare.
m_FirstRange - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis: the first range of the attributes to use.
m_FirstRowIndex - Variable in class adams.gui.InstanceCompare: the index of the first attribute to use for matching rows.
m_fitness - Variable in class adams.opt.optimise.GeneticAlgorithm.GAJob
m_Fitness - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: the fitness of the genes.
m_fitnessfn - Variable in class adams.opt.optimise.GeneticAlgorithm
m_FlowContext - Variable in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction: the flow context.
m_FlowContext - Variable in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction: the flow context.
m_FlowContext - Variable in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction: the flow context.
m_FlowContext - Variable in class adams.multiprocess.WekaCrossValidationExecution: the flow context.
m_FlowContext - Variable in class adams.multiprocess.WekaCrossValidationJob: the flow context.
m_FlowContext - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the flow context.
m_FlowContext - Variable in class weka.classifiers.functions.PyroProxy: the flow context.
m_FlowContextUpdated - Variable in class adams.flow.transformer.WekaFilter: whether the flow context has been updated.
m_FlowFile - Variable in class weka.filters.FlowFilter: the flow file to process the data with.
m_fm - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Fontmetrics used to get the font size which is required for calculating displayable area size, bar height ratio and width of strings that are displayed on top of bars indicating their count.
m_Fold - Variable in class adams.multiprocess.WekaCrossValidationJob: the fold.
m_FoldEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: the evaluation objects from the folds.
m_FoldModels - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: the fold models.
m_FoldPairs - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: the temporary pairs.
m_FoldPairs - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator: the temporary pairs.
m_FoldPairs - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: the temporary pairs.
m_FoldPairs - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: the temporary pairs.
m_FoldPairs - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: the temporary pairs.
m_Folds - Variable in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator: the number of folds for cross-validation.
m_Folds - Variable in class adams.flow.sink.WekaExperimentGenerator: the number of folds to use (only cross-validation).
m_Folds - Variable in class adams.flow.transformer.WekaAttributeSelection: the number of folds.
m_Folds - Variable in class adams.flow.transformer.WekaClassifierRanker: the number of folds to use in cross-validation.
m_Folds - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: the number of folds to use.
m_Folds - Variable in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: the number of folds.
m_Folds - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator: the number of folds.
m_Folds - Variable in class adams.flow.transformer.WekaCrossValidationSplit: the number of folds to generate.
m_Folds - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: the number of folds.
m_Folds - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: the number of folds (in case of cross-validation).
m_Folds - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: the number of folds.
m_Folds - Variable in class adams.multiprocess.WekaCrossValidationExecution: the number of folds.
m_Folds - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: the cross-validation folds.
m_Folds - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the number of folds for cross-validation.
m_Folds - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: the number of folds for cross-validation.
m_FoldsPercLabel - Variable in class weka.gui.explorer.ExperimentPanel: The label for either the number of folds or the percentage for the random split.
m_FoldsPercText - Variable in class weka.gui.explorer.ExperimentPanel: Either the number of folds or the percentage for the random split.
m_ForceCompression - Variable in class weka.core.converters.SimpleArffLoader: whether to force compression.
m_Format - Variable in class weka.filters.unsupervised.attribute.StringToDate: the parse format.
m_Formatter - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the formatter for the history entries.
m_fstat - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: F-statistic for the regression
m_Full - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: the full dataset.
m_FullFilter - Variable in class adams.data.weka.rowfinder.FilteredIQR: the MultiFilter doing all the filtering.
m_FullMeansOrMediansOrModes - Variable in class weka.clusterers.SAXKMeans: Stats on the full data set for comparison purposes.
m_FullMissingCounts - Variable in class weka.clusterers.SAXKMeans
m_FullNominalCounts - Variable in class weka.clusterers.SAXKMeans
m_FullStdDevs - Variable in class weka.clusterers.SAXKMeans
m_ga - Variable in class adams.opt.optimise.GeneticAlgorithm.GAJob: ga.
m_gamma - Variable in class weka.classifiers.functions.GPD
m_Gamma - Variable in class weka.classifiers.trees.XGBoost: The gamma value (minimum split loss).
m_Generated - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: the results generated by the evaluations.
m_Generated - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: whether the split was generated.
m_Generated - Variable in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: whether the split was generated.
m_Generated - Variable in class weka.classifiers.DefaultRandomSplitGenerator: whether the split was generated.
m_Generated - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: whether the split was generated.
m_Generated - Variable in class weka.classifiers.GroupedRandomSplitGenerator: whether the split was generated.
m_GenerateLine - Variable in class adams.data.baseline.AbstractLinearRegressionBased: whether to return the line as fake data or the corrected data.
m_Generator - Variable in class adams.flow.source.AbstractWekaSetupGenerator: the underlying setup generator.
m_Generator - Variable in class adams.flow.transformer.AbstractInstanceGenerator: the generator to use.
m_Generator - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator: the fold generator.
m_Generator - Variable in class adams.flow.transformer.WekaCrossValidationSplit: the fold generator.
m_Generator - Variable in class adams.flow.transformer.WekaEnsembleGenerator: the generator to use.
m_Generator - Variable in class adams.flow.transformer.WekaRandomSplit: the split generator to use.
m_Generator - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: the fold generator.
m_Generator - Variable in class adams.flow.transformer.WekaSplitGenerator: the split generator to use.
m_Generator - Variable in class adams.gui.tools.wekainvestigator.data.DataGeneratorContainer: the generator used to load the data.
m_Generator - Variable in class adams.gui.tools.wekainvestigator.source.DataGenerator: the last filechooser.
m_Generator - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: the fold generator.
m_Generator - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: the split generator to use.
m_Generator - Variable in class adams.multiprocess.WekaCrossValidationExecution: the cross-validation fold generator.
m_Generator - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the fold generator.
m_Generator - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator: the underlying scheme for generating the folds.
m_Generator - Variable in class weka.classifiers.DefaultRandomSplitGenerator: the underlying scheme for generating the split.
m_Generator - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: the underlying scheme for generating the folds.
m_Generator - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: the underlying scheme for generating the folds.
m_Generator - Variable in class weka.classifiers.GroupedRandomSplitGenerator: the underlying scheme for generating the split.
m_Genes - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: the genes.
m_GlobalSource - Variable in class adams.flow.transformer.WekaInstanceEvaluator: the callable actor to use.
m_Glue - Variable in class weka.filters.unsupervised.attribute.JoinAttributes: the glue to use for joining the attributes.
m_GOEFinalModel - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: how to produce the final model.
m_GOEGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: the fold generator.
m_GOEGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: the fold generator.
m_GOEGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: the split generator.
m_GOEGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: the fold generator.
m_GOEGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: the split generator.
m_GOEJobRunner - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: the jobrunner.
m_GOEJobRunner - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: the jobrunner.
m_GOEJobRunner - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: the jobrunner.
m_GOEJobRunner - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: the jobrunner.
m_Grid - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: the size of the grid.
m_Group - Variable in class adams.data.binning.BinnableInstances.StringAttributeGroupExtractor: the group to extract.
m_Group - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: the group expression.
m_Group - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: the group expression.
m_Group - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: the group expression.
m_Group - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: the group expression.
m_Group - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: the group expression.
m_Group - Variable in class weka.classifiers.GroupedRandomSplitGenerator: the group expression.
m_Group - Variable in class weka.core.InstanceGrouping: the replacement string, using the groups from the regexp.
m_Group - Variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: the group expression.
m_Groups - Variable in class weka.classifiers.MultiLevelSplitGenerator: the groups to generate.
m_Groups - Variable in class weka.core.InstanceGrouping: the groups.
m_GrowPolicy - Variable in class weka.classifiers.trees.XGBoost: Controls the way new nodes are added to the tree.
m_Handler - Variable in class adams.flow.sink.WekaExperimentFileWriter: the IO handler.
m_Handler - Variable in class adams.flow.transformer.WekaExperimentFileReader: the IO handler.
m_Handlers - Variable in class adams.opt.genetic.Hermione: the handlers to use for discovery.
m_HasClass - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Data has a class set.
m_HashCode - Variable in class weka.core.AbstractHashableInstance: the current hashcode.
m_Hashed - Variable in class weka.filters.unsupervised.attribute.JoinAttributes: the hashed indices.
m_Header - Variable in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader: the header to load from disk.
m_Header - Variable in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader: the header to load from storage.
m_Header - Variable in class adams.data.conversion.ReportToWekaInstance: the header to use.
m_Header - Variable in class adams.flow.transformer.WekaInstanceDumper: the header of the dataset.
m_Header - Variable in class adams.flow.transformer.WekaInstanceEvaluator: the new header.
m_Header - Variable in class adams.flow.transformer.WekaStreamEvaluator: the current header.
m_Header - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: the header.
m_Header - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: the training header (if any).
m_Header - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: the training header (if any).
m_Header - Variable in class adams.ml.data.InstancesView: the header row.
m_Header - Variable in class weka.classifiers.functions.ClassificationViaPLS: the header of the training set.
m_Header - Variable in class weka.classifiers.meta.PeakTransformed: the header information of the transformed data.
m_Header - Variable in class weka.classifiers.meta.RangeCheck: the training header.
m_Header - Variable in class weka.classifiers.meta.SubsetEnsemble: The header of the training set.
m_Header - Variable in class weka.classifiers.meta.SumTransformed: the header information of the transformed data.
m_Header - Variable in class weka.classifiers.meta.VotedImbalance: The header of the training set.
m_Header - Variable in class weka.classifiers.trees.XGBoost: the training dataset.
m_HeaderPopupMenuCustomizer - Variable in class adams.gui.visualization.instances.InstancesTable: the customizer for the table header popup menu.
m_Helper - Variable in class adams.flow.source.WekaSelectDataset: the helper class.
m_Helper - Variable in class adams.flow.transformer.WekaClassifierRanker: the helper class.
m_Helper - Variable in class adams.flow.transformer.WekaGeneticAlgorithm: the helper class.
m_hiClassifier - Variable in class weka.classifiers.meta.HighLowSplit
m_hiLopoint - Variable in class weka.classifiers.meta.HighLowSplit
m_histBarClassCounts - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: This array holds the per class count (or per class height) of the each of the bars in a barplot or a histogram.
m_histBarCounts - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: This array holds the count (or height) for the each of the bars in a barplot or a histogram.
m_HistogramOptions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Options for the histogram
m_HistogramSetup - Variable in class adams.gui.visualization.instance.InstanceExplorer: the dialog for the histogram setup.
m_HistogramSetup - Variable in class adams.gui.visualization.instance.InstancePanel: the dialog for the histogram setup.
m_History - Variable in class adams.gui.goe.WekaGenericObjectEditorPanel: the history of used setups.
m_History - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the history.
m_History - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the history.
m_History - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the history.
m_History - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the history.
m_History - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the history.
m_History - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the history.
m_History - Variable in class weka.gui.explorer.ExperimentPanel: A panel controlling results viewing.
m_History - Variable in class weka.gui.explorer.MultiExplorer: the history panel.
m_HoldOutPercentage - Variable in class weka.classifiers.meta.ClassifierCascade: the percentage to use for validation set to determine termination criterion (0-100).
m_ICA - Variable in class adams.data.instancesanalysis.FastICA: the Fast ICA analysis to use.
m_ID - Variable in class adams.flow.sink.WekaInstanceViewer: the name of the attribute/field to use as ID.
m_ID - Variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: the ID of the container.
m_ID - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: the ID to use for the returned instances.
m_ID - Variable in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: the attribute with the IDs.
m_ID - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances: the attribute to use for identifying instances.
m_IDCounter - Static variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: the ID counter.
m_IDSplitter - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Column-splitter for separating the ID column.
m_IDTest - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances: the attribute to use for identifying instances in the test set.
m_IgnoreChanges - Variable in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel: whether to ignored changes.
m_IgnoreChanges - Variable in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: whether to ignored changes.
m_IgnoreChanges - Variable in class adams.gui.visualization.instances.InstancesTableModel: whether to ignore changes, i.e.
m_IgnoreClass - Variable in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: whether to ignore the class attribute.
m_IgnoredAttributes - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: the regular expression for attributes to skip.
m_IncludeClass - Variable in class weka.filters.unsupervised.instance.RemoveDuplicates: whether to take the class into account.
m_IncludeClass - Variable in class weka.filters.unsupervised.instance.Sort: whether to take the class into account.
m_Incorrect - Variable in class weka.filters.unsupervised.attribute.SpellChecker: the (misspelled) labels of the attribute to replace.
m_IncorrectCache - Variable in class weka.filters.unsupervised.attribute.SpellChecker: the hashset with the incorret labels (for faster access).
m_Incremental - Variable in class adams.flow.source.WekaDatabaseReader: whether to output the data row-by-row.
m_IncrementalClassifier - Variable in class adams.flow.transformer.WekaTrainClassifier: the classifier to use when training incrementally.
m_IncrementalClusterer - Variable in class adams.flow.transformer.WekaTrainClusterer: the clusterer used when training incrementally.
m_Index - Variable in class adams.data.binning.BinnableInstances.StringAttributeGroupExtractor: the attribute index.
m_Index - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer: the distribution index (0-based).
m_Index - Variable in class adams.data.io.input.InstanceReader: the current index.
m_Index - Variable in class adams.data.weka.classattribute.AttributeIndex: the attribute index.
m_Index - Variable in class adams.data.weka.relationname.AttributeIndex: the attribute index.
m_Index - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: the index to use for grouping.
m_Index - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: the index to use for grouping.
m_Index - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: the index in actor's input array.
m_Index - Variable in class adams.flow.transformer.WekaExtractArray: the index of the row/column to extract.
m_Index - Variable in class adams.flow.transformer.WekaGetInstanceValue: the index of the attribute to get the value from the Instance.
m_Index - Variable in class adams.flow.transformer.WekaSetInstanceValue: the attribute index to set in the Instance.
m_Index - Variable in class adams.flow.transformer.WekaSubsets: the attribute index to split on.
m_Index - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: the current attribute index.
m_Index - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: the index.
m_Index - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: the index to use for grouping.
m_Index - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: the index to use for grouping.
m_Index - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: the index to use for grouping.
m_Index - Variable in class weka.classifiers.GroupedRandomSplitGenerator: the index to use for grouping.
m_Index - Variable in class weka.classifiers.LeaveOneOutByValueGenerator: the index to get the unique values from.
m_Index - Variable in class weka.core.InstanceGrouping: the attribute index.
m_Index - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric: the attribute to convert.
m_Index - Variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: the index to use for grouping.
m_Index - Variable in class weka.filters.unsupervised.instance.RemoveWithLabels: the attribute to remove the labels from.
m_Indexer - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: the currently loaded dataset.
m_IndexOfID - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter
m_Indices - Variable in class adams.data.instances.InstanceComparator: the column indices to use in the comparison.
m_Indices - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the selected indices.
m_Indices - Variable in class weka.classifiers.MultiLevelSplitGenerator: the attribute indices.
m_Indices - Variable in class weka.filters.unsupervised.attribute.AnyToString: the attribute indices to work on.
m_Indices - Variable in class weka.filters.unsupervised.attribute.CorrelationMatrix: the attribute indices to use.
m_Indices - Variable in class weka.filters.unsupervised.attribute.InputSmearing: the indices to work on.
m_Indices - Variable in class weka.filters.unsupervised.attribute.JoinAttributes: the indices to work on.
m_Indices - Variable in class weka.filters.unsupervised.attribute.StringToDate: the attribute indices to work on.
m_Indices1 - Variable in class adams.tools.CompareDatasets: the indices for the first dataset.
m_Indices2 - Variable in class adams.tools.CompareDatasets: the indices for the second dataset.
m_IndicesUnused - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: the indices of the unused attributes.
m_InfoPanel - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: the info panel.
m_init - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: initialised?
m_InitialDirectory - Variable in class adams.flow.source.WekaSelectDataset: the initial directory.
m_InitialFiles - Variable in class adams.flow.source.WekaSelectDataset: the initial files to use.
m_initializationMethod - Variable in class weka.clusterers.SAXKMeans: The initialization method to use
m_Initialized - Variable in class adams.data.instancesanalysis.pls.AbstractPLS: whether the scheme has been initialized.
m_Initialized - Variable in class adams.data.weka.evaluator.AbstractInstanceEvaluator: whether the evaluator got initialized.
m_Initialized - Variable in class adams.flow.transformer.WekaFilter: whether the filter has been initialized.
m_Initialized - Variable in class adams.flow.transformer.WekaStreamFilter: whether the filter has been initialized.
m_Initialized - Variable in class weka.classifiers.AbstractSplitGenerator: whether the iterator has been initialized.
m_InitializeOnce - Variable in class adams.flow.transformer.WekaFilter: whether to initialize filter only with the first batch.
m_InitializeOnce - Variable in class adams.flow.transformer.WekaReorderAttributesToReference: whether to initialize filter only with the first batch.
m_initialStartPoints - Variable in class weka.clusterers.SAXKMeans: Holds the initial start points, as supplied by the initialization method used
m_Instance - Variable in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer: the Instance the container is for.
m_InstanceClass - Variable in class adams.flow.transformer.WekaNewInstance: the class of instance to create.
m_InstancePaintlet - Variable in class adams.gui.visualization.instance.InstancePanel: paintlet for drawing the graph.
m_InstancePanel - Variable in class adams.flow.sink.WekaInstanceViewer: the panel with the instances.
m_instancepct - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_instancepct - Variable in class weka.classifiers.meta.LeastMedianSq
m_InstancePointHitDetector - Variable in class adams.gui.visualization.instance.InstancePanel: the hit detector for the tooltip.
m_Instances - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel: The instances who's attribute structure we are reporting
m_Instances - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: The instances we're playing with
m_Instances - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel: The instances we're playing with
m_Instances - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: the underlying data.
m_Instances - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: the underlying data.
m_Instances - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the full dataset.
m_Instances - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the data to use for cross-validation.
m_Instances - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: the data to use for cross-validation.
m_Instances - Variable in class weka.gui.explorer.ExperimentPanel: The main set of instances we're playing with.
m_InstancesActor - Variable in class adams.flow.transformer.WekaInstanceEvaluator: the callable actor to get the Instances from in case of AbstractDatasetInstanceEvaluator.
m_InstancesHeader - Variable in class adams.ml.model.classification.WekaClassificationModel: the instances used.
m_InstancesHeader - Variable in class adams.ml.model.clustering.WekaClusteringModel: the instances used.
m_InstancesHeader - Variable in class adams.ml.model.regression.WekaRegressionModel: the instances used.
m_InstancesSortPanel - Variable in class adams.gui.visualization.instances.instancestable.DataSort: the sort panel.
m_InstancesSortSetupListeners - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: the listeners for changes in the setup.
m_intercept - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: The intercept
m_Interval - Variable in class adams.flow.transformer.WekaInstanceBuffer: the interval of when to output the Instances object.
m_Interval - Variable in class adams.flow.transformer.WekaStreamEvaluator: the interval at which to output the evaluation.
m_Intervals - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval: the intervals.
m_InverseTransform - Variable in class weka.filters.unsupervised.attribute.FastWavelet: whether to perform inverse transformation.
m_InverseTransform - Variable in class weka.filters.unsupervised.attribute.FFT: whether to perform inverse transformation (wavelet -> normal space).
m_Invert - Variable in class adams.flow.condition.bool.AbstractAttributeCapabilities: whether to invert the matching sense.
m_Invert - Variable in class adams.flow.transformer.WekaMultiLabelSplitter: whether to invert the matching sense.
m_Invert - Variable in class adams.flow.transformer.WekaRegexToRange: invert matching?
m_Invert - Variable in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens: whether to invert the matching sense.
m_Invert - Variable in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Whether to invert the column indices.
m_Invert - Variable in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Whether to invert the row indices.
m_Invert - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances: whether to invert the matching.
m_Invert - Variable in class weka.filters.unsupervised.instance.RemoveWithLabels: whether to invert the matching.
m_invertMatching - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Whether to invert the match so the correctly classified instances are discarded
m_invertMatching - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Whether to invert the match so the correctly classified instances are discarded
m_InvertMatchingSense - Variable in class adams.flow.transformer.WekaInstancesMerge: whether to invert the matching sense for excluding attributes.
m_InvertSelection - Variable in class weka.filters.unsupervised.instance.KennardStone: whether to invert the selection.
m_InvertSelection - Variable in class weka.filters.unsupervised.instance.SafeRemoveRange: whether to invert the selection.
m_IQR - Variable in class adams.data.weka.rowfinder.FilteredIQR: the maximum value of the attribute.
m_IQRs - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp
m_IsPercent - Variable in class weka.classifiers.meta.AbstainAverage
m_IsPercent - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
m_IsPercent - Variable in class weka.classifiers.meta.AbstainVote
m_IsString - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: whether the attribute is numeric or string/nominal.
m_Item - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane: the underlying result item.
m_Iterations - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: number of iterations.
m_Iterations - Variable in class weka.clusterers.SAXKMeans: Keep track of the number of iterations completed before convergence.
m_Iterator - Variable in class adams.flow.transformer.WekaInstanceBuffer: the iterator for broadcasting Instance objects.
m_Job - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the title of the current job.
m_JobCounter - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: the counter for finished jobs.
m_JobRunner - Variable in class adams.flow.transformer.WekaClassifierRanker: the job runner for evaluating the setups.
m_JobRunner - Variable in class adams.flow.transformer.WekaExperimentExecution: the JobRunner template.
m_JobRunner - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: the JobRunner template.
m_JobRunner - Variable in class adams.multiprocess.WekaCrossValidationExecution: the jobrunner template.
m_JobRunner - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the job runner in use.
m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaFilter: the JobRunnerInstance to use.
m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaTestSetEvaluator: the JobRunnerInstance to use.
m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaTrainAssociator: the JobRunnerInstance to use.
m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaTrainClassifier: the JobRunnerInstance to use.
m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaTrainClusterer: the JobRunnerInstance to use.
m_JobRunnerInstance - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator: the JobRunnerInstance to use.
m_JobRunnerSetup - Variable in class adams.flow.transformer.WekaClassifierRanker: the jobrunner setup.
m_JobRunnerSetup - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator: the jobrunner setup.
m_JobRunnerSetup - Variable in class adams.flow.transformer.WekaGeneticAlgorithm: the jobrunner setup.
m_JobRunnerSetup - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: the jobrunner setup.
m_JobRunnerSetup - Variable in class adams.multiprocess.WekaCrossValidationExecution: the jobrunner setup.
m_JobRunnerSetup - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the jobrunner setup.
m_JobTotal - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: the total number of jobs.
m_k - Variable in class weka.classifiers.meta.Corr
m_KeepAttributeNames - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay: whether to keep the original attribute names.
m_KeepAttributeNames - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay2: whether to keep the original attribute names.
m_KeepExisting - Variable in class adams.flow.transformer.WekaInstanceDumper: whether to keep existing output files when actor is called for the first time, in order to allow appending to files from multiple locations in flow.
m_KeepNumComponents - Variable in class adams.data.conversion.SwapPLS: whether to migrate the number of components.
m_KeepOnlySingleUniqueID - Variable in class adams.flow.transformer.WekaInstancesMerge: whether to keep only a single instance of the unique ID attribute.
m_KeepRelationName - Variable in class adams.flow.transformer.WekaFilter: whether to keep the incoming relation name.
m_KeepRelationName - Variable in class adams.flow.transformer.WekaReorderAttributesToReference: whether to keep the incoming relation name.
m_KeepRelationName - Variable in class adams.flow.transformer.WekaStreamFilter: whether to keep the incoming relation name.
m_KeepSupervisedClass - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Whether to keep the supervised filter class or discard it.
m_Kept - Variable in class adams.data.instancesanalysis.PCA: the indices of the kept attributes.
m_kernel - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: Kernel to use *
m_kernel - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: Kernel to use *
m_kernel - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: Kernel to use
m_Kernel - Variable in class adams.data.instancesanalysis.pls.KernelPLS: the kernel to use.
m_KernelIsLinear - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: whether the kernel is a linear one
m_KernelIsLinear - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: whether the kernel is a linear one
m_KernelPLS - Variable in class adams.data.instancesanalysis.pls.KernelPLS: the actual algorithm.
m_Keys - Variable in class adams.flow.source.WekaDatabaseReader: the keys that uniquely identify a single row.
m_kNN - Variable in class weka.classifiers.lazy.LWLDatasetBuilder: The number of neighbours used to select the kernel bandwidth.
m_kNN - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: The number of neighbours used to select the kernel bandwidth.
m_L - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: (negative) covariance matrix in symmetric matrix representation
m_L - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: (negative) covariance matrix in symmetric matrix representation
m_Label - Variable in class weka.classifiers.meta.ThresholdedBinaryClassification: the label to check.
m_Label - Variable in class weka.classifiers.meta.Veto: the label to check.
m_LabelAttributeRange - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: the label for the range.
m_LabelIndex - Variable in class adams.flow.transformer.WekaInstancesInfo: the index of the label.
m_LabelIndex - Variable in class weka.classifiers.functions.ClassificationViaPLS: The label index to get the PLS matrices for.
m_LabelMapping - Variable in class weka.filters.unsupervised.instance.RemoveWithLabels: the label mapping (old -> new).
m_LabelMatch - Variable in class weka.filters.unsupervised.instance.DatasetLabeler: the label to use for a match.
m_LabelNonMatch - Variable in class weka.filters.unsupervised.instance.DatasetLabeler: the label to use for a nonmatch.
m_LabelQuery - Variable in class weka.gui.explorer.SqlPanel: displays the current query
m_LabelRegExp - Variable in class weka.filters.unsupervised.instance.RemoveWithLabels: the regular expression for matching the labels to remove.
m_LabelRowAttribute - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: the label for the attribute names.
m_LabelRows - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the label for the combobox.
m_LabelString - Variable in class weka.classifiers.functions.ClassificationViaPLS: the label string to get the PLS matrices for (overrides the label index).
m_LabelTextNumPoints - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the number of data points.
m_Lambda - Variable in class adams.data.instancesanalysis.pls.DIPLS: lambda
m_Lambda - Variable in class adams.data.instancesanalysis.pls.SparsePLS: Sparsity parameter.
m_Lambda - Variable in class adams.data.instancesanalysis.pls.VCPLS: the lambda value.
m_Lambda - Variable in class weka.classifiers.trees.XGBoost: L2 regularisation term on weights.
m_LastAttributesToVisualize - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the last indices that were visualized.
m_LastBias - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset: the last bias used.
m_LastBoxPlot - Variable in class adams.gui.tools.wekainvestigator.tab.BoxPlotTab: the last boxplot.
m_LastError - Variable in class weka.classifiers.AggregateEvaluations: the last error.
m_LastExport - Variable in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane: the last export scheme.
m_LastLimit - Variable in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer: the last limit.
m_LastNotificationTime - Variable in class adams.opt.optimise.GeneticAlgorithm: the timestamp the last notification got sent.
m_LastPercentage - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset: the last percentage used.
m_LastReader - Variable in class adams.gui.tools.wekainvestigator.source.Clipboard: the last spreadsheet reader used.
m_LastReplacement - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset: whether replacement was used.
m_LastSeed - Variable in class adams.gui.tools.wekainvestigator.datatable.action.Randomize: the last seed.
m_LastSeed - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset: the last seed used.
m_LastSetup - Variable in class adams.gui.tools.wekainvestigator.datatable.action.Merge: the last merge setup.
m_LastSetup - Variable in class adams.gui.visualization.instances.InstancesTable: for keeping track of the setups being used (classname-{plot|process}-{column|row} - setup).
m_LastSourceID - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RemoveTestSet: the last used source ID attribute.
m_LastSplitter - Variable in class adams.gui.tools.wekainvestigator.datatable.action.Split: the last splitter.
m_LastSupervised - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset: whether supervised version was used.
m_LastTable - Variable in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer: the last setup.
m_LastTestSetID - Variable in class adams.gui.tools.wekainvestigator.datatable.action.RemoveTestSet: the last used test set ID attribute.
m_LastUpdated - Variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: the timestamp the data was last updated.
m_Layout - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: the gridlayout in use.
m_left - Variable in class weka.classifiers.trees.m5.RuleNode2: left child node
m_Lenient - Variable in class adams.flow.transformer.WekaReorderAttributesToReference: whether to tolerate attributes that are not present in the incoming data.
m_Less - Variable in class weka.classifiers.trees.RandomRegressionForest.Node
m_Limit - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: the limit type.
m_LinearReg - Variable in class weka.classifiers.trees.RandomRegressionForest.Node
m_List - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: for listing the classifiers.
m_List - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: for listing the files.
m_ListAdditionalAttributes - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the list of additional attribute values to store in the report.
m_ListAdditionalAttributesModel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the model for the additional attributes.
m_ListCommonIDs - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the JList with the common IDs.
m_Listeners - Variable in class adams.gui.visualization.instances.InstancesTableModel: the listeners
m_ListFiles - Variable in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: the list for the file names.
m_ListIDs - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the list with instance IDs to display.
m_ListRows - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the JLiast with the rows.
m_ListRowsModel - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the model for the combobox with the rows.
m_ListType - Variable in class adams.flow.source.wekapackagemanageraction.ListPackages: the type of list to generate.
m_Loader - Variable in class adams.data.io.input.AbstractWekaSpreadSheetReader: the file loader to use.
m_Loader - Variable in class adams.gui.chooser.DatasetFileChooserPanel: the current loader.
m_Loader - Variable in class adams.gui.tools.wekainvestigator.data.FileContainer: the reader used to load the data.
m_Loader - Variable in class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer: the generator used to load the data.
m_Loader - Variable in class adams.gui.tools.wekainvestigator.source.TextDirectory: the last config.
m_LoadFromDatabaseDialog - Variable in class adams.gui.visualization.instance.InstanceExplorer: the SQL viewer dialog.
m_LoadFromDiskDialog - Variable in class adams.gui.visualization.instance.InstanceExplorer: the dialog for loading datasets.
m_Loadings - Variable in class adams.data.instancesanalysis.PCA: the loadings.
m_Loadings - Variable in class adams.data.instancesanalysis.PLS: the loadings.
m_LoadingsCalculations - Variable in class weka.attributeSelection.AbstractPLSAttributeEval: for how to use the loadings.
m_Local - Variable in class weka.classifiers.meta.SocketFacade: the return address for the remote process to use.
m_Locations - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges: the array of indices/regular expressions.
m_Locations - Variable in class adams.flow.transformer.WekaInstancesStatistic: the array of indices/regular expressions.
m_locker - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Lock variable to synchronize the different threads running currently in this class.
m_loClassifier - Variable in class weka.classifiers.meta.HighLowSplit
m_loClassifier - Variable in class weka.classifiers.meta.HighLowSplitSingleClassifier
m_Log - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the log.
m_Log - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: the log.
m_Log - Variable in class weka.gui.explorer.ExperimentPanel: The destination for log/status messages.
m_Log - Variable in class weka.gui.explorer.SqlPanel: The destination for log/status messages
m_LogPanel - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: the log component.
m_LogPanel - Variable in class adams.gui.tools.wekainvestigator.tab.LogTab: the log panel.
m_loHipoint - Variable in class weka.classifiers.meta.HighLowSplit
m_loHipoint - Variable in class weka.classifiers.meta.HighLowSplitSingleClassifier
m_Lookup2 - Variable in class adams.tools.CompareDatasets: the lookup table of indices for the second dataset.
m_Lower - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: the lower value to compute.
m_Lower - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: the lower value to compute.
m_Lower - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: the lower value to compute.
m_Lower - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: the lower value to compute.
m_LR - Variable in class weka.core.WeightedEuclideanDistance
m_LR - Variable in class weka.core.WeightedEuclideanDistanceRidge
m_MainFilter - Variable in class weka.filters.FilteredFilter: The main filter to apply to the data.
m_MakeClassLast - Variable in class adams.flow.transformer.WekaMultiLabelSplitter: whether to move the class attribute to the end.
m_MakeThreadSafe - Variable in class adams.flow.transformer.WekaModelReader: whether to wrap the model in a threadsafe wrapper.
m_Manual - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: for generating class distributions.
m_ManualClassifier - Variable in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: a programmatically supplied classifier.
m_ManualClassifier - Variable in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: a programmatically supplied classifier.
m_ManualMax - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges: the manual maximum.
m_ManualMin - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges: the manual minimum.
m_Mapping - Variable in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: the mapping between fusion subset names and attribute indices.
m_Mapping - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric: the mapping between label and new value.
m_MarkerExtent - Variable in class adams.gui.visualization.instance.InstanceLinePaintlet: the maximum width/height of the shape to plot around the points (= data point marker), if there's enough space.
m_MarkersEnabled - Variable in class adams.gui.visualization.instance.InstanceLinePaintlet: indicates whether marker shapes are painted or not.
m_Matrix - Variable in class adams.flow.transformer.WekaGenericPLSMatrixAccess: the name of the matrix to extract.
m_Matrix - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel: the underlying matrix.
m_MatrixNames - Variable in class weka.filters.supervised.attribute.MultiPLS: the matrix names.
m_MatrixType - Variable in class adams.flow.transformer.WekaExtractPLSMatrix: the matrix type to extract.
m_MatrixValues - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: what values to generate.
m_max - Variable in class adams.opt.optimise.genetic.PackDataDef.DataInfo
m_max - Variable in class weka.classifiers.meta.AbstainAttributePercentile
m_max - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_max - Variable in class weka.classifiers.trees.RandomModelTrees
m_Max - Variable in class adams.flow.transformer.WekaClassifierRanker: the maximum number of top-ranked classifiers to forward.
m_Max - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
m_Max - Variable in class weka.filters.unsupervised.instance.Scale: the maximum to use.
m_MaxActual - Variable in class weka.classifiers.meta.MinMaxLimits: the actual limit to use for the upper limit.
m_MaxAttributeNames - Variable in class adams.data.instancesanalysis.PCA: the maximum number of attribute names.
m_MaxAttributeNames - Variable in class adams.flow.transformer.WekaPrincipalComponents: the maximum number of attribute names to use.
m_MaxAttributes - Variable in class adams.data.instancesanalysis.PCA: the maximum number of attributes.
m_MaxAttributes - Variable in class adams.flow.transformer.WekaPrincipalComponents: the maximum number of attributes to keep.
m_MaxAttributes - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: maximum number of attributes in the transformed data (-1 for all).
m_MaxAttributesToVisualize - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the maximum number of attributes to visualize (summary table/histogram).
m_MaxAttrsInName - Variable in class weka.core.neighboursearch.PCANNSearch: maximum number of attributes in the transformed attribute name.
m_MaxAttrsInName - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: maximum number of attributes in the transformed attribute name.
m_MaxBin - Variable in class weka.classifiers.trees.XGBoost: Maximum number of discrete bins to bucket continuous features.
m_maxCanopyCandidates - Variable in class weka.clusterers.SAXKMeans: The maximum number of candidate canopies to hold in memory at any one time (if using canopy clustering)
m_MaxClassRangePercentage - Variable in class weka.classifiers.meta.MinMaxLimits: the percentage leeway for the class range of the upper limit (0-1 = 0-100%).
m_MaxColWidth - Variable in class adams.gui.tools.wekainvestigator.tab.DataTab: the default max column width.
m_MaxColWidth - Variable in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab: the default max column width.
m_MaxDecimalPlaces - Variable in class weka.core.converters.SimpleArffSaver: Max number of decimal places for numeric values
m_MaxDeltaStep - Variable in class weka.classifiers.trees.XGBoost: Maximum delta step.
m_MaxDepth - Variable in class weka.classifiers.trees.XGBoost: The maximum depth of the tree.
m_MaxDifference - Variable in class weka.classifiers.meta.AbstainAverage
m_MaxDifference - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
m_MaxDifference - Variable in class weka.classifiers.meta.AbstainVote
m_MaxDifferences - Variable in class weka.classifiers.meta.AbstainAverage
m_MaxDifferences - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
m_MaxDifferences - Variable in class weka.classifiers.meta.AbstainVote
m_MaxDifferences_string - Variable in class weka.classifiers.meta.AbstainAverage
m_MaxDifferences_string - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
m_MaxDifferences_string - Variable in class weka.classifiers.meta.AbstainVote
m_MaxDisplayItems - Variable in class adams.gui.goe.WekaGenericArrayEditorPanel: the maximum number of array items to display via toString().
m_Maxes - Variable in class weka.classifiers.meta.AbstainAverage
m_Maxes - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
m_Maxes - Variable in class weka.classifiers.meta.AbstainVote
m_MaxFactor - Variable in class weka.filters.unsupervised.instance.WeightsBasedResample: the upper limit of the multiplication factor (<= 0 is not capped).
m_MaxHandling - Variable in class weka.classifiers.meta.MinMaxLimits: how the upper limit is handled.
m_Maximum - Variable in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: the maximum.
m_Maximum - Variable in class adams.data.weka.rowfinder.ByNumericValue: the maximum value.
m_Maximum - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: the maximum value.
m_MaximumIncluded - Variable in class adams.data.weka.rowfinder.ByNumericValue: whether the maximum value is included.
m_MaximumIncluded - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: whether the maximum value is included.
m_MaxIter - Variable in class adams.data.instancesanalysis.pls.KernelPLS: Inner NIPALS loop maximum number of iterations
m_MaxIter - Variable in class adams.data.instancesanalysis.pls.NIPALS: Inner NIPALS loop maximum number of iterations
m_MaxIter - Variable in class adams.data.instancesanalysis.pls.PRM: Inner loop maximum number of iterations
m_MaxIter - Variable in class adams.data.instancesanalysis.pls.SparsePLS: Inner NIPALS loop maximum number of iterations
m_MaxIterations - Variable in class weka.clusterers.SAXKMeans: Maximum number of iterations to be executed.
m_MaxLabels - Variable in class adams.data.conversion.SpreadSheetToWekaInstances: the threshold for number of labels before an attribute gets switched to Attribute.STRING.
m_MaxLabels - Variable in class adams.data.spreadsheet.filter.WekaFilter: the threshold for number of labels before an attribute gets switched to Attribute.STRING.
m_MaxLeaves - Variable in class weka.classifiers.trees.XGBoost: Maximum number of nodes to be added.
m_MaxLevels - Variable in class weka.classifiers.meta.ClassifierCascade: the maximum number of levels in the cascade.
m_MaxManual - Variable in class weka.classifiers.meta.MinMaxLimits: the manual limit for the upper limit.
m_MaxNeighbors - Variable in class adams.flow.transformer.WekaNearestNeighborSearch: the maximum number of neighbors to return.
m_MaxSize - Variable in class adams.data.weka.predictions.RelativeNumericErrorScaler: the maximum size.
m_MaxTrainTime - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: the maximum number of seconds to train.
m_maxValue - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: This holds the max value of the current attribute.
m_MaxWidth - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased: the maximum width allowed.
m_Mean - Variable in class weka.classifiers.trees.RandomRegressionForest: the mean
m_Means - Variable in class weka.classifiers.functions.LinearRegressionJ: The attributes means
m_Means - Variable in class weka.filters.supervised.attribute.PLSFilterExtended
m_Measure - Variable in class adams.flow.transformer.WekaClassifierRanker: the measure for the evaluation.
m_Measure - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: the measure to use for ranking.
m_Measure - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: the measure to use for evaluating the fitness.
m_Measure - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the measure to use for evaluating the fitness.
m_Measure - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: the measure to use for evaluating the fitness.
m_MeasuresPrefix - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer: the optional prefix to disambiguate the measure attributes from the original ones.
m_Memory - Static variable in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter: for monitoring the Memory consumption
m_Memory - Static variable in class weka.gui.explorer.MultiExplorer: for monitoring the Memory consumption
m_MenuBar - Variable in class adams.gui.tools.DatasetCompatibilityPanel: the menu bar.
m_MenuBar - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the menu bar.
m_MenuBar - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the menu bar.
m_MenuBar - Variable in class adams.gui.visualization.instance.InstanceExplorer: the menu bar, if used.
m_MenuBar - Variable in class weka.gui.explorer.ExplorerExt: the menu bar, if used.
m_MenuFileSources - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the submenu for a sources.
m_MenuItemClearData - Variable in class adams.gui.visualization.instance.InstanceExplorer: the clear data menu item.
m_MenuItemEditData - Variable in class weka.gui.explorer.ExplorerExt: the edit data menu item.
m_MenuItemEditUndo - Variable in class weka.gui.explorer.ExplorerExt: the undo menu item.
m_MenuItemExecutionReset - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the reset menu item.
m_MenuItemExecutionStart - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the start menu item.
m_MenuItemExecutionStop - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the stop menu item.
m_MenuItemFileLoadClassifier - Variable in class weka.gui.explorer.ExplorerExt: the load classifier menu item.
m_MenuItemFileLoadClusterer - Variable in class weka.gui.explorer.ExplorerExt: the load clusterer menu item.
m_MenuItemFileLoadRecent - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the "load recent" submenu.
m_MenuItemFileSave - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the save menu item.
m_MenuItemFileSave - Variable in class weka.gui.explorer.ExplorerExt: the save menu item.
m_MenuItemFileSaveAs - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the save as menu item.
m_MenuItemFileSaveAs - Variable in class weka.gui.explorer.ExplorerExt: the save as menu item.
m_MenuItemLoadRecent - Variable in class adams.gui.visualization.instance.InstanceExplorer: the "load recent" submenu.
m_MenuItemLoadRecent - Variable in class weka.gui.explorer.ExplorerExt: the "load recent" submenu.
m_MenuItemLoadRecent1 - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the recent file menu item (first file).
m_MenuItemLoadRecent2 - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the recent file menu item (second file).
m_MenuItemOptionsCalculateModelSize - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the menu item for enabling/disabling model size calculation.
m_MenuItemOptionsSortAttributeNames - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the menu item for enabling/disabling sorting of attribute names.
m_MenuItemOptionsUndoEnabled - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the menu item for enabling/disabling undo.
m_MenuItemPrefixDatasetsWithIndex - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the prefix datasets menu item.
m_MenuItemReload - Variable in class adams.gui.tools.DatasetCompatibilityPanel: the reload menu item.
m_MenuItemReload - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the reload menu item.
m_MenuItemResultsLoadRecent - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the "load recent" submenu.
m_MenuItemResultsSave - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the save results menu item.
m_MenuItemText - Variable in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: the menu item caption.
m_MenuItemText - Variable in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: the menu item caption.
m_MenuItemUseFilename - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the use filename menu item.
m_MenuItemViewAntiAliasing - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the toggle anti-aliasing menu item.
m_MenuItemViewAntiAliasing - Variable in class adams.gui.visualization.instance.InstanceExplorer: the toggle anti-aliasing menu item.
m_MenuItemViewColorProvider - Variable in class adams.gui.visualization.instance.InstanceExplorer: the color provider menu item.
m_MenuItemViewInstanceExplorer - Variable in class weka.gui.explorer.ExplorerExt: the view instance explorer menu item.
m_MenuItemViewPaintlet - Variable in class adams.gui.visualization.instance.InstanceExplorer: the paintlet menu item.
m_MenuItemViewZoomOverview - Variable in class adams.gui.visualization.instance.InstanceExplorer: the toggle zoom overview menu item.
m_MenuTabNewTab - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the submenu for a new tab.
m_MenuView - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the menu item for view related stuff.
m_MenuView - Variable in class adams.gui.visualization.instance.InstanceExplorer: the menu item for view related stuff.
m_Merged - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes: the name of the merged attribute.
m_Merged - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: the name of the merged attribute.
m_MergedDatasetName - Variable in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: The name to give the resulting dataset.
m_MergedIndex - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes: the position for the merged attribute (empty = leave at default position).
m_MergedIndex - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: the position for the merged attribute (empty = leave at default position).
m_MergeMethod - Variable in class adams.flow.transformer.WekaDatasetsMerge: The method to use to perform the merge.
m_Merger - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Merger for reconstructing partial datasets.
m_Message - Variable in class adams.flow.transformer.WekaChooseAttributes: the message to display to the user.
m_MetaDataColor - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: for obtaining the color from the meta-data.
m_MetaLevelClassifier - Variable in class weka.classifiers.meta.PartitionedStacking: the meta-level classifier.
m_MetaLevelData - Variable in class weka.classifiers.meta.PartitionedStacking: the header for the meta-level data.
m_MetaLevelHeader - Variable in class weka.classifiers.meta.ClassifierCascade: the meta-level structure.
m_MetaLevelStart - Variable in class weka.classifiers.meta.ClassifierCascade: the start indices for the classifier stats in the meta-levels.
m_MethodNamePrediction - Variable in class weka.classifiers.functions.PyroProxy: the Pyro remote method for prediction.
m_MethodNameTrain - Variable in class weka.classifiers.functions.PyroProxy: the Pyro remote method for training.
m_min - Variable in class adams.opt.optimise.genetic.PackDataDef.DataInfo
m_min - Variable in class weka.classifiers.meta.AbstainAttributePercentile
m_min - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_Min - Variable in class weka.classifiers.trees.RandomRegressionForest: the minimum number of instances in subsets
m_Min - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
m_Min - Variable in class weka.filters.unsupervised.instance.Scale: the minimum to use.
m_MinActual - Variable in class weka.classifiers.meta.MinMaxLimits: the actual limit to use for the lower limit.
m_MinChildWeight - Variable in class weka.classifiers.trees.XGBoost: The minimum child weight.
m_MinClassRangePercentage - Variable in class weka.classifiers.meta.MinMaxLimits: the percentage leeway for the class range of the lower limit (0-1 = 0-100%).
m_minClusterDensity - Variable in class weka.clusterers.SAXKMeans: The minimum cluster density (according to T2 distance) allowed.
m_MinHandling - Variable in class weka.classifiers.meta.MinMaxLimits: how the lower limit is handled.
m_Minimal - Variable in class weka.attributeSelection.LinearRegressionAttributeEval: Conserve memory?
m_Minimal - Variable in class weka.classifiers.functions.LinearRegressionJ: Conserve memory?
m_MinImprovement - Variable in class weka.classifiers.meta.ClassifierCascade: the minimum improvement between levels that the statistic must improve.
m_Minimum - Variable in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: the minimum.
m_Minimum - Variable in class adams.data.weka.rowfinder.ByNumericValue: the minimum value.
m_Minimum - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: the minimum value.
m_MinimumIncluded - Variable in class adams.data.weka.rowfinder.ByNumericValue: whether the minimum value is included.
m_MinimumIncluded - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: whether the minimum value is included.
m_MinManual - Variable in class weka.classifiers.meta.MinMaxLimits: the manual limit for the lower limit.
m_minNumInstances - Variable in class weka.classifiers.trees.m5.M5Base2: The minimum number of instances to allow at a leaf node
m_MinProbability - Variable in class weka.classifiers.meta.AbstainMinimumProbability: the minimum probability that the classification must meet (0-1).
m_MinProbability - Variable in class weka.classifiers.meta.ThresholdedBinaryClassification: the minimum probability for the label.
m_Mins - Variable in class weka.classifiers.meta.AbstainAverage
m_Mins - Variable in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
m_Mins - Variable in class weka.classifiers.meta.AbstainVote
m_MinSamples - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: the minimum number of samples.
m_MinWidth - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased: the minimum width encountered.
m_MinZeroes - Variable in class weka.filters.unsupervised.instance.RemoveWithZeroes: the minimum number of zeroes that a row must have.
m_Missing - Variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: for replacing missing values
m_Missing - Variable in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS: for replacing missing values
m_Missing - Variable in class adams.tools.CompareDatasets: the output file for missing tests (CSV format).
m_Missing - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: The filter used to get rid of missing values.
m_Missing - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: The filter used to get rid of missing values.
m_Missing - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: The filter used to get rid of missing values.
m_Missing - Variable in class weka.classifiers.functions.GPD: The filter used to get rid of missing values.
m_MissingColor - Variable in class adams.gui.visualization.instances.AttributeValueCellRenderer: the color for missing values
m_MissingColorSelected - Variable in class adams.gui.visualization.instances.AttributeValueCellRenderer: the color for selected missing values
m_MissingFilter - Variable in class weka.classifiers.functions.LinearRegressionJ: The filter for removing missing values.
m_MissingLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel: Displays the number of missing values
m_Model - Variable in class adams.flow.condition.bool.WekaClassification: the model that was loaded from the model file.
m_Model - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: the model that was loaded from the model file.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: the table model.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: the model.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: the model that is being built.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: the fake model.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: the current model.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: the current model.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: the current model.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: the current model.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: the model.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: the current model.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: the model.
m_Model - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: The table model containing attribute names and selection status
m_Model - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: the model.
m_Model - Variable in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: the model.
m_Model - Variable in class adams.ml.model.classification.WekaClassificationModel: the underlying model.
m_Model - Variable in class adams.ml.model.clustering.WekaClusteringModel: the underlying model.
m_Model - Variable in class adams.ml.model.regression.WekaRegressionModel: the underlying model.
m_Model - Variable in class weka.attributeSelection.AbstractPLSAttributeEval: the underlying model.
m_Model - Variable in class weka.attributeSelection.LinearRegressionAttributeEval: the underlying model.
m_Model - Variable in class weka.classifiers.functions.GeneticAlgorithm: the final model.
m_ModelActor - Variable in class adams.flow.condition.bool.WekaClassification: the callable actor to get the model from.
m_ModelAttributesColor - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the color attribute model.
m_ModelAttributesID - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the attribute model.
m_ModelBuilt - Variable in class weka.classifiers.functions.LinearRegressionJ: Model already built?
m_ModelClass - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: the class attribute model.
m_ModelCommonIDs - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the model with the common IDs.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the datasets model.
m_ModelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the datasets model.
m_ModelEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the model with the available evaluations.
m_ModelEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the model with the available evaluations.
m_ModelEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the model with the available evaluations.
m_ModelEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the model with the available evaluations.
m_ModelFile - Variable in class adams.flow.condition.bool.WekaClassification: the serialized model to load.
m_ModelFileChooser - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: the file chooser for models.
m_ModelFileChooser - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: the file chooser for models.
m_ModelFileChooser - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: the file chooser for models.
m_ModelFirstDataset - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the first dataset model.
m_ModelFirstID - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the first ID attribute model.
m_ModelIDs - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the model with the IDs.
m_ModelLoader - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: the model loader.
m_ModelLoader - Variable in class adams.flow.transformer.WekaFilter: the model loader.
m_ModelMetric - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the model for the metric.
m_ModelName - Variable in class weka.classifiers.functions.PyroProxy: the model name.
m_ModelResetVariable - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: the variable to monitor for changes, triggering resets of the model.
m_ModelSecondDataset - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the second dataset model.
m_ModelSecondID - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the second ID attribute model.
m_ModelSetups - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the model with the available setups.
m_Modified - Variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: whether the data has been modified.
m_Modified - Variable in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: whether the setup has been modified.
m_ModifiedSearchMethod - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter
m_Monitor - Variable in class adams.gui.tools.wekainvestigator.data.FileContainer: the file monitor to use.
m_More - Variable in class weka.classifiers.trees.RandomRegressionForest.Node
m_Morphologies - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: the morphologies to apply.
m_Multiplier - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev: the multiplier for the standard deviation.
m_myInstances - Variable in class weka.core.neighboursearch.PCANNSearch
m_myInstances - Variable in class weka.core.neighboursearch.TransformNNSearch: Transformed instances.
m_n - Variable in class weka.core.SAXDistance: pre-sax number of attributes.
m_N - Variable in class weka.filters.supervised.attribute.YGradientEPO: Number of eigenvectors to keep.
m_name - Variable in class adams.opt.optimise.genetic.PackDataDef.DataInfo
m_Name - Variable in class adams.data.weka.classattribute.ByExactName: the string to match the attribute names against.
m_Name - Variable in class adams.data.weka.columnfinder.ByExactName: the string to match the attribute names against.
m_Name - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: the name of the item.
m_Name - Variable in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer: the column name.
m_NameLowerCase - Variable in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer: the lower case name.
m_Names - Variable in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: the names for the fusion subsets.
m_NameServer - Variable in class weka.classifiers.functions.PyroProxy: the Pyro nameserver.
m_NameServerActor - Variable in class weka.classifiers.functions.PyroProxy: the nameserver actor.
m_NameServerProxy - Variable in class weka.classifiers.functions.PyroProxy: the nameserver.
m_NameSuffix - Variable in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem: the name suffix to use (optional).
m_neighbours - Variable in class weka.core.neighboursearch.NewNNSearch
m_NestedItems - Variable in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem: nested result items.
m_NewFilter - Variable in class adams.data.conversion.SwapPLS: the new PLS filter.
m_NextInstance - Variable in class adams.flow.source.WekaDatabaseReader: the next instance to output.
m_NIPALS - Variable in class adams.data.instancesanalysis.pls.NIPALS: the actual algorithm.
m_NNSearch - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: The nearest neighbour search algorithm to use.
m_NoCheck - Variable in class adams.flow.transformer.WekaExperiment: whether not to check for experiment file to exist (e.g., when it generated on the fly).
m_NoCleanUp - Variable in class adams.gui.tools.wekainvestigator.data.DataContainerList: whether to suppress automatic cleanup.
m_node - Variable in class weka.classifiers.trees.RandomModelTrees
m_Node - Variable in class weka.classifiers.trees.RandomRegressionForest: the generated nodes
m_Nominal - Variable in class weka.classifiers.meta.ClassifierCascade: whether regression or classification.
m_NominalToBinary - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: The filter used to make attributes numeric.
m_NominalToBinary - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: The filter used to make attributes numeric.
m_NominalToBinary - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: The filter used to make attributes numeric.
m_NominalToBinary - Variable in class weka.classifiers.functions.GPD: The filter used to make attributes numeric.
m_NominalToBinaryFilter - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Filter for turning nominal values into numeric ones.
m_NonInteractive - Variable in class adams.flow.source.WekaSelectDataset: whether to automate the actor.
m_NonInteractive - Variable in class adams.flow.transformer.WekaChooseAttributes: whether to automate the actor.
m_NoReplacement - Variable in class weka.classifiers.meta.VotedImbalance: Whether to perform sampling with replacement or without.
m_norm - Variable in class weka.core.SAXDistance: suid.
m_norm - Variable in class weka.core.WeightedEuclideanDistance
m_norm - Variable in class weka.core.WeightedEuclideanDistanceRidge
m_NormaliseType - Variable in class weka.classifiers.trees.XGBoost: Type of normalisation algorithm.
m_Normalize - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges: whether to normalize the data.
m_NormalPlotOptions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: options for the normal plot
m_NormYWeights - Variable in class adams.data.instancesanalysis.pls.NIPALS: Flag to normalize Y weights
m_Notes - Variable in class adams.data.instance.Instance: the notes for the chromatogram.
m_Notes - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: the notes for the experiment.
m_NotificationEnabled - Variable in class adams.gui.visualization.instances.InstancesTableModel: whether notification is enabled
m_NoUpdate - Variable in class weka.classifiers.lazy.LWLDatasetBuilder: whether to suppress the update of the nearest-neighbor search algorithm when making predictions.
m_NoUpdate - Variable in class weka.classifiers.lazy.LWLSynchro: whether to suppress the update of the nearest-neighbor search algorithm when making predictions.
m_NoUpdate - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter: whether to suppress the update of the nearest-neighbor search algorithm when making predictions.
m_NoUpdate - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: whether to suppress the update of the nearest-neighbor search algorithm when making predictions.
m_NthPoint - Variable in class weka.filters.unsupervised.attribute.DownSample: the nth point.
m_NumAttribs - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Number of attributes.
m_NumAttributes - Variable in class adams.data.instancesanalysis.PCA: the number of attributes in the data (excl class).
m_NumAttributesLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel: Displays the number of attributes
m_NumBalanced - Variable in class weka.classifiers.meta.VotedImbalance: the number of balanced datasets to generate.
m_NumberInSubset - Variable in class weka.filters.unsupervised.instance.KennardStone: Number of spectra to select in subset
m_NumberOfParallelTrees - Variable in class weka.classifiers.trees.XGBoost: The number of parallel trees constructed during each iteration.
m_NumberOfRounds - Variable in class weka.classifiers.trees.XGBoost: The number of boosting rounds to perform.
m_NumberOfThreads - Variable in class weka.classifiers.trees.XGBoost: The number of threads to use.
m_NumBins - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges: the number of bins in case of manual bin calculation.
m_numbits - Variable in class adams.opt.genetic.Hermione
m_NumChrom - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: number of chromosomes.
m_NumClusters - Variable in class weka.clusterers.SAXKMeans: number of clusters to generate.
m_NumCoefficients - Variable in class adams.data.instancesanalysis.pls.SIMPLS: the number of coefficients in W to keep (0 keep all).
m_NumComponents - Variable in class adams.data.instancesanalysis.pls.AbstractPLS: the maximum number of components to generate
m_NumComponents - Variable in class weka.attributeSelection.AbstractPLSAttributeEval: the number of components parameter.
m_NumCycles - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: the number of cycles to apply.
m_NumDecimals - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges: the number of decimals to show.
m_NumDecimals - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: the number of decimals to use.
m_NumDecimals - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: the number of decimals to round to.
m_NumDecimals - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: the number of decimals to round to.
m_numericClassifyThreshold - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: The threshold for deciding when a numeric value is correctly classified
m_numericClassifyThreshold - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: The threshold for deciding when a numeric value is correctly classified
m_numericClassifyThresholdAbs - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: if Absolute error is less than this, then we're ok
m_numericClassifyThresholdAbs - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: if Absolute error is less than this, then we're ok
m_NumEvaluationBins - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: the number of evaluation bins.
m_NumExecutionSlots - Variable in class weka.classifiers.meta.SubsetEnsemble: The number of threads to have executing at any one time
m_NumExecutionSlots - Variable in class weka.classifiers.meta.VotedImbalance: The number of threads to have executing at any one time
m_NumFolds - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: the number of folds.
m_NumFolds - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: the number of folds.
m_NumFolds - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: the number of folds.
m_NumFolds - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator: the number of folds.
m_NumFolds - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: the number of folds.
m_NumFolds - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: the number of folds.
m_NumFolds - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: the number of folds.
m_NumFolds - Variable in class weka.classifiers.meta.ClassifierCascade: the number of folds for cross-validation.
m_NumFolds - Variable in class weka.filters.supervised.instance.RemoveOutliers: the number of folds to use.
m_NumGenes - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: number of genes per chromosome.
m_numInstances - Variable in class weka.classifiers.trees.m5.RuleNode2: the number of instances reaching this node
m_NumInstances - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Number of instances.
m_NumInstancesLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel: Displays the number of instances
m_numIterations - Variable in class weka.classifiers.trees.RandomModelTrees: The number of iterations.
m_NumIterations - Variable in class weka.classifiers.trees.RandomRegressionForest: The number of iterations.
m_NumLabels - Variable in class weka.classifiers.meta.AbstainMinimumProbability: the number of class labels.
m_NumNumericAttributes - Variable in class weka.filters.unsupervised.instance.RemoveWithZeroes: the number of numeric attributes in the dataset.
m_numOfCleansingIterations - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: The maximum number of cleansing iterations to perform (<1 = until fully cleansed)
m_numOfCleansingIterations - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: The maximum number of cleansing iterations to perform (<1 = until fully cleansed)
m_numOfCrossValidationFolds - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: The number of cross validation folds to perform (<2 = no cross validation)
m_numOfCrossValidationFolds - Variable in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: The number of cross validation folds to perform (<2 = no cross validation)
m_numParameters - Variable in class weka.classifiers.trees.m5.RuleNode2: the number of paramters in the chosen model for this node---either the subtree model or the linear model.
m_NumPoints - Variable in class weka.filters.unsupervised.attribute.AndrewsCurves: the number of data points.
m_NumPoints - Variable in class weka.filters.unsupervised.attribute.EquiDistance: the number of points to output ("-1" uses the same amount of points as currently in the data).
m_NumPoints - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay2: the number of points to the left of a data point.
m_NumPointsLeft - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay: the number of points to the left of a data point.
m_NumPointsRight - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay: the number of points to the right of a data point.
m_NumPredictions - Variable in class adams.flow.transformer.WekaAccumulatedError: the number of overall predictions.
m_NumRandomFeatures - Variable in class weka.classifiers.meta.SubsetEnsemble: the number of random features to use (in addition to base attribute).
m_numreg - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_numreg - Variable in class weka.classifiers.meta.LeastMedianSq
m_NumRows - Variable in class adams.data.conversion.WekaCapabilitiesToInstances: the number of data rows to generate.
m_NumSimplsCoefficients - Variable in class adams.data.instancesanalysis.pls.PRM: the number of SIMPLS coefficients.
m_NumSubSamples - Variable in class adams.flow.transformer.WekaBootstrapping: the number of random sub-samples to generate.
m_NumThreads - Variable in class adams.flow.transformer.WekaClassifierRanker: the number of threads to use for parallel execution.
m_NumThreads - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator: the number of threads to use for parallel execution.
m_NumThreads - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: the number of threads to use for parallel execution.
m_NumThreads - Variable in class adams.multiprocess.WekaCrossValidationExecution: the number of threads to use for parallel execution (only used if no JobRunnerSetup/JobRunner set).
m_NumThreads - Variable in class weka.classifiers.meta.ClassifierCascade: the number of threads to use.
m_NumThreads - Variable in class weka.filters.supervised.instance.RemoveOutliers: the number of threads to use for parallel execution.
m_NumTokensAccepted - Variable in class adams.gui.visualization.instance.SimpleInstancePanelUpdater: the number of tokens accepted.
m_NumTrain - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: The number of training instances
m_NumTrain - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: The number of training instances
m_NumTrain - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: The number of training instances
m_NumTrain - Variable in class weka.classifiers.functions.GPD: The number of training instances
m_numTrials - Variable in class weka.classifiers.trees.RandomModelTrees
m_NumZeroes - Variable in class weka.filters.unsupervised.instance.RemoveWithZeroes: the number (or percentage) of zeroes that the row must contain to be removed.
m_Objective - Variable in class weka.classifiers.trees.XGBoost: The learning objective.
m_Offline - Variable in class adams.data.instances.AbstractInstanceGenerator: whether to operate in offline mode.
m_ok - Variable in class weka.classifiers.meta.AbstainAttributePercentile
m_ok - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_OldFilter - Variable in class adams.data.conversion.SwapPLS: the old PLS filter.
m_OldFilterCommandLine - Variable in class adams.data.conversion.SwapPLS: the command-line of the old filter.
m_OneDrop - Variable in class weka.classifiers.trees.XGBoost: Whether to always drop at least one tree during dropout.
m_OneMissing - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes: what to do if one value is missing.
m_OneMissing - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: what to do if one value is missing.
m_OnlyFirstBatch - Variable in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Whether to only apply during first batch.
m_OnlyNominal - Variable in enum adams.flow.core.EvaluationStatistic: whether applies only to nominal classes or not.
m_OnTheFly - Variable in class adams.flow.condition.bool.WekaClassification: whether the model gets built on the fly and might not be present at the start.
m_OnTheFly - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: whether the model gets built on the fly and might not be present at the start.
m_OnTheFly - Variable in class adams.flow.transformer.WekaReorderAttributesToReference: whether the dataset gets generated on the fly and might not be available at setUp time.
m_Operation - Variable in class adams.flow.transformer.WekaInstanceBuffer: the way the buffer operates.
m_OPLS - Variable in class adams.data.instancesanalysis.pls.OPLS: the actual algorithm.
m_Optimizer - Variable in class adams.flow.transformer.WekaClassifierOptimizer: the classifier optimizer.
m_Optional - Variable in class adams.flow.transformer.WekaGeneticAlgorithm: whether the callable actor is optional.
m_original - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter
m_OriginalIndices - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: the original indices.
m_OriginalIndices - Variable in class adams.multiprocess.WekaCrossValidationExecution: the original indices.
m_OriginalIndices - Variable in class weka.classifiers.AbstractSplitGenerator: the original indicies.
m_OtherIndices - Variable in class weka.filters.supervised.attribute.MultiPLS: the indices of the other attributes.
m_OtherLabel - Variable in class weka.classifiers.meta.ThresholdedBinaryClassification: the index of the other label.
m_OtherParameters - Variable in class weka.classifiers.trees.XGBoost: Allows the user to enter arbitrary parameters.
m_Output - Variable in class adams.flow.transformer.AbstractWekaClassifierEvaluator: for generating predictions output.
m_Output - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationOutput: the output to generate.
m_Output - Variable in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob: the output to use.
m_Output - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: for collecting the output.
m_Output - Variable in class adams.multiprocess.WekaCrossValidationExecution: for generating predictions output.
m_outputAdditionalStats - Variable in class weka.attributeSelection.LinearRegressionAttributeEval: Whether to output additional statistics such as std.
m_outputAdditionalStats - Variable in class weka.classifiers.functions.LinearRegressionJ: Whether to output additional statistics such as std.
m_outputAdditionalStats - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Whether to output additional statistics such as std.
m_OutputArray - Variable in class adams.flow.source.AbstractWekaSetupGenerator: whether to output an array or a sequence of setups.
m_OutputBestSetup - Variable in class adams.flow.transformer.WekaClassifierRanker: whether to output the best setup in case of GridSearch/MultiSearch.
m_OutputBestSetup - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: whether to output the best classifier.
m_OutputBuffer - Variable in class adams.flow.transformer.AbstractWekaClassifierEvaluator: the buffer for the predictions.
m_OutputBuffer - Variable in class adams.multiprocess.WekaCrossValidationExecution: the buffer for the predictions.
m_OutputContainer - Variable in class adams.flow.transformer.WekaFilter: whether to output a container.
m_OutputDirectory - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the directory to store the generated ARFF files in.
m_OutputDirectory - Variable in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: the directory to store the generated ARFF files in.
m_OutputDistribution - Variable in class adams.flow.transformer.wekaclusterer.AddCluster: output distribution instead of cluster index.
m_OutputFile - Variable in class adams.flow.sink.WekaExperimentGenerator: the file to store the experiment in.
m_OutputFile - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: the output file.
m_OutputFile - Variable in class adams.tools.CompareDatasets: the output file (CSV format).
m_OutputFile - Variable in class weka.core.converters.SimpleArffSaver: the file to write to.
m_OutputFile - Variable in class weka.core.converters.SpreadSheetSaver: the file to write to.
m_OutputFormat - Variable in class adams.data.instancesanalysis.pls.AbstractPLS: the output format.
m_OutputFormat - Variable in class adams.flow.source.wekapackagemanageraction.ListPackages: the output format.
m_OutputFormat - Variable in class adams.flow.transformer.WekaExperimentEvaluation: the output format.
m_OutputFormat - Variable in class adams.flow.transformer.WekaInstanceDumper: the output format.
m_OutputFormat - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: the output format.
m_OutputGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem: the originating output generator.
m_OutputGenerator - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane: the output generator used.
m_OutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the output generators to use.
m_OutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the output generators to use.
m_OutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the output generators to use.
m_OutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the output generators to use.
m_OutputGenerators - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the output generators to use.
m_OutputHeader - Variable in class adams.data.instances.AbstractInstanceGenerator: the generated header.
m_OutputHeader - Variable in class adams.flow.transformer.WekaExperimentEvaluation: whether to output the header.
m_OutputHeader - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: whether to output the header.
m_OutputIndices - Variable in class adams.flow.transformer.WekaAttributeIterator: whether to output indices instead of the strings.
m_OutputInstance - Variable in class adams.flow.transformer.WekaClassifying: whether to output weka.core.Instance objects or PredictionContainers.
m_OutputModel - Variable in class adams.flow.transformer.WekaTestSetClustererEvaluator: whether to output the model as well.
m_OutputModel - Variable in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator: whether to output the model as well.
m_OutputNominal - Variable in class weka.filters.unsupervised.attribute.SAX: If true output nominal, false output numeric .
m_OutputNumAtts - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: The number of attributes in the pc transformed data.
m_OutputOnlyModel - Variable in class adams.flow.transformer.AbstractWekaModelReader: whether to only output the model.
m_OutputPrefix - Variable in class adams.flow.transformer.WekaInstanceDumper: the output prefix.
m_OutputPrefixType - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the type of prefix to use for the output.
m_OutputRelationName - Variable in class adams.flow.transformer.WekaEvaluationSummary: whether to print the relation name of the dataset a well.
m_OutputType - Variable in class adams.flow.transformer.WekaFileReader: how to output the data.
m_OutputType - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the type of output to generate.
m_OutText - Variable in class weka.gui.explorer.ExperimentPanel: The output area for classification results.
m_Overlays - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: the overlays to use.
m_Override - Variable in class adams.flow.transformer.WekaClassSelector: whether to override any set class attribute.
m_OverrideJobRunner - Variable in class adams.flow.transformer.WekaExperimentExecution: whether to override the jobrunner in the experiment.
m_Owner - Variable in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.job.InvestigatorJob: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.source.AbstractSource: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.InvestigatorTabbedPane: the owner.
m_Owner - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: the owner.
m_Owner - Variable in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel: the owner.
m_Owner - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel.HistoryPanel: the owner.
m_Owner - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: the owner.
m_Owner - Variable in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: the experimenter this runner belongs to.
m_Owner - Variable in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel: the setup panel this option panel belongs to.
m_Owner - Variable in class adams.gui.visualization.instance.InstanceContainerManager: the owning panel.
m_Owner - Variable in class adams.gui.visualization.instance.InstancePointHitDetector: the owner of this detector.
m_Owner - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: the owning sort panel.
m_Owner - Variable in class adams.ml.data.DataCellView: the owning row.
m_Owner - Variable in class adams.ml.data.InstanceView: the owner.
m_P - Variable in class adams.data.instancesanalysis.pls.PLS1: the P matrix
m_packed - Variable in class adams.opt.optimise.genetic.PackDataDef
m_Padding - Variable in class weka.filters.unsupervised.attribute.FastWavelet: the type of padding.
m_PaddingType - Variable in class weka.filters.unsupervised.attribute.FFT: the type of padding to use.
m_Paintlet - Variable in class adams.flow.sink.WekaInstanceViewer: the paintlet to use.
m_Paintlet - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: the paintlet.
m_Paintlet - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: the paintlet to use.
m_Panel - Variable in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog: the setup panel.
m_Panel - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel: the currently output panel.
m_Panel - Variable in class weka.gui.explorer.ExplorerEntryPanel: the panel to display the results in.
m_PanelAnalysis - Variable in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel: the current panel.
m_PanelAnalysis - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the analysis panel.
m_PanelAtt - Variable in class adams.flow.sink.WekaAttributeSummary: the visualization panel (if only one in range).
m_PanelAttSelection - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the attribute selection panel.
m_PanelAttSummary - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the attribute summary panel.
m_PanelAttVisualization - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the attribute visualization panel.
m_PanelBoth - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the panel for displaying the two instances.
m_PanelButtons - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: the panel for the buttons.
m_PanelButtons - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage: the panel for the buttons.
m_PanelButtons - Variable in class weka.gui.explorer.MultiExplorer: the panel for the buttons.
m_PanelButtons - Variable in class weka.gui.explorer.SqlPanel: the panel for the buttons
m_PanelChooser - Variable in class adams.gui.tools.weka.AbstractPanelWithFile: the chooser panel.
m_PanelClassAttribute - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: the panel for the class attribute heuristic.
m_PanelClassifiers - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: for specifying the classifiers.
m_PanelClassifiers - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: for specifying the classifiers.
m_PanelColorProvider - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the color provider.
m_PanelComboBox - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel: the panel for the combobox.
m_PanelComboBoxData - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the panel for the combobox listing the datasets.
m_PanelCompare - Variable in class adams.gui.InstanceCompare: the panel for comparing the datasets.
m_PanelComparison - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the overall panel for comparison.
m_PanelComparison - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the panel for displaying the two instances.
m_PanelComponents - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the components plot.
m_PanelCurve - Variable in class adams.gui.tools.weka.CostCurvePanel: for displaying the cost curve.
m_PanelData - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: the panel with the data.
m_PanelData - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the panel for the data.
m_PanelData - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the panel holding the table and buttons for the dataset.
m_PanelDataAction - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the panel with buttons etc.
m_PanelDataset - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: the panel for loading the file.
m_PanelDataset1 - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the panel for the first dataset.
m_PanelDataset2 - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the panel for the second dataset.
m_PanelDatasets - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the panel for the datasets.
m_PanelDatasets - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: for specifying the datasets.
m_PanelDatasets - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: for specifying the datasets.
m_PanelDefinitions - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: the panel holding the defintion panels.
m_PanelDifference - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the panel with the difference.
m_PanelDifference - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the panel with the difference.
m_PanelEditor - Variable in class adams.gui.goe.WekaExperimentFileEditor: the editor panel.
m_PanelEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the panel with the evaluation.
m_PanelEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the panel with the evaluation.
m_PanelEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the panel with the evaluation.
m_PanelEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the panel with the evaluation.
m_PanelEvaluation - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the panel with the evaluation.
m_PanelEvaluationSetup - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the panel for the evaluation setup to be embedded in.
m_PanelEvaluationSetup - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the panel for the evaluation setup to be embedded in.
m_PanelEvaluationSetup - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the panel for the evaluation setup to be embedded in.
m_PanelEvaluationSetup - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the panel for the evaluation setup to be embedded in.
m_PanelEvaluator - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the GOe with the evaluator.
m_PanelExecutionButtons - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the panel with the buttons.
m_PanelExecutionButtons - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the panel with the buttons.
m_PanelExecutionButtons - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the panel with the buttons.
m_PanelExecutionButtons - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the panel with the buttons.
m_PanelExecutionButtons - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the panel with the buttons.
m_PanelExplorer - Variable in class weka.gui.explorer.MultiExplorer: the actual panel for displaying the other panels.
m_PanelFile - Variable in class adams.gui.goe.WekaExperimentFileEditor: the panel for selecting the experiment file.
m_PanelFile - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: the preditions file.
m_PanelFile - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: the chooser panel for the indexed splits file.
m_PanelFile - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel: the file chooser panel.
m_PanelFile - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel: the file chooser panel.
m_PanelFile - Variable in class adams.gui.wizard.WekaSelectDatasetPage: the panel for selecting the file.
m_PanelFilter - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: the filter panel.
m_PanelGenerator - Variable in class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns: the GOE panel for the generator.
m_PanelGenerator - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: the fold generator.
m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the GOe with the associator.
m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the GOe with the classifier.
m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the GOe with the clusterer.
m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the GOe with the classifier.
m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the algorithm.
m_PanelGOE - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the GOe with the filter.
m_PanelGOE - Variable in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: the GOE for setting up classifiers.
m_PanelGOE - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel: the GOE panel.
m_PanelHistory - Variable in class weka.gui.explorer.MultiExplorer: the history panel.
m_PanelICA - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the ICA setup.
m_PanelInstance - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the plot.
m_PanelInstance - Variable in class adams.gui.visualization.instance.InstanceExplorer: the panel for displaying.
m_PanelInstSummary - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the instances summary panel.
m_PanelJobRunner - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: the JobRunner setup.
m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the panel on the left-hand side.
m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the panel on the left-hand side.
m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the panel on the left-hand side.
m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the panel on the left-hand side.
m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the panel on the left-hand side.
m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the left panel.
m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the left panel.
m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the left panel.
m_PanelLeft - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the left panel.
m_PanelLeft - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the panel on the left.
m_PanelLoadings - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the loadings plot.
m_PanelLoadings - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the loadings plot.
m_PanelLog - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the log panel.
m_PanelMain - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the panel for the preprocess panels.
m_PanelMatrix - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the GOE for the result matrix.
m_PanelModel - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: the serialized model.
m_PanelModel - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: the serialized model.
m_PanelModel - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: the serialized model.
m_PanelModel - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: the serialized model.
m_PanelOptions - Variable in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: the panel with the options.
m_PanelOutput - Variable in class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns: the chooser panel for the output file.
m_PanelOutput - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: the panel for the output type.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: the panel with the parameters.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the parameter panel.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the parameter panel.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the parameter panel.
m_PanelParameters - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the parameter panel.
m_PanelParameters - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: for listing all the options.
m_PanelParameters - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: for listing all the options.
m_PanelParametersAdvanced - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: the panel with the advanced parameters.
m_PanelQuery - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: the query panel.
m_PanelReader - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: the GOE panel for the indexed splits reader.
m_PanelResultsHandler - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: the panel for the results handler.
m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the panel on the right-hand side (displays results).
m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the panel on the right-hand side (displays results).
m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the panel on the right-hand side (displays results).
m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the panel on the right-hand side (displays results).
m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the panel on the right-hand side (displays results).
m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the right panel.
m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the right panel.
m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the right panel.
m_PanelRight - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the right panel.
m_PanelRight - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the panel on the right.
m_Panels - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: the panels currently being displayed.
m_Panels - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: the panels currently being displayed.
m_Panels - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel: the map for panel name / panel object relation.
m_Panels - Variable in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: the list of definitions to use.
m_PanelScores - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the scores plot.
m_PanelScores - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the scores plot.
m_PanelSearch - Variable in class adams.gui.tools.wekainvestigator.output.TableContentPanel: the search panel.
m_PanelSearch - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the GOe with the search.
m_PanelSearch - Variable in class adams.gui.visualization.instances.InstancesPanel: the search panel.
m_PanelSearchID - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the search panel for the IDs.
m_PanelSetup - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the panel for the execution setup to be embedded in.
m_PanelSetup - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the current setup panel.
m_PanelSheet - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage: the parameter panel for displaying the parameters.
m_PanelSources - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the sources plot.
m_PanelsResults - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the results panels.
m_PanelStructure - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the panel for the structure.
m_PanelTester - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the GOE for the tester.
m_PanelTextAction - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the panel with buttons etc.
m_PanelTextAll - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the panel for the text tab.
m_PanelTop - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the panel for the filter and the buttons.
m_PanelWeights - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the plot of the loadings.
m_panelWidth - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel.BarCalc
m_PanelWriter - Variable in class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns: the GOE panel for the writer.
m_PanelZoomOverview - Variable in class adams.gui.visualization.instance.InstancePanel: the zoom overview panel.
m_Parameters - Variable in class adams.gui.menu.AbstractParameterHandlingWekaMenuItemDefinition: the additional parameters.
m_Params - Variable in class weka.classifiers.trees.XGBoost: the xgboost parameters.
m_ParentComponentActor - Variable in class adams.flow.source.WekaSelectDataset: the (optional) parent component to use.
m_ParentComponentActorConfigured - Variable in class adams.flow.source.WekaSelectDataset: whether the callable actor has been configured.
m_Parser - Variable in class weka.classifiers.functions.MathExpressionClassifier: the expression parser to use.
m_Password - Variable in class adams.flow.sink.WekaDatabaseWriter: the password for the user used for connecting.
m_Password - Variable in class adams.flow.source.WekaDatabaseReader: the password for the user used for connecting.
m_Password - Variable in class adams.gui.tools.wekainvestigator.data.DatabaseContainer: the password.
m_Pattern - Variable in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens: the pattern in use.
m_PatternRegEx - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: The current regular expression.
m_PauseStateManager - Variable in class adams.flow.transformer.WekaGeneticAlgorithm: the pause state manager.
m_pca - Variable in class weka.core.neighboursearch.PCANNSearch: The neighbourhood of instances to find neighbours in.
m_pctile - Variable in class weka.classifiers.meta.AbstainAttributePercentile
m_pdd - Variable in class adams.opt.genetic.PackDataGeneticAlgorithm
m_pdd - Variable in class adams.opt.optimise.genetic.PackData
m_pdd - Variable in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm
m_pdd - Variable in class adams.opt.optimise.GeneticAlgorithm
m_Percent - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst: the percentage of the worst predictions to remove (0-1).
m_Percentage - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: the percentage.
m_Percentage - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: the percentage.
m_Percentage - Variable in class adams.flow.transformer.WekaBootstrapping: the size for the sub-samples (0-1).
m_Percentage - Variable in class adams.flow.transformer.WekaRandomSplit: the percentage for the split (0-1).
m_Percentage - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: the split percentage.
m_Percentage - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: the percentage.
m_Percentage - Variable in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: the percentage.
m_Percentage - Variable in class weka.classifiers.DefaultRandomSplitGenerator: the percentage.
m_Percentage - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: the percentage.
m_Percentage - Variable in class weka.classifiers.GroupedRandomSplitGenerator: the percentage.
m_Percentiles - Variable in class adams.flow.transformer.WekaBootstrapping: the percentiles to output (0-1).
m_Performance - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: the performance.
m_PerformTraining - Variable in class weka.classifiers.functions.PyroProxy: whether to perform training.
m_periodicPruningRate - Variable in class weka.clusterers.SAXKMeans: Prune low-density candidate canopies after every x instances have been seen (if using canopy clustering)
m_PlotCache - Variable in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab: the cache for the plots.
m_PlotInstances - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator: the underlying data.
m_PlotName - Variable in class adams.flow.transformer.WekaAccumulatedError: the name of the plot.
m_PlotShapes - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator: for storing the plot shapes.
m_PlotSizes - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator: for storing the plot sizes.
m_PLS - Variable in class weka.classifiers.trees.RandomRegressionForest: the number of components to use in PLS
m_PLS - Variable in class weka.filters.supervised.attribute.MultiPLS: the PLS algorithms corresponding to the Y attributes.
m_plsfilter - Variable in class weka.core.neighboursearch.PLSNNSearch: The neighbourhood of instances to find neighbours in.
m_PLSFilter - Variable in class weka.classifiers.trees.RandomRegressionForest: the PLS filter used internally
m_PolynomialOrder - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay: the polynomial order.
m_PolynomialOrder - Variable in class weka.filters.unsupervised.attribute.SavitzkyGolay2: the polynomial order.
m_PopupMenu - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: the popup menu for the recent items.
m_Positions - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis: the new positions for the attributes.
m_PostProcessor - Variable in class adams.flow.transformer.WekaClustererPostProcessor: the post-processor.
m_PostProcessor - Variable in class adams.flow.transformer.WekaEvaluationPostProcessor: the post-processor to use.
m_PostProcessor - Variable in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob: the postprocessor.
m_PostProcessor - Variable in class adams.flow.transformer.WekaTrainClusterer: the post-processor.
m_PostProcessors - Variable in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor: the post-processors to apply.
m_PostProcessors - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor: the post-processors to combine.
m_PostTokenizer - Variable in class weka.core.tokenizers.PreCleanedTokenizer: the post tokenizer to use.
m_Predicted - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions: the column with the predicted values.
m_Predicted - Variable in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure: the collected predicted.
m_Predicted - Variable in class weka.classifiers.functions.FromPredictions: the column with the predicted values.
m_PredictedIndex - Variable in class weka.classifiers.functions.FromPredictions: the predicted column index.
m_PredictedMax - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: the maximum to use for the predicted values (pos inf = no restriction).
m_PredictedMin - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: the minimum to use for the predicted values (neg inf = no restriction).
m_Prediction - Variable in class adams.flow.transformer.WekaAccumulatedError.SortablePrediction: the wrapped prediction.
m_Predictions - Variable in class adams.flow.transformer.WekaAccumulatedError: the sorted predictions.
m_Predictions - Variable in class weka.classifiers.AggregateEvaluations: the collected predictions.
m_Predictions - Variable in class weka.classifiers.functions.FromPredictions: the actual predictions.
m_PredictionsFile - Variable in class weka.classifiers.functions.FromPredictions: the predictions to use.
m_PredictionType - Variable in class adams.data.instancesanalysis.pls.AbstractPLS: the prediction type to perform.
m_PredictMax - Variable in class weka.classifiers.functions.FakeClassifier: the maximum to use for the predictions.
m_PredictMin - Variable in class weka.classifiers.functions.FakeClassifier: the minimum to use for the predictions.
m_Predictor - Variable in class weka.classifiers.meta.Consensus: the index of the classifier to use for making the actual prediction.
m_Predictor - Variable in class weka.classifiers.trees.XGBoost: The type of predictor algorithm to use.
m_PredictWait - Variable in class weka.classifiers.functions.FakeClassifier: the predict wait time in msec.
m_PreferJobRunner - Variable in class adams.flow.transformer.WekaFilter: whether to offload filtering into a JobRunnerInstance.
m_PreferJobRunner - Variable in class adams.flow.transformer.WekaTestSetEvaluator: whether to offload training into a JobRunnerInstance.
m_PreferJobRunner - Variable in class adams.flow.transformer.WekaTrainAssociator: whether to offload training into a JobRunnerInstance.
m_PreferJobRunner - Variable in class adams.flow.transformer.WekaTrainClassifier: whether to offload training into a JobRunnerInstance.
m_PreferJobRunner - Variable in class adams.flow.transformer.WekaTrainClusterer: whether to offload training into a JobRunnerInstance.
m_PreferJobRunner - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator: whether to offload train/evaluate onto a JobRunnerInstance.
m_PreFilter - Variable in class adams.data.weka.rowfinder.FilteredIQR: the filter to apply to the data first.
m_PreFilter - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter
m_PreFilter - Variable in class weka.filters.FilteredFilter: The pre-filter to apply to the data.
m_PreFilter - Variable in class weka.filters.unsupervised.instance.KennardStone: Pre filter to apply before selection
m_Prefix - Variable in class adams.flow.transformer.WekaInstancesMerge: the additional prefix name to use, apart from the index.
m_Prefix - Variable in class weka.filters.unsupervised.attribute.EquiDistance: the prefix for the new attributes.
m_PrefixDatasetsWithIndex - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: whether to prefix the relation names with the index.
m_PrefixDatasetsWithIndex - Variable in class weka.experiment.ExtExperiment: whether to prefix the relation names with the index.
m_Prefixes - Variable in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: The prefixes.
m_Prefixes - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: The prefixes.
m_PrefixSeparator - Variable in class adams.flow.transformer.WekaInstancesMerge: the separator between index and actual attribute name.
m_Preparation - Variable in class weka.classifiers.meta.SocketFacade: the data preparation to use.
m_Preprocessing - Variable in class weka.core.neighboursearch.PCANNSearch: the type of preprocessing
m_Preprocessing - Variable in class weka.core.neighboursearch.PLSNNSearch: the type of preprocessing
m_PreprocessingType - Variable in class adams.data.instancesanalysis.pls.AbstractPLS: the preprocessing type to perform.
m_PreprocessingType - Variable in class weka.attributeSelection.AbstractPLSAttributeEval: the preprocessing type to perform.
m_PreSelection - Variable in class adams.flow.transformer.WekaChooseAttributes: the regular expression for pre-selecting attributes by name.
m_PreserveIDColumn - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Whether to treat the first attribute as an ID.
m_PreserveOrder - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: whether to preserve the order.
m_PreserveOrder - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: whether to preserve the order.
m_PreserveOrder - Variable in class adams.flow.transformer.WekaRandomSplit: whether to preserve the order.
m_PreserveOrder - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: whether to preserve the order.
m_PreserveOrder - Variable in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: whether to preserve the order.
m_PreserveOrder - Variable in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: whether to preserve the order.
m_PreserveOrder - Variable in class weka.classifiers.DefaultRandomSplitGenerator: whether to preserve the order.
m_PreserveOrder - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: whether to preserve the order.
m_PreserveOrder - Variable in class weka.classifiers.GroupedRandomSplitGenerator: whether to preserve the order.
m_PreserveOrder - Variable in class weka.clusterers.SAXKMeans: Preserve order of instances.
m_PreTokenizer - Variable in class weka.core.tokenizers.PreCleanedTokenizer: the pre tokenizer to use.
m_PRM - Variable in class adams.data.instancesanalysis.pls.PRM: the actual algorithm.
m_Probability - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer: the probability.
m_Processed - Variable in class adams.flow.sink.WekaClassifierErrors.DataGenerator: whether the data has already been processed.
m_Processed - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: temporary filter results when determining output format to avoid duplicate processing of data.
m_Processor - Variable in class adams.flow.transformer.WekaClassifierSetupProcessor: the processor to use.
m_ProcessType - Variable in class weka.classifiers.trees.XGBoost: The type of boosting process to run.
m_Properties - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the properties.
m_Properties - Static variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the properties.
m_Properties - Static variable in class adams.gui.visualization.instance.InstanceComparePanel: the properties.
m_Properties - Static variable in class adams.gui.visualization.instance.InstanceExplorer: the properties.
m_Property - Variable in class adams.core.discovery.genetic.GenericDoubleResolution: the property name.
m_Property - Variable in class adams.core.discovery.genetic.GenericFloatResolution: the property name.
m_Property - Variable in class adams.core.discovery.genetic.GenericInteger: the property name.
m_Property - Variable in class adams.core.discovery.genetic.GenericString: the property name.
m_PropertyDescriptor - Variable in class adams.core.discovery.genetic.GenericDoubleResolution: the property descriptor.
m_PropertyDescriptor - Variable in class adams.core.discovery.genetic.GenericFloatResolution: the property descriptor.
m_PropertyDescriptor - Variable in class adams.core.discovery.genetic.GenericInteger: the property descriptor.
m_PropertyDescriptor - Variable in class adams.core.discovery.genetic.GenericString: the property descriptor.
m_Query - Variable in class adams.flow.source.WekaDatabaseReader: the query to execute.
m_Query - Variable in class adams.gui.tools.wekainvestigator.data.DatabaseContainer: the query used to load the data.
m_Queue - Variable in class adams.flow.transformer.WekaSubsets: the generated subsets.
m_r_hat - Variable in class adams.data.instancesanalysis.pls.PLS1: the regression vector "r-hat"
m_random - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_random - Variable in class weka.classifiers.meta.LeastMedianSq
m_Random - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: the random number generator.
m_Random - Variable in class weka.classifiers.functions.FakeClassifier: for generating the random numbers.
m_Random - Variable in class weka.classifiers.meta.AbstainVote: the random number generator used for breaking ties in majority voting
m_Random - Variable in class weka.filters.unsupervised.attribute.InputSmearing: the random number generator to use.
m_Randomize - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: whether to randomize the data.
m_Randomize - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: whether to randomize the data.
m_Randomize - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: whether to randomize the data.
m_Randomize - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator: whether to randomize the data.
m_Randomize - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: whether to randomize the data.
m_Randomize - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: whether to randomize the data.
m_Randomize - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: whether to randomize the data.
m_Randomize - Variable in class weka.classifiers.LeaveOneOutByValueGenerator: whether to randomize the data.
m_Randomize - Variable in class weka.filters.unsupervised.instance.RemoveDuplicates: whether to randomize the data after the removal.
m_randomseed - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_randomseed - Variable in class weka.classifiers.meta.LeastMedianSq
m_Range - Variable in class adams.data.weka.rowfinder.FilteredIQR: the attribute range to work on.
m_Range - Variable in class adams.flow.sink.WekaAttributeSummary: the attribute to visualize.
m_Range - Variable in class adams.flow.transformer.WekaAttributeIterator: the range of attributes to work on.
m_Range - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: the range of attributes to use.
m_Range - Variable in class weka.classifiers.meta.AbstainAttributePercentile
m_Range - Variable in class weka.filters.unsupervised.attribute.AnyToString: the attribute range to process.
m_Range - Variable in class weka.filters.unsupervised.attribute.EquiDistance: the attribute range to use.
m_Range - Variable in class weka.filters.unsupervised.attribute.StringToDate: the attribute range to process.
m_Range - Variable in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor: the range of attributes to work on.
m_Range - Variable in class weka.filters.unsupervised.instance.SafeRemoveRange: Range of instances requested by the user.
m_Range1 - Variable in class adams.tools.CompareDatasets: the first range of attributes.
m_Range2 - Variable in class adams.tools.CompareDatasets: the second range of attributes.
m_RangePaintlet - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: the paintlet to use for the lower/upper statistic.
m_Ranges - Variable in class adams.data.weka.rowfinder.ByNumericRange: the intervals.
m_Ranges - Variable in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange: the intervals.
m_Ranges - Variable in class weka.classifiers.meta.AbstainAttributePercentile: the ranges (attribute index <-> double[]).
m_Ranges - Variable in class weka.classifiers.meta.PartitionedStacking: the attribute ranges for the base-classifiers.
m_Ranges - Variable in class weka.classifiers.meta.RangeCheck: the ranges (attribute index <-> double[]).
m_Ranges - Variable in class weka.filters.unsupervised.attribute.detrend.RangeBased: the ranges to calculate the intercept/slope for.
m_Ranges - Variable in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased: the ranges to calculate the intercept/slope for.
m_Ranges - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: The attribute ranges.
m_Ranking - Variable in class weka.attributeSelection.AbstractPLSAttributeEval: the determined attribute ranking.
m_Ranking - Variable in class weka.attributeSelection.LinearRegressionAttributeEval: the degtermined attribute ranking.
m_RateDrop - Variable in class weka.classifiers.trees.XGBoost: Dropout rate.
m_RawColumns - Variable in class adams.data.weka.columnfinder.Constant: The raw representation of the columns to find.
m_RawRows - Variable in class adams.data.weka.rowfinder.Constant: The raw form of the rows.
m_Reader - Variable in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer: the reader used to load the data.
m_Reader - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: the spreadsheet reader to use.
m_Reader - Variable in class weka.classifiers.functions.FromPredictions: the spreadsheet reader to use.
m_Reader - Variable in class weka.core.converters.SpreadSheetLoader: the reader to use.
m_ReaderFileFilters - Static variable in class adams.gui.chooser.AdamsExperimentFileChooser: the file filters for the readers.
m_ReaderFileFilters - Static variable in class adams.gui.chooser.WekaFileChooser: the file filters for the readers.
m_ReadOnly - Variable in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: whether the model is read-only.
m_ReadOnly - Variable in class adams.gui.visualization.instances.InstancesTableModel: whether the table is read-only
m_Real - Variable in class weka.filters.unsupervised.attribute.FFT: whether to return complex or real part of the transformation.
m_RecentFilesHandler - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the recent files handler.
m_RecentFilesHandler - Variable in class adams.gui.visualization.instance.InstanceExplorer: the recent files handler.
m_RecentFilesHandler - Variable in class weka.gui.explorer.ExplorerExt: the recent files handler.
m_RecentFilesHandler1 - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the recent files handler.
m_RecentFilesHandler2 - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the recent files handler.
m_RecentFilesHandlerResults - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the recent files handler for results.
m_RecentFilesHandlerSetups - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the recent files handler for setups.
m_RecentStatementsHandler - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: the recent files handler.
m_Reference - Variable in class adams.flow.transformer.WekaReorderAttributesToReference: the reference dataset.
m_ReferenceActor - Variable in class adams.flow.transformer.WekaReorderAttributesToReference: the callable actor to get the reference data from.
m_ReferenceDataset - Variable in class weka.filters.unsupervised.instance.AlignDataset: the file containing the reference dataset.
m_ReferenceError - Variable in class adams.data.weka.predictions.NumericErrorScalerWithReference: the reference error.
m_ReferenceFile - Variable in class adams.flow.transformer.WekaReorderAttributesToReference: the reference dataset to load.
m_ReferenceSize - Variable in class adams.data.weka.predictions.NumericErrorScalerWithReference: the reference size.
m_Regex - Variable in class adams.flow.transformer.WekaRegexToRange: regular expression used to determine attribute list.
m_RegexName - Variable in class adams.flow.transformer.WekaClassSelector: the regular expression on the attribute for selecting the sub-set of attributes.
m_RegExp - Variable in class adams.data.binning.BinnableInstances.StringAttributeGroupExtractor: the regular expression.
m_RegExp - Variable in class adams.data.weka.classattribute.ByName: the regular expression to use on the name.
m_RegExp - Variable in class adams.data.weka.columnfinder.ByName: the regular expression to match the attribute names against.
m_RegExp - Variable in class adams.data.weka.rowfinder.ByLabel: the regular expression to match the labels against.
m_RegExp - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: the regular expression for the nominal/string attribute.
m_RegExp - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: the regular expression for the nominal/string attribute.
m_RegExp - Variable in class adams.flow.transformer.WekaAttributeIterator: the regular expression applied to the attribute names.
m_RegExp - Variable in class adams.flow.transformer.WekaMultiLabelSplitter: the regular expression that the class attribute names have to match.
m_RegExp - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: the regular expression for the nominal/string attribute.
m_RegExp - Variable in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: the regular expression for the nominal/string attribute.
m_RegExp - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: the regular expression for the nominal/string attribute.
m_RegExp - Variable in class weka.classifiers.GroupedRandomSplitGenerator: the regular expression for the nominal/string attribute.
m_RegExp - Variable in class weka.core.InstanceGrouping: the regular expression.
m_RegExp - Variable in class weka.filters.unsupervised.attribute.EquiDistance: the regular expression to use.
m_RegExp - Variable in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: The prefixes.
m_RegExp - Variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: the regular expression for the nominal/string attribute.
m_RegExps - Variable in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: the regular expressions to identify fusion subsets.
m_RegExps - Variable in class weka.classifiers.MultiLevelSplitGenerator: the regular expressions to apply to determine the grouping.
m_Registered - Static variable in class adams.gui.goe.WekaEditorsRegistration: whether registration already occurred.
m_regressionTree - Variable in class weka.classifiers.trees.m5.M5Base2: Make a regression tree/rule instead of a model tree/rule
m_RelationName - Variable in class adams.flow.source.WekaNewInstances: the name for the relation, if any.
m_RelationName - Variable in class adams.flow.transformer.WekaCrossValidationSplit: the format of the relation names of the generated datasets.
m_RelationName - Variable in class weka.classifiers.AggregateEvaluations: dataset name.
m_RelationName - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: the template for the relation name.
m_RelationName - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator: the template for the relation name.
m_RelationName - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: the template for the relation name.
m_RelationName - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: the template for the relation name.
m_RelationName - Variable in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: the template for the relation name.
m_RelationName - Variable in class weka.classifiers.LeaveOneOutByValueGenerator: the template for the relation name.
m_RelationNameHeuristic - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the heuristic for updating the relation name.
m_RelationNameLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel: Displays the name of the relation
m_RelativeWidths - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased: whether to divide the calculated widths by the class value.
m_RelativeWidths - Variable in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval: whether the widths are relative.
m_Remote - Variable in class weka.classifiers.meta.SocketFacade: the address of the remote process.
m_RemoteObject - Variable in class weka.classifiers.functions.PyroProxy: the remote object.
m_RemoteObjectName - Variable in class weka.classifiers.functions.PyroProxy: the Pyro remote object.
m_remove - Variable in class weka.classifiers.meta.Corr
m_Remove - Variable in class adams.flow.transformer.WekaChooseAttributes: the Remove filter in use.
m_Remove - Variable in class adams.flow.transformer.WekaInstancesMerge: whether to remove when not all present.
m_Remove - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: the remove filter for trimming the range of attributes to return.
m_Remove - Variable in class weka.classifiers.meta.FilteredClassifierExt: The additional remove filter.
m_Remove - Variable in class weka.classifiers.meta.PartitionedStacking: the filters for removing the unwanted attributes for the base classifiers.
m_Remove - Variable in class weka.filters.unsupervised.attribute.DatasetCleaner: the remove filter to use.
m_RemoveChars - Variable in class weka.filters.unsupervised.attribute.MergeManyAttributes: the characters to remove from the merged name (start/end).
m_RemoveChars - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: the characters to remove from the merged name (start/end).
m_removetrain - Variable in class weka.classifiers.meta.AbstainAttributePercentile
m_RemoveUnused - Variable in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Whether unused attributes are left out of the output.
m_RemoveUnused - Variable in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Whether unused attributes are left out of the output.
m_Renderer - Variable in class adams.gui.visualization.instances.InstancesTable: the renderer to use.
m_Reorder - Variable in class adams.flow.transformer.WekaReorderAttributesToReference: the reorder filter to use.
m_Replace - Variable in class adams.flow.transformer.WekaRenameRelation: the string to replace with.
m_Replace - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric: the replacement string.
m_ReplaceMissing - Variable in class adams.data.instancesanalysis.pls.AbstractPLS: whether to replace missing values
m_ReplaceMissing - Variable in class weka.attributeSelection.AbstractPLSAttributeEval: the replace missing values parameter.
m_ReplaceMissingFilter - Variable in class weka.clusterers.SAXKMeans: replace missing values in training instances.
m_ReplaceMissingFilter - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Filters for replacing missing values.
m_Report - Variable in class adams.data.instance.Instance: the automatically generated report.
m_Reports - Variable in class adams.gui.visualization.instance.InstanceExplorer: the reports.
m_ReportTable - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the table with the report.
m_ReportTable - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the table with the report.
m_ResetModel - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: whether we need to reset the model.
m_ResetResults - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: whether to reset the results before starting the experiment.
m_Residuals - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_Residuals - Variable in class weka.classifiers.meta.LeastMedianSq
m_Result - Variable in class adams.gui.goe.WekaGenericArrayEditorDialog: whether the dialog was cancelled or ok'ed.
m_Result - Variable in class adams.gui.goe.WekaGenericObjectEditorDialog: whether the dialog was cancelled or ok'ed.
m_ResultFile - Variable in class adams.flow.sink.WekaExperimentGenerator: the file to store the result in.
m_ResultFormat - Variable in class adams.flow.sink.WekaExperimentGenerator: the result format.
m_Results - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel: the raw results from the experiment.
m_Results - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: the generated results.
m_Results - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: the generated results.
m_ResultsFileChooser - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: the file chooser for the results.
m_ResultsHandler - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: the handler for the results.
m_Reverse - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions: whether to reverse the sorting.
m_Reverse - Variable in class weka.classifiers.AggregateEvaluations: whether to reverse the sorting.
m_ridge - Variable in class weka.classifiers.trees.RandomModelTrees
m_Ridge - Variable in class adams.data.baseline.AbstractLinearRegressionBased: the ridge.
m_Ridge - Variable in class weka.attributeSelection.LinearRegressionAttributeEval: The ridge parameter
m_Ridge - Variable in class weka.classifiers.functions.LinearRegressionJ: The ridge parameter
m_Ridge - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_Ridge - Variable in class weka.classifiers.meta.LeastMedianSq
m_Ridge - Variable in class weka.core.WeightedEuclideanDistanceRidge
m_right - Variable in class weka.classifiers.trees.m5.RuleNode2: right child node
m_Row - Variable in class adams.flow.transformer.WekaExperimentEvaluation: the row (= datasets).
m_Row - Variable in class adams.flow.transformer.WekaGetInstancesValue: the index of the row.
m_Row - Variable in class adams.flow.transformer.WekaSetInstancesValue: the index of the row.
m_Row - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: the row (= datasets).
m_RowAttribute1 - Variable in class adams.tools.CompareDatasets: the optional attribute for matching up rows (dataset 1).
m_RowAttribute2 - Variable in class adams.tools.CompareDatasets: the optional attribute for matching up rows (dataset 2).
m_RowAttributeIsString - Variable in class adams.tools.CompareDatasets: whether the row attribute is a string/nominal attribute or not.
m_RowFinder - Variable in class adams.data.weka.columnfinder.RowFilteredColumnFinder: the RowFinder to use first.
m_RowFinder - Variable in class adams.data.weka.datasetsplitter.RowSplitter: The selector for splitting rows between the two datasets.
m_RowFinder - Variable in class adams.data.weka.rowfinder.AbstractFilteredRowFinder: the RowFinder to apply.
m_RowFinder - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: The row-finder which separates training data from actual data.
m_RowFinder - Variable in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: The classifier template used to do the classification.
m_RowFinder - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: the row finder to use if enabled.
m_RowFinderEnabled - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: whether to use the row finder.
m_RowIndex - Variable in class adams.gui.visualization.instance.InstanceComparePanel: the internal index.
m_RowRange - Variable in class weka.filters.unsupervised.instance.KeepRange: the index of the attribute to sort on.
m_Rows - Variable in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: num rows
m_Rows - Variable in class adams.data.weka.rowfinder.Constant: The constant set of rows to find.
m_Rows - Variable in class adams.gui.event.WekaInvestigatorDataEvent: the affected rows, null for all.
m_Rows - Variable in class weka.core.InstancesView: the rows to use.
m_Rows - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
m_RowSelection - Variable in class weka.filters.unsupervised.instance.MultiRowProcessor: the row selection scheme.
m_RowSplitter - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Row-splitter for splitting training and actual data.
m_rsquared - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: R^2 value for the regression
m_rsquaredAdj - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Adjusted R^2 value for the regression
m_ruleSet - Variable in class weka.classifiers.trees.m5.M5Base2: the rule set
m_run - Variable in class weka.classifiers.lazy.LWLSynchroPrefilter
m_Run - Variable in class adams.gui.tools.wekainvestigator.job.InvestigatorTabRunnableJob: the runnable to execute.
m_Run - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: the run.
m_RunEvaluations - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: the evaluation objects from the runs.
m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: the run information.
m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics: whether to print the run information as well.
m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: the run information.
m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: whether to print the run information as well.
m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: the run information.
m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics: whether to print the run information as well.
m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: the run information.
m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: whether to print the run information as well.
m_RunInformation - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: the run information.
m_RunModels - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: the run models.
m_Runner - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the runner thread.
m_Running - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: whether the experiment is running.
m_Running - Variable in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: whether the experiment is still running.
m_Running - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: whether the algorithm is still running.
m_RunOriginalIndices - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: the original indices (runs).
m_Runs - Variable in class adams.flow.sink.WekaExperimentGenerator: the number of runs to perform.
m_Runs - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: the number of runs to perform.
m_Runs - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: the number of runs.
m_RunsSpinner - Variable in class weka.gui.explorer.ExperimentPanel: The spinner for the number of runs.
m_RunThread - Variable in class weka.gui.explorer.ExperimentPanel: A thread that classification runs in.
m_SamplePercentage - Variable in class weka.classifiers.meta.VotedImbalance: the sample percentage to use (0-100).
m_SampleSize - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: the sample size to use.
m_SampleType - Variable in class weka.classifiers.trees.XGBoost: Type of sampling algorithm.
m_saveInstances - Variable in class weka.classifiers.trees.m5.M5Base2: Save instances at each node in an M5 tree for visualization purposes.
m_SaveOut - Variable in class weka.gui.explorer.ExperimentPanel: The buffer saving object for saving output.
m_Saver - Variable in class adams.data.io.output.AbstractWekaSpreadSheetWriter: the file loader to use.
m_Saver - Variable in class adams.flow.sink.WekaDatabaseWriter: the database saver.
m_Saver - Variable in class adams.gui.chooser.DatasetFileChooserPanel: the current saver.
m_scale - Variable in class adams.opt.optimise.genetic.PackDataDef.DataInfo
m_scalefactor - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_scalefactor - Variable in class weka.classifiers.meta.LeastMedianSq
m_ScalePositiveWeights - Variable in class weka.classifiers.trees.XGBoost: Scales the weights of positive instances by this factor.
m_Scaler - Variable in class adams.data.weka.predictions.AutoScaler: the scaler to use for numeric classes.
m_Scores - Variable in class adams.data.instancesanalysis.PCA: the scores.
m_Scores - Variable in class adams.data.instancesanalysis.PLS: the scores.
m_Search - Variable in class adams.flow.transformer.WekaAttributeSelection: the search method.
m_Search - Variable in class adams.flow.transformer.WekaNearestNeighborSearch: the neighboorhood search to use.
m_Search - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: the search algorithm.
m_Search - Variable in class weka.classifiers.lazy.LWLDatasetBuilder: The nearest neighbour search algorithm to use.
m_SearchPanel - Variable in class adams.gui.visualization.instance.InstanceExplorer: for searching the fields in the reports.
m_SearchPanel - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the search panel.
m_Second - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis: the positions of the second range.
m_SecondAttribute - Variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: the name of the second attribute.
m_SecondAttributeRange - Variable in class adams.gui.InstanceCompare: the second attribute range to use.
m_SecondAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the second set of attributes.
m_SecondBestFitness - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: the best fitness so far (second evaluation).
m_SecondBestSetup - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: the best setup so far (second evaluation).
m_SecondBestWeights - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: the best weights/bits so far (second evaluation).
m_SecondCrossValidationSeed - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: the cross-validation seed (second evaluation).
m_SecondData - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the second dataset.
m_SecondFile - Variable in class adams.gui.InstanceCompare: the second file to compare.
m_SecondFitness - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob: the current fitness (second evaluation).
m_SecondFolds - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob: the cross-validation folds (second evaluation).
m_SecondFolds - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: the number of folds for cross-validation (second evaluation).
m_SecondRange - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis: the second range of the attributes to use.
m_SecondRowIndex - Variable in class adams.gui.InstanceCompare: the index of the second attribute to use for matching rows.
m_SecondSeed - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob: the cross-validation seed (second evaluation).
m_SecondStoredResults - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: the cache for results (second evaluation).
m_Seed - Variable in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator: the random seed for cross-valiation.
m_Seed - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: the seed value.
m_Seed - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: the seed value.
m_Seed - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: the seed value.
m_Seed - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: the seed value.
m_Seed - Variable in class adams.flow.transformer.WekaAttributeSelection: the seed value.
m_Seed - Variable in class adams.flow.transformer.WekaBootstrapping: the random number seed.
m_Seed - Variable in class adams.flow.transformer.WekaClassifierRanker: the random seed to use.
m_Seed - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: the seed value to use.
m_Seed - Variable in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: the seed value.
m_Seed - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator: the seed value.
m_Seed - Variable in class adams.flow.transformer.WekaCrossValidationSplit: the seed value.
m_Seed - Variable in class adams.flow.transformer.WekaRandomSplit: the seed value.
m_Seed - Variable in class adams.multiprocess.WekaCrossValidationExecution: the seed value.
m_Seed - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: the cross-validation seed.
m_Seed - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: the seed value.
m_Seed - Variable in class weka.classifiers.AbstractSplitGenerator: the seed value.
m_Seed - Variable in class weka.classifiers.functions.FakeClassifier: the seed.
m_Seed - Variable in class weka.classifiers.trees.XGBoost: The random number seed.
m_Seed - Variable in class weka.filters.supervised.instance.RemoveOutliers: the seed value.
m_Seed - Variable in class weka.filters.unsupervised.attribute.InputSmearing: The random number seed.
m_Seed - Variable in class weka.filters.unsupervised.instance.RemoveDuplicates: the seed value for the randomization.
m_Seed - Variable in class weka.filters.unsupervised.instance.WeightsBasedResample: the seed for randomizing the final dataset.
m_seIntercept - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: standard error of the intercept
m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: the additional attributes to store.
m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: the additional attributes to store.
m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: the additional attributes to store.
m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: the additional attributes to store.
m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: the additional attributes to store.
m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: the additional attributes to store.
m_SelectAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: the additional attributes to store.
m_SelectColumns - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the dataset keys.
m_SelectComparisonBase - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the comparison base.
m_SelectedAttributes - Variable in class weka.classifiers.functions.LinearRegressionJ: Which attributes are relevant?
m_SelectionListeners - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: the listeners for changes in the selection.
m_SelectionProcessor - Variable in class weka.filters.unsupervised.instance.MultiRowProcessor: the row processing scheme.
m_SelectRows - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the resultset keys.
m_Self - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the dialog itself.
m_SeparateFolds - Variable in class adams.multiprocess.WekaCrossValidationExecution: whether to separate folds.
m_Serialized - Variable in class weka.filters.SerializedFilter: the flow file to process the data with.
m_Server - Variable in class weka.classifiers.meta.SocketFacade: the server socket for receiving the replies.
m_seSlope - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: standard error of the slope
m_Setup - Variable in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: the property for the genetic algorithm setup.
m_Setups - Variable in class adams.flow.source.AbstractWekaSetupGenerator: all the setups.
m_SetupUpload - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: for uploading the setups.
m_SharedStringsTable - Variable in class adams.ml.data.InstancesView: the shared string table.
m_ShortcutProperties - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the shortcut properties.
m_ShowAttributeIndex - Variable in class adams.gui.visualization.instances.InstancesTableModel: whether to display the attribute index in the table header.
m_ShowAttributeWeights - Variable in class adams.gui.visualization.instances.InstancesTableModel: whether to show attribute weights.
m_ShowDistribution - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer: whether to output the class distribution (only nominal classes).
m_ShowDistribution - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: whether to output the class distribution (only nominal classes).
m_ShowError - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer: whether to add an error colunm.
m_ShowError - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: whether to add an error colunm.
m_ShowProbability - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer: whether to output the probability of the prediction (only nominal classes).
m_ShowProbability - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: whether to output the probability of the prediction (only nominal classes).
m_ShowWeight - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer: whether to output the weight as well.
m_ShowWeight - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: whether to output the weight as well.
m_ShowWeightsColumn - Variable in class adams.gui.visualization.instances.InstancesTableModel: whether to show a weights column.
m_showZeroInstancesAsUnknown - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel: Whether to display 0 or ? for the number of instances in cases where a dataset has only structure.
m_Significance - Variable in class adams.flow.transformer.WekaExperimentEvaluation: the significance.
m_Significance - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: the significance.
m_Silent - Variable in class weka.classifiers.MultiLevelSplitGenerator: whether to suppress error output.
m_SimpleAttributeNames - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: whether to just number the attributes rather than compiling them from other attribute names.
m_SIMPLS_MATRIX_LOCAL - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilter
m_SIMPLS_MATRIX_LOCAL - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
m_Size - Variable in class adams.data.weka.predictions.FixedSizeErrorScaler: the size.
m_SizeLimit - Variable in class weka.filters.unsupervised.instance.WeightsBasedResample: the maximum size of the dataset to generate (<= 0 is off, <= 10 is percentage, > 10 is absolute).
m_SkipBuild - Variable in class adams.flow.transformer.WekaTrainClassifier: whether to skip the buildClassifier call for incremental classifiers.
m_SkipDrop - Variable in class weka.classifiers.trees.XGBoost: Probability of skipping the dropout procedure during the boosting operation.
m_SkipHistory - Variable in class weka.gui.explorer.AbstractExplorerPanelHandler: whether to skip the history panels.
m_SkipIdentical - Variable in class weka.core.neighboursearch.NewNNSearch: Whether to skip instances from the neighbours that are identical to the query instance.
m_SkipNominal - Variable in class adams.data.instancesanalysis.PCA: whether to skip nominal attributes (and not apply NominalToBinary).
m_SkipTrain - Variable in class weka.classifiers.meta.SocketFacade: whether to skip training.
m_slope - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: The slope
m_sort_packed - Variable in class adams.opt.optimise.genetic.PackDataDef
m_SortAttributes - Variable in class adams.gui.tools.wekainvestigator.datatable.DataTable: whether to sort the attributes alphabetically.
m_SortDefinitionPanel - Variable in class adams.gui.event.InstancesSortSetupEvent: the definition panel that was added/removed.
m_SortedEigens - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Sorted eigenvalues.
m_SortLabels - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions: whether to sort the labels.
m_SortLabels - Variable in class weka.classifiers.AggregateEvaluations: whether to sort the labels.
m_Source - Variable in class adams.data.io.input.InstanceReader: the data source for reading.
m_Source - Variable in class adams.flow.source.WekaDatabaseReader: the actual loader for loading the data.
m_Source - Variable in class adams.flow.transformer.WekaFileReader: the actual loader for loading the data.
m_Source - Variable in class adams.gui.tools.wekainvestigator.data.FileContainer: the source.
m_Source - Variable in class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer: the source.
m_SourceCodeClass - Variable in class adams.flow.transformer.WekaClassifierInfo: the name of the source code class.
m_sourceFile - Variable in class weka.core.converters.SpreadSheetLoader: Holds the source of the data set.
m_SourceLookup - Variable in class adams.data.weka.datasetsplitter.ColumnSplitter: Mapping from the split attributes to their source in the original dataset.
m_Sources - Variable in class adams.data.instancesanalysis.FastICA: the sources.
m_SparseFormat - Variable in class adams.flow.source.WekaDatabaseReader: whether to output data in sparse format.
m_SparsePLS - Variable in class adams.data.instancesanalysis.pls.SparsePLS: the actual algorithm.
m_speedUpDistanceCompWithCanopies - Variable in class weka.clusterers.SAXKMeans: Whether to reducet the number of distance calcs done by k-means with canopies
m_SpinnerFolds - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: the number of folds.
m_SpinnerFolds - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: the number of folds.
m_SpinnerFolds - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: the number of folds.
m_SpinnerFolds - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: the number of folds.
m_SpinnerFolds - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: the number of folds.
m_SpinnerRuns - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: the number of runs.
m_SpinnerRuns - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: the number of runs.
m_SpinnerRuns - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: the number of runs.
m_SplitIndex - Variable in class weka.classifiers.trees.RandomRegressionForest.Node
m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: the split pane.
m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the split pane for left/right panels.
m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the split pane for left/right panels.
m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the split pane for left/right panels.
m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the split pane for left/right panels.
m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the split pane for left/right panels.
m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the split pane.
m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the split pane.
m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the split pane.
m_SplitPane - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the split pane.
m_SplitPane - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the split pane.
m_SplitPane - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel: the split pane.
m_SplitPane - Variable in class weka.gui.explorer.MultiExplorer: the split pane for the components.
m_SplitPercentage - Variable in class adams.flow.sink.WekaExperimentGenerator: the split-percentage to use (only train/test splits).
m_splitpoint - Variable in class weka.classifiers.meta.HighLowSplit
m_splitpoint - Variable in class weka.classifiers.meta.HighLowSplitSingleClassifier
m_Splits - Variable in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: the number of splits.
m_Splits - Variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
m_Splitter - Variable in class adams.flow.transformer.WekaDatasetSplit: The splitter to use.
m_SplitValue - Variable in class weka.classifiers.trees.RandomRegressionForest.Node
m_SpreadSheetType - Variable in class adams.data.conversion.WekaInstancesToSpreadSheet: the type of spreadsheet to use.
m_squaredErrors - Variable in class weka.clusterers.SAXKMeans: Holds the squared errors for all clusters.
m_SSR - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_SSR - Variable in class weka.classifiers.meta.LeastMedianSq
m_standardizeFilter - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Filter for standardizing the data
m_start - Variable in class adams.opt.genetic.Hermione
m_StartBut - Variable in class weka.gui.explorer.ExperimentPanel: Click to start running the experiment.
m_Statistic - Variable in class adams.flow.transformer.WekaInstancesStatistic: the statistic to generate.
m_Statistic - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: the statistic to generate.
m_Statistic - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: the statistic to generate.
m_Statistic - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: the statistic to generate.
m_Statistic - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: the statistic to generate.
m_Statistic - Variable in class weka.classifiers.meta.ClassifierCascade: the statistic to use for termination.
m_Statistics - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: the statistics to output.
m_Statistics - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: the statistics to output.
m_StatisticValue - Variable in class adams.flow.transformer.WekaEvaluationValuePicker: the comparison field.
m_StatisticValues - Variable in class adams.flow.transformer.WekaBootstrapping: the comparison fields.
m_StatisticValues - Variable in class adams.flow.transformer.WekaEvaluationValues: the comparison fields.
m_StatsTable - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: the statistics table.
m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the status bar.
m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.tab.AssociateTab: the status bar.
m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: the status bar.
m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: the status bar.
m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.tab.ClusterTab: the status bar.
m_StatusBar - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: the status bar.
m_StatusBar - Variable in class adams.gui.visualization.instance.InstanceComparePanel: for displaying error messages.
m_StatusBar - Variable in class adams.gui.visualization.instance.InstanceExplorer: the status bar.
m_StatusBarDateFormat - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: for timestamps in the statusbar.
m_StatusMessageHandler - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: for notifications.
m_StatusMessageHandler - Variable in class adams.multiprocess.WekaCrossValidationExecution: for outputting notifications.
m_StatusMessageHandler - Variable in class adams.multiprocess.WekaCrossValidationJob: for outputting notifications.
m_StdDev - Variable in class weka.classifiers.meta.InputSmearing: the standard deviation multiplier to use.
m_StdDev - Variable in class weka.filters.unsupervised.attribute.InputSmearing: the standard deviation multiplier to use.
m_StdDevs - Variable in class weka.classifiers.functions.LinearRegressionJ: The attribute standard deviations
m_StdDevs - Variable in class weka.filters.supervised.attribute.PLSFilterExtended
m_StdDevs - Variable in class weka.filters.unsupervised.attribute.InputSmearing: the std devs to use.
m_StopBut - Variable in class weka.gui.explorer.ExperimentPanel: Click to stop a running experiment.
m_StopFlowIfCanceled - Variable in class adams.flow.source.WekaSelectDataset: whether to stop the flow if canceled.
m_StopMode - Variable in class adams.flow.source.WekaSelectDataset: how to perform the stop.
m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: whether the build was stopped.
m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: whether the build was stopped.
m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: whether the build was stopped.
m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: whether the build was stopped.
m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: whether the build was stopped.
m_Stopped - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup: whether the experiment got stopped.
m_Stopped - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: whether the experiment was stopped.
m_Stopped - Variable in class adams.multiprocess.WekaCrossValidationExecution: whether the execution has been stopped.
m_Stopped - Variable in class weka.classifiers.evaluation.StoppableEvaluation: whether the execution was stopped.
m_Stopped - Variable in class weka.classifiers.MultiLevelSplitGenerator: whether the generation got stopped.
m_Stopped - Variable in class weka.classifiers.StoppableClassifier: whether the classifier was stopped.
m_Stopped - Variable in class weka.classifiers.StoppableRandomizableClassifier: whether the classifier was stopped.
m_Stopped - Variable in class weka.classifiers.StoppableSingleClassifierEnhancer: whether the classifier was stopped.
m_Stopping - Variable in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: whether the execution is in the process of stopping.
m_Stopping - Variable in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: whether the execution is in the process of stopping.
m_Storage - Variable in class adams.flow.transformer.WekaNearestNeighborSearch: the storage item.
m_StorageName - Variable in class adams.data.conversion.MapToWekaInstance: the name of the stored value.
m_StorageName - Variable in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: the name of the datasets in the internal storage.
m_StoredResults - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the cache for results.
m_StoredResults - Variable in class adams.opt.optimise.GeneticAlgorithm: the cache for results.
m_StoreFilename - Variable in class adams.flow.transformer.WekaTextDirectoryReader: whether to store the filename as extra attribute.
m_Stratify - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: whether to stratify the data (in case of nominal class).
m_Stratify - Variable in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: whether to stratify the data (in case of nominal class).
m_Stratify - Variable in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: whether to stratify the data (in case of nominal class).
m_Stratify - Variable in class weka.classifiers.DefaultCrossValidationFoldGenerator: whether to stratify the data (in case of nominal class).
m_Stratify - Variable in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: whether to stratify the data (in case of nominal class).
m_Stratify - Variable in class weka.classifiers.GroupedCrossValidationFoldGenerator: whether to stratify the data (in case of nominal class).
m_Strict - Variable in class adams.flow.transformer.WekaInstancesMerge: whether to fail if IDs not unique.
m_structure - Variable in class weka.core.converters.SpreadSheetLoader: Holds the determined structure (header) of the data set.
m_Structure - Variable in class adams.data.io.input.InstanceReader: the current data structure.
m_Structure - Variable in class adams.flow.source.WekaDatabaseReader: the structure.
m_Structure - Variable in class adams.flow.transformer.WekaFileReader: the structure.
m_SubProcess - Variable in class weka.filters.FlowFilter: the flow for processing the data.
m_Subsample - Variable in class weka.classifiers.trees.XGBoost: Subsample ratio of the training instances.
m_SubSample - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_SubSample - Variable in class weka.classifiers.meta.LeastMedianSq
m_subset - Variable in class weka.classifiers.meta.Corr
m_SummaryFilter - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: The filter which performs attribute summarising.
m_SumOfEigenValues - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: sum of the eigenvalues.
m_sumOfWeightsLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel: Displays the sum of instance weights
m_SupervisedClassSplitter - Variable in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Column-splitter for removing the supervised filter class.
m_SupplementaryData - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: supplementary data.
m_SupplementaryName - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: the supplementary name.
m_SuppliedPrefix - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the supplied prefix.
m_SuppliedReferenceDataset - Variable in class weka.filters.unsupervised.instance.AlignDataset: the supplied test set, when using programmatically.
m_SuppliedTestSet - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances: the supplied test set, when using programmatically.
m_Support - Variable in class weka.classifiers.meta.ConsensusOrVote: the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.
m_Support - Variable in class weka.classifiers.meta.Veto: the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.
m_Support - Variable in class weka.gui.explorer.SqlPanel: Manages sending notifications to people when we change the set of working instances.
m_Supported - Variable in class adams.data.instancesanalysis.PCA: the supported attributes.
m_suppressErrorMessage - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: If true, suppress error message if no useful attribute was found
m_SuppressModelOutput - Variable in class weka.classifiers.meta.AbstainingCascade: whether to suppress the model output.
m_SuppressModelOutput - Variable in class weka.classifiers.meta.ConsensusOrVote: whether to suppress the model output.
m_SuppressModelOutput - Variable in class weka.classifiers.meta.SuppressModelOutput: whether to suppress the model output.
m_SuppressModelOutput - Variable in class weka.classifiers.meta.ThresholdedBinaryClassification: whether to suppress the model output.
m_SuppressModelOutput - Variable in class weka.classifiers.meta.Veto: whether to suppress the model output.
m_SuppressModelOutput - Variable in class weka.classifiers.meta.VotedImbalance: whether to suppress the model output.
m_SwapAxes - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: whether to swap the axes.
m_SwapRowsAndColumns - Variable in class adams.flow.transformer.WekaExperimentEvaluation: whether to swap rows and columns.
m_SwapRowsAndColumns - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: whether to swap rows and columns.
m_t - Variable in class weka.classifiers.functions.GaussianProcessesAdaptive: The vector of target values.
m_t - Variable in class weka.classifiers.functions.GaussianProcessesNoWeights: The vector of target values.
m_t - Variable in class weka.classifiers.functions.GaussianProcessesWeighted: The vector of target values.
m_t - Variable in class weka.classifiers.functions.GPD: The vector of target values.
m_t1 - Variable in class weka.clusterers.SAXKMeans: The t1 radius to pass through to Canopy
m_t2 - Variable in class weka.clusterers.SAXKMeans: The t2 radius to pass through to Canopy
m_TabbedPane - Variable in class adams.flow.sink.WekaAttributeSummary: the tabbed pane with the attribute visualizations (if more than one in range).
m_TabbedPane - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the tabbed pane for the tabs.
m_TabbedPane - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: the tabbed pane with the generated output.
m_TabbedPane - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: the tabbed pane in case multiple panels get displayed.
m_TabbedPane - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: the tabbed pane in case multiple panels get displayed.
m_TabbedPane - Variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the tabbed pane.
m_TabbedPane - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: the tabbed pane for datasets and classifiers.
m_TabbedPane - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: the tabbed pane for datasets and classifiers.
m_TabbedPane - Variable in class adams.gui.visualization.instance.InstanceExplorer: the tabbed pane for the data to display.
m_TabbedPane - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the tabbed pane.
m_TabbedPane - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the tabbed pane for displaying the data.
m_TabbedPaneData - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the tabbed pane for the data.
m_TabbedPanePlots - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the tabbed pane for the plots.
m_TabbedPanePlots - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the tabbed pane for the plots.
m_TabbedPanePlots - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the tabbed pane for the plots.
m_Table - Variable in class adams.flow.sink.WekaInstancesDisplay: the table with the instances.
m_Table - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: the table.
m_Table - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: The table displaying attribute names and selection status
m_Table - Variable in class adams.gui.visualization.instances.InstancesColumnComboBox: the associated table.
m_Table - Variable in class adams.gui.visualization.instances.InstancesPanel: the table.
m_TableCache - Variable in class adams.gui.tools.wekainvestigator.tab.DataTab: the cache for the tables.
m_TableData - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the table for displaying the instances.
m_TableData - Variable in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: the table with the dataset.
m_TableName - Variable in class adams.flow.sink.WekaDatabaseWriter: protected the name of the table to store the data in.
m_TableResult - Variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: the generated spreadsheet.
m_TableResults - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel: the table with the statistics.
m_Target - Variable in class adams.gui.wizard.WekaPropertySheetPanelPage: the current target.
m_Template - Variable in class adams.data.conversion.MapToWekaInstance: the template.
m_Template - Variable in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels: the vote template.
m_Template - Variable in class adams.flow.transformer.wekaensemblegenerator.VotedModels: the vote template.
m_Template - Variable in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: the template.
m_Template - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds: the vote template.
m_Template - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: the template.
m_Template - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: the template.
m_Template - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: the template.
m_Test - Variable in class adams.flow.transformer.WekaClassifierRanker: the callable actor to obtain the test dataset for train/test evaluation from.
m_Test - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: the test data to evaluate with (if folds less than 2).
m_Test - Variable in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob: the data to use for testing.
m_Test - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: the data to use for testing.
m_Test - Variable in class adams.multiprocess.WekaCrossValidationJob: the test set.
m_TestAttributes - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer: the additional attributes from the test data to add to the output.
m_TestBase - Variable in class adams.flow.transformer.WekaExperimentEvaluation: the test base.
m_TestBase - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: the test base.
m_TestData - Variable in class adams.flow.transformer.WekaGeneticAlgorithm: the storage name of the test data.
m_TestData - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: the test data to use (can be null).
m_Tester - Variable in class adams.flow.transformer.WekaExperimentEvaluation: the tester class to use.
m_Tester - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: the tester class to use.
m_TestInstances - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the data to use for evaluation (if null, cross-validation is used).
m_TestLoader - Variable in class weka.gui.explorer.ExperimentPanel: The loader used to load the user-supplied test set (if any).
m_Testset - Variable in class adams.flow.transformer.WekaTestSetClustererEvaluator: the name of the callable trainset provider.
m_Testset - Variable in class adams.flow.transformer.WekaTestSetEvaluator: the name of the callable trainset provider.
m_TestSet - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances: the file containing the test set.
m_TestSplitName - Variable in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: the split to use for testing.
m_TestSplitName - Variable in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: the split to use for testing.
m_TextActual - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: the text with the actual column index.
m_TextAdditional - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: the columns with the additional data to store.
m_TextAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the additional attribute range.
m_TextAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the additional attribute range.
m_TextAdditionalAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the additional attribute range.
m_TextArea - Variable in class adams.gui.tools.DatasetCompatibilityPanel: the text area to output the results in.
m_TextArea - Variable in class adams.gui.tools.wekamultiexperimenter.LogPanel: the text area for outputting the log.
m_TextAreaCodeOutput - Variable in class adams.gui.tools.WekaOptionsConversionPanel: the text area for the output.
m_TextAreaInput - Variable in class adams.gui.tools.WekaOptionsConversionPanel: the text area for the input.
m_TextAreaKey - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel: for displaying the results.
m_TextAreaResults - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.PlainTextResultsPanel: for displaying the results.
m_TextAttributeRange - Variable in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: the attribute range.
m_TextAttributeRange - Variable in class adams.gui.tools.wekainvestigator.tab.InstanceTab: the attribute range.
m_TextAttributeRange - Variable in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: the attribute range.
m_TextAttributeRange - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the attribute range.
m_TextAttributeRange - Variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: the edit field for the range.
m_TextAttributeRange - Variable in class adams.gui.visualization.instance.LoadDatasetDialog: the text field for the attribute range.
m_TextClassDistribution - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: the columns with the class distribution columns range.
m_TextCommon - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the IDs present in both datasets.
m_TextEvaluation - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: the evaluation parameter.
m_TextEvaluation - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: the evaluation parameter.
m_TextFirstRange - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the text field for the first attribute range.
m_TextMaxAttributeNames - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the maximum number of attribute names.
m_TextMaxAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the maximum number of attributes.
m_TextNotes - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: the notes.
m_TextOnlyFirst - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the IDs only present in the first dataset.
m_TextOnlySecond - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the IDs only present in the second dataset.
m_TextPassword - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel: the password.
m_TextPercentage - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: the split percentage.
m_TextPercentage - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: the split percentage.
m_TextPercentage - Variable in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: the split percentage.
m_TextPredicted - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: the text with the predicted column index.
m_TextRepetitions - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: the number of repetitions.
m_TextRepetitions - Variable in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: the number of repetitions.
m_TextSecondRange - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the text field for the second attribute range.
m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: the seed value.
m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: the seed value.
m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: the seed value.
m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: the seed value.
m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: the seed value.
m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: the seed value.
m_TextSeed - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: the seed value.
m_TextSelectedAttributes - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: the currently selected attributes.
m_TextSignificance - Variable in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: the significance.
m_TextStructure - Variable in class adams.gui.tools.wekainvestigator.tab.CompareTab: the text area with the structure output.
m_TextTestSplitName - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: the text with the name for the test split.
m_TextTrainSplitName - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: the text with the name for the train split.
m_TextURL - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel: the JDBC URL.
m_TextUser - Variable in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel: the user name.
m_TextVariance - Variable in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: the variance.
m_TextWeight - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: the text with the weight column index.
m_threadRun - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: True if the thread m_hc above is running.
m_Threshold - Variable in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator: the percentage to the threshold.
m_Threshold - Variable in class adams.tools.CompareDatasets: the threshold for listing correlations.
m_Threshold - Variable in class weka.classifiers.meta.ClassifierCascade: the threshold for the statistic for termination.
m_ThresholdCheck - Variable in class weka.classifiers.meta.ClassifierCascade: whether to go below or above the threshold.
m_Thresholds - Variable in class weka.classifiers.meta.VotedImbalance: the thresholds to use (pair: probability minority class = num balanced).
m_Timeout - Variable in class weka.classifiers.meta.SocketFacade: the timeout for the socket.
m_Timestamp - Variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: the timestamp.
m_TimestampCache - Variable in class adams.gui.tools.wekainvestigator.tab.DataTab: the cache for the last update cache.
m_TimestampCache - Variable in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab: the cache for the last update cache.
m_Title - Variable in class adams.gui.tools.wekainvestigator.job.InvestigatorJob: the title of the job.
m_Title - Variable in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob: the title of the job.
m_Title - Variable in class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary: the title.
m_Title - Variable in class weka.gui.explorer.ExplorerEntryPanel: the parent's default title.
m_TitleClassDetails - Variable in class adams.flow.transformer.WekaEvaluationSummary: the title to use for the summary.
m_TitleGenerator - Variable in class weka.gui.explorer.ExplorerExt: for generating the title.
m_TitleMatrix - Variable in class adams.flow.transformer.WekaEvaluationSummary: the title to use for the matrix.
m_TitleNameColumn - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: the title of the name column.
m_TitleSummary - Variable in class adams.flow.transformer.WekaEvaluationSummary: the title to use for the summary.
m_TitleValueColumn - Variable in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: the title of the value column.
m_Tokenizers - Variable in class weka.core.tokenizers.MultiTokenizer: the tokenizers to use.
m_Tokens - Variable in class weka.core.tokenizers.MultiTokenizer: the collected tokens.
m_Tol - Variable in class adams.data.instancesanalysis.pls.KernelPLS: Inner NIPALS loop improvement tolerance
m_Tol - Variable in class adams.data.instancesanalysis.pls.NIPALS: Inner NIPALS loop improvement tolerance
m_Tol - Variable in class adams.data.instancesanalysis.pls.PRM: Inner loop improvement tolerance
m_Tol - Variable in class adams.data.instancesanalysis.pls.SparsePLS: Inner NIPALS loop improvement tolerance
m_TolerateHeaderChanges - Variable in class adams.data.instances.AbstractInstanceGenerator: whether to tolerate header changes.
m_ToolTipMaxColumns - Variable in class adams.gui.visualization.instance.InstancePanel: the maximum number of columns for the tooltip.
m_ToolTipMaxRows - Variable in class adams.gui.visualization.instance.InstancePanel: the maximum number of rows for the tooltip.
m_TopK - Variable in class weka.classifiers.trees.XGBoost: The number of top features to select.
m_topOfTree - Variable in class weka.classifiers.trees.m5.Rule2: the top of the m5 tree for this rule
m_Train - Variable in class adams.flow.transformer.WekaClassifierRanker: the callable actor to obtain the training dataset from.
m_Train - Variable in class adams.flow.transformer.WekaClassifierRanker.RankingJob: the train data to evaluate with.
m_Train - Variable in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: the data to use for training.
m_Train - Variable in class adams.multiprocess.WekaCrossValidationJob: the training set.
m_Train - Variable in class weka.classifiers.lazy.LWLDatasetBuilder: The training instances used for classification.
m_TrainCopy - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Keep a copy for the class attribute (if set).
m_Trained - Variable in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder: whether the column finder was trained already.
m_Trained - Variable in class adams.data.weka.rowfinder.AbstractTrainableRowFinder: whether the row finder was trained already.
m_TrainInstances - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: The data to transform analyse/transform.
m_TrainSplitName - Variable in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: the split to use for training.
m_TrainSplitName - Variable in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: the split to use for training.
m_TrainStart - Variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: the time when training commenced.
m_TransformedData - Variable in class weka.classifiers.functions.LinearRegressionJ: Variable for storing transformed training data.
m_TransformedFormat - Variable in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: The header for the transformed data format.
m_TransformFilter - Variable in class weka.classifiers.functions.LinearRegressionJ: The filter storing the transformation from nominal to binary attributes.
m_TreeMethod - Variable in class weka.classifiers.trees.XGBoost: The tree construction algorithm.
m_tstatIntercept - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: t-statistic of the intercept
m_tstatSlope - Variable in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: t-statistic of the slope
m_TurnOffAbstaining - Variable in class weka.classifiers.meta.AbstainingClassifierWrapper: whether to turn off abstaining.
m_TweedieVariancePower - Variable in class weka.classifiers.trees.XGBoost: Parameter that controls the variance of the Tweedie distribution.
m_Type - Variable in class adams.flow.transformer.WekaClassifierInfo: the type of information to generate.
m_Type - Variable in class adams.flow.transformer.WekaClustererInfo: the type of information to generate.
m_Type - Variable in class adams.flow.transformer.WekaEvaluationInfo: the type of information to generate.
m_Type - Variable in class adams.flow.transformer.WekaExtractArray: the type of extraction.
m_Type - Variable in class adams.flow.transformer.WekaInstancesInfo: the type of information to generate.
m_Type - Variable in class adams.gui.event.InstancesSortSetupEvent: what type of event occurred.
m_Type - Variable in class adams.gui.event.WekaInvestigatorDataEvent: the event type.
m_Type - Variable in class weka.filters.unsupervised.attribute.NominalToNumeric: the type of conversion to perform.
m_Types - Variable in class weka.filters.unsupervised.attribute.OuterProductAnalysis: the types of the attributes.
m_Undo - Variable in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: the undo manager.
m_Undo - Variable in class adams.gui.visualization.instance.InstancePanel: the undo manager.
m_UndoEnabled - Variable in class adams.gui.tools.wekainvestigator.data.DataContainerList: whether undo is enabled.
m_UndoEnabled - Variable in class adams.gui.visualization.instances.InstancesTableModel: whether undo is active
m_UndoHandler - Variable in class adams.gui.visualization.instances.InstancesTableModel: optional undo handler.
m_UndoList - Variable in class adams.gui.visualization.instances.InstancesTableModel: the undo list (contains temp.
m_UniqueID - Variable in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: The name of the attribute to use as the merge key.
m_UniqueID - Variable in class adams.flow.transformer.WekaInstancesMerge: the string or numeric attribute to use as unique identifier for rows.
m_UniqueIDAtts - Variable in class adams.flow.transformer.WekaInstancesMerge: the unique ID attributes.
m_UniqueLab - Variable in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel: Displays the number of unique values
m_UniqueValues - Variable in class weka.classifiers.LeaveOneOutByValueGenerator: the unique values.
m_Unset - Variable in class adams.flow.transformer.WekaClassSelector: whether to unset the class index.
m_Unsupported - Variable in class adams.data.instancesanalysis.PCA: the unsupported attributes.
m_UpdateContainerColor - Variable in class adams.gui.visualization.instance.ReportColorInstancePaintlet: whether to update the color of the container.
m_UpdateHeader - Variable in class weka.filters.unsupervised.instance.RemoveWithLabels: whether to update the header.
m_UpdateInterval - Variable in class adams.gui.visualization.instance.SimpleInstancePanelUpdater: the interval of tokens processed after which to update the display.
m_Updater - Variable in class adams.flow.sink.WekaInstanceViewer: the updater to use.
m_Updater - Variable in class weka.classifiers.trees.XGBoost: Choice of algorithm to fit linear model.
m_UpdateRelationName - Variable in class adams.flow.transformer.WekaMultiLabelSplitter: whether to use the class attribute name as new relation name.
m_UpdateWait - Variable in class weka.classifiers.functions.FakeClassifier: the update wait time in msec.
m_Upper - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: the upper value to compute.
m_Upper - Variable in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: the upper value to compute.
m_Upper - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: the upper value to compute.
m_Upper - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: the upper value to compute.
m_URL - Variable in class adams.flow.sink.WekaDatabaseWriter: the database URL to query.
m_URL - Variable in class adams.flow.source.WekaDatabaseReader: the database URL to query.
m_URL - Variable in class adams.gui.tools.wekainvestigator.data.DatabaseContainer: the database URL.
m_UseAbsoluteError - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer: whether to use absolute errors.
m_UseAbsoluteError - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: whether to use absolute errors.
m_UseAllK - Variable in class weka.classifiers.lazy.LWLDatasetBuilder: True if m_kNN should be set to all instances.
m_UseColumnNamesAsClassLabels - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions: whether to use the column name as class labels.
m_UseCustomLoader - Variable in class adams.flow.transformer.WekaFileReader: whether to use a custom converter.
m_UseCustomLoader - Variable in class adams.flow.transformer.WekaReorderAttributesToReference: whether to use a custom converter.
m_UseCustomLoader - Variable in class weka.filters.unsupervised.instance.AlignDataset: whether to use a custom loader for the reference data.
m_UseCustomLoader - Variable in class weka.filters.unsupervised.instance.RemoveTestInstances: whether to use a custom loader for the test set.
m_UseCustomPaintlet - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: whether to use a custom paintlet.
m_UseCustomSaver - Variable in class adams.flow.sink.WekaFileWriter: whether to use a custom converter.
m_UseError - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: whether to use the error for the cross-size.
m_UseFilename - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: whether to use the filename (w/o path) instead of relationname.
m_UseFilename - Variable in class weka.experiment.ExtExperiment: whether to use the filename (w/o path) instead of relationname.
m_UseFixedMinMax - Variable in class adams.flow.transformer.WekaInstancesHistogramRanges: whether to use fixed min/max for manual bin calculation.
m_UseMedian - Variable in class adams.flow.transformer.wekaclusterer.ClusterCenters: compute median instead of mean.
m_UseModelResetVariable - Variable in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: whether to use a variable to monitor for changes, triggering resets of the model.
m_UseOriginalIndices - Variable in class adams.flow.transformer.AbstractWekaPredictionsTransformer: whether to align output with original dataset (if possible).
m_UseOuterWindow - Variable in class adams.flow.source.WekaSelectDataset: whether to use the outer window as parent.
m_UsePrefix - Variable in class adams.flow.transformer.WekaInstancesMerge: whether to prefix the attribute names of each dataset with an index.
m_UseProbabilities - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: whether to use the probabilities rather 0 and 1.
m_User - Variable in class adams.flow.sink.WekaDatabaseWriter: the database user to use for connecting.
m_User - Variable in class adams.flow.source.WekaDatabaseReader: the database user to use for connecting.
m_User - Variable in class adams.gui.tools.wekainvestigator.data.DatabaseContainer: the user.
m_UseRelationNameAsFilename - Variable in class adams.flow.sink.WekaFileWriter: whether to use the relation name as filename.
m_UseRelationNameAsFilename - Variable in class adams.flow.transformer.WekaInstanceDumper: whether to use the relation name as filename.
m_UseRelationNameAsTable - Variable in class adams.flow.sink.WekaDatabaseWriter: whether to use the relation as table name.
m_UseRowAttribute - Variable in class adams.tools.CompareDatasets: whether to use the row attribute or not.
m_UseSecondEvaluation - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation.ClassifierBasedGeneticAlgorithmWithSecondEvaluationJob: whether to use second evaluation.
m_UseSecondEvaluation - Variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: whether to use second evaluation with different seed.
m_useUnpruned - Variable in class weka.classifiers.trees.m5.M5Base2: Do not prune tree/rules
m_UseViews - Variable in class adams.flow.transformer.WekaCrossValidationEvaluator: whether to use views.
m_UseViews - Variable in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: whether to use views.
m_UseViews - Variable in class adams.multiprocess.WekaCrossValidationExecution: whether to use views.
m_UseViews - Variable in class weka.classifiers.AbstractSplitGenerator: whether to use views.
m_UseWekaEditors - Static variable in class adams.gui.goe.WekaEditorsRegistration: whether to use the Weka editors.
m_UseY - Variable in class adams.data.instance.InstancePointComparator: whether to compare Y or X.
m_Value - Variable in class adams.flow.transformer.WekaSetInstancesValue: the value to set.
m_Value - Variable in class adams.flow.transformer.WekaSetInstanceValue: the value to set.
m_VariableName - Variable in class adams.flow.template.InstanceDumperVariable: the variable to update.
m_VariableName - Variable in class adams.flow.transformer.WekaInstanceBuffer: the variable to listen to.
m_VariableName - Variable in class adams.flow.transformer.WekaNearestNeighborSearch: the variable to listen to.
m_variance - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_Variance - Variable in class adams.data.instancesanalysis.PCA: the variance to cover.
m_VCPLS - Variable in class adams.data.instancesanalysis.pls.VCPLS: the actual algorithm.
m_Verbosity - Variable in class weka.classifiers.trees.XGBoost: Verbosity of printing messages.
m_VersusFitOptions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Options for the vs fit
m_VersusOrderOptions - Variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Options for the vs order
m_ViewDialogs - Variable in class adams.gui.visualization.instance.InstancePanel: the dialog for displaying a sequence.
m_Viewer - Variable in class weka.gui.explorer.SqlPanel: the SQL panel
m_Visible - Variable in class adams.gui.visualization.instance.InstanceContainer: whether the instance is visible.
m_VisualizePanel - Variable in class adams.flow.sink.WekaClassifierErrors: the Weka plot panel.
m_VisualizePanel - Variable in class adams.flow.sink.WekaCostCurve: the panel.
m_VisualizePanel - Variable in class adams.flow.sink.WekaInstancesPlot: the text area.
m_VisualizePanel - Variable in class adams.flow.sink.WekaMarginCurve: the panel.
m_VisualizePanel - Variable in class adams.flow.sink.WekaThresholdCurve: the text area.
m_Vote - Variable in class weka.classifiers.meta.ConsensusOrVote: the ensemble.
m_Vote - Variable in class weka.classifiers.meta.Veto: the ensemble.
m_VotingType - Variable in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs: the type of voting to perform .
m_W - Variable in class adams.data.instancesanalysis.pls.PLS1: the W matrix
m_W - Variable in class adams.data.instancesanalysis.pls.SIMPLS: the W matrix
m_WaitForJobs - Variable in class adams.multiprocess.WekaCrossValidationExecution: whether to wait for jobs to finish when stopping.
m_WaveNo - Variable in class weka.filters.unsupervised.attribute.Detrend: the extracted wave numbers.
m_WaveNo - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: the extracted wave numbers.
m_WaveNo - Variable in class weka.filters.unsupervised.attribute.SimpleDetrend: the fake wave numbers.
m_WaveNoRegExp - Variable in class weka.filters.unsupervised.attribute.Detrend: the regexp for extracting the wavenumbers from the attribute name.
m_WaveNoRegExp - Variable in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: the regexp for extracting the wavenumbers from the attribute name.
m_weight - Variable in class weka.classifiers.meta.AbstainLeastMedianSq
m_weight - Variable in class weka.classifiers.meta.LeastMedianSq
m_Weight - Variable in class adams.flow.transformer.WekaSpreadSheetToPredictions: the (optional) column with the instance weights.
m_Weight - Variable in class weka.classifiers.functions.FromPredictions: the column with the error values (optional).
m_WeightIndex - Variable in class weka.classifiers.functions.FromPredictions: the weight column index.
m_WeightKernel - Variable in class weka.classifiers.lazy.LWLDatasetBuilder: The weighting kernel method currently selected.
m_WeightKernel - Variable in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: The weighting kernel method currently selected.
m_weights - Variable in class adams.opt.optimise.GeneticAlgorithm.GAJob: weights.
m_Weights - Variable in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: the property for the weights (optional).
m_windows - Variable in class weka.filters.unsupervised.attribute.PAA: number of windows.
m_windows - Variable in class weka.filters.unsupervised.attribute.SAX: number of windows.
m_WithReplacement - Variable in class adams.flow.transformer.WekaBootstrapping: whether to use with replacement or not.
m_Wizard - Variable in class adams.gui.tools.weka.AppendDatasetsPanel: the wizard pane.
m_Wizard - Variable in class adams.gui.tools.weka.BatchFilterDatasetsPanel: the wizard pane.
m_Worker - Variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: for executing operations (loading files etc).
m_Worker - Variable in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: whether the evaluation is currently running.
m_Worker - Variable in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: whether the evaluation is currently running.
m_WorkspaceFileChooser - Variable in class weka.gui.explorer.MultiExplorer: the file chooser for the workspaces.
m_Writer - Variable in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: the spreadsheet writer to use.
m_Writer - Variable in class weka.core.converters.SpreadSheetSaver: the spreadsheet writer to use.
m_WriterFileFilters - Static variable in class adams.gui.chooser.AdamsExperimentFileChooser: the file filters for the writers.
m_WriterFileFilters - Static variable in class adams.gui.chooser.WekaFileChooser: the file filters for the writers.
m_Writing - Variable in class adams.flow.transformer.WekaInstanceDumper: whether currently writing to disk.
m_X - Variable in class adams.data.instance.InstancePoint: the X value.
m_XIndices - Variable in class weka.filters.supervised.attribute.MultiPLS: the indices of the X attributes.
m_XRegExp - Variable in class weka.filters.supervised.attribute.MultiPLS: the regular expression for the X columns.
m_Y - Variable in class adams.data.instance.InstancePoint: the Y value.
m_YIndices - Variable in class weka.filters.supervised.attribute.MultiPLS: the indices of the Y attributes.
m_YRegExp - Variable in class weka.filters.supervised.attribute.MultiPLS: the regular expression for the Y columns.
m_zerocount - Variable in class adams.opt.optimise.GeneticAlgorithm
m_ZoomOverview - Variable in class adams.flow.sink.WekaInstanceViewer: whether to display the zoom overview.
M5Base2 - Class in weka.classifiers.trees.m5: M5Base.
M5Base2() - Constructor for class weka.classifiers.trees.m5.M5Base2: Constructor
M5P2 - Class in weka.classifiers.trees: M5Base.
M5P2() - Constructor for class weka.classifiers.trees.M5P2: Creates a new M5P instance.
MAE - adams.flow.transformer.WekaClassifierRanker.Measure: evaluation via: Mean absolute error.
MAE - adams.opt.genetic.Measure: Mean absolute error.
MAE - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure: evaluation via: Mean absolute error.
main(String[]) - Static method in class adams.data.io.input.ArffSpreadSheetReader: Runs the reader from the command-line.
main(String[]) - Static method in class adams.data.io.input.JSONSpreadSheetReader: Runs the reader from the command-line.
main(String[]) - Static method in class adams.data.io.input.LibSVMSpreadSheetReader: Runs the reader from the command-line.
main(String[]) - Static method in class adams.data.io.input.MatlabSpreadSheetReader: Runs the reader from the command-line.
main(String[]) - Static method in class adams.data.io.input.SVMLightSpreadSheetReader: Runs the reader from the command-line.
main(String[]) - Static method in class adams.data.io.input.XrffSpreadSheetReader: Runs the reader from the command-line.
main(String[]) - Static method in class adams.gui.goe.WekaGenericArrayEditorDialog: For testing only.
main(String[]) - Static method in class adams.gui.goe.WekaGenericObjectEditorDialog: For testing only.
main(String[]) - Static method in class adams.gui.InstanceCompare: Starts the frame.
main(String[]) - Static method in class adams.gui.tools.wekainvestigator.InvestigatorManagerPanel: Just for testing.
main(String[]) - Static method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: Tests out the attribute summary panel from the command line.
main(String[]) - Static method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel: Tests out the instance summary panel from the command line.
main(String[]) - Static method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter: Starts the experimenter environment.
main(String[]) - Static method in class adams.gui.wizard.WekaPropertySheetPanelPage: For testing only.
main(String[]) - Static method in class adams.opt.optimise.GeneticAlgorithm
main(String[]) - Static method in class weka.attributeSelection.LinearRegressionAttributeEval: Main method for running this class from commandline.
main(String[]) - Static method in class weka.attributeSelection.PLS1AttributeEval: Main method for running this class from commandline.
main(String[]) - Static method in class weka.attributeSelection.SIMPLSAttributeEval: Main method for running this class from commandline.
main(String[]) - Static method in class weka.classifiers.functions.ClassificationViaPLS: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.functions.FakeClassifier: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.functions.GaussianProcessesAdaptive: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.GaussianProcessesNoWeights: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.GaussianProcessesWeighted: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.GeneticAlgorithm: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.functions.GPD: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.LinearRegressionJ: Generates a linear regression function predictor.
main(String[]) - Static method in class weka.classifiers.functions.MathExpressionClassifier: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.functions.PLSClassifierWeighted: Main method for running this classifier from commandline.
main(String[]) - Static method in class weka.classifiers.functions.PLSClassifierWeightedWithLoadings: Main method for running this classifier from commandline.
main(String[]) - Static method in class weka.classifiers.functions.PLSWeighted: Main method for running this classifier from commandline.
main(String[]) - Static method in class weka.classifiers.functions.PyroProxy: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.functions.SimpleLinearRegressionIntervalEstimator: Generates a linear regression function predictor.
main(String[]) - Static method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Main method for testing this class
main(String[]) - Static method in class weka.classifiers.lazy.LWLIntervalEstimator: Main method for executing this classifier.
main(String[]) - Static method in class weka.classifiers.lazy.LWLSynchro: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.lazy.LWLSynchroPrefilter: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.AbstainAttributePercentile: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.AbstainAverage: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.AbstainingClassifierWrapper: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.AbstainLeastMedianSq: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.AbstainVote: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.ClassificationViaRegressionD: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.ClassifierCascade: Main method for executing the class.
main(String[]) - Static method in class weka.classifiers.meta.Corr: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.FilteredClassifierExt: Main method for running this classifier.
main(String[]) - Static method in class weka.classifiers.meta.HighLowSplit: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.HighLowSplitSingleClassifier: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.InputSmearing: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.LeastMedianSq: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.LogClassRegressor: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.LogTargetRegressor: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.MinMaxLimits: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.PartitionedStacking: Main method for running this classifier.
main(String[]) - Static method in class weka.classifiers.meta.PeakTransformed: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.SubsetEnsemble: Main method for running this class from commandline.
main(String[]) - Static method in class weka.classifiers.meta.SumTransformed: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.ThreadSafeClassifierWrapper: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.meta.VotedImbalance: Main method for running this class from commandline.
main(String[]) - Static method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Main method for running this class.
main(String[]) - Static method in class weka.classifiers.trees.M5P2: Main method by which this class can be tested
main(String[]) - Static method in class weka.classifiers.trees.RandomModelTrees: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.trees.RandomRegressionForest: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.trees.XGBoost: Main method for running this class.
main(String[]) - Static method in class weka.clusterers.SAXKMeans: Main method for executing this class.
main(String[]) - Static method in class weka.core.converters.SimpleArffLoader: Main method.
main(String[]) - Static method in class weka.core.converters.SimpleArffSaver: Main method.
main(String[]) - Static method in class weka.core.converters.SpreadSheetLoader: Main method.
main(String[]) - Static method in class weka.core.converters.SpreadSheetSaver: Main method.
main(String[]) - Static method in class weka.experiment.ResultMatrixAdamsCSV: for testing only.
main(String[]) - Static method in class weka.experiment.ResultMatrixMediaWiki: for testing only.
main(String[]) - Static method in class weka.filters.FilteredFilter: Main method for running this filter.
main(String[]) - Static method in class weka.filters.SerializedFilter: Main method for running this filter.
main(String[]) - Static method in class weka.filters.supervised.attribute.MultiPLS: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.supervised.attribute.PLS: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.supervised.attribute.PLSFilterWithLoadings: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.supervised.attribute.YGradientEPO: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.supervised.attribute.YGradientGLSW: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.AndrewsCurves: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.AnyToString: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.CorrelationMatrix: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Detrend: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.DownSample: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.EquiDistance: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.FastWavelet: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.FFT: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.InputSmearing: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.JoinAttributes: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.LogTransform: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MergeManyAttributes: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Main method for executing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NominalToNumeric: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NormalizeAdaptive: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.PAA: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Main method for executing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.RowSum: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.SAX: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.SetMissingValue: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.SimpleDetrend: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.SpellChecker: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.StringToDate: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.AlignDataset: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.KeepRange: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.instance.LatestRecords: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.instance.MultiRowProcessor: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveDuplicates: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveTestInstances: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveWithLabels: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveWithWeights: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RowNorm: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.SafeRemoveRange: Main method for running this filter from command-line.
main(String[]) - Static method in class weka.filters.unsupervised.instance.Scale: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.Sort: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.instance.SortOnAttribute: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.instance.WeightsBasedResample: Main method for testing this class.
main(String[]) - Static method in class weka.gui.explorer.ExperimentPanel: Tests out the Experiment panel from the command line.
main(String[]) - Static method in class weka.gui.explorer.ExplorerExt: Starts the explorer environment.
main(String[]) - Static method in class weka.gui.explorer.MultiExplorer: Starts the explorer environment.
main(String[]) - Static method in class weka.gui.explorer.SqlPanel: For testing only.
mainFilterTipText() - Method in class weka.filters.FilteredFilter: Returns the tip text for this property.
MAJORITY_VOTING_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType
MAJORITY_VOTING_RULE - Static variable in class weka.classifiers.meta.AbstainVote: combination rule: Majority Voting (only nominal classes)
makeClassLastTipText() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns the tip text for this property.
MakeCompatibleDatasets - Class in adams.gui.menu: For making compatible ARFF datasets.
MakeCompatibleDatasets() - Constructor for class adams.gui.menu.MakeCompatibleDatasets: Initializes the menu item with no owner.
MakeCompatibleDatasets(AbstractApplicationFrame) - Constructor for class adams.gui.menu.MakeCompatibleDatasets: Initializes the menu item.
makeThreadSafeTipText() - Method in class adams.flow.transformer.WekaModelReader: Returns the tip text for this property.
MANUAL - weka.classifiers.meta.MinMaxLimits.LimitHandling: manually supplied value for limit.
manualMaxTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the tip text for this property.
manualMinTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the tip text for this property.
MapToWekaInstance - Class in adams.data.conversion: Converts a map into a Weka Instance, using the provided storage object (Instances) as template.
MapToWekaInstance() - Constructor for class adams.data.conversion.MapToWekaInstance
MarginCurve - Class in adams.gui.menu: Displays a margin curve.
MarginCurve() - Constructor for class adams.gui.menu.MarginCurve: Initializes the menu item with no owner.
MarginCurve(AbstractApplicationFrame) - Constructor for class adams.gui.menu.MarginCurve: Initializes the menu item.
markerExtentTipText() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Returns the tip text for this property.
markersDisabledTipText() - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Returns the tip text for this property.
match(String) - Method in class adams.flow.transformer.WekaRegexToRange: Return match, given invert status.
match(List<Struct2<Instances, Instances>>, List<Struct2<Instances, Instances>>, int) - Method in class weka.classifiers.MultiLevelSplitGenerator: Combines train and test splits as long as there are matches.
match(Instance) - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader: Matches the input instance against the header.
MatchWekaInstanceAgainstFileHeader - Class in adams.data.conversion: Matches an Instance against a dataset header loaded from a file, i.e., it automatically converts STRING attributes into NOMINAL ones and vice versa.
The file can be any format that WEKA recognizes.
MatchWekaInstanceAgainstFileHeader() - Constructor for class adams.data.conversion.MatchWekaInstanceAgainstFileHeader
MatchWekaInstanceAgainstStorageHeader - Class in adams.data.conversion: Matches an Instance against a dataset header from storage, i.e., it automatically converts STRING attributes into NOMINAL ones and vice versa.
MatchWekaInstanceAgainstStorageHeader() - Constructor for class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader
MathExpressionClassifier - Class in weka.classifiers.functions: Simple classifier that uses a pre-defined formula that can make use of attribute values using their names.
Grammar:
expr_list ::= '=' expr_list expr_part | expr_part ;
expr_part ::= expr ;

expr ::= ( expr )

# data types
| number
| string
| boolean
| date

# constants
| true
| false
| pi
| e
| now()
| today()

# negating numeric value
| -expr

# comparisons
| expr < expr
| expr <= expr
| expr > expr
| expr >= expr
| expr = expr
| expr != expr (or: expr <> expr)

# boolean operations
| ! expr (or: not expr)
| expr & expr (or: expr and expr)
| expr | expr (or: expr or expr)
| if[else] ( expr , expr (if true) , expr (if false) )
| ifmissing ( variable , expr (default value if variable is missing) )
| isNaN ( expr )

# arithmetics
| expr + expr
| expr - expr
| expr * expr
| expr / expr
| expr ^ expr (power of)
| expr % expr (modulo)
;

# numeric functions
| abs ( expr )
| sqrt ( expr )
| cbrt ( expr )
| log ( expr )
| log10 ( expr )
| exp ( expr )
| sin ( expr )
| sinh ( expr )
| cos ( expr )
| cosh ( expr )
| tan ( expr )
| tanh ( expr )
| atan ( expr )
| atan2 ( exprY , exprX )
| hypot ( exprX , exprY )
| signum ( expr )
| rint ( expr )
| floor ( expr )
| pow[er] ( expr , expr )
| ceil ( expr )
| min ( expr1 , expr2 )
| max ( expr1 , expr2 )
| year ( expr )
| month ( expr )
| day ( expr )
| hour ( expr )
| minute ( expr )
| second ( expr )
| weekday ( expr )
| weeknum ( expr )

# string functions
| substr ( expr , start [, end] )
| left ( expr , len )
| mid ( expr , start , len )
| right ( expr , len )
| rept ( expr , count )
| concatenate ( expr1 , expr2 [, expr3-5] )
| lower[case] ( expr )
| upper[case] ( expr )
| trim ( expr )
| matches ( expr , regexp )
| trim ( expr )
| len[gth] ( str )
| find ( search , expr [, pos] )
| replace ( str , pos , len , newstr )
| substitute ( str , find , replace [, occurrences] )
;

Notes:
- Variables are either all upper case letters (e.g., "ABC") or any character apart from "]" enclosed by "[" and "]" (e.g., "[Hello World]").
- 'start' and 'end' for function 'substr' are indices that start at 1.
- Index 'end' for function 'substr' is excluded (like Java's 'String.substring(int,int)' method)
- Line comments start with '#'.
- Semi-colons (';') or commas (',') can be used as separator in the formulas,
e.g., 'pow(2,2)' is equivalent to 'pow(2;2)'
- dates have to be of format 'yyyy-MM-dd' or 'yyyy-MM-dd HH:mm:ss'
- times have to be of format 'HH:mm:ss' or 'yyyy-MM-dd HH:mm:ss'
- the characters in square brackets in function names are optional:
e.g.
MathExpressionClassifier() - Constructor for class weka.classifiers.functions.MathExpressionClassifier: Constructor.
MatlabSpreadSheetReader - Class in adams.data.io.input: Reads WEKA datasets in ARFF format and turns them into spreadsheets.
MatlabSpreadSheetReader() - Constructor for class adams.data.io.input.MatlabSpreadSheetReader
MatlabSpreadSheetWriter - Class in adams.data.io.output: Writes a spreadsheet in ARFF file format.
MatlabSpreadSheetWriter() - Constructor for class adams.data.io.output.MatlabSpreadSheetWriter
matrixAlgoToWeka(Matrix) - Static method in class adams.data.instancesanalysis.pls.MatrixHelper: Turns a matrix-algorithm matrix into a Weka one.
MatrixHelper - Class in adams.data.instancesanalysis.pls: Helper class for the matrix-algorithm library.
MatrixHelper - Class in weka.core.matrix: Some matrix operations.
MatrixHelper() - Constructor for class adams.data.instancesanalysis.pls.MatrixHelper
MatrixHelper() - Constructor for class weka.core.matrix.MatrixHelper
MatrixTab - Class in adams.gui.tools.wekainvestigator.tab: Visualizes the selected dataset as matrix plot.
MatrixTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.MatrixTab
matrixTipText() - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess: Returns the tip text for this property.
matrixToBits(Matrix, double, double, int, int, int, int) - Static method in class adams.core.discovery.genetic.WekaGeneticHelper: Convert weka Matrix into bit string
matrixToSpreadSheet(Matrix, String) - Static method in class adams.data.instancesanalysis.pls.MatrixHelper: Turns the matrix into a spreadsheet.
matrixTypeTipText() - Method in class adams.flow.transformer.WekaExtractPLSMatrix: Returns the tip text for this property.
matrixValuesTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Returns the tip text for this property.
MATTHEWS_CORRELATION_COEFFICIENT - adams.flow.core.EvaluationStatistic
MATTHEWS_CORRELATION_COEFFICIENT - adams.flow.core.ExperimentStatistic
MAX - adams.flow.transformer.WekaInstancesInfo.InfoType: the maximum value (selected attribute, only numeric).
MAX - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.UpperStatistic
MAX - Static variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
MAX_COLUMN_WIDTH - Static variable in class adams.gui.tools.wekainvestigator.datatable.DataTable: the maximum column width.
MAX_DATA_POINTS - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: the maximum number of data points before turning off anti-aliasing.
MAX_DECIMAL - Static variable in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: the maximum number of decimals after the decimal point to use.
MAX_HTML_LENGTH - Static variable in class adams.gui.tools.wekainvestigator.output.RunInformationHelper: the maximum length for HTML cells.
MAX_LEVELS - Static variable in class weka.classifiers.meta.ClassifierCascade
MAX_POINTS - Static variable in class adams.gui.visualization.instances.instancestable.JFreeChart: the maximum of data points to plot.
MAX_POINTS - Static variable in class adams.gui.visualization.instances.instancestable.SimplePlot: the maximum of data points to plot.
MAX_RELATIONNAME_LENGTH - Static variable in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: the maximum length for the relationname when assembling the name.
MAX_ROWS - Static variable in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer
MAX_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType
MAX_RULE - Static variable in class weka.classifiers.meta.AbstainVote: combination rule: Maximum Probability
maxAttributeNamesTipText() - Method in class adams.data.instancesanalysis.PCA: Returns the tip text for this property.
maxAttributesTipText() - Method in class adams.data.instancesanalysis.PCA: Returns the tip text for this property.
maxBinTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the maxBin option.
maxClassRangePercentageTipText() - Method in class weka.classifiers.meta.MinMaxLimits: Returns the tip text for this property.
maxDecimalPlacesTipText() - Method in class weka.core.converters.SimpleArffSaver: Returns the tip text for this property.
maxDepthTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the maxDepth option.
maxDifferenceTipText() - Method in class weka.classifiers.meta.AbstainAverage: Returns the tip text for this property
maxDifferenceTipText() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Returns the tip text for this property
maxDifferenceTipText() - Method in class weka.classifiers.meta.AbstainVote: Returns the tip text for this property
maxFactorTipText() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns the tip text for this property.
maxHandlingTipText() - Method in class weka.classifiers.meta.MinMaxLimits: Returns the tip text for this property.
maximumAttributeNamesTipText() - Method in class adams.flow.transformer.WekaPrincipalComponents: Returns the tip text for this property.
maximumAttributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Returns the tip text for this property.
maximumAttributesTipText() - Method in class adams.flow.transformer.WekaPrincipalComponents: Returns the tip text for this property.
maximumAttributesTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Returns the tip text for this property.
maximumDeltaStepTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the maximumDeltaStep option.
maximumIncludedTipText() - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns the tip text for this property.
maximumIncludedTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Returns the tip text for this property.
maximumTipText() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the tip text for this property.
maximumTipText() - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns the tip text for this property.
maximumTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Returns the tip text for this property.
maxIterationsTipText() - Method in class weka.clusterers.SAXKMeans: Returns the tip text for this property.
maxIterationsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Returns the tip text for this property
maxIterationsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Returns the tip text for this property
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 - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.CenterStatistic
MEAN_ABSOLUTE_ERROR - adams.flow.core.EvaluationStatistic
MEAN_ABSOLUTE_ERROR - adams.flow.core.ExperimentStatistic
means() - Method in class weka.filters.supervised.attribute.PLSFilterExtended: the mean of all the attributes
means(Instances) - Method in class weka.classifiers.meta.Corr
Measure - Enum in adams.opt.genetic: The measure to use for evaluating.
measureNumRules() - Method in class weka.classifiers.trees.m5.M5Base2: return the number of rules
measuresPrefixTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the tip text for this property.
measureTipText() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the tip text for this property.
measureTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
measureTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the tip text for this property.
median - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp.IQRs
MEDIAN - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.CenterStatistic
MEDIAN - weka.classifiers.meta.ClassifierCascade.Combination: use the median of the probabilities/classifications.
MEDIAN_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType
MEDIAN_RULE - Static variable in class weka.classifiers.meta.AbstainVote: combination rule: Median Probability (only numeric class)
MemoryContainer - Class in adams.gui.tools.wekainvestigator.data: Dataset exists only in memory.
MemoryContainer(Instances) - Constructor for class adams.gui.tools.wekainvestigator.data.MemoryContainer: Uses the specified data.
MenuItemComparator - Class in adams.gui.tools.wekainvestigator.history: Comparator for sorting the menu items for the history panel.
MenuItemComparator - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold: Comparator for sorting the menu items for the per-fold pane.
MenuItemComparator() - Constructor for class adams.gui.tools.wekainvestigator.history.MenuItemComparator
MenuItemComparator() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.MenuItemComparator
menuItemTextTipText() - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: Returns the tip text for this property.
menuItemTextTipText() - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: Returns the tip text for this property.
merge(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Merges the datasets.
merge(Instances[], Instances[], HashSet) - Method in class adams.flow.transformer.WekaInstancesMerge: Merges the datasets based on the collected IDs.
Merge - Class in adams.gui.tools.wekainvestigator.datatable.action: Merges the selected datasets (side-by-side).
Merge() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Merge: Instantiates the action.
MergeDatasets - Class in adams.gui.menu: For merging datasets (side-by-side) into single dataset.
MergeDatasets() - Constructor for class adams.gui.menu.MergeDatasets: Initializes the menu item with no owner.
MergeDatasets(AbstractApplicationFrame) - Constructor for class adams.gui.menu.MergeDatasets: Initializes the menu item.
mergedIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Returns the tip text for this property.
mergedIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Returns the tip text for this property.
mergeInstance(Instance) - Method in class weka.core.AbstractHashableInstance: Merges this instance with the given instance and returns the result.
MergeManyAttributes - Class in weka.filters.unsupervised.attribute: Merges two or more attributes, offers various strategies if values differ or not present.
Uses the common subsequence (either from start or end) of the attributes as name of the merged attribute, otherwise the concatenation of them (separated by '-').
MergeManyAttributes() - Constructor for class weka.filters.unsupervised.attribute.MergeManyAttributes
mergeMethodTipText() - Method in class adams.flow.transformer.WekaDatasetsMerge: Gets the tip-text for the merge method option.
MergeTwoAttributes - Class in weka.filters.unsupervised.attribute: Merges two attributes, offers various strategies if values differ or not present.
Uses the common subsequence (either from start or end) of the two attributes as name of the merged attribute, otherwise the concatenation of the both (separated by '-').
MergeTwoAttributes() - Constructor for class weka.filters.unsupervised.attribute.MergeTwoAttributes
mergeWith(Row) - Method in class adams.ml.data.InstancesHeaderRow: Merges its own data with the one provided by the specified row.
mergeWith(Row) - Method in class adams.ml.data.InstanceView: Merges its own data with the one provided by the specified row.
mergeWith(SpreadSheet) - Method in class adams.ml.data.InstancesView: Puts the content of the provided spreadsheet on the right.
messageTipText() - Method in class adams.flow.transformer.WekaChooseAttributes: Returns the tip text for this property.
metaDataColorTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
metaLevelClassifierTipText() - Method in class weka.classifiers.meta.PartitionedStacking: Returns the tip text for this property.
MetaPartitionedMultiFilter - Class in weka.filters.unsupervised.attribute: With each specified filter, a regular expression is associated that defines the range of attributes to apply the filter to.
MetaPartitionedMultiFilter() - Constructor for class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter
methodNamePredictionTipText() - Method in class weka.classifiers.functions.PyroProxy: Returns the tip text for this property.
methodNameTrainTipText() - Method in class weka.classifiers.functions.PyroProxy: Returns the tip text for this property.
MIN - adams.flow.transformer.WekaInstancesInfo.InfoType: the minimum value (selected attribute, only numeric).
MIN - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.LowerStatistic
MIN - Static variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
MIN_GLIBC_VERSION - Static variable in class weka.classifiers.trees.XGBoost
MIN_IMPROVEMENT - Static variable in class weka.classifiers.meta.ClassifierCascade
MIN_PROBABILITY - Static variable in class weka.classifiers.meta.AbstainMinimumProbability
MIN_PROBABILITY - Static variable in class weka.classifiers.meta.ThresholdedBinaryClassification
MIN_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType
MIN_RULE - Static variable in class weka.classifiers.meta.AbstainVote: combination rule: Minimum Probability
MIN_SAMPLES - Static variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp
minChildWeightTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the minChildWeight option.
minClassRangePercentageTipText() - Method in class weka.classifiers.meta.MinMaxLimits: Returns the tip text for this property.
minHandlingTipText() - Method in class weka.classifiers.meta.MinMaxLimits: Returns the tip text for this property.
minimalTipText() - Method in class weka.classifiers.functions.LinearRegressionJ: Returns the tip text for this property.
minImprovementTipText() - Method in class weka.classifiers.meta.ClassifierCascade: Returns the tip text for this property.
minimumIncludedTipText() - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns the tip text for this property.
minimumIncludedTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Returns the tip text for this property.
minimumTipText() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the tip text for this property.
minimumTipText() - Method in class adams.data.weka.rowfinder.ByNumericValue: Returns the tip text for this property.
minimumTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Returns the tip text for this property.
minManualTipText() - Method in class weka.classifiers.meta.MinMaxLimits: Returns the tip text for this property.
MinMaxLimits - Class in weka.classifiers.meta: Allows to influence the handling of lower/upper limits of the built classifier when making predictions.
The following types of handling are available: AS_IS, MANUAL, CLASS_RANGE
Details on the types:
- AS_IS: prediction does not get changed
- MANUAL: applies the manual limit, ie at most this limit is output
- CLASS_RANGE: applies the percentage leeway to the class attribute range of the training set to determine the actual limit value.
MinMaxLimits() - Constructor for class weka.classifiers.meta.MinMaxLimits
MinMaxLimits.LimitHandling - Enum in weka.classifiers.meta: Determines the type of handling for the limit
minNumInstancesTipText() - Method in class weka.classifiers.trees.m5.M5Base2: Returns the tip text for this property
minNumRows() - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic: Returns the minimum number of rows that the plugin requires.
minNumRows() - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights: Returns the minimum number of rows that the plugin requires.
minNumRows() - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset: Returns the minimum number of rows that the plugin requires.
minNumRows() - Method in class adams.gui.visualization.instances.instancestable.JFreeChart: Returns the minimum number of rows that the plugin requires.
minNumRows() - Method in interface adams.gui.visualization.instances.instancestable.PlotSelectedRows: Returns the minimum number of rows that the plugin requires.
minNumRows() - Method in interface adams.gui.visualization.instances.instancestable.ProcessSelectedRows: Returns the minimum number of rows that the plugin requires.
minNumRows() - Method in class adams.gui.visualization.instances.instancestable.SimplePlot: Returns the minimum number of rows that the plugin requires.
minProbabilityTipText() - Method in class weka.classifiers.meta.AbstainMinimumProbability: Returns the tip text for this property
minProbabilityTipText() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Returns the tip text for this property.
minSamplesTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Returns the tip text for this property.
minTipText() - Method in class weka.classifiers.trees.RandomRegressionForest: Returns the tip text for this property
minTipText() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
minTipText() - Method in class weka.filters.unsupervised.instance.Scale: Returns the tip text for this property.
MISSING_CLASS_VALUES - adams.flow.core.Capability: can handle missing values in class attribute.
MISSING_VALUES - adams.flow.core.Capability: can handle missing values in attributes.
missingTipText() - Method in class adams.tools.CompareDatasets: Returns the tip text for this property.
mNumComponents - Variable in class weka.core.neighboursearch.PLSNNSearch
MODEL - adams.flow.transformer.WekaClassifierInfo.InfoType: model.
MODEL - adams.flow.transformer.WekaClustererInfo.InfoType: model.
modelActorTipText() - Method in class adams.flow.condition.bool.WekaClassification: Returns the tip text for this property.
modelActorTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the tip text for this property.
modelActorTipText() - Method in class adams.flow.transformer.WekaFilter: Returns the tip text for this property.
modelFileTipText() - Method in class adams.flow.condition.bool.WekaClassification: Returns the tip text for this property.
modelFileTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the tip text for this property.
modelFileTipText() - Method in class adams.flow.transformer.WekaFilter: Returns the tip text for this property.
modelLoadingTypeTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the tip text for this property.
modelLoadingTypeTipText() - Method in class adams.flow.transformer.WekaFilter: Returns the tip text for this property.
modelNameTipText() - Method in class weka.classifiers.functions.PyroProxy: Returns the tip text for this property.
ModelOutput - Class in adams.gui.tools.wekainvestigator.tab.associatetab.output: Outputs the model if available.
ModelOutput - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Outputs the model if available.
ModelOutput - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output: Outputs the model if available.
ModelOutput() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.output.ModelOutput
ModelOutput() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.ModelOutput
ModelOutput() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.ModelOutput
ModelOutputHandler - Interface in weka.core: Interface for classes that allow user to decide whether to output a model in string representation or not.
modelResetVariableTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the tip text for this property.
modelStorageTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the tip text for this property.
modelStorageTipText() - Method in class adams.flow.transformer.WekaFilter: Returns the tip text for this property.
modelToSpreadSheet() - Method in class adams.gui.visualization.instances.InstancesTable: Returns the underlying sheet.
ModificationActionListener() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationActionListener
ModificationChangeListener() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationChangeListener
ModificationDocumentListener() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationDocumentListener
modified() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel: Sets the modified flag in the owner.
MODIFIED - adams.gui.event.InstancesSortSetupEvent.EventType: the setup was modified.
MonitoringDataContainer - Interface in adams.gui.tools.wekainvestigator.data: Interface for data containers that monitor their source for changes.
morphologiesTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Returns the tip text for this property.
moveCentroid(int, Instances, boolean, boolean) - Method in class weka.clusterers.SAXKMeans: Move the centroid to it's new coordinates.
MOVED - adams.gui.event.InstancesSortSetupEvent.EventType: the setup was moved.
moveDefinition(boolean) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: Moves itself around in the list of sorting panels.
moveDefinition(InstancesSortDefinitionPanel, boolean) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Moves the panel up/down.
MSLE - Class in weka.classifiers.evaluation: Computes the mean squared log error (MSLE) for regression models.
MSLE - adams.flow.core.EvaluationStatistic
MSLE - adams.flow.core.ExperimentStatistic
MSLE - adams.opt.genetic.Measure: Mean squared logarithmic error.
MSLE() - Constructor for class weka.classifiers.evaluation.MSLE
msq(Instances) - Method in class weka.classifiers.meta.Corr
MultiAttributeSummaryPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab: Can display one or more instances of AttributeSummaryPanel class.
MultiAttributeSummaryPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel
MultiAttributeVisualizationPanel - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab: Can display one or more instances of AttributeVisualizationPanel class.
MultiAttributeVisualizationPanel() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel
MultiClassifiersCombinerModels - Class in adams.flow.transformer.wekaensemblegenerator: Generates a MultipleClassifiersCombiner meta-classifier from the incoming pre-built classifier models.
MultiClassifiersCombinerModels() - Constructor for class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels
MultiCleaner - Class in weka.core.tokenizers.cleaners: Combines multiple cleaners, applies them sequentially.
MultiCleaner() - Constructor for class weka.core.tokenizers.cleaners.MultiCleaner
MultiClustererPostProcessor - Class in adams.flow.transformer.wekaclusterer: Applies the specified post-processors sequentially.
MultiClustererPostProcessor() - Constructor for class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor
MultiColumnFinder - Class in adams.data.weka.columnfinder: Applies multiple column finding algorithms to the data.
The indices can be either joined or intersected.
MultiColumnFinder() - Constructor for class adams.data.weka.columnfinder.MultiColumnFinder
MultiColumnFinder.Combination - Enum in adams.data.weka.columnfinder: How combine the indices.
MultiExperimenter - Class in adams.gui.tools.wekamultiexperimenter: Extended interface for the WEKA Experimenter, allowing for an arbitrary number of Experimenter panels.
MultiExperimenter() - Constructor for class adams.gui.tools.wekamultiexperimenter.MultiExperimenter
MultiExplorer - Class in adams.gui.menu: Opens the (multi-version of the) WEKA Explorer.
MultiExplorer - Class in weka.gui.explorer: Extended interface for the WEKA Explorer, allowing for an arbitrary number of Explorer panels.
MultiExplorer() - Constructor for class adams.gui.menu.MultiExplorer: Initializes the menu item with no owner.
MultiExplorer() - Constructor for class weka.gui.explorer.MultiExplorer
MultiExplorer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.MultiExplorer: Initializes the menu item.
MultiLevelSplitGenerator - Class in weka.classifiers: Generates splits based on groups extracted via regular expressions.
MultiLevelSplitGenerator() - Constructor for class weka.classifiers.MultiLevelSplitGenerator
MultiplicativeScatterCorrection - Class in weka.filters.unsupervised.attribute: Performs Multiplicative Scatter Correction, using the specified correction scheme.
MultiplicativeScatterCorrection() - Constructor for class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection
multiplierTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev: Returns the tip text for this property.
MultiPLS - Class in weka.filters.supervised.attribute: For each Y that gets identified by the regular expression for Y attributes, the specified PLS (partial least squares) algorithm gets applied to the X attributes identified by the corresponding regular expression.
MultiPLS() - Constructor for class weka.filters.supervised.attribute.MultiPLS
MultiPostProcessor - Class in adams.flow.transformer.wekaevaluationpostprocessor: Applies the specified post-processors sequentially to the input data and combines their output.
MultiPostProcessor() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor
MultiRowFinder - Class in adams.data.weka.rowfinder: Applies multiple row finding algorithms to the data.
The indices can be either joined or intersected.
MultiRowFinder() - Constructor for class adams.data.weka.rowfinder.MultiRowFinder
MultiRowFinder.Combination - Enum in adams.data.weka.rowfinder: How combine the indices.
MultiRowProcessor - Class in weka.filters.unsupervised.instance: Uses the specified row selection scheme to identify groups of rows in the data coming through and then applies the selected row processor to these subsets.
MultiRowProcessor() - Constructor for class weka.filters.unsupervised.instance.MultiRowProcessor
MultiTokenizer - Class in weka.core.tokenizers: Combines the tokens of several tokenizers, skipping duplicate tokens.
MultiTokenizer() - Constructor for class weka.core.tokenizers.MultiTokenizer

N

NAME - Static variable in class weka.classifiers.evaluation.Bias
NAME - Static variable in class weka.classifiers.evaluation.Dice
NAME - Static variable in class weka.classifiers.evaluation.MSLE
NAME - Static variable in class weka.classifiers.evaluation.RPD
NAME - Static variable in class weka.classifiers.evaluation.RSquared
NAME - Static variable in class weka.classifiers.evaluation.SDR
names() - Method in class adams.flow.container.WekaAssociatorContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaAttributeSelectionContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaClusterEvaluationContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaClusteringContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaEvaluationContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaExperimentContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaFilterContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaGeneticAlgorithmContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaGeneticAlgorithmInitializationContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaModelContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaNearestNeighborSearchContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaPredictionContainer: Returns all value names that can be used (theoretically).
names() - Method in class adams.flow.container.WekaTrainTestSetContainer: Returns all value names that can be used (theoretically).
nameServerTipText() - Method in class weka.classifiers.functions.PyroProxy: Returns the tip text for this property.
nameServerTipText() - Method in interface weka.core.PyroProxyObject: Returns the tip text for this property.
namesTipText() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Returns the tip text for this property.
nameTipText() - Method in class adams.data.weka.classattribute.ByExactName: Returns the tip text for this property.
nameTipText() - Method in class adams.data.weka.columnfinder.ByExactName: Returns the tip text for this property.
NAN - Static variable in class adams.data.weka.rowfinder.ByNumericValue: the placeholder for NaN.
NAN - Static variable in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: the placeholder for NaN.
nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.NewNNSearch: Returns the nearest instance in the current neighbourhood to the supplied instance.
nearestNeighbourSearchAlgorithmTipText() - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Returns the tip text for this property.
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.
numDecimalsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Returns the tip text for this property.
numDecimalsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Returns the tip text for this property.
NUMERIC_ATTRIBUTES - adams.flow.core.Capability: can handle numeric attributes.
NUMERIC_CLASS - adams.flow.core.Capability: can handle numeric classes.
NumericClassGroupExtractor() - Constructor for class adams.data.binning.BinnableInstances.NumericClassGroupExtractor
NumericErrorScalerWithReference - Class in adams.data.weka.predictions: Scales the errors for numeric class attributes, using an user-specified error as reference point for a specified size.
NumericErrorScalerWithReference() - Constructor for class adams.data.weka.predictions.NumericErrorScalerWithReference
numEvaluationBinsTipText() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Returns the tip text for this property.
numExecutionSlotsTipText() - Method in class weka.classifiers.meta.SubsetEnsemble: Returns the tip text for this property.
numExecutionSlotsTipText() - Method in class weka.classifiers.meta.VotedImbalance: Returns the tip text for this property.
numExecutionSlotsTipText() - Method in class weka.clusterers.SAXKMeans: Returns the tip text for this property
numFoldsTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Returns the tip text for this property.
numFoldsTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the tip text for this property.
numFoldsTipText() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
numFoldsTipText() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns the tip text for this property.
numFoldsTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
numFoldsTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the tip text for this property.
numFoldsTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns the tip text for this property.
numFoldsTipText() - Method in class weka.classifiers.meta.ClassifierCascade: Returns the tip text for this property.
numFoldsTipText() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the tip text for this property.
numFoldsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Returns the tip text for this property
numFoldsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Returns the tip text for this property
numInstances() - Method in class weka.core.InstancesView: Returns the number of instances in the dataset.
numIterationsTipText() - Method in class weka.classifiers.trees.RandomModelTrees: Returns the tip text for this property.
numIterationsTipText() - Method in class weka.classifiers.trees.RandomRegressionForest: Returns the tip text for this property
numLeaves(int) - Method in class weka.classifiers.trees.m5.RuleNode2: Sets the leaves' numbers
numParameters() - Method in class weka.classifiers.functions.LinearRegressionJ: Get the number of coefficients used in the model
numPointsLeftTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns the tip text for this property.
numPointsRightTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Returns the tip text for this property.
numPointsTipText() - Method in class weka.filters.unsupervised.attribute.AndrewsCurves: Returns the tip text for this property.
numPointsTipText() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the tip text for this property.
numPointsTipText() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Returns the tip text for this property.
numRandomFeaturesTipText() - Method in class weka.classifiers.meta.SubsetEnsemble: Returns the tip text for this property.
numRegressionsTipText() - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Returns the tip text for this property
numRegressionsTipText() - Method in class weka.classifiers.meta.LeastMedianSq: Returns the tip text for this property
numRowsTipText() - Method in class adams.data.conversion.WekaCapabilitiesToInstances: Returns the tip text for this property.
numSimplsCoefficientsTipText() - Method in class adams.data.instancesanalysis.pls.PRM: Returns the tip text for this property
numSubSamplesTipText() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the tip text for this property.
numThreadsTipText() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the tip text for this property.
numThreadsTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the tip text for this property.
numThreadsTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the tip text for this property.
numThreadsTipText() - Method in class weka.classifiers.meta.ClassifierCascade: Returns the tip text for this property.
numThreadsTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the numThreads option.
numThreadsTipText() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the tip text for this property.
numValues() - Method in class weka.core.AbstractHashableInstance: Returns the number of values present in a sparse representation.
numZeroesTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Returns the tip text for this property.

O

objectiveTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the objective option.
offlineTipText() - Method in class adams.data.instances.AbstractInstanceGenerator: Returns the tip text for this property.
oldFilterTipText() - Method in class adams.data.conversion.SwapPLS: Returns the tip text for this property.
oneDropTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the oneDrop option.
ONEMISSING_MISSING - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes: what to do if one is missing: missing.
ONEMISSING_MISSING - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: what to do if one is missing: missing.
ONEMISSING_USE_FIRST_PRESENT - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes: what to do if one is missing: use first present value.
ONEMISSING_USE_PRESENT - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: what to do if one is missing: use present value.
oneMissingTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Returns the tip text for this property.
oneMissingTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Returns the tip text for this property.
ONLY_MULTIINSTANCE - adams.flow.core.Capability: can handle multi-instance data.
onlyFirstBatchTipText() - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Returns the tip text for this property.
onTheFlyTipText() - Method in class adams.flow.condition.bool.WekaClassification: Returns the tip text for this property.
onTheFlyTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the tip text for this property.
onTheFlyTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the tip text for this property.
open() - Method in class adams.gui.tools.DatasetCompatibilityPanel: Brings up dialog for selecting files.
open() - Method in class weka.gui.explorer.ExplorerExt: Lets the user choose a file.
open(File) - Method in class weka.gui.explorer.ExplorerExt: For opening an external file.
open(File[]) - Method in class adams.gui.tools.DatasetCompatibilityPanel: Opens the specified files, determines the loader automatically.
open(File[], AbstractFileLoader) - Method in class adams.gui.tools.DatasetCompatibilityPanel: Opens the specified files with the given loader.
openFile() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Lets user select a dataset.
openFile(File) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Lets user select a dataset.
openRecent(RecentItemEvent<JMenu, RecentFilesHandlerWithCommandline.Setup>) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: For opening a recently used file.
openRecent(RecentItemEvent<JMenu, File>) - Method in class weka.gui.explorer.ExplorerExt: For opening a recently used file.
openRecentResults(RecentItemEvent<JMenu, RecentFilesHandlerWithCommandline.Setup>) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: For opening a recently used results file.
openRecentSetup(RecentItemEvent<JMenu, File>) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: For opening a recently used experiment file.
openResults() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Loads the results from a file.
openResults(File, AbstractFileLoader) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Loads the results from the file.
openResultsDB() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Loads the results from a database.
openSetup() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Lets the user choose an experiment file.
openSetup(File) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: For opening an experiment file.
openWorkspace() - Method in class weka.gui.explorer.MultiExplorer: Opens a workspace.
operationTipText() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns the tip text for this property.
OPLS - Class in adams.data.instancesanalysis.pls
OPLS() - Constructor for class adams.data.instancesanalysis.pls.OPLS
optimise(OptData, FitnessFunction) - Method in class adams.opt.optimise.GeneticAlgorithm
optimizerTipText() - Method in class adams.flow.transformer.WekaClassifierOptimizer: Returns the tip text for this property.
optionalTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns the tip text for this property.
originalIndices - Variable in class weka.classifiers.lazy.LWLDatasetBuilder.LWLContainer: the indices (from the training dataset).
otherParametersTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the otherParameters option.
OuterProductAnalysis - Class in weka.filters.unsupervised.attribute: Performs Outer Product Analysis (OPA).

For more information, see:
Fabricio S.Terra, Raphael A.Viscarra Rossel, Jose A.M.Dematte (2019).
OuterProductAnalysis() - Constructor for class weka.filters.unsupervised.attribute.OuterProductAnalysis
output() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Returns the generated token.
output() - Method in class adams.flow.source.WekaDatabaseReader: Returns the generated token.
output() - Method in class adams.flow.transformer.WekaAccumulatedError: Returns the generated token.
output() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the generated token.
output() - Method in class adams.flow.transformer.WekaFileReader: Returns the generated token.
output() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns the generated token.
output() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Returns the generated token.
output() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns the generated token.
output() - Method in class adams.flow.transformer.WekaSubsets: Returns the generated token.
outputAdditionalStatsTipText() - Method in class weka.classifiers.functions.LinearRegressionJ: Returns the tip text for this property.
outputAdditionalStatsTipText() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns the tip text for this property.
outputArrayTipText() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Returns the tip text for this property.
outputArrayTipText() - Method in class adams.flow.source.WekaSelectDataset: Returns the tip text for this property.
outputArrayTipText() - Method in class adams.flow.source.WekaSelectObjects: Returns the tip text for this property.
outputArrayTipText() - Method in class adams.flow.transformer.WekaAttributeIterator: Returns the tip text for this property.
outputArrayTipText() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor: Returns the tip text for this property.
outputArrayTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns the tip text for this property.
outputArrayTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the tip text for this property.
outputArrayTipText() - Method in class adams.flow.transformer.WekaInstancesInfo: Returns the tip text for this property.
outputArrayTipText() - Method in class adams.flow.transformer.WekaRandomSplit: Returns the tip text for this property.
outputArrayTipText() - Method in class adams.flow.transformer.WekaSplitGenerator: Returns the tip text for this property.
outputBestSetupTipText() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the tip text for this property.
outputContainerTipText() - Method in class adams.flow.transformer.WekaFilter: Returns the tip text for this property.
outputDataset(double, Instances) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Saves the instances to a file.
outputDirectoryTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
outputDirectoryTipText() - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Returns the tip text for this property.
outputDistributionTipText() - Method in class adams.flow.transformer.wekaclusterer.AddCluster: Returns the tip text for this property.
outputFileTipText() - Method in class adams.flow.sink.AbstractWekaModelWriter: Returns the tip text for this property.
outputFileTipText() - Method in class adams.flow.sink.WekaExperimentFileWriter: Returns the tip text for this property.
outputFileTipText() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the tip text for this property.
outputFileTipText() - Method in class adams.flow.sink.WekaFileWriter: Returns the tip text for this property.
outputFileTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Returns the tip text for this property.
outputFileTipText() - Method in class adams.tools.CompareDatasets: Returns the tip text for this property.
outputFormatTipText() - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: Returns the tip text for this property.
outputFormatTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the tip text for this property.
outputFormatTipText() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns the tip text for this property.
outputFormatTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the tip text for this property.
outputHeaderTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the tip text for this property.
outputHeaderTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the tip text for this property.
outputIndicesTipText() - Method in class adams.flow.transformer.WekaAttributeIterator: Returns the tip text for this property.
outputInstanceTipText() - Method in class adams.flow.transformer.WekaClassifying: Returns the tip text for this property.
outputModelTipText() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Returns the tip text for this property.
outputModelTipText() - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator: Returns the tip text for this property.
outputNameTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Gets the tip-text for the output name option.
outputOnlyModelTipText() - Method in class adams.flow.transformer.AbstractWekaModelReader: Returns the tip text for this property.
OutputPanel - Class in adams.gui.tools.wekamultiexperimenter.setup.weka: Allows the user to select the output type, e.g., ARFF file or JDBC database.
OutputPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel
outputPrefixTipText() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns the tip text for this property.
OutputPrefixType - Enum in adams.opt.genetic: Defines what kind of prefix to use for outputting data and setups.
outputPrefixTypeTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
outputRelationNameTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the tip text for this property.
outputSetup(double, Instances, Classifier, int, int[]) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Saves the setup to a props file.
OutputTabbedPane - Class in adams.gui.tools.wekainvestigator.output: Tabbed pane for the output.
OutputTabbedPane() - Constructor for class adams.gui.tools.wekainvestigator.output.OutputTabbedPane
outputTipText() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Returns the tip text for this property.
outputTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the tip text for this property.
outputTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the tip text for this property.
outputTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput: Returns the tip text for this property.
OutputType - Enum in adams.opt.genetic: Defines what to output during a genetic algorithm run.
outputTypeTipText() - Method in class adams.flow.transformer.WekaFileReader: Returns the tip text for this property.
outputTypeTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
overlaysTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
overrideJobRunnerTipText() - Method in class adams.flow.transformer.WekaExperimentExecution: Returns the tip text for this property.
overrideTipText() - Method in class adams.flow.transformer.WekaClassSelector: Returns the tip text for this property.
ownerChanged() - Method in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel: Gets called when the owner changes.
ownerChanged() - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel: Gets called when the owner changes.
ownerChanged() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel: Gets called when the owner changes.
ownerChanged() - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: Gets called when the owner changes.

P

PAA - Class in weka.filters.unsupervised.attribute: Valid options are:
PAA() - Constructor for class weka.filters.unsupervised.attribute.PAA
PACKAGE - adams.flow.source.wekapackagemanageraction.ListPackages.OutputFormat
PackageManager - Class in adams.gui.menu: Opens the WEKA PackageManager.
PackageManager() - Constructor for class adams.gui.menu.PackageManager: Initializes the menu item with no owner.
PackageManager(AbstractApplicationFrame) - Constructor for class adams.gui.menu.PackageManager: Initializes the menu item.
PackData - Class in adams.opt.optimise.genetic: ???
PackData(PackDataDef) - Constructor for class adams.opt.optimise.genetic.PackData
PackDataDef - Class in adams.opt.optimise.genetic: ???
PackDataDef() - Constructor for class adams.opt.optimise.genetic.PackDataDef
PackDataDef.DataInfo - Class in adams.opt.optimise.genetic
PackDataGeneticAlgorithm - Class in adams.opt.genetic: ???
PackDataGeneticAlgorithm - Class in adams.opt.optimise.genetic: ???
PackDataGeneticAlgorithm() - Constructor for class adams.opt.genetic.PackDataGeneticAlgorithm
PackDataGeneticAlgorithm() - Constructor for class adams.opt.optimise.genetic.PackDataGeneticAlgorithm
PackDataInitialSetupsProvider<T extends PackDataGeneticAlgorithm> - Class in adams.opt.genetic.initialsetups
PackDataInitialSetupsProvider() - Constructor for class adams.opt.genetic.initialsetups.PackDataInitialSetupsProvider
pad(Instances) - Method in class weka.filters.unsupervised.attribute.FastWavelet: pads the data to conform to the necessary number of attributes.
PADDING_ZERO - Static variable in class weka.filters.unsupervised.attribute.FastWavelet: the type of padding: Zero padding.
paddingTipText() - Method in class weka.filters.unsupervised.attribute.FastWavelet: Returns the tip text for this property.
paintComponent(Graphics) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Paints this component
paintletTipText() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the tip text for this property.
paintletTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Returns the tip text for this property.
paintletTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the tip text for this property.
paintValue(Graphics, Rectangle) - Method in class adams.gui.goe.WekaExperimentFileEditor: Paints a representation of the current Object.
Panel() - Constructor for class adams.gui.visualization.instance.HistogramFactory.Panel
Panel() - Constructor for class adams.gui.visualization.instance.InstanceReportFactory.Panel: Initializes the tabbed pane with not reports.
PARAM_CLASSVALUES - Static variable in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS
PARAM_CLASSVALUES - Static variable in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS
PARAMETERS - adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption
parametersTipText() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Returns the tip text for this property.
paramValue() - Method in enum weka.classifiers.trees.XGBoost.Objective
paramValue() - Method in interface weka.classifiers.trees.XGBoost.ParamValueProvider: Provides a proxy object suitable for the XGBoost parameter system in place of this object.
paramValue() - Method in enum weka.classifiers.trees.XGBoost.Predictor
paramValue() - Method in enum weka.classifiers.trees.XGBoost.Verbosity
parentComponentActorTipText() - Method in class adams.flow.source.WekaSelectDataset: Returns the tip text for this property.
parentNode() - Method in class weka.classifiers.trees.m5.RuleNode2: Get the parent of this node
parse(String) - Method in class adams.data.instance.InstancePoint: Parses a string and instantiates a sequence point of it.
parse(String) - Method in enum adams.flow.core.EvaluationStatistic: Parses the given string and returns the associated enum.
parse(String) - Method in enum adams.flow.core.ExperimentStatistic: Parses the given string and returns the associated enum.
parse(String) - Method in enum adams.flow.sink.WekaThresholdCurve.AttributeName: Parses the given string and returns the associated enum.
parse(String) - Method in enum adams.flow.transformer.WekaClassifierRanker.Measure: Parses the given string and returns the associated enum.
parse(String) - Method in class adams.gui.goe.WekaAttributeIndexEditor: Parses the given string and returns the generated object.
parse(String) - Method in class adams.gui.goe.WekaAttributeRangeEditor: Parses the given string and returns the generated object.
parse(String) - Method in class adams.gui.goe.WekaLabelIndexEditor: Parses the given string and returns the generated object.
parse(String) - Method in class adams.gui.goe.WekaLabelRangeEditor: Parses the given string and returns the generated object.
parse(String) - Method in class adams.gui.goe.WekaUnorderedAttributeRangeEditor: Parses the given string and returns the generated object.
parse(String[], char) - Static method in class weka.core.WekaOptionUtils: Parses an array option, returns all the occurrences of the option as a string array.
parse(String[], char, double) - Static method in class weka.core.WekaOptionUtils: Parses a double option, uses default if option is missing.
parse(String[], char, float) - Static method in class weka.core.WekaOptionUtils: Parses a float option, uses default if option is missing.
parse(String[], char, int) - Static method in class weka.core.WekaOptionUtils: Parses an int option, uses default if option is missing.
parse(String[], char, long) - Static method in class weka.core.WekaOptionUtils: Parses an long option, uses default if option is missing.
parse(String[], char, BaseObject) - Static method in class weka.core.WekaOptionUtils: Parses a BaseObject option, uses default if option is missing.
parse(String[], char, BaseObject[]) - Static method in class weka.core.WekaOptionUtils: Parses a BaseObject option, uses default if option is missing.
parse(String[], char, Index) - Static method in class weka.core.WekaOptionUtils: Parses an Index option, uses default if option is missing.
parse(String[], char, Index[]) - Static method in class weka.core.WekaOptionUtils: Parses an Index option, uses default if option is missing.
parse(String[], char, OptionHandler) - Static method in class weka.core.WekaOptionUtils: Parses an adams.core.option.OptionHandler option, uses default if option is missing.
parse(String[], char, OptionHandler[], Class) - Static method in class weka.core.WekaOptionUtils: Parses an adams.core.option.OptionHandler array option, uses default if option is missing.
parse(String[], char, Range) - Static method in class weka.core.WekaOptionUtils: Parses a Range option, uses default if option is missing.
parse(String[], char, Range[]) - Static method in class weka.core.WekaOptionUtils: Parses a Range option, uses default if option is missing.
parse(String[], char, File) - Static method in class weka.core.WekaOptionUtils: Parses a File option, uses default if option is missing.
parse(String[], char, Class<T>) - Static method in class weka.core.WekaOptionUtils: Parses an array option, returns all the occurrences of the option as a string array.
parse(String[], char, Enum) - Static method in class weka.core.WekaOptionUtils: Parses an enum option, uses default if option is missing.
parse(String[], char, String) - Static method in class weka.core.WekaOptionUtils: Parses a String option, uses default if option is missing.
parse(String[], char, OptionHandler) - Static method in class weka.core.WekaOptionUtils: Parses an OptionHandler option, uses default if option is missing.
parse(String[], char, OptionHandler[], Class) - Static method in class weka.core.WekaOptionUtils: Parses an OptionHandler array option, uses default if option is missing.
parse(String[], String) - Static method in class weka.core.WekaOptionUtils: Parses an array option, returns all the occurrences of the option as a string array.
parse(String[], String, double) - Static method in class weka.core.WekaOptionUtils: Parses a double option, uses default if option is missing.
parse(String[], String, float) - Static method in class weka.core.WekaOptionUtils: Parses a float option, uses default if option is missing.
parse(String[], String, int) - Static method in class weka.core.WekaOptionUtils: Parses an int option, uses default if option is missing.
parse(String[], String, long) - Static method in class weka.core.WekaOptionUtils: Parses a long option, uses default if option is missing.
parse(String[], String, BaseObject) - Static method in class weka.core.WekaOptionUtils: Parses a BaseObject option, uses default if option is missing.
parse(String[], String, BaseObject[]) - Static method in class weka.core.WekaOptionUtils: Parses a BaseObject option, uses default if option is missing.
parse(String[], String, Index) - Static method in class weka.core.WekaOptionUtils: Parses a Index option, uses default if option is missing.
parse(String[], String, Index[]) - Static method in class weka.core.WekaOptionUtils: Parses a Index option, uses default if option is missing.
parse(String[], String, PlaceholderDirectory) - Static method in class weka.core.WekaOptionUtils: Parses a PlaceholderDirectory option, uses default if option is missing.
parse(String[], String, PlaceholderFile) - Static method in class weka.core.WekaOptionUtils: Parses a PlaceholderFile option, uses default if option is missing.
parse(String[], String, OptionHandler) - Static method in class weka.core.WekaOptionUtils: Parses an adams.core.option.OptionHandler option, uses default if option is missing.
parse(String[], String, OptionHandler[], Class) - Static method in class weka.core.WekaOptionUtils: Parses an adams.core.option.OptionHandler array option, uses default if option is missing.
parse(String[], String, Range) - Static method in class weka.core.WekaOptionUtils: Parses a Range option, uses default if option is missing.
parse(String[], String, Range[]) - Static method in class weka.core.WekaOptionUtils: Parses a Range option, uses default if option is missing.
parse(String[], String, File) - Static method in class weka.core.WekaOptionUtils: Parses a File option, uses default if option is missing.
parse(String[], String, Class<T>) - Static method in class weka.core.WekaOptionUtils: Parses an array option, returns all the occurrences of the option as a string array.
parse(String[], String, Enum) - Static method in class weka.core.WekaOptionUtils: Parses an enum option, uses default if option is missing.
parse(String[], String, Object, Class) - Static method in class weka.core.WekaOptionUtils: Parses an array option, uses default if option is missing.
parse(String[], String, String) - Static method in class weka.core.WekaOptionUtils: Parses a String option, uses default if option is missing.
parse(String[], String, OptionHandler) - Static method in class weka.core.WekaOptionUtils: Parses an OptionHandler option, uses default if option is missing.
parse(String[], String, OptionHandler[], Class) - Static method in class weka.core.WekaOptionUtils: Parses an OptionHandler array option, uses default if option is missing.
parseAttribute(String) - Method in class weka.core.converters.SimpleArffLoader: Extracts the attribute name, type and date format from the line.
parseClassify(byte[]) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation: Parses the data received from the process, to be returned by the Classifier.classifyInstance(Instance) method.
parseClassify(byte[]) - Method in class weka.classifiers.meta.socketfacade.Simple: Parses the data received from the process, to be returned by the Classifier.classifyInstance(Instance) method.
parseContent(String) - Method in class adams.ml.data.DataCellView: Attempts to determine the data type of the string.
parseContent(String, Cell.ContentType) - Method in class adams.ml.data.DataCellView: Parses the content of the cell using the specified type.
parseDense(Instances, String) - Method in class weka.core.converters.SimpleArffLoader: Parses a dense instance.
parseDistribution(byte[], int) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation: Parses the data received from the process, to be returned by the Classifier.distributionForInstance(Instance) method.
parseDistribution(byte[], int) - Method in class weka.classifiers.meta.socketfacade.Simple: Parses the data received from the process, to be returned by the Classifier.distributionForInstance(Instance) method.
parsePrediction(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Parses the prediction.
parsePredictions(PyroProxy, Object) - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Parses the predictions.
parseSparse(Instances, String) - Method in class weka.core.converters.SimpleArffLoader: Parses a data row in sparse format.
parseString(String) - Method in class weka.classifiers.meta.AbstainAverage: Expect ; separated entries with min,max,difference e.g.
parseString(String) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Expect ; separated entries with min,max,difference e.g.
parseString(String) - Method in class weka.classifiers.meta.AbstainVote: Expect ; separated entries with min,max,difference e.g.
parseSubRange(String) - Method in class adams.data.weka.WekaUnorderedAttributeRange: Parses the subrange.
parseTrain(byte[]) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation: Parses the data received from the process from the training process.
parseTrain(byte[]) - Method in class weka.classifiers.meta.socketfacade.Simple: Parses the data received from the process from the training process.
parseWeights(String) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Expect "1,1,1,1"
PartialLeastSquaresTab - Class in adams.gui.tools.wekainvestigator.tab: Visualizes the PLS loadings and PLS space calculated from the selected dataset.
PartialLeastSquaresTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab
PartitionedMultiFilter2 - Class in weka.filters.unsupervised.attribute: A filter that applies filters on subsets of attributes and assembles the output into a new dataset.
PartitionedMultiFilter2() - Constructor for class weka.filters.unsupervised.attribute.PartitionedMultiFilter2
PartitionedStacking - Class in weka.classifiers.meta: Builds the base-classifiers on subsets of the data defined by ranges that correspond to the base-classifiers.
PartitionedStacking() - Constructor for class weka.classifiers.meta.PartitionedStacking
PassThrough - Class in adams.data.weka.evaluator: A dummy evaluator that OKs all data.
PassThrough - Class in adams.flow.transformer.wekaclassifiersetupprocessor: Simply returns the same setups.
PassThrough - Class in adams.flow.transformer.wekaclusterer: Dummy post-processor that just returns the model container as it is.
PassThrough - Class in adams.flow.transformer.wekaevaluationpostprocessor: Does nothing, just passes through the input data.
PassThrough - Class in weka.core.tokenizers.cleaners: Dummy, never removes a token.
PassThrough - Class in weka.filters.unsupervised.instance.multirowprocessor.processor: Just passes through the data.
PassThrough() - Constructor for class adams.data.weka.evaluator.PassThrough
PassThrough() - Constructor for class adams.flow.transformer.wekaclassifiersetupprocessor.PassThrough
PassThrough() - Constructor for class adams.flow.transformer.wekaclusterer.PassThrough
PassThrough() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.PassThrough
PassThrough() - Constructor for class weka.core.tokenizers.cleaners.PassThrough
PassThrough() - Constructor for class weka.filters.unsupervised.instance.multirowprocessor.processor.PassThrough
passwordTipText() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the tip text for this property.
passwordTipText() - Method in class adams.flow.source.WekaDatabaseReader: Returns the tip text for this property.
PATTERN - Static variable in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens: the pattern to use.
pauseExecution() - Method in class adams.flow.transformer.WekaClassifierRanker: Pauses the execution.
pauseExecution() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Pauses the execution.
PCA - Class in adams.data.instancesanalysis: Performs principal components analysis and allows access to loadings and scores.
PCA() - Constructor for class adams.data.instancesanalysis.PCA
PCANNSearch - Class in weka.core.neighboursearch: Class implementing the brute force search algorithm for nearest neighbour search, filtered using PLS.
PCANNSearch() - Constructor for class weka.core.neighboursearch.PCANNSearch: Constructor.
PCANNSearch(Instances) - Constructor for class weka.core.neighboursearch.PCANNSearch: Constructor that uses the supplied set of instances.
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.
postExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup: Hook method for after executing the experiment, e.g., cleaning up temp files.
postExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Hook method for after executing the experiment, e.g., cleaning up temp files.
postExecute(Classifier, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Hook method for after executing the experiment, e.g., cleaning up temp files.
postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Hook method that gets called after finishing a job.
postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Hook method that gets called after finishing a job.
postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Hook method that gets called after finishing a job.
postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Hook method that gets called after finishing a job.
postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Hook method that gets called after finishing a job.
postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Hook method that gets called after finishing a job.
postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Hook method that gets called after finishing a job.
postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Hook method that gets called after stopping a job.
postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Hook method that gets called after finishing a job.
postExecutionFinished() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Hook method that gets called after finishing a job.
postGenerate(Object, IndexedSplitsRuns, MessageCollection) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: For post-processing successfully generated splits.
postProcess(WekaEvaluationContainer) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor: Post-processes the evaluation container.
postProcess(WekaModelContainer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClustererPostProcessor: Post-processes the model container.
postProcess(Evaluation) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.AbstractWekaEvaluationPostProcessor: Post-processes the evaluation.
postProcess(Evaluation) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Post-processes the Evaluation if necessary.
postProcessCheck() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Checks whether all post-conditions have been met.
postProcessCheck() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob: Checks whether all post-conditions have been met.
postProcessCheck() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob: Checks whether all post-conditions have been met.
postProcessCheck() - Method in class adams.flow.transformer.WekaTrainAssociator.TrainJob: Checks whether all post-conditions have been met.
postProcessCheck() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob: Checks whether all post-conditions have been met.
postProcessCheck() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob: Checks whether all post-conditions have been met.
postProcessCheck() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: Checks whether all post-conditions have been met.
postProcessCheck() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: Checks whether all post-conditions have been met.
postProcessCheck() - Method in class adams.multiprocess.WekaCrossValidationJob: Checks whether all post-conditions have been met.
postProcessCheck() - Method in class adams.opt.optimise.GeneticAlgorithm.GAJob
postProcessDistances(double[]) - Method in class weka.core.SAXDistance: Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).
postProcessDistances(double[]) - Method in class weka.core.WeightedEuclideanDistance: Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).
postProcessDistances(double[]) - Method in class weka.core.WeightedEuclideanDistanceRidge: Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).
postProcessHeader(T) - Method in class adams.data.instances.AbstractInstanceGenerator: Adds IDs, notes, additional fields to header.
postProcessorsTipText() - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor: Returns the tip text for this property.
postProcessorsTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor: Returns the tip text for this property.
postProcessorTipText() - Method in class adams.flow.transformer.WekaClustererPostProcessor: Returns the tip text for this property.
postProcessorTipText() - Method in class adams.flow.transformer.WekaEvaluationPostProcessor: Returns the tip text for this property.
postProcessorTipText() - Method in class adams.flow.transformer.WekaTrainClusterer: Returns the tip text for this property.
postProcessOutput(T, Instance) - Method in class adams.data.instances.AbstractInstanceGenerator: For adding IDs, notes, additional fields to the data.
postRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob: Gets called after execution.
postRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob: Gets called after execution.
postRun() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Further clean-ups in derived classes.
postRun(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractAdamsExperimentRunner: Hook method that gets executed after the experiment has finished (successfully or not).
postRun(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Hook method that gets executed after the experiment has finished (successfully or not).
postRun(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractWekaExperimentRunner: Hook method that gets executed after the experiment has finished (successfully or not).
postRun(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.runner.DefaultWekaExperimentRunner: Hook method that gets executed after the experiment has finished (successfully or not).
postRun(String) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Further clean-ups in derived classes.
postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Hook method that gets called after successfully starting a job.
postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Hook method that gets called after successfully starting a job.
postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Hook method that gets called after successfully starting a job.
postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Hook method that gets called after successfully starting a job.
postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Hook method that gets called after successfully starting a job.
postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Hook method that gets called after successfully starting a job.
postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Hook method that gets called after successfully starting a job.
postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Hook method that gets called after successfully starting a job.
postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Hook method that gets called after successfully starting a job.
postStartExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Hook method that gets called after successfully starting a job.
postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Hook method that gets called after stopping a job.
postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Hook method that gets called after stopping a job.
postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Hook method that gets called after stopping a job.
postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Hook method that gets called after stopping a job.
postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Hook method that gets called after stopping a job.
postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Hook method that gets called after stopping a job.
postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Hook method that gets called after stopping a job.
postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Hook method that gets called after stopping a job.
postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Hook method that gets called after stopping a job.
postStopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Hook method that gets called after stopping a job.
postTokenizerTipText() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Returns the tip text for this property.
postTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: Postprocesses the data.
postTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Postprocesses the data.
postTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS: Postprocesses the data.
postUpdate() - Method in class adams.gui.visualization.instance.InstancePanel: Hook method, called after the update was performed.
PRE_FILTER - Static variable in class weka.filters.unsupervised.instance.KennardStone
PRE_TOKENIZER - Static variable in class weka.core.tokenizers.PreCleanedTokenizer
PRECISION - adams.flow.sink.WekaThresholdCurve.AttributeName
PRECISION - adams.opt.genetic.Measure: precision.
PreCleanedTokenizer - Class in weka.core.tokenizers: Allows the cleaning of tokens before actual tokenization.
PreCleanedTokenizer() - Constructor for class weka.core.tokenizers.PreCleanedTokenizer
predict(Instances) - Method in class adams.data.instancesanalysis.pls.PLS1: Performs predictions on the data.
PREDICTED_CLUSTER - Static variable in class adams.flow.transformer.wekaclusterer.AddCluster
PREDICTED_DISTRIBUTION - Static variable in class adams.flow.transformer.wekaclusterer.AddCluster
PREDICTED_MINUS_ACTUAL - adams.flow.transformer.WekaBootstrapping.ErrorCalculation
predictedMaxTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
predictedMinTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
predictedTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the tip text for this property.
predictedTipText() - Method in class weka.classifiers.functions.FromPredictions: Returns the tip text for this property.
predictIntervals(Instance, double) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Predicts a confidence interval for the given instance and confidence level.
predictIntervals(Instance, double) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Computes a prediction interval for the given instance and confidence level.
predictIntervals(Instance, double) - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Predicts a confidence interval for the given instance and confidence level.
predictIntervals(Instance, double) - Method in class weka.classifiers.functions.SimpleLinearRegressionIntervalEstimator: Returns an N * 2 array, where N is the number of prediction intervals.
predictIntervals(Instance, double) - Method in class weka.classifiers.lazy.LWLIntervalEstimator: Returns an N * 2 array, where N is the number of prediction intervals.
predictIntervals(Instance, double) - Method in class weka.classifiers.meta.FilteredClassifierExt: Returns an N * 2 array, where N is the number of prediction intervals.
PredictionEccentricity - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Generates classifier prediction eccentricity.
PredictionEccentricity() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity
predictionForInstance(Instance, boolean) - Method in class weka.classifiers.meta.ClassifierCascade: Returns the prediction for the instance.
PredictionHelper - Class in adams.gui.tools.wekainvestigator.tab.classifytab: Helper class for dealing with predictions from result items.
PredictionHelper() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.PredictionHelper
Predictions - Class in adams.flow.transformer.wekarepeatedcrossvalidationoutput: Generates statistics for predictions from repeated cross-validation runs.
Predictions - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Displays the predictions.
Predictions - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated: Generates statistics for predictions from repeated cross-validation runs.
Predictions() - Constructor for class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions
Predictions() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions
Predictions() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions
PREDICTIONS_RECORDED - adams.flow.transformer.WekaEvaluationInfo.InfoType
predictionsFileTipText() - Method in class weka.classifiers.functions.FromPredictions: Returns the tip text for this property.
PredictionTrend - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Generates a 'prediction trend' for classifier errors: sorts the predictions on the actual value and plots actual and predicted side-by-side.
PredictionTrend() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend
PredictionType - Enum in adams.data.instancesanalysis.pls: The type of prediction to perform.
predictionTypeTipText() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns the tip text for this property
PredictionUtils - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated: Helper class for predictions from repeated cross-validation runs.
PredictionUtils() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.PredictionUtils
predictMaxTipText() - Method in class weka.classifiers.functions.FakeClassifier: Returns the tip text for this property.
predictMinTipText() - Method in class weka.classifiers.functions.FakeClassifier: Returns the tip text for this property.
predictorTipText() - Method in class weka.classifiers.meta.Consensus: Returns the tip text for this property.
predictorTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the predictor option.
predictWaitTipText() - Method in class weka.classifiers.functions.FakeClassifier: Returns the tip text for this property.
preExecute() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Hook method just before the experiment is run (after initialization).
preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaFilter: Returns the tip text for this property.
preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaTestSetEvaluator: Returns the tip text for this property.
preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaTrainAssociator: Returns the tip text for this property.
preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaTrainClassifier: Returns the tip text for this property.
preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaTrainClusterer: Returns the tip text for this property.
preferJobRunnerTipText() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator: Returns the tip text for this property.
preFilterTipText() - Method in class adams.data.weka.rowfinder.FilteredIQR: Returns the tip text for this property.
preFilterTipText() - Method in class weka.filters.FilteredFilter: Returns the tip text for this property.
preFilterTipText() - Method in class weka.filters.unsupervised.instance.KennardStone: Returns the tip text for this property.
prefix(int, StringBuffer) - Method in class weka.classifiers.trees.RandomRegressionForest.Node: generates the tree structure prefix
PREFIX - Static variable in class weka.filters.unsupervised.attribute.EquiDistance: the option for the prefix of the new attribute names.
PREFIX_ADDITIONALFIELDS - Static variable in class adams.data.weka.ArffUtils: the prefix for additional fields.
PREFIX_DATASET_ATTRIBUTE - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator
PREFIX_NOTE - Static variable in class adams.data.weka.ArffUtils: the prefix for notes.
prefixAttributes(Instances, int) - Method in class adams.flow.transformer.WekaInstancesMerge: Prefixes the attributes.
prefixDatasetsWithIndexTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the tip text for this property.
prefixesTipText() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Returns the tip text for this property.
prefixesTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Returns the tip text for this property.
prefixSeparatorTipText() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the tip text for this property.
prefixTipText() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the tip text for this property.
prefixTipText() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the tip text for this property.
preparationTipText() - Method in class weka.classifiers.meta.SocketFacade: Returns the tip text for this property.
prepareClassify(Instance, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation: Prepares the instance for the Classifier.classifyInstance(Instance) method.
prepareClassify(Instance, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.Simple: Prepares the instance for the Classifier.classifyInstance(Instance) method.
prepareData(Instances, int) - Method in class adams.flow.transformer.WekaInstancesMerge: Prepares the data, prefixing attributes, removing columns, etc, before merging it.
prepareDistribution(Instance, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation: Prepares the instance for the Classifier.distributionForInstance(Instance) method.
prepareDistribution(Instance, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.Simple: Prepares the instance for the Classifier.distributionForInstance(Instance) method.
prepareTrain(Instances, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.AbstractDataPreparation: Prepares the data for training.
prepareTrain(Instances, SocketFacade) - Method in class weka.classifiers.meta.socketfacade.Simple: Prepares the data for training.
prepareUpdate() - Method in class adams.gui.visualization.instance.InstancePanel: Updates the axes with the min/max of the new data.
preProcessCheck() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Checks whether all pre-conditions have been met.
preProcessCheck() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob: Checks whether all pre-conditions have been met.
preProcessCheck() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob: Checks whether all pre-conditions have been met.
preProcessCheck() - Method in class adams.flow.transformer.WekaTrainAssociator.TrainJob: Checks whether all pre-conditions have been met.
preProcessCheck() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob: Checks whether all pre-conditions have been met.
preProcessCheck() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob: Checks whether all pre-conditions have been met.
preProcessCheck() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: Checks whether all pre-conditions have been met.
preProcessCheck() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: Checks whether all pre-conditions have been met.
preProcessCheck() - Method in class adams.multiprocess.WekaCrossValidationJob
preProcessCheck() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm.ClassifierBasedGeneticAlgorithmJob: Checks whether all pre-conditions have been met.
preProcessCheck() - Method in class adams.opt.optimise.GeneticAlgorithm.GAJob
PreprocessHandler - Class in weka.gui.explorer: Manages the PreprocessPanel.
PreprocessHandler() - Constructor for class weka.gui.explorer.PreprocessHandler
PreprocessingType - Enum in adams.data.instancesanalysis.pls: The preprocessing type.
preprocessingTypeTipText() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns the tip text for this property
preprocessingTypeTipText() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Returns the tip text for this property
PreprocessTab - Class in adams.gui.tools.wekainvestigator.tab: Preprocessing tab.
PreprocessTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.PreprocessTab
preRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob: Gets called before the execution.
preRun() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob: Gets called before the execution.
preRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Hook method that gets executed before the experiment gets initialized.
preRun() - Method in class adams.gui.tools.wekamultiexperimenter.runner.RemoteWekaExperimentRunner: Hook method that gets executed before the experiment gets initialized.
preRun() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Some more initializations.
preRun() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Further initializations in derived classes.
preRun() - Method in class adams.opt.genetic.DarkLord: Some more initializations.
preRun() - Method in class adams.opt.genetic.Hermione: Some more initializations.
preRun() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Further initializations in derived classes.
preRun() - Method in class adams.opt.optimise.GeneticAlgorithm: Some more initializations.
preRun() - Method in class adams.tools.CompareDatasets: Before the actual run is executed.
preSelectionTipText() - Method in class adams.flow.transformer.WekaChooseAttributes: Returns the tip text for this property.
preserveIDColumnTipText() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the tip-text for the preserve-id-column option.
preserveInstancesOrderTipText() - Method in class weka.clusterers.SAXKMeans: Returns the tip text for this property.
preserveOrderTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns the tip text for this property.
preserveOrderTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Returns the tip text for this property.
preserveOrderTipText() - Method in class adams.flow.transformer.WekaRandomSplit: Returns the tip text for this property.
preserveOrderTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: Returns the tip text for this property.
preserveOrderTipText() - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Returns the tip text for this property.
preserveOrderTipText() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Returns the tip text for this property.
preserveOrderTipText() - Method in class weka.classifiers.DefaultRandomSplitGenerator: Returns the tip text for this property.
preserveOrderTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns the tip text for this property.
preserveOrderTipText() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns the tip text for this property.
preTokenizerTipText() - Method in class weka.core.tokenizers.PreCleanedTokenizer: Returns the tip text for this property.
preTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: Preprocesses the data.
preTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Preprocesses the data.
preTransform(Instances, Map<String, Object>) - Method in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS: Preprocesses the data.
PrincipalComponentsJ - Class in weka.filters.unsupervised.attribute: * Performs a principal components analysis and transformation of the data.
* Dimensionality reduction is accomplished by choosing enough eigenvectors to account for some percentage of the variance in the original data -- default 0.95 (95%).
* Based on code of the attribute selection scheme 'PrincipalComponents' by Mark Hall and Gabi Schmidberger.
PrincipalComponentsJ() - Constructor for class weka.filters.unsupervised.attribute.PrincipalComponentsJ
PrincipalComponentsTab - Class in adams.gui.tools.wekainvestigator.tab: Visualizes the PCA loadings and PCA space calculated from the selected dataset.
PrincipalComponentsTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab
print(double[]) - Method in class adams.opt.genetic.PackDataGeneticAlgorithm: Outputs the bits with the logger - logging needs to be enabled.
print(double[]) - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm
printAllModels() - Method in class weka.classifiers.trees.m5.RuleNode2: Print all the linear models at the learf (debugging purposes)
printBits(int[]) - Method in class adams.opt.genetic.PackDataGeneticAlgorithm: Outputs the bits with the logger - logging needs to be enabled.
printBits(int[]) - Method in class adams.opt.optimise.genetic.PackDataGeneticAlgorithm
printLeafModels() - Method in class weka.classifiers.trees.m5.RuleNode2: print all leaf models
printNodeLinearModel() - Method in class weka.classifiers.trees.m5.RuleNode2: print the linear model at this node
PRM - Class in adams.data.instancesanalysis.pls
PRM() - Constructor for class adams.data.instancesanalysis.pls.PRM
process() - Method in class adams.flow.sink.WekaClassifierErrors.DataGenerator: Processes the data if necessary.
process() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Does the actual execution of the job.
process() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob: Does the actual execution of the job.
process() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob: Does the actual execution of the job.
process() - Method in class adams.flow.transformer.WekaTrainAssociator.TrainJob: Does the actual execution of the job.
process() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob: Does the actual execution of the job.
process() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob: Does the actual execution of the job.
process() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: Does the actual execution of the job.
process() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: Does the actual execution of the job.
process() - Method in class adams.multiprocess.WekaCrossValidationJob: Does the actual execution of the job.
process() - Method in class adams.opt.optimise.GeneticAlgorithm.GAJob: Does the actual execution of the job.
process() - Method in class weka.core.InstanceGrouping: Performs the grouping.
process(Classifier[]) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.AbstractClassifierSetupProcessor: Processes the classifier array.
process(Instance) - Method in class weka.filters.unsupervised.attribute.AndrewsCurves: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.AnyToString: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.DownSample: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.FFT: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.LogTransform: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.PAA: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.RowSum: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.SAX: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.SetMissingValue: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.SpellChecker: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.attribute.StringToDate: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.instance.RowNorm: processes the given instance (may change the provided instance) and returns the modified version.
process(Instance) - Method in class weka.filters.unsupervised.instance.Scale: processes the given instance (may change the provided instance) and returns the modified version.
process(Instances) - Method in class weka.filters.FilteredFilter: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.FlowFilter: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.SerializedFilter: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.supervised.attribute.MultiPLS: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.supervised.attribute.PLS: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.supervised.attribute.PLSFilterExtended: Override in order to have the destandardized predictions for multiple y added.
process(Instances) - Method in class weka.filters.supervised.attribute.YGradientEPO: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.supervised.attribute.YGradientGLSW: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.supervised.instance.RemoveOutliers: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.Detrend: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.EquiDistance: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.FastWavelet: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.InputSmearing: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.AlignDataset: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.KeepRange: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.KennardStone: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.LatestRecords: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.Sort: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.SortOnAttribute: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Processes the given data (may change the provided dataset) and returns the modified version.
process(Instances, Instance) - Method in class weka.filters.unsupervised.attribute.EquiDistance: processes the given instance (may change the provided instance) and returns the modified version.
processCell(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessCell: Processes the specified column.
processCell(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.ProcessCell: Processes the specified cell.
ProcessCell - Interface in adams.gui.visualization.instances.instancestable: Interface for plugins that process a cell.
processColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessColumn: Processes the specified column.
processColumn(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.ProcessColumn: Processes the specified column.
ProcessColumn - Interface in adams.gui.visualization.instances.instancestable: Interface for plugins that process a column.
processData(T) - Method in class adams.data.baseline.AbstractLinearRegressionBased: Performs the actual correcting.
processData(Instances) - Method in class weka.filters.unsupervised.attribute.FastWavelet: processes the instances using the HAAR/JSci algorithm.
processDatasetWithClusterer(Instances, Clusterer) - Method in class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor: Performs some form of processing on the full dataset.
processDatasetWithClusterer(Instances, Clusterer) - Method in class adams.flow.transformer.wekaclusterer.AddCluster: Performs some form of processing on the full dataset.
processDatasetWithClusterer(Instances, Clusterer) - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters: Performs some form of processing on the full dataset.
processDatasetWithClusterer(Instances, Clusterer) - Method in class adams.flow.transformer.wekaclusterer.ClusterCounts: Performs some form of processing on the full dataset.
processDatasetWithClusterer(Instances, Clusterer) - Method in class adams.flow.transformer.wekaclusterer.ClusterStatistics: Performs some form of processing on the full dataset.
processHit(MouseEvent, List<InstancePoint>) - Method in class adams.gui.visualization.instance.InstancePointHitDetector: Performs the action when a hit is detected.
processInstance(Instance) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Processes the instance and generates the output token.
processInstance(Instance) - Method in class adams.flow.transformer.WekaClassifying: Processes the instance and generates the output token.
processInstance(Instance) - Method in class adams.flow.transformer.WekaClustering: Processes the instance and generates the output token.
processorTipText() - Method in class adams.flow.transformer.WekaClassifierSetupProcessor: Returns the tip text for this property.
processRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessRow: Processes the specified row.
processRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic: Processes the specified row.
processRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.ChangeInstanceWeights: Processes the specified row.
processRow(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.InvestigatorAsNewDataset: Processes the specified row.
processRow(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.ProcessRow: Processes the specified row.
ProcessRow - Interface in adams.gui.visualization.instances.instancestable: Interface for plugins that process a row.
processRows(List<Instance>) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractSelectionProcessor: Returns the list of row indices generated from the data.
processSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: Plots the specified rows.
processSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: Processes the specified rows.
processSelectedRows(InstancesTablePopupMenuItemHelper.TableState) - Method in interface adams.gui.visualization.instances.instancestable.ProcessSelectedRows: Processes the specified row.
ProcessSelectedRows - Interface in adams.gui.visualization.instances.instancestable: Interface for plugins that processes selected rows.
processSIMPLS(Instances) - Method in class weka.filters.supervised.attribute.PLSFilterExtended: Extended superclass method for increasing dimensions and/of changing handling of the Matrices C,W,P,Q to deal with multiple Y variables.
processSIMPLS(Instances) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter
processSIMPLS(Instances) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
processTipText(PlotPanel, Point, String) - Method in class adams.gui.visualization.instance.InstancePanel: Processes the given tip text.
processTypeTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the processType option.
PRODUCT_RULE - adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType
PRODUCT_RULE - Static variable in class weka.classifiers.meta.AbstainVote: combination rule: Product of Probabilities (only nominal classes)
PROMPT - Static variable in class adams.gui.menu.PackageManager
promptHistogramSetup() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.CompareModels: Prompts the user for a histogram setup.
promptParameters(InstancesTable) - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic: Prompts the user for parameters.
promptParameters(InstancesTablePopupMenuItemHelper.TableState, boolean) - Method in class adams.gui.visualization.instances.instancestable.Binning: Prompts the user to configure the parameters.
promptParameters(InstancesTablePopupMenuItemHelper.TableState, boolean) - Method in class adams.gui.visualization.instances.instancestable.Histogram: Prompts the user to configure the parameters.
promptParameters(InstancesTablePopupMenuItemHelper.TableState, boolean) - Method in class adams.gui.visualization.instances.instancestable.JFreeChart: Prompts the user to configure the parameters.
promptParameters(InstancesTable, boolean) - Method in class adams.gui.visualization.instances.instancestable.SimplePlot: Prompts the user to configure the parameters.
PROPERTY_CMDLINE - Static variable in class adams.gui.wizard.WekaPropertySheetPanelPage: the identifier for the commandline of the object.
PROPERTY_WEKAEDITORS - Static variable in class adams.gui.goe.WekaEditorsRegistration: property indicating whether to use the Weka editors instead of the Adams ones.
propertyTipText() - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Returns the tip text for this property.
propertyTipText() - Method in class adams.core.discovery.genetic.GenericFloatResolution: Returns the tip text for this property.
propertyTipText() - Method in class adams.core.discovery.genetic.GenericInteger: Returns the tip text for this property.
propertyTipText() - Method in class adams.core.discovery.genetic.GenericString: Returns the tip text for this property.
PROPS_FILTER - Static variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the key for a filter setup in the setup properties.
PROPS_FILTER - Static variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: the key for a filter setup in the setup properties.
PROPS_MASK - Static variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the key for the mask in the setup properties.
PROPS_MASK - Static variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: the key for the mask in the setup properties.
PROPS_RELATION - Static variable in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: the key for the relation name in the generated properties file.
PROPS_RELATION - Static variable in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: the key for the relation name in the generated properties file.
prune() - Method in class weka.classifiers.trees.m5.RuleNode2: Recursively prune the tree
pruneBackup() - Method in class adams.flow.sink.WekaDatabaseWriter: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaAccumulatedError: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaAggregateEvaluations: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaFileReader: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaFilter: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaInstanceBuffer: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaInstanceDumper: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaStreamEvaluator: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaTrainClassifier: Removes entries from the backup.
pruneBackup() - Method in class adams.flow.transformer.WekaTrainClusterer: Removes entries from the backup.
PublicPrincipalComponents - Class in weka.filters.unsupervised.attribute: Class that is identical to the Principal components class except it contains a public method to get the coefficients from the principal components model
PublicPrincipalComponents() - Constructor for class weka.filters.unsupervised.attribute.PublicPrincipalComponents
PullUpClassifier - Class in adams.gui.goe.popupmenu: For pulling up classifiers from SingleClassifierEnhancer wrappers.
PullUpClassifier() - Constructor for class adams.gui.goe.popupmenu.PullUpClassifier
PullUpClusterer - Class in adams.gui.goe.popupmenu: For pulling up clusterers from SingleClustererEnhancer wrappers.
PullUpClusterer() - Constructor for class adams.gui.goe.popupmenu.PullUpClusterer
PullUpInstancesColumnFinder - Class in adams.gui.goe.popupmenu: Pulls up the base Instances ColumnFinder from a filtered ColumnFinder.
PullUpInstancesColumnFinder() - Constructor for class adams.gui.goe.popupmenu.PullUpInstancesColumnFinder
PullUpInstancesRowFinder - Class in adams.gui.goe.popupmenu: Pulls up the base Instances RowFinder from a filtered RowFinder.
PullUpInstancesRowFinder() - Constructor for class adams.gui.goe.popupmenu.PullUpInstancesRowFinder
putBits(int[]) - Method in class adams.opt.optimise.genetic.PackData
PyroProxy - Class in weka.classifiers.functions: Proxy for a python model using Pyro4 for communication.
PyroProxy() - Constructor for class weka.classifiers.functions.PyroProxy
PyroProxyObject - Interface in weka.core: Interface for classes that make use of Pyro4.

Q

quartile1 - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp.IQRs
QUARTILE25 - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.LowerStatistic
quartile3 - Variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp.IQRs
QUARTILE75 - adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.UpperStatistic
queryTipText() - Method in class adams.flow.source.WekaDatabaseReader: Returns the tip text for this property.
queryUser(PerFoldMultiPagePane, ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation: Queries the user for the range.
queryUser(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation: Queries the user for the range.

R

RAE - adams.flow.transformer.WekaClassifierRanker.Measure: evaluation via: Relative absolute error.
RAE - adams.opt.genetic.Measure: Relative absolute error.
RAE - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure: evaluation via: Relative absolute error.
RANDOM - weka.classifiers.trees.XGBoost.FeatureSelector
RANDOM - Static variable in class weka.clusterers.SAXKMeans
randomize(TIntList, Random) - Method in class weka.classifiers.AbstractSplitGenerator: Randomizes the indices using the given random number generator.
Randomize - Class in adams.gui.tools.wekainvestigator.datatable.action: Randomizes the selected dataset.
Randomize() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Randomize: Instantiates the action.
randomizeTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Returns the tip text for this property.
randomizeTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the tip text for this property.
randomizeTipText() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
randomizeTipText() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns the tip text for this property.
randomizeTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
randomizeTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the tip text for this property.
randomizeTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns the tip text for this property.
randomizeTipText() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Returns the tip text for this property.
randomizeTipText() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns the tip text for this property.
RandomModelTrees - Class in weka.classifiers.trees
RandomModelTrees() - Constructor for class weka.classifiers.trees.RandomModelTrees
RandomRegressionForest - Class in weka.classifiers.trees: RandomRegressionForest: subtract mean and pls, then grow completely random trees (leaf: min ..
RandomRegressionForest() - Constructor for class weka.classifiers.trees.RandomRegressionForest
RandomRegressionForest.Node - Class in weka.classifiers.trees: TODO: description of class
randomSeedTipText() - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Returns the tip text for this property
randomSeedTipText() - Method in class weka.classifiers.meta.LeastMedianSq: Returns the tip text for this property
RandomSplitGenerator - Interface in weka.classifiers: Interface for generators of random splits of datasets.
RandomSubset - Class in adams.gui.tools.wekainvestigator.datatable.action: Creates a random subset from a dataset and inserts it as a new dataset.
RandomSubset() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset: Instantiates the action.
range - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState: the row range.
RANGE - weka.filters.unsupervised.attribute.EquiDistance.AttributeSelection
RANGE - Static variable in class weka.filters.unsupervised.attribute.EquiDistance: the option for the attribute range.
RANGE - Static variable in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor
range1TipText() - Method in class adams.tools.CompareDatasets: Returns the tip text for this property.
range2TipText() - Method in class adams.tools.CompareDatasets: Returns the tip text for this property.
RangeBased - Class in weka.filters.unsupervised.attribute.detrend: Performs the correction using slopes/intercepts calculated for the defined ranges.
RangeBased - Class in weka.filters.unsupervised.attribute.multiplicativescattercorrection: Performs the correction using slopes/intercepts calculated for the defined ranges.
RangeBased() - Constructor for class weka.filters.unsupervised.attribute.detrend.RangeBased
RangeBased() - Constructor for class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased
RangeCheck - Class in weka.classifiers.meta: Keeps track of the ranges in case of numeric attributes.
RangeCheck() - Constructor for class weka.classifiers.meta.RangeCheck
RangeCheckClassifier - Interface in weka.classifiers: Interface for classifiers that allow checks whether data is outside the training range of the classifier.
RangeCheckHelper - Class in weka.classifiers: Helper class for generating range checks.
RangeCheckHelper() - Constructor for class weka.classifiers.RangeCheckHelper
rangePaintletTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the tip text for this property.
rangesTipText() - Method in class adams.data.weka.rowfinder.ByNumericRange: Returns the tip text for this property.
rangesTipText() - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange: Returns the tip text for this property.
rangesTipText() - Method in class weka.classifiers.meta.PartitionedStacking: Returns the tip text for this property.
rangesTipText() - Method in class weka.filters.unsupervised.attribute.detrend.RangeBased: Returns the tip text for this property.
rangesTipText() - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased: Returns the tip text for this property.
rangesTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Returns the tip text for this property.
rangeTipText() - Method in class adams.flow.sink.WekaAttributeSummary: Returns the tip text for this property.
rangeTipText() - Method in class adams.flow.transformer.WekaAttributeIterator: Returns the tip text for this property.
rangeTipText() - Method in class weka.filters.unsupervised.attribute.AnyToString: Returns the tip text for this property.
rangeTipText() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the tip text for this property.
rangeTipText() - Method in class weka.filters.unsupervised.attribute.StringToDate: Returns the tip text for this property.
rangeTipText() - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor: Returns the tip text for this property.
RankingJob(Classifier, int, Instances, Instances, long, int, WekaClassifierRanker.Measure, WekaLabelIndex, boolean) - Constructor for class adams.flow.transformer.WekaClassifierRanker.RankingJob: Initializes the job.
rateDropTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the rateDrop option.
rbfKernel(double[], double[], double) - Method in class weka.classifiers.functions.GPD: Computes the RBF kernel.
read() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractResultsHandler: Loads the results (if possible).
read() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Loads the results (if possible).
read(PlaceholderFile) - Method in class adams.data.io.input.AbstractAdamsExperimentReader: Reads the experiment file.
read(BufferedReader) - Method in class weka.core.converters.SimpleArffLoader: Performs the actual reading.
read(File, MultiExplorer) - Static method in class weka.gui.explorer.WorkspaceHelper: Reads the explorer session and initializes the explorer object.
readData() - Method in class adams.data.io.input.InstanceReader: Uses the named setup to read the data.
readerForFile(File) - Static method in class adams.gui.chooser.AdamsExperimentFileChooser: Returns the reader for the specified file.
readerForFile(File) - Static method in class adams.gui.chooser.WekaFileChooser: Returns the reader for the specified file.
readerTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Returns the tip text for this property.
readerTipText() - Method in class weka.classifiers.functions.FromPredictions: Returns the tip text for this property.
readerTipText() - Method in class weka.core.converters.SpreadSheetLoader: The tip text for this property.
realTipText() - Method in class weka.filters.unsupervised.attribute.FFT: Returns the tip text for this property.
RECALL - adams.flow.sink.WekaThresholdCurve.AttributeName
RECALL - adams.opt.genetic.Measure: recall.
receive() - Method in class weka.classifiers.meta.SocketFacade: Receives the response data.
recordClassAttributes() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Scans the datasets for attributes that should be considered classes, and keeps a record of them.
redo() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Performs a redo if possible.
ReducedData - Class in adams.gui.tools.wekainvestigator.tab.attseltab.output: Generates the reduced dataset.
ReducedData() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.output.ReducedData
reduceNumberOfDistanceCalcsViaCanopiesTipText() - Method in class weka.clusterers.SAXKMeans: Returns the tip text for this property.
ReevaluateModel - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation: Re-evaluates a serialized model.
ReevaluateModel - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation: Re-evaluates a serialized model.
ReevaluateModel() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel
ReevaluateModel() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel
REFERENCE_SIZE - Static variable in class weka.gui.visualize.plugins.ClassRangeBasedClassifierErrors: the error size of the reference error (mid-class range).
referenceActorTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the tip text for this property.
referenceErrorTipText() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference: Returns the tip text for this property.
referenceFileTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the tip text for this property.
referenceSizeTipText() - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference: Returns the tip text for this property.
RefreshCache - Class in adams.flow.standalone.wekapackagemanageraction: Refreshes the package cache.
RefreshCache() - Constructor for class adams.flow.standalone.wekapackagemanageraction.RefreshCache
regenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Regenerates the output.
regenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Regenerates the output.
regenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Regenerates the output.
regenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Regenerates the output.
regenerateOutput(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Regenerates the output.
regexNameTipText() - Method in class adams.flow.transformer.WekaClassSelector: Returns the tip text for this property.
REGEXP - weka.filters.unsupervised.attribute.EquiDistance.AttributeSelection
REGEXP - Static variable in class weka.filters.unsupervised.attribute.EquiDistance: the option for the attribute regexp.
REGEXP - Static variable in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression
regExpsTipText() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Returns the tip text for this property.
regExpsTipText() - Method in class weka.classifiers.MultiLevelSplitGenerator: Returns the tip text for this property.
regExpTipText() - Method in class adams.data.weka.classattribute.ByName: Returns the tip text for this property.
regExpTipText() - Method in class adams.data.weka.columnfinder.ByName: Returns the tip text for this property.
regExpTipText() - Method in class adams.data.weka.rowfinder.ByLabel: Returns the tip text for this property.
regExpTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the tip text for this property.
regExpTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns the tip text for this property.
regExpTipText() - Method in class adams.flow.transformer.WekaAttributeIterator: Returns the tip text for this property.
regExpTipText() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns the tip text for this property.
regExpTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
regExpTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns the tip text for this property.
regExpTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the tip text for this property.
regExpTipText() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns the tip text for this property.
regExpTipText() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Returns the tip text for this property.
regExpTipText() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Returns the tip text for this property.
regExpTipText() - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Returns the tip text for this property.
regexTipText() - Method in class adams.flow.transformer.WekaRegexToRange: Returns the tip text for this property.
registerAdditionalHandler(Class, AbstractExplorerPanelHandler) - Static method in class weka.gui.explorer.WorkspaceHelper: Registers an additional handler for an Explorer.ExplorerPanel.
registerEditors(Map<String, Map<String, String>>) - Method in class adams.gui.goe.WekaEditorsRegistration: Reregisters class hierarchies with ADAMS object editors.
registerEditors(Properties) - Method in class adams.gui.goe.WekaEditorsRegistration: Reregisters class hierarchies with ADAMS object editors.
registerHierarchies(Map<String, Map<String, String>>) - Method in class adams.gui.goe.WekaEditorsRegistration: Registers the class hierarchies with ADAMS.
registerHierarchies(Properties) - Method in class adams.gui.goe.WekaEditorsRegistration: Registers the class hierarchies with ADAMS.
REGRESSION - adams.flow.sink.WekaExperimentGenerator.ExperimentType: regression.
regressionPrediction(Instance, boolean[], double[]) - Method in class weka.classifiers.functions.LinearRegressionJ: Calculate the dependent value for a given instance for a given regression model.
RELATION - adams.opt.genetic.OutputPrefixType: the relation name.
RELATION_NAME - adams.flow.transformer.WekaEvaluationInfo.InfoType
RELATION_NAME - adams.flow.transformer.WekaInstancesInfo.InfoType: the name of the dataset.
RELATIONAL_ATTRIBUTES - adams.flow.core.Capability: can handle relational attributes.
RELATIONAL_CLASS - adams.flow.core.Capability: can handle relational classes.
relationalValue(int) - Method in class weka.core.AbstractHashableInstance: Returns the relational value of a relational attribute.
relationalValue(Attribute) - Method in class weka.core.AbstractHashableInstance: Returns the relational value of a relational attribute.
relationNameTemplateTipText() - Static method in class weka.classifiers.CrossValidationHelper: Returns the tiptext for the relation name template.
relationNameTipText() - Method in class adams.flow.source.WekaNewInstances: Returns the tip text for this property.
relationNameTipText() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the tip text for this property.
relationNameTipText() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
relationNameTipText() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns the tip text for this property.
relationNameTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
relationNameTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the tip text for this property.
relationNameTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns the tip text for this property.
relationNameTipText() - Static method in class weka.classifiers.LeaveOneOutByValueGenerator: Returns the tiptext for the relation name template.
RELATIVE_ABSOLUTE_ERROR - adams.flow.core.EvaluationStatistic
RELATIVE_ABSOLUTE_ERROR - adams.flow.core.ExperimentStatistic
RelativeNumericErrorScaler - Class in adams.data.weka.predictions: Scales the errors for numeric class attributes.
RelativeNumericErrorScaler() - Constructor for class adams.data.weka.predictions.RelativeNumericErrorScaler
relativeWidthsTipText() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Returns the tip text for this property.
reload() - Method in class adams.gui.tools.DatasetCompatibilityPanel: Re-compares the currently loaded files.
reload() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Reloads the data.
reload() - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer: Reloads the data.
reload() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Reloads the currently loaded dataset.
reload() - Method in class adams.gui.visualization.instance.InstanceComparePanel: Reloads the datasets.
remoteObjectNameTipText() - Method in class weka.classifiers.functions.PyroProxy: Returns the tip text for this property.
remoteObjectNameTipText() - Method in interface weka.core.PyroProxyObject: Returns the tip text for this property.
remoteTipText() - Method in class weka.classifiers.meta.SocketFacade: Returns the tip text for this property.
RemoteWekaExperimentIO - Class in adams.gui.tools.wekamultiexperimenter.io: IO handler for remote experiments.
RemoteWekaExperimentIO() - Constructor for class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO
RemoteWekaExperimentRunner - Class in adams.gui.tools.wekamultiexperimenter.runner: A class that handles running a copy of the experiment in a separate thread.
RemoteWekaExperimentRunner(ExperimenterPanel) - Constructor for class adams.gui.tools.wekamultiexperimenter.runner.RemoteWekaExperimentRunner: Initializes the thread.
remove() - Method in class weka.classifiers.AbstractSplitGenerator: Unsupported.
remove() - Method in interface weka.classifiers.SplitGenerator: Unsupported.
remove(int) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList
remove(int) - Method in class adams.gui.visualization.instance.InstanceContainerManager: Removes the container at the specified position.
remove(int) - Method in class weka.core.InstancesView: Removes the instance at the given position.
remove(Object) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList
Remove - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction: Removes the selected attributes.
Remove() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.Remove: Instantiates the action.
REMOVE - adams.gui.event.InstancesSortSetupEvent.EventType: a definition was removed.
removeAccessoryLabel(Container) - Static method in class weka.gui.AdamsHelper: Removes the label in the accessory component, to make space for the bookmarks.
removeAll(Collection<?>) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList
removeAttributeIndicesTipText() - Method in class weka.classifiers.meta.FilteredClassifierExt: Returns the tip text for this property.
removeAttributeType(String) - Method in class weka.core.converters.SimpleArffLoader: Removes the attribute type.
removeCell(int) - Method in class adams.ml.data.InstancesHeaderRow: Removes the cell at the specified index.
removeCell(int) - Method in class adams.ml.data.InstanceView: Removes the cell at the specified index.
removeCell(String) - Method in class adams.ml.data.InstancesHeaderRow: Removes the cell at the specified index.
removeCell(String) - Method in class adams.ml.data.InstanceView: Removes the cell at the specified index.
removeChangeListener(ChangeListener) - Method in class adams.gui.goe.WekaGenericObjectEditorPopupMenu: Removes the listener from the internal list of listeners that get notified when the user changes the setup.
removeChangeListener(ChangeListener) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Removes the change listener from the internal list.
removeChangeListener(ChangeListener) - Method in class adams.gui.visualization.instances.InstancesTable: Removes the listener from the pool of listeners that get notified when the data changes.
removeCharsTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Returns the tip text for this property.
removeCharsTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Returns the tip text for this property.
removeClassAttribute(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Removes the class attribute from the dataset (if present).
removeClassAttributes() - Method in class adams.ml.data.InstancesView: Removes all set class attributes.
removeColumn(int) - Method in class adams.ml.data.InstancesView: Removes the specified column.
removeColumn(String) - Method in class adams.ml.data.InstancesView: Removes the specified column.
removeData(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Removes the selected rows, removes all if rows are null.
removeDefinition() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: Removes itself from the list of sorting panels.
removeDefinition(InstancesSortDefinitionPanel) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Removes the panel from the list of sort definitions.
RemoveDuplicateIDs - Class in weka.filters.unsupervised.instance: Removes rows with IDs that occur multiple times.
Also skips rows with missing ID.
RemoveDuplicateIDs() - Constructor for class weka.filters.unsupervised.instance.RemoveDuplicateIDs
RemoveDuplicates - Class in weka.filters.unsupervised.instance: Removes all duplicate instances.
RemoveDuplicates() - Constructor for class weka.filters.unsupervised.instance.RemoveDuplicates
removeEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Removes the specified entry.
removeEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Removes the specified entry.
removeEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Removes the specified entry.
removeEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Removes the specified entry.
removeEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Removes the specified entry.
removeEntry(String) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel.HistoryPanel: Removes the specified entry.
removeIf(Predicate<? super DataContainer>) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList
removeIncomplete(int, Classifier, Instances) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Removes the incomplete rows of the classifier/dataset combination.
removeInstancesSortSetupListener(InstancesSortSetupListener) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Removes the specified listener.
RemoveInstancesWithMissingValue - Class in weka.filters.unsupervised.instance: Removes all instances that contain missing values.
RemoveInstancesWithMissingValue() - Constructor for class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue
RemoveMisclassifiedAbs - Class in weka.filters.unsupervised.instance: A filter that removes instances which are incorrectly classified.
RemoveMisclassifiedAbs() - Constructor for class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs
RemoveMisclassifiedRel - Class in weka.filters.unsupervised.instance: A filter that removes instances which are incorrectly classified.
RemoveMisclassifiedRel() - Constructor for class weka.filters.unsupervised.instance.RemoveMisclassifiedRel
removeMissing() - Method in class adams.ml.data.InstancesHeaderRow: Removes all cells marked "missing".
removeMissing() - Method in class adams.ml.data.InstancesView: Removes all cells marked "missing".
removeMissing() - Method in class adams.ml.data.InstanceView: Removes all cells marked "missing".
RemoveNonWordCharTokens - Class in weka.core.tokenizers.cleaners: Removes tokens that contain non-word characters.
RemoveNonWordCharTokens() - Constructor for class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens
RemoveOutliers - Class in weka.filters.supervised.instance: Cross-validates the specified classifier on the incoming data and applies the outlier detector to the actual vs predicted data to remove the outliers.
NB: only works on full dataset, not instance by instance.
RemoveOutliers() - Constructor for class weka.filters.supervised.instance.RemoveOutliers
removePanel(int) - Method in class weka.gui.explorer.MultiExplorer: Removes the panel at the specified index.
removePanel(String) - Method in class weka.gui.explorer.MultiExplorer: Removes the panel with the given name.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.SqlPanel: Removes a PropertyChangeListener.
removeRange(int, int) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList
removeRow(int) - Method in class adams.ml.data.InstancesView: Removes the specified row.
removeRow(String) - Method in class adams.ml.data.InstancesView: Removes the specified row.
removeSelectionListener(ListSelectionListener) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Remove a listener from the list that's notified each time a change to the selection occurs.
removeTabAt(int) - Method in class adams.gui.tools.wekainvestigator.output.OutputTabbedPane: Removes the tab.
removeTableModelListener(TableModelListener) - Method in class adams.gui.visualization.instances.InstancesTableModel: removes a listener from the list that is notified each time a change to the data model occurs
RemoveTestInstances - Class in weka.filters.unsupervised.instance: Removes all instances of the provided test set from the data passing through.
Requires an attribute in the data that uniquely identifies instances across datasets.
RemoveTestInstances() - Constructor for class weka.filters.unsupervised.instance.RemoveTestInstances
RemoveTestSet - Class in adams.gui.tools.wekainvestigator.datatable.action: Removes the test instances from one dataset in another.
RemoveTestSet() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.RemoveTestSet: Instantiates the action.
removeTipText() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the tip text for this property.
removeTrainTipText() - Method in class weka.classifiers.meta.AbstainAttributePercentile
removeUnusedTipText() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Returns the tip text for this property.
removeUnusedTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Returns the tip text for this property.
removeUpdate(DocumentEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationDocumentListener
RemoveWithLabels - Class in weka.filters.unsupervised.instance: Allows the user to remove nominal labels via a regular expression.
RemoveWithLabels() - Constructor for class weka.filters.unsupervised.instance.RemoveWithLabels
RemoveWithWeights - Class in weka.filters.unsupervised.instance: Removes instances with weights outside the defined limits.
RemoveWithWeights() - Constructor for class weka.filters.unsupervised.instance.RemoveWithWeights
RemoveWithZeroes - Class in weka.filters.unsupervised.instance: Removes all instances that contain at least the specified number (or percentage) of zeroes in numeric attributes.
RemoveWithZeroes() - Constructor for class weka.filters.unsupervised.instance.RemoveWithZeroes
RemoveWorst - Class in adams.flow.transformer.wekaevaluationpostprocessor: Removes the worst predictions, which are considered outliers that detract from the actual model performance.
RemoveWorst() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst
RemoveWorstStdDev - Class in adams.flow.transformer.wekaevaluationpostprocessor: Removes the worst predictions, which are considered outliers that detract from the actual model performance.
RemoveWorstStdDev() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev
Rename - Class in adams.gui.tools.wekainvestigator.datatable.action: Renames the selected dataset.
Rename - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction: Renames the selected attribute.
Rename() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Rename: Instantiates the action.
Rename() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.Rename: Instantiates the action.
renameAttribute(int, String) - Method in class weka.core.InstancesView: Renames an attribute.
renameAttributeAt(int, String) - Method in class adams.gui.visualization.instances.InstancesTableModel: renames the attribute at the given col index
renameAttributes(Instances, String) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: renames all the attributes in the dataset (excluding the class if present) by adding the prefix to the name.
renameAttributeValue(int, int, String) - Method in class weka.core.InstancesView: Renames the value of a nominal (or string) attribute value.
renameData(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Renames the selected row, does nothing if 0 or more than 1 selected.
ReorderAttributes - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction: Allows the user to reorder the attributes.
ReorderAttributes() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ReorderAttributes: Instantiates the action.
RepeatedCrossValidation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation: Performs repeated cross-validation.
RepeatedCrossValidation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation
REPLACE - Static variable in class weka.filters.unsupervised.attribute.NominalToNumeric
replaceAttributeAt(Attribute, int) - Method in class weka.core.InstancesView: Replaces the attribute at the given position (0 to numAttributes()) with the given attribute and sets all its values to be missing.
replaceMissingTipText() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Returns the tip text for this property
replaceMissingTipText() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Returns the tip text for this property
replaceMissingValues(double[]) - Method in class weka.core.AbstractHashableInstance: Replaces all missing values in the instance with the values contained in the given array.
ReplaceMissingValuesWithZero - Class in weka.filters.unsupervised.attribute: Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means from the training data.
ReplaceMissingValuesWithZero() - Constructor for class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero
replaceTipText() - Method in class adams.flow.transformer.WekaRenameRelation: Returns the tip text for this property.
replaceTipText() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Returns the tip text for this property.
REPORT_ADDITIONAL_PREFIX - Static variable in class adams.data.instance.Instance: the key prefix in the report for the additional attributes.
REPORT_CLASS - Static variable in class adams.data.instance.Instance: the key in the report for the class.
REPORT_DATASET - Static variable in class adams.data.instance.Instance: the key in the report for the dataset name.
REPORT_DB_ID - Static variable in class adams.data.instance.Instance: the key in the report for the database ID.
REPORT_DISPLAY_ID - Static variable in class adams.data.instance.Instance: the key in the report for the display ID.
REPORT_ID - Static variable in class adams.data.instance.Instance: the key in the report for the ID.
REPORT_ROW - Static variable in class adams.data.instance.Instance: the key in the report for the row in the dataset.
ReportColorInstancePaintlet - Class in adams.gui.visualization.instance: Paintlet for generating a line plot using the color stored in the report.
ReportColorInstancePaintlet() - Constructor for class adams.gui.visualization.instance.ReportColorInstancePaintlet
ReportToWekaInstance - Class in adams.data.conversion: Converts a report into a weka.core.Instance objects.
ReportToWekaInstance() - Constructor for class adams.data.conversion.ReportToWekaInstance
requiresFlowContext() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns whether flow context is actually required.
requiresFlowContext() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Returns whether flow context is actually required.
requiresInitialization() - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix: Returns whether the handler requires an initialization.
requiresWrapper() - Method in class adams.gui.application.WekaExperimenterPreferencesPanel: Returns whether the panel requires a wrapper scrollpane/panel for display.
requiresWrapper() - Method in class adams.gui.application.WekaExplorerPreferencesPanel: Returns whether the panel requires a wrapper scrollpane/panel for display.
requiresWrapper() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel: Returns whether the panel requires a wrapper scrollpane/panel for display.
reset() - Method in class adams.core.discovery.genetic.GenericDoubleResolution
reset() - Method in class adams.core.discovery.genetic.GenericFloatResolution
reset() - Method in class adams.core.discovery.genetic.GenericInteger
reset() - Method in class adams.core.discovery.genetic.GenericString
reset() - Method in class adams.data.conversion.AbstractMatchWekaInstanceAgainstHeader: Resets the converter.
reset() - Method in class adams.data.conversion.ReportToWekaInstance: Resets the scheme.
reset() - Method in class adams.data.conversion.SwapPLS: Resets the scheme.
reset() - Method in class adams.data.instances.AbstractInstanceGenerator: Resets the generator (but does not clear the input data!).
reset() - Method in class adams.data.instancesanalysis.FastICA: Resets the scheme.
reset() - Method in class adams.data.instancesanalysis.PCA: Resets the scheme.
reset() - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: Resets the scheme.
reset() - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Resets the scheme.
reset() - Method in class adams.data.instancesanalysis.pls.AbstractSingleClassPLS: Resets the scheme.
reset() - Method in class adams.data.instancesanalysis.pls.PLS1: Resets the scheme.
reset() - Method in class adams.data.instancesanalysis.PLS: Resets the scheme.
reset() - Method in class adams.data.instancesanalysis.pls.SIMPLS: Resets the scheme.
reset() - Method in class adams.data.io.input.InstanceReader: Resets the filter.
reset() - Method in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder: Resets the object, including the trained state.
reset() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator: Resets the scheme.
reset() - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Resets the scheme.
reset() - Method in class adams.data.weka.rowfinder.AbstractTrainableRowFinder: Resets the object, including the trained state.
reset() - Method in class adams.data.weka.rowfinder.FilteredIQR: Resets the object.
reset() - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities: Resets the scheme.
reset() - Method in class adams.flow.sink.WekaDatabaseWriter: Resets the actor.
reset() - Method in class adams.flow.source.WekaDatabaseReader: Resets the scheme.
reset() - Method in class adams.flow.source.WekaSelectDataset: Resets the scheme.
reset() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Resets the scheme.
reset() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaAccumulatedError: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaAggregateEvaluations: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaFileReader: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaFilter: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaInstanceBuffer: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaInstanceDumper: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Resets the actor.
reset() - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Resets the actor.
reset() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaRandomSplit: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Resets the actor.
reset() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Resets the actor.
reset() - Method in class adams.flow.transformer.WekaSplitGenerator: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaStreamEvaluator: Initializes the members.
reset() - Method in class adams.flow.transformer.WekaStreamFilter: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaTrainClassifier: Resets the scheme.
reset() - Method in class adams.flow.transformer.WekaTrainClusterer: Resets the scheme.
reset() - Method in class adams.gui.application.WekaInvestigatorPreferencesPanel: Resets the settings to their default.
reset() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Invalidates the indexer.
reset() - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater: Resets the object.
reset() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Removes all sort definition panels.
reset() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Resets the genetic algorihtm.
reset() - Method in class adams.opt.optimise.GeneticAlgorithm: Resets the genetic algorihtm.
reset() - Method in class weka.classifiers.AbstractSplitGenerator: Resets the generator.
reset() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Resets the generator.
reset() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Resets the generator.
reset() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Resets the generator.
reset() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Resets the generator.
reset() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Resets the generator.
reset() - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Resets the scheme.
reset() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Resets the generator.
reset() - Method in class weka.classifiers.MultiLevelSplitGenerator: Resets the scheme.
reset() - Method in class weka.core.converters.SimpleArffLoader: Resets the loader.
reset() - Method in class weka.core.converters.SpreadSheetLoader: Resets the loader ready to read a new data set
reset() - Method in class weka.core.tokenizers.cleaners.AbstractTokenCleaner: Resets the cleaner.
reset() - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens: Resets the cleaner.
reset() - Method in class weka.filters.FlowFilter: Resets the filter.
reset() - Method in class weka.filters.SerializedFilter: Resets the filter.
reset() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString: Resets the cleaner.
reset() - Method in class weka.filters.unsupervised.attribute.AnyToString: resets the filter, i.e., m_NewBatch to true and m_FirstBatchDone to false.
reset() - Method in class weka.filters.unsupervised.attribute.Detrend: Resets the filter.
reset() - Method in class weka.filters.unsupervised.attribute.EquiDistance: Resets the filter.
reset() - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: resets the filter.
reset() - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Resets the filter.
reset() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Resets the cleaner.
reset() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Resets the filter.
reset() - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Resets the filter.
reset() - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Resets the filter.
reset() - Method in class weka.filters.unsupervised.attribute.SpellChecker: resets the filter.
reset() - Method in class weka.filters.unsupervised.attribute.StringToDate: resets the filter, i.e., m_NewBatch to true and m_FirstBatchDone to false.
reset() - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin: Resets the scheme.
reset() - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Resets the filter.
RESET - adams.gui.event.InstancesSortSetupEvent.EventType: the setup was reset.
resetColorProvider() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Resets the color provider to the default one.
resetDefinitions() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Resets the definitions.
resetInternalState(Instances[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Resets the internal state of the merge method when new datasets are supplied.
resetMinMax(double, double) - Method in class adams.opt.optimise.genetic.PackDataDef.DataInfo
resetOptions() - Method in class weka.core.converters.SimpleArffSaver
resetOptions() - Method in class weka.core.converters.SpreadSheetSaver
resetResultsTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the tip text for this property.
ResettableExperiment - Interface in adams.gui.tools.wekamultiexperimenter.experiment: Interface for experiments that can clear any prior results.
ResidualsVsFitted - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Plots the residuals vs the fitted values (= predictions).
ResidualsVsFitted() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsFitted
ResidualsVsPredictor - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Plots the residuals vs the predictor.
ResidualsVsPredictor() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.ResidualsVsPredictor
restoreGOE(Map, String, Object, GenericObjectEditor) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Restores the value of the GenericObjectEditor.
restoreSelectedIndex(Map, String, Integer, JComboBox) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Restores the selected index of the BaseComboBox.
restoreSelectedIndices(Map, String, int[], JList) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Restores the selected indices of the JList.
restoreSelectedState(Map, String, Boolean, JCheckBox) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Sets the selected state of the checkbox.
restoreSelectedState(JCheckBox, Boolean) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Sets the selected state of the checkbox.
restoreSelection(DataContainer[]) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Tries to restore the selection using the provided containers.
restoreSpinner(Map, String, Integer, JSpinner) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Restores the integer value of the JSpinner.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.sink.WekaDatabaseWriter: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaAccumulatedError: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaAggregateEvaluations: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaCrossValidationSplit: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaFileReader: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaFilter: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaInstanceBuffer: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaInstanceDumper: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaStreamEvaluator: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaStreamFilter: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaTrainClassifier: Restores the state of the actor before the variables got updated.
restoreState(Hashtable<String, Object>) - Method in class adams.flow.transformer.WekaTrainClusterer: Restores the state of the actor before the variables got updated.
restoreText(Map, String, String, JTextComponent) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Restores the text of the text component, e.g., a BaseTextField.
resultFileTipText() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the tip text for this property.
resultFormatTipText() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the tip text for this property.
ResultItem - Class in adams.gui.tools.wekainvestigator.tab.associatetab: Container for an evaluation, model, training set header.
ResultItem - Class in adams.gui.tools.wekainvestigator.tab.attseltab: Container for an attribute selection, evaluator and search method.
ResultItem - Class in adams.gui.tools.wekainvestigator.tab.classifytab: Container for an evaluation, model, training set header.
ResultItem - Class in adams.gui.tools.wekainvestigator.tab.clustertab: Container for an evaluation, model, training set header.
ResultItem - Class in adams.gui.tools.wekainvestigator.tab.experimenttab: Container for an experiment run.
ResultItem(Associator, Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: Initializes the item.
ResultItem(ASEvaluation, ASSearch, Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Initializes the item.
ResultItem(Classifier, Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Initializes the item.
ResultItem(Classifier, Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: Initializes the item.
ResultItem(Clusterer, Instances) - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Initializes the item.
ResultMatrixAdamsCSV - Class in weka.experiment: Generates the matrix in ADAMS CSV ('comma-separated values') format.
ResultMatrixAdamsCSV() - Constructor for class weka.experiment.ResultMatrixAdamsCSV: initializes the matrix as 1x1 matrix.
ResultMatrixAdamsCSV(int, int) - Constructor for class weka.experiment.ResultMatrixAdamsCSV: initializes the matrix with the given dimensions.
ResultMatrixAdamsCSV(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixAdamsCSV: initializes the matrix with the values from the given matrix.
ResultMatrixMediaWiki - Class in weka.experiment: Generates table output in MediaWiki format.
ResultMatrixMediaWiki() - Constructor for class weka.experiment.ResultMatrixMediaWiki: initializes the matrix as 1x1 matrix.
ResultMatrixMediaWiki(int, int) - Constructor for class weka.experiment.ResultMatrixMediaWiki: initializes the matrix with the given dimensions.
ResultMatrixMediaWiki(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixMediaWiki: initializes the matrix with the values from the given matrix.
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.
rowTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the tip text for this property.
RPD - Class in weka.classifiers.evaluation: Computes the RPD (Ratio of Performance to Deviation) for regression models: RPD = SD / RMSE
https://www.academia.edu/4303409/Why_you_dont_need_to_use_RPD
RPD - adams.flow.core.EvaluationStatistic
RPD - adams.flow.core.ExperimentStatistic
RPD() - Constructor for class weka.classifiers.evaluation.RPD
RRSE - adams.flow.transformer.WekaClassifierRanker.Measure: evaluation via: Root relative squared error.
RRSE - adams.opt.genetic.Measure: Root relative squared error.
RRSE - adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure: evaluation via: Root relative squared error.
RSquared - Class in weka.classifiers.evaluation: Computes the R^2 for regression models.
RSquared() - Constructor for class weka.classifiers.evaluation.RSquared
RSQUARED - adams.flow.core.EvaluationStatistic
RSQUARED - adams.flow.core.ExperimentStatistic
RSQUARED - adams.opt.genetic.Measure: R^2.
Rule2 - Class in weka.classifiers.trees.m5: Generates a single m5 tree or rule
Rule2() - Constructor for class weka.classifiers.trees.m5.Rule2: Constructor declaration
RuleNode2 - Class in weka.classifiers.trees.m5: Constructs a node for use in an m5 tree or rule
RuleNode2(double, double, RuleNode2) - Constructor for class weka.classifiers.trees.m5.RuleNode2: Creates a new RuleNode instance.
Rules - Class in adams.gui.tools.wekainvestigator.tab.associatetab.output: Outputs the rules if available AssociationRulesProducer.
Rules() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.output.Rules
run() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorJob: Executes the job.
run() - Method in class adams.gui.tools.wekainvestigator.job.InvestigatorTabJob: Executes the job.
run() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel.BarCalc
run() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel.HistCalc
run() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Starts running the experiment.
run() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Runs the genetic algorithm.
runClassifier(Classifier, String[]) - Static method in class weka.classifiers.simple.AbstractSimpleClassifier: runs the classifier instance with the given options.
runExperimenter(String[]) - Static method in class adams.gui.tools.wekamultiexperimenter.MultiExperimenter: Runs an experimenter instance.
runExplorer(String[]) - Static method in class weka.gui.explorer.ExplorerExt: Runs an explorer instance.
runExplorer(String[]) - Static method in class weka.gui.explorer.MultiExplorer: Runs an explorer instance.
runGeneticAlgorithm(Class, Class, String[]) - Static method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Runs the genetic algorithm with the given options.
RunInformation - Class in adams.gui.tools.wekainvestigator.tab.associatetab.output: Generates run information.
RunInformation - Class in adams.gui.tools.wekainvestigator.tab.attseltab.output: Generates run information.
RunInformation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Generates run information.
RunInformation - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output: Generates run information.
RunInformation - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.output: Generates run information.
RunInformation() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.output.RunInformation
RunInformation() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.output.RunInformation
RunInformation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.RunInformation
RunInformation() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.RunInformation
RunInformation() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.output.RunInformation
RunInformationHelper - Class in adams.gui.tools.wekainvestigator.output: Helper class for run information.
RunInformationHelper() - Constructor for class adams.gui.tools.wekainvestigator.output.RunInformationHelper
runInformationTipText() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics: Returns the tip text for this property.
runInformationTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Returns the tip text for this property.
runInformationTipText() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics: Returns the tip text for this property.
runInformationTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the tip text for this property.
runsTipText() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the tip text for this property.
runsTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the tip text for this property.
runsTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the tip text for this property.

S

SafeRemoveRange - Class in weka.filters.unsupervised.instance: A filter that removes a given range of instances of a dataset.
Works just like weka.filters.unsupervised.instance.RemoveRange, but has a more robust handling of instance ranges.
SafeRemoveRange() - Constructor for class weka.filters.unsupervised.instance.SafeRemoveRange
SAMPLE_SIZE - adams.flow.sink.WekaThresholdCurve.AttributeName
SAMPLE_SIZE - Static variable in class weka.filters.unsupervised.attribute.InterquartileRangeSamp
sampleCorrs(Instances) - Method in class weka.classifiers.meta.Corr
sampleDevs(Instances, double[]) - Method in class weka.classifiers.meta.Corr
SamplePlot - Class in adams.flow.transformer.wekarepeatedcrossvalidationoutput: Generates plot containers with statistics derived for each sample across the cross-validation runs.
SamplePlot - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated: Generates a plot with statistics derived for each sample across the cross-validation runs.
SamplePlot() - Constructor for class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot
SamplePlot() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot
sampleSizeTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Returns the tip text for this property.
sampleTypeTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the sampleType option.
save() - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu: Pops up the filechooser.
save() - Method in class weka.gui.explorer.ExplorerExt: Allows the user to save the file.
save(AbstractExperiment, File) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultAdamsExperimentIO: Saves an experiment.
save(File) - Method in class adams.gui.tools.wekainvestigator.output.AbstractOutputPanelWithPopupMenu: Saves the content to the specified file.
save(File) - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel: Saves the content to the specified file.
save(File) - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel: Saves the content to the specified file.
save(File) - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel: Saves the content to the specified file.
save(T, File) - Method in class adams.gui.tools.wekamultiexperimenter.io.AbstractExperimentIO: Saves an experiment.
save(Experiment, File) - Method in class adams.gui.tools.wekamultiexperimenter.io.DefaultWekaExperimentIO: Saves an experiment.
save(RemoteExperiment, File) - Method in class adams.gui.tools.wekamultiexperimenter.io.RemoteWekaExperimentIO: Saves an experiment.
Save - Class in adams.gui.tools.wekainvestigator.datatable.action: Saves the selected data.
Save() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Save: Instantiates the action.
saveAs() - Method in class weka.gui.explorer.ExplorerExt: Allows the user to save the file.
saveAs(TableRowRange) - Method in class adams.gui.visualization.instances.InstancesTable: Exports the data.
SaveAs - Class in adams.gui.visualization.instance.containerlistpopup: Allows the saving of an instance container.
SaveAs() - Constructor for class adams.gui.visualization.instance.containerlistpopup.SaveAs
saveBuffer(String) - Method in class weka.gui.explorer.ExperimentPanel: Save the currently selected experiment output to a file.
saveDataset() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Saves the result as a new dataset.
saveExperimentData(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Saves the results to a file.
SaveGraph - Class in weka.gui.visualize.plugins: Allows user to save graph (eg generated by BayesNet) as file.
SaveGraph() - Constructor for class weka.gui.visualize.plugins.SaveGraph
SaveIndexedSplitsRuns - Class in adams.gui.tools.wekainvestigator.datatable.action: Saves the indexed splits runs generated from the selected data.
SaveIndexedSplitsRuns() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns: Instantiates the action.
saveInstance(InstanceContainer) - Method in class adams.gui.visualization.instance.InstancePanel: Saves the specified instance as spreadsheet file.
saveInstancesTipText() - Method in class weka.classifiers.trees.M5P2: Returns the tip text for this property
saveModel(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Saves the model to a file.
saveModel(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Saves the model to a file.
saveModel(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Saves the model to a file.
saveObject(Object) - Method in class weka.classifiers.meta.Corr
saveParameters() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Prompts the user to select a yaml file to store the parameters of the tab under.
saveProperties() - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: Saves properties to a file, prompts the user to select props file.
saveReducedData(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Saves the reduced data to a file.
saveResults() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Saves the results to a file.
saveResults(File) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Saves the results to the file.
saveResults(File, AbstractFileSaver) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Saves the results to the file.
saveSetup() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Allows the user to save the file.
saveSetup(File) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Saves the experiment to the specified file.
saveSetupAs() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Allows the user to save the file.
SaveTree - Class in weka.gui.visualize.plugins: Saves a tree in dotty notation as file.
SaveTree() - Constructor for class weka.gui.visualize.plugins.SaveTree
SaveVisible - Class in adams.gui.visualization.instance.plotpopup: Allows the user to save the visible containers as ARFF.
SaveVisible() - Constructor for class adams.gui.visualization.instance.plotpopup.SaveVisible
saveWorkspace() - Method in class weka.gui.explorer.MultiExplorer: Saves the current workspace.
SavitzkyGolay - Class in weka.filters.unsupervised.attribute: A filter that applies Savitzky-Golay smoothing.
If a class attribute is present this will not be touched and moved to the end.

For more information see:

A.
SavitzkyGolay() - Constructor for class weka.filters.unsupervised.attribute.SavitzkyGolay
SavitzkyGolay2 - Class in weka.filters.unsupervised.attribute: A filter that applies Savitzky-Golay smoothing.
If a class attribute is present this will not be touched and moved to the end.

For more information see:

A.
SavitzkyGolay2() - Constructor for class weka.filters.unsupervised.attribute.SavitzkyGolay2
SavitzkyGolay2NumPoints - Class in adams.core.discovery.genetic: SavitzkyGolay numPoints handler.
SavitzkyGolay2NumPoints() - Constructor for class adams.core.discovery.genetic.SavitzkyGolay2NumPoints
SAX - Class in weka.filters.unsupervised.attribute: A simple filter that retains only every nth attribute.
SAX() - Constructor for class weka.filters.unsupervised.attribute.SAX
SAXDistance - Class in weka.core: Implementing Euclidean distance (or similarity) function.

One object defines not one distance but the data model in which the distances between objects of that data model can be computed.

Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.

For more information, see:

Wikipedia.
SAXDistance() - Constructor for class weka.core.SAXDistance: Constructs an Euclidean Distance object, Instances must be still set.
SAXDistance(Instances) - Constructor for class weka.core.SAXDistance: Constructs an Euclidean Distance object and automatically initializes the ranges.
SAXKMeans - Class in weka.clusterers: SimpleKMeans adapted for SAX.
SAXKMeans() - Constructor for class weka.clusterers.SAXKMeans: the default constructor.
scale(ArrayList) - Method in class adams.data.weka.predictions.AbstractErrorScaler: Scales the errors.
scale(ArrayList) - Method in class adams.data.weka.predictions.AutoScaler: Scales the errors.
scale(ArrayList) - Method in class adams.data.weka.predictions.FixedSizeErrorScaler: Scales the errors.
scale(ArrayList) - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference: Scales the errors.
scale(ArrayList) - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler: Scales the errors.
scale(ArrayList) - Method in class adams.data.weka.predictions.RoundErrorScaler: Scales the errors.
Scale - Class in weka.filters.unsupervised.instance: Scales all numeric attributes between the specified min/max.
Scale() - Constructor for class weka.filters.unsupervised.instance.Scale
scalePositiveWeightsTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the scalePositiveWeights option.
scalerTipText() - Method in class adams.data.weka.predictions.AutoScaler: Returns the tip text for this property.
ScatterPlotTab - Class in adams.gui.tools.wekainvestigator.tab: For plotting attributes against each other.
ScatterPlotTab() - Constructor for class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab
SDR - Class in weka.classifiers.evaluation: Computes the SDR (Standard Deviation of Residuals) for regression models.
SDR - adams.flow.core.EvaluationStatistic
SDR - adams.flow.core.ExperimentStatistic
SDR() - Constructor for class weka.classifiers.evaluation.SDR
search() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Searches the panel with the filter.
search() - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Performs a search in the fields.
searchTipText() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns the tip text for this property.
searchTipText() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns the tip text for this property.
secondAttributeRangeTipText() - Method in class adams.gui.InstanceCompare: Returns the tip text for this property.
secondAttributeTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Returns the tip text for this property.
secondCrossValidationSeedTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Returns the tip text for this property.
secondDatasetTipText() - Method in class adams.gui.InstanceCompare: Returns the tip text for this property.
secondFoldsTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Returns the tip text for this property.
secondRangeTipText() - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Returns the tip text for this property.
secondRowIndexTipText() - Method in class adams.gui.InstanceCompare: Returns the tip text for this property.
seedTipText() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator: Returns the tip text for this property.
seedTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Returns the tip text for this property.
seedTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the tip text for this property.
seedTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Returns the tip text for this property.
seedTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Returns the tip text for this property.
seedTipText() - Method in class adams.flow.transformer.WekaAttributeSelection: Returns the tip text for this property.
seedTipText() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the tip text for this property.
seedTipText() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the tip text for this property.
seedTipText() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Returns the tip text for this property.
seedTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the tip text for this property.
seedTipText() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Returns the tip text for this property.
seedTipText() - Method in class adams.flow.transformer.WekaRandomSplit: Returns the tip text for this property.
seedTipText() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Returns the tip text for this property.
seedTipText() - Method in class weka.classifiers.AbstractSplitGenerator: Returns the tip text for this property.
seedTipText() - Method in class weka.classifiers.functions.FakeClassifier: Returns the tip text for this property.
seedTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the seed option.
seedTipText() - Method in class weka.filters.supervised.instance.RemoveOutliers: Returns the tip text for this property.
seedTipText() - Method in class weka.filters.unsupervised.attribute.InputSmearing: Returns the tip text for this property
seedTipText() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns the tip text for this property.
seedTipText() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns the tip text for this property.
selCol - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState: the selected column.
selectAttributes(Instances, List<Integer>) - Method in class adams.flow.transformer.WekaChooseAttributes: Prompts the user to select attributes.
selectColorProvider() - Method in class adams.gui.visualization.instance.InstanceExplorer: Lets the user select a new color provider.
SELECTION_GREEDY - Static variable in class weka.classifiers.functions.LinearRegressionJ: Attribute selection method: Greedy method
SELECTION_M5 - Static variable in class weka.classifiers.functions.LinearRegressionJ: Attribute selection method: M5 method
SELECTION_NONE - Static variable in class weka.classifiers.functions.LinearRegressionJ: Attribute selection method: No attribute selection
SELECTION_PROCESSOR - Static variable in class weka.filters.unsupervised.instance.MultiRowProcessor
selectionProcessorTipText() - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Returns the tip text for this property.
selectionRowToModelRow(int) - Method in class adams.gui.visualization.instances.InstancesTable: Determines the actual row index.
selectPaintlet() - Method in class adams.gui.visualization.instance.InstanceExplorer: Lets the user select a new paintlet.
selectRows(Instances) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.AbstractRowSelection: Returns the list of row indices generated from the data.
selectSubSample(Instances, Random) - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Produces a random sample from m_Data in m_SubSample.
selectSubSample(Instances, Random) - Method in class weka.classifiers.meta.LeastMedianSq: Produces a random sample from m_Data in m_SubSample.
selRow - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState: the selected row.
selRows - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState: the selected rows.
send(byte[]) - Method in class weka.classifiers.meta.SocketFacade: Sends the data to the remote host.
serialize(InvestigatorPanel) - Method in class adams.gui.tools.wekainvestigator.InvestigatorWorkspaceHelper: Generates a view of the panel that can be serialized.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Generates a view of the tab that can be serialized.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Returns the objects for serialization.
serialize(Set<AbstractInvestigatorTab.SerializationOption>) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Returns the objects for serialization.
serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Generates a view of the explorer panel that can be serialized.
serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AssociationsHandler: Generates a view of the explorer panel that can be serialized.
serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.AttributeSelectionHandler: Generates a view of the explorer panel that can be serialized.
serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ClassifierHandler: Generates a view of the explorer panel that can be serialized.
serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ClustererHandler: Generates a view of the explorer panel that can be serialized.
serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.DefaultHandler: Generates a view of the explorer panel that can be serialized.
serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.ExperimentHandler: Generates a view of the explorer panel that can be serialized.
serialize(Explorer.ExplorerPanel) - Method in class weka.gui.explorer.PreprocessHandler: Generates a view of the explorer panel that can be serialized.
serialize(ExplorerExt, String, ObjectOutputStream, boolean) - Static method in class weka.gui.explorer.WorkspaceHelper: Serializes the explorer instance to the output stream.
serialize(GenericObjectEditor) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Serializes the content of a GenericObjectEditor.
serialize(ResultHistoryPanel) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Serializes a ResultHistoryPanel.
SERIALIZED_MODEL_SIZE - adams.flow.core.ExperimentStatistic
SERIALIZED_TEST_SET_SIZE - adams.flow.core.ExperimentStatistic
SERIALIZED_TRAIN_SET_SIZE - adams.flow.core.ExperimentStatistic
SerializedAdamsExperimentReader - Class in adams.data.io.input: Reads serialized ADAMS Experiments.
SerializedAdamsExperimentReader() - Constructor for class adams.data.io.input.SerializedAdamsExperimentReader
SerializedAdamsExperimentWriter - Class in adams.data.io.output: Writes serialized ADAMS experiments.
SerializedAdamsExperimentWriter() - Constructor for class adams.data.io.output.SerializedAdamsExperimentWriter
SerializedFilter - Class in weka.filters: Processes the data with a the (trained) filter deserialized from the specified file.
SerializedFilter() - Constructor for class weka.filters.SerializedFilter
serializedTipText() - Method in class weka.filters.SerializedFilter: Returns the tip text for this property.
SESSION_FILE - Static variable in class adams.gui.tools.wekainvestigator.InvestigatorPanel: the file to store the recent files in.
SESSION_FILE - Static variable in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: the file to store the recent files in.
SESSION_FILE - Static variable in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: the file to store the recent files in.
SESSION_FILE - Static variable in class adams.gui.visualization.instance.InstanceExplorer: the file to store the recent files in.
SESSION_FILE - Static variable in class weka.gui.explorer.ExplorerExt: the file to store the recent files in.
SESSION_FILE_1 - Static variable in class adams.gui.visualization.instance.InstanceComparePanel: the file to store the recent files in (first file).
SESSION_FILE_2 - Static variable in class adams.gui.visualization.instance.InstanceComparePanel: the file to store the recent files in (second file).
set(int, DataContainer) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList
set(int, InstanceContainer) - Method in class adams.gui.visualization.instance.InstanceContainerManager: Replaces the container at the given position.
set(int, Instance) - Method in class weka.core.InstancesView: Replaces the instance at the given position.
set(String, double) - Method in class adams.opt.optimise.genetic.PackData
set(Instance) - Method in class adams.data.instance.Instance: Clears the container and adds the data from the weka.core.Instance (internal values).
set(Instance, int, int[], Range, HashSet<Integer>) - Method in class adams.data.instance.Instance: Clears the container and adds the data from the weka.core.Instance (internal values).
setAbsErr(double) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Sets the threshold for the max error when predicting a numeric class.
setAbsErr(double) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Sets the threshold for the max error when predicting a numeric class.
setAbsolute(boolean) - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: Sets whether to return the absolute values of the coefficients.
setAcceptListener(ChangeListener) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Sets the listener for the event that the user accepts the input.
setAction(AbstractWekaPackageManagerAction) - Method in class adams.flow.source.WekaPackageManagerAction: Sets the action to use.
setAction(AbstractWekaPackageManagerAction) - Method in class adams.flow.standalone.WekaPackageManagerAction: Sets the action to use.
setAction(AbstractWekaPackageManagerAction) - Method in class adams.flow.transformer.WekaPackageManagerAction: Sets the action to use.
setActual(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Sets the column with the actual values.
setActual(SpreadSheetColumnIndex) - Method in class weka.classifiers.functions.FromPredictions: Sets the column with the actual values.
setActualMax(double) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets the upper limit in use for the actual values.
setActualMin(double) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets the lower limit in use for the actual values.
setAddAttributeInformation(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: Sets whether to add attribute information to the metadata.
setAddClassification(boolean) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Sets whether to add the numeric classification (label index for nominal classes).
setAddClassificationLabel(boolean) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Sets whether to add the classification label (only for nominal classes).
setAddDatabaseID(boolean) - Method in class adams.data.instances.AbstractInstanceGenerator: Sets whether the database ID is added to the data or not.
setAddDatasetInformation(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.AbstractInstancesIndexedSplitsRunsGenerator: Sets whether to add dataset information to the metadata.
setAddDistribution(boolean) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Sets whether to add the class distribution (only for nominal classes).
setAddIndex(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge: Sets whether to add the dataset index number to the prefix.
setAdditional(SpreadSheetColumnRange) - Method in class weka.classifiers.functions.FromPredictions: Sets the additional columns to add to the plot containers.
setAdditionalAttributes(SpreadSheet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Sets the additional attributes data.
setAdditionalFields(Field[]) - Method in interface adams.data.instances.InstanceGeneratorWithAdditionalFields: Sets the additional fields to add.
setAdditionalParameters(String[]) - Method in class adams.gui.menu.AbstractParameterHandlingWekaMenuItemDefinition: Sets the additional parameters.
setAddLabelIndex(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Sets whether to prefix the labels with the index.
setAddLabelIndex(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Sets whether to prefix the labels with the index.
setAddOne(boolean) - Method in class weka.filters.unsupervised.attribute.LogTransform: Sets whether to add '1' to the values before log-transform.
setAdjustToVisibleData(boolean) - Method in class adams.gui.visualization.instance.InstancePanel: Sets whether the display is adjusted to only the visible data or everything currently loaded.
setAlgorithm(BinningAlgorithm) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Sets the binning algorithm.
setAlgorithm(BinningAlgorithm) - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Sets the binning algorithm.
setAlgorithm(BinningAlgorithm) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Sets the binning algorithm.
setAlgorithm(BinningAlgorithm) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Sets the binning algorithm.
setAlgorithm(AbstractPLS) - Method in class adams.data.instancesanalysis.PLS: Sets the algorithm to use.
setAlgorithm(AbstractPLS) - Method in class weka.classifiers.functions.PLSWeighted: Set the PLS algorithm (only used for setup).
setAlgorithm(AbstractPLS) - Method in class weka.filters.supervised.attribute.MultiPLS: Sets the PLS algorithm to use.
setAlgorithm(AbstractPLS) - Method in class weka.filters.supervised.attribute.PLS: Sets the PLS algorithm to use.
setAlgorithm(AbstractClassifierBasedGeneticAlgorithm) - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Sets the genetic algorithm to apply to the dataset.
setAlgorithm(AbstractClassifierBasedGeneticAlgorithm) - Method in class weka.classifiers.functions.GeneticAlgorithm: Sets the genetic algorithm to use.
setAlgorithm(SelectedTag) - Method in class weka.filters.unsupervised.attribute.FastWavelet: Sets the type of algorithm to use.
setAlgorithms(BinningAlgorithm[]) - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Sets the binning algorithms to choose from.
setAlpha(double) - Method in class weka.filters.supervised.attribute.YGradientEPO: Set the alpha parameter.
setAlpha(double) - Method in class weka.filters.supervised.attribute.YGradientGLSW: Set the alpha parameter.
setAlpha(float) - Method in class weka.classifiers.trees.XGBoost: Sets the L1 regularisation term on weights.
setAlwaysShowMarkers(boolean) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Sets whether to always draw markers.
setAlwaysUseContainer(boolean) - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Sets whether to always use an evaluation container as output.
setAmount(double) - Method in class weka.filters.unsupervised.instance.LatestRecords: Sets the amount of records to keep (0,1]=percentage, (1,+inf)=absolute number.
setAntiAliasingEnabled(boolean) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Sets whether to use anti-aliasing.
setAntiAliasingEnabled(boolean) - Method in class adams.gui.visualization.instance.InstancePanel: Sets whether to use anti-aliasing.
setAntiAliasingEnabled(boolean) - Method in class adams.gui.visualization.instance.SimpleInstanceLinePaintlet: Sets whether to use anti-aliasing.
setAntiAliasingEnabled(AutoOnOff) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets whether to use anti-aliasing.
setAssociator(CallableActorReference) - Method in class adams.flow.transformer.WekaTrainAssociator: Sets the name of the callable associator to use.
setAssociator(Associator) - Method in class adams.flow.source.WekaAssociatorSetup: Sets the associator to use.
setAttRange(Range) - Method in class weka.filters.unsupervised.instance.KennardStone: Sets the attribute range to use for distance calculation (after applying pre-filter).
setAttRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.Detrend: Sets the regular expression used for identifying the attributes to process.
setAttRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Sets the regular expression used for identifying the attributes to process.
setAttribute(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: Sets the attribute that statistics will be displayed for.
setAttribute(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Tells the panel which attribute to visualize.
setAttribute(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: Displays a single attribute.
setAttribute(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: Displays a single attribute.
setAttribute(String) - Method in class weka.classifiers.meta.AbstainAttributePercentile
setAttributeIndex(Index) - Method in class adams.data.weka.rowfinder.ByLabel: Sets the index of the attribute to perform the matching on.
setAttributeIndex(WekaAttributeIndex) - Method in class adams.data.weka.rowfinder.ByNumericRange: Sets the index of the column to perform the matching on.
setAttributeIndex(WekaAttributeIndex) - Method in class adams.data.weka.rowfinder.ByNumericValue: Sets the index of the column to perform the matching on.
setAttributeIndex(WekaAttributeIndex) - Method in class adams.flow.transformer.WekaInstancesInfo: Sets the attribute index to use for attribute-specific information.
setAttributeIndex(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Sets the index of the attribute to use for indexing.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.SpellChecker: Sets the attribute index (1-based) of the attribute to process.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.instance.SortOnAttribute: Sets the attribute index (1-based) of the attribute to sort on.
setAttributeName(String) - Method in class adams.flow.transformer.WekaGetInstanceValue: Sets the name of the attribute to get the value for.
setAttributeName(String) - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Set the new attribute's name.
setAttributeName(String) - Method in class weka.filters.unsupervised.instance.LatestRecords: Sets the name of the attribute containing the numeric database ID.
setAttributeNames(BaseList) - Method in class adams.flow.source.WekaNewInstances: Sets the list of attribute names.
setAttributeNames(BaseString[]) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Sets the names of the attributes.
setAttributePrefix(String) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Sets the second attribute range to use (regular expression on attribute names).
setAttributeRange(Range) - Method in class adams.data.weka.rowfinder.FilteredIQR: Sets the attribute range to work on.
setAttributeRange(Range) - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Sets the range of attributes to detrend.
setAttributeRange(WekaAttributeRange) - Method in class adams.data.instancesanalysis.FastICA: Sets the attribute range parameter.
setAttributeRange(WekaAttributeRange) - Method in class adams.data.instancesanalysis.PCA: Sets the attribute range parameter.
setAttributeRange(WekaAttributeRange) - Method in class adams.data.instancesanalysis.PLS: Sets the attribute range parameter.
setAttributeRange(WekaAttributeRange) - Method in class weka.filters.unsupervised.attribute.InputSmearing: Sets the range (1-based) of the attributes to work on.
setAttributeRange(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Sets the range of attributes.
setAttributeRange(String) - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: Sets the range of attributes to compute the matrix for.
setAttributeRange(String) - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Sets the range (1-based) of the attributes to combine.
setAttributeRange(String) - Method in class weka.filters.unsupervised.attribute.LogTransform: Sets the range of attributes to process.
setAttributeRange(String) - Method in class weka.filters.unsupervised.attribute.SetMissingValue: Sets the range of attributes to compute the matrix for.
setAttributeRenamesExp(BaseRegExp[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Sets the array of attribute rename expressions.
setAttributeRenamesFormat(BaseString[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Sets the array of format strings used for attribute renaming.
setAttributes(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: Displays multiple attributes.
setAttributes(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: Displays multiple attributes.
setAttributes(Range) - Method in class adams.flow.transformer.WekaInstanceStreamPlotGenerator: Sets the range of attributes to create plot containers for.
setAttributeSelection(EquiDistance.AttributeSelection) - Method in class weka.filters.unsupervised.attribute.EquiDistance: Sets how the attributes get selected.
setAttributeSelectionMethod(SelectedTag) - Method in class weka.classifiers.functions.LinearRegressionJ: Sets the method used to select attributes for use in the linear regression.
setAttributeTypes(AttributeTypeList) - Method in class adams.flow.source.WekaNewInstances: Sets the list of attribute types.
setAttributeX(WekaAttributeIndex) - Method in class adams.flow.sink.WekaInstancesPlot: Sets the attribute to show on the X axis.
setAttributeX(WekaThresholdCurve.AttributeName) - Method in class adams.flow.sink.WekaThresholdCurve: Sets the attribute to show on the X axis.
setAttributeX(WekaThresholdCurve.AttributeName) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Sets the attribute to show on the X axis.
setAttributeY(WekaAttributeIndex) - Method in class adams.flow.sink.WekaInstancesPlot: Sets the attribute to show on the Y axis.
setAttributeY(WekaThresholdCurve.AttributeName) - Method in class adams.flow.sink.WekaThresholdCurve: Sets the attribute to show on the Y axis.
setAttributeY(WekaThresholdCurve.AttributeName) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Sets the attribute to show on the Y axis.
setAutoKeyGeneration(boolean) - Method in class adams.flow.sink.WekaDatabaseWriter: Sets whether to automatically generate a primary key.
setAxisX(AxisPanelOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Sets the setup for the X axis.
setAxisY(AxisPanelOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Sets the setup for the Y axis.
setBase(AbstractPLS) - Method in class adams.data.instancesanalysis.pls.OPLS: Sets the base PLS algorithm to use.
setBase(Classifier) - Method in class weka.classifiers.meta.Fallback: Sets the base classifier.
setBaseScore(float) - Method in class weka.classifiers.trees.XGBoost: Sets the initial prediction score of all instances (global bias).
setBatchSize(String) - Method in class weka.classifiers.functions.PyroProxy: Set the batch size to use.
setBestRange(Range) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Sets the best range of attributes.
setBestRange(String) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Sets the best range of attributes.
setBias(double) - Method in class weka.classifiers.meta.VotedImbalance: Sets the bias towards a uniform class.
setBinCalculation(ArrayHistogram.BinCalculation) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Sets how the number of bins is calculated.
setBins(int) - Method in class weka.core.SAXDistance: Sets the nth point setting.
setBins(int) - Method in class weka.filters.unsupervised.attribute.SAX: Sets the nth point setting.
setBinWidth(double) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Sets the bin width to use (for some calculations).
setBits(int) - Method in class adams.opt.optimise.GeneticAlgorithm: Bits per gene.
setBitsForPosition(int, int[], List<Integer>, List<Integer>, int, int[]) - Method in class adams.opt.genetic.Hermione: Updates the bits.
setBitsPerGene(int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the bits per gene to use.
setBitstring(String) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
setBooster(XGBoost.BoosterType) - Method in class weka.classifiers.trees.XGBoost: Sets the type of booster to use.
setBorder(int) - Method in class weka.experiment.ResultMatrixMediaWiki: Sets the thickness of the border.
setBorderTitle(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Sets the title of the border.
setBufferSize(int) - Method in class adams.flow.transformer.WekaInstanceDumper: Sets the number of instances to buffer before writing them to disk.
setBuildRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.M5Base2: Set the value of regressionTree.
setBuildWait(int) - Method in class weka.classifiers.functions.FakeClassifier: Sets the time in msec to wait when calling buildClassifier.
setButtonPanelVisible(boolean) - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: Sets the visibility state of the buttons panel (load/save).
setC(double) - Method in class adams.data.instancesanalysis.pls.PRM: Tuning parameter.
setCallableName(CallableActorReference) - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Sets the name of the callable sink to use.
setCancelListener(ChangeListener) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Sets the listener for the event that the user discarded the input.
setCanChangeClassInDialog(PropertyEditor, boolean) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler: Sets whether the class can be changed in the dialog.
setCanopyMaxNumCanopiesToHoldInMemory(int) - Method in class weka.clusterers.SAXKMeans: Set the maximum number of candidate canopies to retain in memory during training.
setCanopyMinimumCanopyDensity(double) - Method in class weka.clusterers.SAXKMeans: Set the minimum T2-based density below which a canopy will be pruned during periodic pruning.
setCanopyPeriodicPruningRate(int) - Method in class weka.clusterers.SAXKMeans: Set the how often to prune low density canopies during training (if using canopy clustering)
setCanopyT1(double) - Method in class weka.clusterers.SAXKMeans: Set the t1 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs
setCanopyT2(double) - Method in class weka.clusterers.SAXKMeans: Set the t2 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs
setCapabilities(Capability[]) - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities: Sets the capabilities.
setCellPadding(int) - Method in class weka.experiment.ResultMatrixMediaWiki: Sets the cell padding for the table.
setCellPopupMenuCustomizer(PopupMenuCustomizer) - Method in class adams.gui.visualization.instances.InstancesTable: Sets the popup menu customizer to use (for the cells).
setCellRenderingCustomizer(CellRenderingCustomizer) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Sets the cell rendering customizer.
setCellSpacing(int) - Method in class weka.experiment.ResultMatrixMediaWiki: Sets the cell spacing for the table.
setCenterData(boolean) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Set whether to center (rather than standardize) the data.
setCharSet(String) - Method in class adams.flow.transformer.WekaTextDirectoryReader: Sets the character set to use.
setCheckHeader(boolean) - Method in class adams.flow.transformer.WekaInstanceBuffer: Sets whether to check the header or not.
setCheckHeader(boolean) - Method in class adams.flow.transformer.WekaInstanceDumper: Sets whether to check the header or not.
setClassAttribute(int, boolean) - Method in class adams.ml.data.InstancesView: Sets the class attribute status for a column.
setClassAttribute(AbstractClassAttributeHeuristic) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets the heuristic for determining the class attribute (if not explicitly set).
setClassAttribute(String, boolean) - Method in class adams.ml.data.InstancesView: Sets the class attribute status for a column.
setClassAttributeByName(String, boolean) - Method in class adams.ml.data.InstancesView: Sets the class attribute status for a column.
setClassAttributeHeuristic(AbstractClassAttributeHeuristic) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Sets the class attribute heuristic.
setClassAttributes(BaseRegExp) - Method in class adams.data.instancesanalysis.pls.AbstractMultiClassPLS: Sets the regular expression for identifying the class attributes (besides an explicitly set one).
setClassDetails(boolean) - Method in class adams.flow.transformer.WekaEvaluationSummary: Sets whether the class details are output as well.
setClassDetails(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Sets whether the class details are output as well.
setClassDistribution(SpreadSheetUnorderedColumnRange) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Sets the columns with the class distribution (nominal class).
setClassDistribution(SpreadSheetUnorderedColumnRange) - Method in class weka.classifiers.functions.FromPredictions: Sets the class distribution columns.
setClassFinder(ColumnFinder) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Sets the finder to use for finding class attributes in the source datasets.
setClassificationEntry(String) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Sets the value for the 'Name' column for the numeric classification.
setClassificationLabelEntry(String) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Sets the value for the 'Name' column for the classification label.
setClassifier(CallableActorReference) - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator: Sets the name of the callable classifier to use.
setClassifier(CallableActorReference) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Sets the name of the callable classifier to use.
setClassifier(CallableActorReference) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Sets the name of the callable classifier to use.
setClassifier(CallableActorReference) - Method in class adams.flow.transformer.WekaTrainClassifier: Sets the name of the callable classifier to use.
setClassifier(Classifier) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Sets the classifier to use, must implement weka.classifiers.IntervalEstimator.
setClassifier(Classifier) - Method in class adams.flow.source.WekaClassifierSetup: Sets the classifier to use.
setClassifier(Classifier) - Method in class adams.ml.model.classification.WekaClassifier: Sets the classifier to use.
setClassifier(Classifier) - Method in class adams.ml.model.regression.WekaRegressor: Sets the classifier to use.
setClassifier(Classifier) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets the classifier to use.
setClassifier(Classifier) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the classifier to use.
setClassifier(Classifier) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Sets the classifier to use (if no serialized model is used).
setClassifier(Classifier) - Method in class weka.classifiers.lazy.LWLIntervalEstimator: Set the base learner, which must implement IntervalEstimator.
setClassifier(Classifier) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: Set the base learner.
setClassifier(Classifier) - Method in class weka.classifiers.meta.VotedImbalance
setClassifier(Classifier) - Method in class weka.filters.supervised.instance.RemoveOutliers: Sets the classifier.
setClassifier(Classifier) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Sets the classifier to classify instances with.
setClassifier(Classifier) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Sets the classifier to classify instances with.
setClassifiers(Classifier[]) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets the classifiers to use.
setClassifiers(Classifier[]) - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: Sets the classifiers to use.
setClassifierWeights(String) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
setClassIndex(int) - Method in class weka.classifiers.meta.ClassifierCascade: the class index.
setClassIndex(int) - Method in class weka.core.InstancesView: Sets the class index of the set.
setClassIndex(int) - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive
setClassIndex(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Sets the attribute on which misclassifications are based.
setClassIndex(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Sets the attribute on which misclassifications are based.
setClassIndex(Index) - Method in class adams.flow.transformer.WekaClassSelector: Sets the class index.
setClassIndex(WekaAttributeIndex) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the class index.
setClassIndex(WekaLabelIndex) - Method in class adams.flow.sink.WekaCostBenefitAnalysis: Sets the index of class label (1-based).
setClassIndex(WekaLabelIndex) - Method in class adams.flow.transformer.WekaBootstrapping: Sets the index of class label index (1-based).
setClassIndex(WekaLabelIndex) - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Sets the class label index (1-based).
setClassIndex(WekaLabelIndex) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Sets the index of class label index (1-based).
setClassIndex(WekaLabelIndex) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostBenefitAnalysis: Sets the index of class label (1-based).
setClassIndex(WekaLabelIndex) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Sets the index of class label index (1-based).
setClassIndex(WekaLabelRange) - Method in class adams.flow.transformer.WekaEvaluationValues: Sets the range of class labels indices (1-based).
setClassIndex(String) - Method in class adams.flow.source.WekaNewInstances: Sets the index of the class attribute.
setClassIndex(String) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Sets the class index.
setClassLabel(WekaLabelIndex) - Method in class adams.flow.transformer.WekaClassifierRanker: Sets the class label index to use for class-specific measures.
setClassLabelIndex(Index) - Method in class adams.data.conversion.WekaEvaluationToCostCurve: Sets the class label index (1-based index).
setClassLabelIndex(Index) - Method in class adams.data.conversion.WekaEvaluationToThresholdCurve: Sets the class label index (1-based index).
setClassLabelIndex(Index) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets the index of the class label to use when generating per-class statistics.
setClassLabelIndex(WekaLabelIndex) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the index of the class label to use for statistics that work on a per-label-basis.
setClassLabelRange(WekaLabelRange) - Method in class adams.flow.sink.WekaCostCurve: Sets the class label indices.
setClassLabelRange(WekaLabelRange) - Method in class adams.flow.sink.WekaThresholdCurve: Sets the class label indices.
setClassLabelRange(WekaLabelRange) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyCostCurve: Sets the class label indices.
setClassLabelRange(WekaLabelRange) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.LegacyThresholdCurve: Sets the class label indices.
setClassLabels(List<String>) - Method in class weka.classifiers.AggregateEvaluations: Sets the class labels to use.
setClassMissing() - Method in class weka.core.AbstractHashableInstance: Sets the class value of an instance to be "missing".
setClassname(BaseClassname) - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Sets the classname to be the handler for.
setClassname(BaseClassname) - Method in class adams.core.discovery.genetic.GenericFloatResolution: Sets the classname to be the handler for.
setClassname(BaseClassname) - Method in class adams.core.discovery.genetic.GenericInteger: Sets the classname to be the handler for.
setClassname(BaseClassname) - Method in class adams.core.discovery.genetic.GenericString: Sets the classname to be the handler for.
setClassname(String) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode: Sets the classname to use.
setClassName(BaseString) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Sets the name of the attribute to use as the class attribute for supervised summary filters.
setClassName(String) - Method in class adams.flow.source.WekaNewInstances: Sets the name of the class attribute.
setClassNoise(double) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Set the level of Gaussian Noise for the class.
setClassType(PropertyEditor, Class) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler: Sets the class type to use.
setClassValue(double) - Method in class weka.core.AbstractHashableInstance: Sets the class value of an instance to the given value (internal floating-point format).
setClassValue(String) - Method in class weka.core.AbstractHashableInstance: Sets the class value of an instance to the given value.
setCleaner(TokenCleaner) - Method in class weka.core.tokenizers.PreCleanedTokenizer: Sets the cleaner to use for cleaning the tokens from the initial tokenization.
setCleaners(TokenCleaner[]) - Method in class weka.core.tokenizers.cleaners.MultiCleaner: Sets the cleaners to use.
setClearBuffer(boolean) - Method in class adams.flow.transformer.WekaInstanceBuffer: Sets whether to clear the buffer once the dataset has been forwarded.
setClusterer(CallableActorReference) - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator: Sets the name of the callable clusterer to use.
setClusterer(CallableActorReference) - Method in class adams.flow.transformer.WekaTrainClusterer: Sets the clusterer to use.
setClusterer(Clusterer) - Method in class adams.flow.source.WekaClustererSetup: Sets the clusterer to use.
setClusterer(Clusterer) - Method in class adams.ml.model.clustering.WekaClusterer: Sets the clusterer to use.
setColName(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: Sets the spreadsheet column with the name.
setColName(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.wekapackagemanageraction.Uninstall: Sets the spreadsheet column with the name.
setColor(Color) - Method in class adams.gui.visualization.instance.InstanceContainer: Sets the color to use.
setColorField(Field) - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet: Sets the report field that contains the color.
setColoringIndex(int) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Set the coloring (class) index for the plot
setColorProvider(ColorProvider) - Method in class adams.flow.sink.WekaInstanceViewer: Sets the color provider to use.
setColorProvider(ColorProvider) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Sets the color provider for the plots.
setColorProvider(ColorProvider) - Method in class adams.gui.visualization.instance.InstanceContainerManager: Sets the color provider to use.
setColumn(BaseString[]) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Sets list of fields that identify a column.
setColumn(BaseString[]) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Sets list of fields that identify a column.
setColumn(WekaAttributeIndex) - Method in class adams.flow.transformer.WekaGetInstancesValue: Sets the column.
setColumn(WekaAttributeIndex) - Method in class adams.flow.transformer.WekaSetInstancesValue: Sets the column index.
setColumnFinder(ColumnFinder) - Method in class adams.data.weka.columnfinder.AbstractFilteredColumnFinder: Sets the column finder to use.
setColumnFinder(ColumnFinder) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter: Sets the column finder.
setColumnFinder(ColumnFinder) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Sets the column finder to use.
setColumnFinder(ColumnFinder) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Sets the column finder which selects the attributes for summarisation.
setColumns(int) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Sets the size of array.
setColumns(int) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
setColumns(BaseInteger[]) - Method in class adams.data.weka.columnfinder.Constant: Sets the constant set of columns to find.
setColumnSampleByLevel(float) - Method in class weka.classifiers.trees.XGBoost: Sets the sub-sample ratio of columns for each level.
setColumnSampleByNode(float) - Method in class weka.classifiers.trees.XGBoost: Sets the sub-sample ratio of columns for each node (split).
setColumnSampleByTree(float) - Method in class weka.classifiers.trees.XGBoost: Sets the sub-sample ratio of columns when constructing each tree.
setColVersion(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.wekapackagemanageraction.InstallOfficial: Sets the (optional) spreadsheet column with the version.
setCombination(MultiColumnFinder.Combination) - Method in class adams.data.weka.columnfinder.MultiColumnFinder: Sets how the indices are combined.
setCombination(MultiRowFinder.Combination) - Method in class adams.data.weka.rowfinder.MultiRowFinder: Sets how the indices are combined.
setCombination(ClassifierCascade.Combination) - Method in class weka.classifiers.meta.ClassifierCascade: how to combine the statistics.
setCombinationRule(SelectedTag) - Method in class weka.classifiers.meta.AbstainVote: Sets the combination rule to use.
setCombinationRule(SelectedTag) - Method in class weka.classifiers.meta.SubsetEnsemble: Sets the combination rule to use.
setCombinationRule(SelectedTag) - Method in class weka.classifiers.meta.VotedImbalance: Sets the combination rule to use.
setComment(BaseText) - Method in class adams.flow.transformer.WekaClusterEvaluationSummary: Sets the comment to output in the summary.
setComment(BaseText) - Method in class adams.flow.transformer.WekaEvaluationSummary: Sets the comment to output in the summary.
setCommunication(AbstractCommunicationProcessor) - Method in class weka.classifiers.functions.PyroProxy: Sets the model proxy to use for communication.
setCommunication(AbstractCommunicationProcessor) - Method in interface weka.core.PyroProxyObject: Sets the handler for the communication.
setComparator(Comparator) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Sets the comparator to use.
setComparator(Comparator) - Method in class weka.classifiers.AggregateEvaluations: Sets the comparator to use.
setComparisonField(ExperimentStatistic) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Sets the comparison field.
setComparisonField(ExperimentStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Sets the comparison field.
setCompleteRowsOnly(boolean) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Sets whether incomplete rows should be skipped.
setComplexityStatistics(boolean) - Method in class adams.flow.transformer.WekaEvaluationSummary: Sets whether to output complexity stats as well.
setComplexityStatistics(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Sets whether to output complexity stats as well.
setComponentRange(Range) - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Sets the range of components to be used.
setConfidenceLevel(double) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Sets the confidence level.
setConfusionMatrix(boolean) - Method in class adams.flow.transformer.WekaEvaluationSummary: Sets whether to output the confusion matrix as well.
setConfusionMatrix(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Sets whether to output the confusion matrix as well.
setContainerManager(InstanceContainerManager) - Method in class adams.gui.visualization.instance.InstanceExplorer: Sets the manager for handling the containers.
setContent(DateTime) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContent(DateTimeMsec) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContent(Time) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContent(TimeMsec) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContent(Boolean) - Method in class adams.ml.data.DataCellView: Ignored.
setContent(Byte) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContent(Double) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContent(Float) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContent(Integer) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContent(Long) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContent(Short) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContent(String) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContent(Date) - Method in class adams.ml.data.DataCellView: Sets the content of the cell.
setContentAs(String, Cell.ContentType) - Method in class adams.ml.data.DataCellView: Sets the content of the cell, trying to parse the content using the specified content type.
setContentAsString(String) - Method in class adams.ml.data.DataCellView: Sets the string content of the cell.
setConversion(Conversion) - Method in class weka.core.converters.SpreadSheetLoader: Sets the conversion to use for converting the spreadsheet into an Instances object.
setConverter(Converter) - Method in class adams.data.conversion.WekaCommandToCode: Sets the converter to use.
setCorrect(String) - Method in class weka.filters.unsupervised.attribute.SpellChecker: Sets the correct label.
setCorrection(AbstractDetrend) - Method in class weka.filters.unsupervised.attribute.Detrend: Sets the correction scheme to apply.
setCorrection(AbstractDetrend) - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Sets the correction scheme to apply.
setCorrection(AbstractMultiplicativeScatterCorrection) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Sets the correction scheme to apply.
setCreateView(boolean) - Method in interface adams.data.weka.InstancesViewCreator: Sets whether to create a view only.
setCreateView(boolean) - Method in class adams.flow.transformer.WekaCrossValidationSplit: Sets whether to create a view only.
setCreateView(boolean) - Method in class adams.flow.transformer.WekaRandomSplit: Sets whether to create a view only.
setCrossValidationSeed(int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the seed value to use for cross-validation.
setCrossValidationSeed(int) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Sets the seed value to use for cross-validation.
setCurrent(File) - Method in class adams.gui.chooser.DatasetFileChooserPanel: Sets the current value.
setCurrent(File) - Method in class adams.gui.tools.weka.AbstractPanelWithFile: Sets the current file to use.
setCurrent(File) - Method in class adams.gui.tools.weka.CostCurvePanel: Sets the current file to use.
setCurrent(File) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Sets the current file.
setCurrent(File) - Method in class adams.gui.wizard.WekaSelectDatasetPage: Sets the current file.
setCurrent(File[]) - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: Sets the current files.
setCurrent(Object) - Method in class adams.gui.goe.WekaGenericArrayEditorDialog: Sets the current object.
setCurrent(Object) - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Sets the current value.
setCurrent(Object) - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: Sets the current object.
setCurrent(Object) - Method in class adams.gui.goe.WekaGenericObjectEditorPanel: Sets the current value.
setCurrentDirectory(File) - Method in class adams.gui.chooser.DatasetFileChooserPanel: Sets the current directory to use for the file chooser.
setCurrentDirectory(File) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Sets the current directory to use for the file chooser.
setCurrentDirectory(File) - Method in class adams.gui.wizard.WekaSelectDatasetPage: Sets the current directory to use for the file chooser.
setCurrentDirectory(File) - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: Sets the current directory to use for the file chooser.
setCurrentFile(File) - Method in class weka.gui.explorer.ExplorerExt: Only updates the current file member, does not load it.
setCustomLoader(AbstractFileLoader) - Method in class adams.flow.transformer.WekaFileReader: Sets the custom loader to use.
setCustomLoader(AbstractFileLoader) - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Sets the custom loader to use.
setCustomLoader(AbstractFileLoader) - Method in class weka.filters.unsupervised.instance.AlignDataset: Sets the custom loader to use (if enabled).
setCustomLoader(AbstractFileLoader) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Sets the custom loader to use (if enabled).
setCustomPaintlet(XYSequencePaintlet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets the custom paintlet.
setCustomPropsFile(PlaceholderFile) - Method in class adams.flow.sink.WekaDatabaseWriter: Sets the custom properties file to use for initializing the database setup instead of WEKA's default one.
setCustomPropsFile(PlaceholderFile) - Method in class adams.flow.source.WekaDatabaseReader: Sets the custom properties file to use for initializing the database setup instead of WEKA's default one.
setCustomSaver(AbstractFileSaver) - Method in class adams.flow.sink.WekaFileWriter: Sets the custom saver to use.
setCustomStopMessage(String) - Method in class adams.flow.source.WekaSelectDataset: Sets the custom message to use when stopping the flow.
setData(Instance) - Method in class adams.gui.visualization.instance.InstanceContainer: Sets the instance.
setData(List<DataContainer>) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: Sets the underlying data and notifies listeners of change.
setData(List<DataContainer>, boolean) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: Sets the underlying data.
setData(Instances) - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator: Sets the data set to use for training and so forth.
setData(Instances) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Sets the data.
setData(Instances) - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer: Sets the data.
setData(Instances) - Method in class adams.gui.visualization.instance.InstanceTable: Sets the Instances object to display.
setData(Instances) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets the data to use.
setData(Instances) - Method in class weka.classifiers.AbstractSplitGenerator: Sets the original data.
setData(Instances) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Sets the original data.
setData(Instances) - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Sets the original data.
setData(Instances) - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Sets the original data.
setData(Instances) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Sets the original data.
setData(Instances) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Sets the original data.
setData(Instances) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Sets the original data.
setData(Instances) - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Sets the original data.
setData(Instances) - Method in interface weka.classifiers.SplitGenerator: Sets the original data.
setDatabaseConnection(AbstractDatabaseConnection) - Method in class adams.data.instances.AbstractInstanceGenerator: Sets the database connection object to use.
setDataGenerator(DataGenerator) - Method in class adams.flow.source.WekaDataGenerator: Sets the data generator to use.
setDataPaintlet(Paintlet) - Method in class adams.gui.visualization.instance.InstancePanel: Sets the paintlet to use for painting the data.
setDataRowClass(Class) - Method in class adams.ml.data.InstancesView: Sets the default data row class to use.
setDataRowType(DataRow) - Method in class adams.data.conversion.WekaInstancesToSpreadSheet: Sets the type of data row to use.
setDataset(PlaceholderFile) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Sets the filename of the dataset to use for cross-validation.
setDataset(StorageName) - Method in class adams.flow.transformer.WekaStoreInstance: Sets the name of the dataset in internal storage to append to.
setDataset(File) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Sets the dataset to use.
setDataset(Instances) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Sets the dataset to index.
setDataset(Instances) - Method in class weka.core.AbstractHashableInstance: Sets the reference to the dataset.
setDataset1(PlaceholderFile) - Method in class adams.tools.CompareDatasets: Sets the first dataset for the comparison.
setDataset2(PlaceholderFile) - Method in class adams.tools.CompareDatasets: Sets the second dataset for the comparison.
setDatasetNames(BaseString[]) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Sets the list of names to use in attribute renaming in place of the {DATASET} keyword.
setDatasets(PlaceholderFile[]) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets the datasets to use.
setDataType(WekaInstancesStatisticDataType) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Sets what type of data to retrieve from the Instances object.
setDataType(WekaInstancesStatisticDataType) - Method in class adams.flow.transformer.WekaInstancesStatistic: Sets what type of data to retrieve from the Instances object.
setDateLenient(boolean) - Method in class adams.ml.data.InstancesView: Sets whether parsing of dates is to be lenient or not.
setDateTimeLenient(boolean) - Method in class adams.ml.data.InstancesView: Sets whether parsing of date/times is to be lenient or not.
setDateTimeMsecLenient(boolean) - Method in class adams.ml.data.InstancesView: Sets whether parsing of date/time mses is to be lenient or not.
setDebug(boolean) - Method in class weka.classifiers.meta.AbstainLeastMedianSq: sets whether or not debugging output shouild be printed
setDebug(boolean) - Method in class weka.classifiers.meta.LeastMedianSq: sets whether or not debugging output shouild be printed
setDebug(boolean) - Method in class weka.core.converters.SpreadSheetLoader: Sets whether to print some debug information.
setDebug(boolean) - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin: Sets whether to output debugging information.
setDefaultAttributeRange(String) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Sets the default range of attributes to use.
setDefaultClassIndex(String) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Sets the default class index to use.
setDefaultColor(Color) - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet: Sets the default color to use when no color information in the report.
setDefaultIDIndex(String) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Sets the default ID index to use.
setDefaultIncludeAttributes(int, boolean) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Sets the default for the specified type of attribute.
setDefaultSortIndex(String) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Sets the default sort index to use.
setDeflationMode(NIPALS.DeflationMode) - Method in class adams.data.instancesanalysis.pls.NIPALS: Sets the deflation mode to use.
setDerivativeOrder(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Sets the order of the derivative.
setDerivativeOrder(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Sets the order of the derivative.
setDestination(File) - Method in class weka.core.converters.SimpleArffSaver: Sets the destination file (and directories if necessary).
setDestination(File) - Method in class weka.core.converters.SpreadSheetSaver: Sets the destination file (and directories if necessary).
setDestination(OutputStream) - Method in class weka.core.converters.SimpleArffSaver: Default implementation throws an IOException.
setDestination(OutputStream) - Method in class weka.core.converters.SpreadSheetSaver: Default implementation throws an IOException.
setDetector(AbstractOutlierDetector) - Method in class weka.filters.supervised.instance.RemoveOutliers: Sets the detector.
setDev(double) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive
setDiameter(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets the cross diameter.
setDiffer(SelectedTag) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Sets the type of strategy to apply if the two values differ.
setDiffer(SelectedTag) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Sets the type of strategy to apply if the two values differ.
setDiscardPredictions(boolean) - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator: Sets whether to discard the predictions instead of collecting them for future use, in order to conserve memory.
setDiscardPredictions(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Sets whether to discard the predictions instead of collecting them for future use, in order to conserve memory.
setDiscardPredictions(boolean) - Method in class adams.flow.transformer.WekaTestSetEvaluator: Sets whether to discard the predictions instead of collecting them for future use, in order to conserve memory.
setDiscardPredictions(boolean) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets whether to discard the predictions instead of collecting them for future use, in order to conserve memory.
setDisplayStdDevs(boolean) - Method in class weka.clusterers.SAXKMeans: Sets whether standard deviations and nominal count.
setDistanceFunction(DistanceFunction) - Method in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient: Sets the distance function to use.
setDistanceFunction(DistanceFunction) - Method in class weka.clusterers.SAXKMeans: sets the distance function to use for instance comparison.
setDistributionFormat(String) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Sets the format for the 'Name' column for the class distribution.
setDistributionSorting(WekaPredictionContainerToSpreadSheet.Sorting) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Sets the sorting for the distribution array.
setDontReplaceMissingValues(boolean) - Method in class weka.clusterers.SAXKMeans: Sets whether missing values are to be replaced.
setDropAbove(double) - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Sets the threshold of the weights above which to drop instances.
setDropAtMost(double) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Sets the maximum percentage of instances to drop.
setDropBelow(double) - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Sets the threshold of the weights below which to drop instances.
setDropBelow(double) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Sets the threshold of the normalized weights below which to drop instances.
setDropNonClassYs(boolean) - Method in class weka.filters.supervised.attribute.MultiPLS: Sets whether to remove Y attributes from the output that are not the class attribute.
setEditor(PropertyEditor) - Method in class adams.gui.goe.WekaGenericObjectEditorDialog: Sets the editor to use.
setEliminateColinearAttributes(boolean) - Method in class weka.classifiers.functions.LinearRegressionJ: Set the value of EliminateColinearAttributes.
setEncoding(BaseCharset) - Method in class adams.data.io.input.NestedAdamsExperimentReader: Sets the encoding to use.
setEncoding(BaseCharset) - Method in class weka.core.converters.SimpleArffLoader: Sets the encoding to use.
setEncoding(BaseCharset) - Method in class weka.core.converters.SimpleArffSaver: Sets the encoding to use.
setEnsureEqualValues(boolean) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Sets whether to check all data-sources for a merged attribute have the same value.
setError(int) - Method in class weka.classifiers.meta.AbstainLeastMedianSq
setError(int) - Method in class weka.classifiers.meta.LeastMedianSq
setErrorCalculation(WekaBootstrapping.ErrorCalculation) - Method in class adams.flow.transformer.WekaBootstrapping: Sets how to calculate the errors for the percentiles.
setErrorScaler(AbstractErrorScaler) - Method in class adams.flow.sink.WekaClassifierErrors: Sets the scheme for scaling the errors.
setEta(float) - Method in class weka.classifiers.trees.XGBoost: Sets the step size shrinkage to use in updates to prevent overfitting.
setEvaluationPostProcessor(AbstractWekaEvaluationPostProcessor) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the post-processing scheme for the evaluation.
setEvaluationType(WekaExperimentGenerator.EvaluationType) - Method in class adams.flow.sink.WekaExperimentGenerator: Sets the type of evaluation to perform.
setEvaluator(AbstractInstanceEvaluator) - Method in class adams.flow.transformer.WekaInstanceEvaluator: Sets the evaluator to use.
setEvaluator(ASEvaluation) - Method in class adams.flow.transformer.WekaAttributeSelection: Sets the evaluation method to use.
setExactMatch(boolean) - Method in class adams.data.conversion.SwapPLS: Sets whether to use the complete command-line for comparison rather than just the class name.
setExcludeClass(boolean) - Method in class weka.core.AbstractHashableInstance: Sets whether to exclude the class from the hashcode computation.
setExcludedAttributes(String) - Method in class adams.flow.transformer.WekaInstancesMerge: Sets the regular expression for excluding attributes.
setExcludeWeight(boolean) - Method in class weka.core.AbstractHashableInstance: Sets whether to exclude the weight from the hashcode computation.
setExperiment(AbstractExperiment) - Method in class adams.flow.source.WekaNewExperiment: Sets the experiment setup.
setExperiment(AbstractExperiment) - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicAdamsSetupPanel: Sets the experiment to use.
setExperiment(Object) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Sets the experiment to use.
setExperiment(T) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: Sets the experiment to use.
setExperiment(Experiment) - Method in class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog: Sets the experiment to use.
setExperiment(Experiment) - Method in class adams.gui.tools.wekamultiexperimenter.setup.BasicWekaSetupPanel: Sets the experiment to use.
setExperimentFile(WekaExperimentFile) - Method in class adams.flow.transformer.WekaExperiment: Sets the file the experiment is stored in.
setExperimentType(WekaExperimentGenerator.ExperimentType) - Method in class adams.flow.sink.WekaExperimentGenerator: Sets the type of experiment to perform.
setExplorer(Explorer) - Method in class weka.gui.explorer.ExperimentPanel: Sets the Explorer to use as parent frame (used for sending notifications about changes in the data).
setExplorer(Explorer) - Method in class weka.gui.explorer.SqlPanel: Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
setExplorerOptions(Explorer, Hashtable<String, Object>) - Static method in class weka.gui.explorer.WorkspaceHelper: Restores the Explorer options from the hashtable.
setExpression(MathematicalExpressionText) - Method in class weka.classifiers.functions.MathExpressionClassifier: Sets the mathematical expression to evaluate.
setFallback(Classifier) - Method in class weka.classifiers.meta.Fallback: Sets the fallback classifier.
setFastDistanceCalc(boolean) - Method in class weka.clusterers.SAXKMeans: Sets whether to use faster distance calculation.
setFavorZeroes(boolean) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Sets whether 0s are favored over 1s.
setFeatureSelector(XGBoost.FeatureSelector) - Method in class weka.classifiers.trees.XGBoost: Gets the feature selection and ordering method.
setFields(Field[]) - Method in class adams.data.conversion.ReportToWekaInstance: Sets the fields to use.
setFields(Field[]) - Method in interface adams.data.instances.InstanceGeneratorWithFields: Sets the targets to add.
setFile(File) - Method in class weka.core.converters.SimpleArffLoader: Set the file to load from/ to save in
setFileChooserTitle(String) - Method in class adams.flow.source.WekaSelectDataset: Sets the title for the file chooser dialog.
setFiles(File[]) - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: Sets the files to use.
setFilter(Filter) - Method in class adams.data.spreadsheet.filter.WekaFilter: Sets the filter to use.
setFilter(Filter) - Method in class adams.data.weka.rowfinder.FilteredIQR: Sets the IQR filter.
setFilter(Filter) - Method in class adams.flow.transformer.WekaFilter: Sets the filter to use.
setFilter(Filter) - Method in class weka.classifiers.functions.ClassificationViaPLS: Set the PLS filter (only used for setup).
setFilter(Filter) - Method in class weka.classifiers.functions.PLSClassifierWeighted: Set the PLS filter (only used for setup).
setFilter(Filter) - Method in class weka.classifiers.lazy.LWLSynchroPrefilter
setFilter(Filter) - Method in class weka.core.neighboursearch.FilteredSearch: Sets the filter
setFilter(Filter) - Method in class weka.filters.unsupervised.attribute.FastWavelet: Set the preprocessing filter (only used for setup).
setFilter(StreamableFilter) - Method in class adams.flow.transformer.WekaStreamFilter: Sets the filter to use.
setFilters(Filter[]) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Sets the list of possible filters to choose from.
setFilters(Filter[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Sets the list of possible filters to choose from.
setFilterType(SelectedTag) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Sets how the training data will be transformed.
setFilterType(SelectedTag) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Sets how the training data will be transformed.
setFilterType(SelectedTag) - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Sets how the training data will be transformed.
setFilterType(SelectedTag) - Method in class weka.classifiers.functions.GPD: Sets how the training data will be transformed.
setFinalModel(boolean) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Sets whether to build a final model on the full dataset.
setFind(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Sets the regular expression to use for extracting the numeric part from the label.
setFind(String) - Method in class adams.flow.transformer.WekaRenameRelation: Sets the string to find.
setFinders(ColumnFinder[]) - Method in class adams.data.weka.columnfinder.MultiColumnFinder: Sets the column finders to use.
setFinders(RowFinder[]) - Method in class adams.data.weka.rowfinder.MultiRowFinder: Sets the row finders to use.
setFirstAttribute(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Sets the name of the first attribute.
setFirstAttributeRange(String) - Method in class adams.gui.InstanceCompare: Sets the first attribute range ('first' and 'last' can be used as well).
setFirstAttributeRange(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel: Sets the first attribute range ('first' and 'last' can be used as well).
setFirstDataset(PlaceholderFile) - Method in class adams.gui.InstanceCompare: Sets the first dataset.
setFirstDataset(File) - Method in class adams.gui.visualization.instance.InstanceComparePanel: Sets the first dataset.
setFirstRange(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Sets the first attribute range to use (regular expression on attribute names).
setFirstRowIndex(String) - Method in class adams.gui.InstanceCompare: Sets the first row index ('first' and 'last' can be used as well).
setFirstRowIndex(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel: Sets the first row index ('first' and 'last' can be used as well).
setFlowContext(Actor) - Method in class adams.flow.source.wekapackagemanageraction.AbstractWekaPackageManagerAction: Sets the flow context.
setFlowContext(Actor) - Method in class adams.flow.standalone.wekapackagemanageraction.AbstractWekaPackageManagerAction: Sets the flow context.
setFlowContext(Actor) - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction: Sets the flow context.
setFlowContext(Actor) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets the flow context.
setFlowContext(Actor) - Method in class adams.multiprocess.WekaCrossValidationJob: Sets the flow context.
setFlowContext(Actor) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the flow context, if any.
setFlowContext(Actor) - Method in class weka.classifiers.functions.PyroProxy: Sets the flow context.
setFlowFile(FlowFile) - Method in class weka.filters.FlowFilter: Sets the flow to process the data with.
setFolds(int) - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator: Sets the number of folds for cross-validation.
setFolds(int) - Method in class adams.flow.sink.WekaExperimentGenerator: Sets the number of folds to use (only CV).
setFolds(int) - Method in class adams.flow.transformer.WekaAttributeSelection: Sets the number of folds.
setFolds(int) - Method in class adams.flow.transformer.WekaClassifierRanker: Sets the number of folds to use.
setFolds(int) - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Sets the number of folds.
setFolds(int) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Sets the number of folds.
setFolds(int) - Method in class adams.flow.transformer.WekaCrossValidationSplit: Sets the number of folds to use.
setFolds(int) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Sets the number of folds.
setFolds(int) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: Sets the number of folds.
setFolds(int) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets the number of folds.
setFolds(int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the number of folds to use in cross-validation.
setFolds(int) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Sets the number of folds to use in cross-validation.
setForceCompression(boolean) - Method in class weka.core.converters.SimpleArffLoader: Set whether the file gets interpreted as gzip-compressed ARFF file.
setFormat(String) - Method in class weka.filters.unsupervised.attribute.StringToDate: Sets the parse format to use.
setFormula(String) - Method in class adams.ml.data.DataCellView: Ignored.
setGamma(double) - Method in class weka.classifiers.functions.GPD: Set the gamma for the RBF kernel.
setGamma(float) - Method in class weka.classifiers.trees.XGBoost: Sets the minimum loss reduction required to make a further partition on a leaf node of the tree.
setGene(int, int, boolean) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Sets the value of the specified gene.
setGene(int, int, int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Sets the value of the specified gene.
setGenerateLine(boolean) - Method in class adams.data.baseline.AbstractLinearRegressionBased: Sets whether to return the line as fake data or the corrected data.
setGenerateRules(boolean) - Method in class weka.classifiers.trees.m5.M5Base2: Generate rules (decision list) rather than a tree
setGenerator(AbstractInstanceGenerator) - Method in class adams.flow.transformer.AbstractInstanceGenerator: Sets the generator to use.
setGenerator(AbstractWekaEnsembleGenerator) - Method in class adams.flow.transformer.WekaEnsembleGenerator: Sets the ensemble generator to use.
setGenerator(CrossValidationFoldGenerator) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Sets the scheme for generating the folds.
setGenerator(CrossValidationFoldGenerator) - Method in class adams.flow.transformer.WekaCrossValidationSplit: Sets the scheme for generating the folds.
setGenerator(CrossValidationFoldGenerator) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Sets the scheme for generating the folds.
setGenerator(CrossValidationFoldGenerator) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment: Sets the scheme for generating the folds.
setGenerator(CrossValidationFoldGenerator) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets the generator to use for generating the folds.
setGenerator(CrossValidationFoldGenerator) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the scheme for generating the folds.
setGenerator(RandomSplitGenerator) - Method in class adams.flow.transformer.WekaRandomSplit: Sets the scheme for generating the split.
setGenerator(RandomSplitGenerator) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: Sets the scheme for generating the split.
setGenerator(SplitGenerator) - Method in class adams.flow.transformer.WekaSplitGenerator: Sets the scheme for generating the split.
setGlue(String) - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Sets the glue to use.
setGrid(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Sets the size of the grid.
setGroup(String) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Sets the replacement string to use as group (eg '$2').
setGroup(String) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Sets the replacement string to use as group (eg '$2').
setGroup(String) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Sets the replacement string to use as group (eg '$2').
setGroup(String) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Sets the replacement string to use as group (eg '$2').
setGroup(String) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Sets the replacement string to use as group (eg '$2').
setGroup(String) - Method in class weka.classifiers.GroupedRandomSplitGenerator: Sets the replacement string to use as group (eg '$2').
setGroup(String) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Sets the replacement string to use as group (eg '$2').
setGroups(BaseString[]) - Method in class weka.classifiers.MultiLevelSplitGenerator: Sets the groups to generate.
setGrowPolicy(XGBoost.GrowPolicy) - Method in class weka.classifiers.trees.XGBoost: Sets the way new nodes are added to the tree.
setHandler(AbstractExperimentIO) - Method in class adams.flow.sink.WekaExperimentFileWriter: Sets the IO handler.
setHandler(AbstractExperimentIO) - Method in class adams.flow.transformer.WekaExperimentFileReader: Sets the IO handler.
setHandlers(AbstractGeneticDiscoveryHandler[]) - Method in class adams.opt.genetic.Hermione: Sets the discovery handlers to use.
setHeader(PlaceholderFile) - Method in class adams.data.conversion.MatchWekaInstanceAgainstFileHeader: Sets the file to load the dataset header from.
setHeader(StorageName) - Method in class adams.data.conversion.MatchWekaInstanceAgainstStorageHeader: Sets the name of the storage value representing the dataset header.
setHeaderPopupMenuCustomizer(PopupMenuCustomizer) - Method in class adams.gui.visualization.instances.InstancesTable: Sets the popup menu customizer to use (for the header).
setHiClassifier(Classifier) - Method in class weka.classifiers.meta.HighLowSplit
setHiLopoint(double) - Method in class weka.classifiers.meta.HighLowSplit
setHistogramOptions(HistogramOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Set the options for the histogram.
setHoldOutPercentage(double) - Method in class weka.classifiers.meta.ClassifierCascade: the percentage to use for validation set to determine termination criterion (0-100).
setICA(FastICA) - Method in class adams.data.instancesanalysis.FastICA: Sets the ICA analysis.
setID(WekaAttributeIndex) - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Sets the attribute name/index of attribute with IDs.
setID(WekaAttributeIndex) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Sets the attribute name/index to use for identifying rows.
setID(String) - Method in class adams.data.instance.Instance: Sets the ID of the sequence.
setID(String) - Method in class adams.flow.sink.WekaInstanceViewer: Sets the name of the attribute/field to use as ID in the display.
setID(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Sets the ID to use for the returned instances.
setID(String) - Method in class adams.gui.visualization.instance.InstanceContainer: Sets the container's ID.
setIDTest(WekaAttributeIndex) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Sets the attribute name/index to use for identifying rows in the test set.
setIgnoreChanges(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: Sets whether to ignore changes, ie don't set the modified flag.
setIgnoreClass(boolean) - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: Sets whether to ignore the class.
setIgnoredAttributes(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Sets the regular expression for ignored/skipped attributes.
setIncludeAttributes(int, boolean) - Method in class adams.gui.visualization.instance.LoadDatasetDialog: Sets whether only numeric attributes should be used.
setIncludeClass(boolean) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Sets whether to include the class attribute in the comparison.
setIncludeClass(boolean) - Method in class weka.filters.unsupervised.instance.Sort: Sets whether to include the class attribute in the comparison.
setIncorrect(String) - Method in class weka.filters.unsupervised.attribute.SpellChecker: Sets the incorrect labels, blank-separated list.
setIncremental(boolean) - Method in class adams.flow.source.WekaDatabaseReader: Sets whether to output single Instance objects or just one Instances object.
setIndex(Index) - Method in class adams.flow.transformer.WekaExtractArray: Sets the type of extraction to perform.
setIndex(Index) - Method in class adams.flow.transformer.WekaGetInstanceValue: Sets the 1-based index of the attribute value to retrieve from the Instance.
setIndex(WekaAttributeIndex) - Method in class adams.data.weka.classattribute.AttributeIndex: Sets the index of the attribute to select.
setIndex(WekaAttributeIndex) - Method in class adams.data.weka.relationname.AttributeIndex: Sets the index of the attribute to select.
setIndex(WekaAttributeIndex) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Sets the attribute index to use for grouping.
setIndex(WekaAttributeIndex) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Sets the attribute index to use for grouping.
setIndex(WekaAttributeIndex) - Method in class adams.flow.transformer.WekaSetInstanceValue: Sets the 1-based attribute index to set in the Instance.
setIndex(WekaAttributeIndex) - Method in class adams.flow.transformer.WekaSubsets: Sets the index of the attribute to split on.
setIndex(WekaAttributeIndex) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Sets the attribute index to use for grouping.
setIndex(WekaAttributeIndex) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Sets the attribute index to use for grouping.
setIndex(WekaAttributeIndex) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Sets the attribute index to use for grouping.
setIndex(WekaAttributeIndex) - Method in class weka.classifiers.GroupedRandomSplitGenerator: Sets the attribute index to use for grouping.
setIndex(WekaAttributeIndex) - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Sets the attribute index to use for grouping.
setIndex(WekaAttributeIndex) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Sets the index of the attribute to convert.
setIndex(WekaAttributeIndex) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Sets the attribute index to use for grouping.
setIndex(WekaAttributeIndex) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Sets the index of the attribute to convert.
setIndices(WekaAttributeIndex[]) - Method in class weka.classifiers.MultiLevelSplitGenerator: Sets the attribute indices.
setInfoData(Vector<Instances>) - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Sets the underlying data.
setInitialDirectory(PlaceholderDirectory) - Method in class adams.flow.source.WekaSelectDataset: Sets the initial directory.
setInitialFiles(PlaceholderFile[]) - Method in class adams.flow.source.WekaSelectDataset: Sets the initial files.
setInitializationMethod(SelectedTag) - Method in class weka.clusterers.SAXKMeans: Set the initialization method to use
setInitializeOnce(boolean) - Method in class adams.flow.transformer.WekaFilter: Sets whether the filter gets initialized only with the first batch.
setInitializeOnce(boolean) - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Sets whether the internal reorder filter gets initialized only with the first batch.
setInlineValue(String) - Method in class adams.gui.goe.WekaExperimentFileEditor: Sets the value to use.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValuesWithZero: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Sets the format of the input instances.
setInstanceClass(BaseClassname) - Method in class adams.flow.transformer.WekaNewInstance: Sets the class name of the Instance object to create.
setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel.AttributeTableModel: Sets the tablemodel to look at a new set of instances.
setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Sets the instances to display the attribute names for.
setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel: Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeVisualizationPanel: Sets the instances for use
setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel: Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: Sets the instances to display.
setInstances(Instances) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: Sets the instances to display.
setInstances(Instances) - Method in class adams.gui.visualization.instances.InstancesPanel: Sets the instances to display.
setInstances(Instances) - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Sets the Instances to use.
setInstances(Instances) - Method in class adams.gui.visualization.instances.InstancesTable: sets the data
setInstances(Instances) - Method in class adams.gui.visualization.instances.InstancesTableModel: sets the data
setInstances(Instances) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the data to use for cross-validation.
setInstances(Instances) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Sets the data to use for cross-validation.
setInstances(Instances) - Method in class weka.core.neighboursearch.FilteredSearch: Sets the instances comprising the current neighbourhood.
setInstances(Instances) - Method in class weka.core.neighboursearch.NewNNSearch: Sets the instances comprising the current neighbourhood.
setInstances(Instances) - Method in class weka.core.neighboursearch.PCANNSearch: Sets the instances comprising the current neighbourhood.
setInstances(Instances) - Method in class weka.core.neighboursearch.PLSNNSearch: Sets the instances comprising the current neighbourhood.
setInstances(Instances) - Method in class weka.gui.explorer.ExperimentPanel: Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.explorer.SqlPanel: ignored
setInstancesActor(CallableActorReference) - Method in class adams.flow.transformer.WekaInstanceEvaluator: Sets the callable actor from which to retrieve Instances in case of AbstractDatasetInstanceEvaluator-derived evaluators.
setInstancesIndices(String) - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Sets the range of instances to be selected.
setInt(int[], int, int, int) - Method in class adams.opt.optimise.genetic.PackData
setInterval(int) - Method in class adams.flow.transformer.WekaInstanceBuffer: Sets the interval for outputting the Instances objects.
setInterval(int) - Method in class adams.flow.transformer.WekaStreamEvaluator: Sets the output interval.
setInverseTransform(boolean) - Method in class weka.filters.unsupervised.attribute.FastWavelet: Sets whether to use the inverse tranform.
setInverseTransform(boolean) - Method in class weka.filters.unsupervised.attribute.FFT: Sets whether to compute inverse.
setInvert(boolean) - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities: Sets whether to invert the matching sense of the capabilities.
setInvert(boolean) - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Sets whether to invert the matching sense.
setInvert(boolean) - Method in class adams.flow.transformer.WekaRegexToRange: Invert match?
setInvert(boolean) - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens: Sets whether to invert the matching sense, ie keep only the emoticons rather than removing them.
setInvert(boolean) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Set whether the invert the column indices.
setInvert(boolean) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Set whether the invert the row indices.
setInvert(boolean) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Set whether selection is inverted.
setInvert(boolean) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Set whether selection is inverted.
setInvert(boolean) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Sets whether to invert the matching sense (ie keep rather than remove).
setInvert(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Sets whether to invert the matching sense.
setInvertMatchingSense(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge: Sets whether to invert the matching sense.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.KennardStone: Sets if selection is to be inverted.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Sets if selection is to be inverted.
setIqr(double) - Method in class adams.data.weka.rowfinder.FilteredIQR: Sets the IQR multiplier.
setIterations(int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Sets the iterations to use.
setJobRunner(JobRunner) - Method in class adams.flow.transformer.WekaExperimentExecution: Sets the jobrunner for the experiment.
setJobRunner(JobRunner) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets the jobrunner for the experiment.
setJobRunner(JobRunner) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets the JobRunner.
setJobRunnerSetup(JobRunnerSetup) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets the JobRunnerSetup.
setJobRunnerSetup(JobRunnerSetup) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the jobrunner setup to use.
setKeepAttributeNames(boolean) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Sets whether to keep the original attribute names.
setKeepAttributeNames(boolean) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Sets whether to keep the original attribute names.
setKeepExisting(boolean) - Method in class adams.flow.transformer.WekaInstanceDumper: Sets whether to keep any existing file on first execution.
setKeepNumComponents(boolean) - Method in class adams.data.conversion.SwapPLS: Sets whether the 'number of components' of the old filter are retained.
setKeepOnlySingleUniqueID(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge: Sets whether to keep only a single instance of the unique ID attribute.
setKeepRelationName(boolean) - Method in class adams.flow.transformer.WekaFilter: Sets whether the filter doesn't change the relation name.
setKeepRelationName(boolean) - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Sets whether the filter doesn't change the relation name.
setKeepRelationName(boolean) - Method in class adams.flow.transformer.WekaStreamFilter: Sets whether the filter doesn't change the relation name.
setKeepSupervisedClass(boolean) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Sets whether to keep the class attribute of the summary attributes in the final dataset.
setKernel(AbstractKernel) - Method in class adams.data.instancesanalysis.pls.KernelPLS: Sets the kernel to use.
setKernel(Kernel) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Sets the kernel to use.
setKernel(Kernel) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Sets the kernel to use.
setKernel(Kernel) - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Sets the kernel to use.
setKeys(String) - Method in class adams.flow.source.WekaDatabaseReader: Sets the keys to use for identifying a single row (comma-separated list).
setKNN(int) - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Sets the number of neighbours used for kernel bandwidth setting.
setKNN(int) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Sets the number of neighbours used for kernel bandwidth setting.
setLabel(WekaLabelIndex) - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Sets the label index to use.
setLabel(WekaLabelIndex) - Method in class weka.classifiers.meta.Veto: Sets the label index to use.
setLabelIndex(WekaLabelIndex) - Method in class adams.flow.transformer.WekaInstancesInfo: Sets the index of the label to use.
setLabelIndex(String) - Method in class weka.classifiers.functions.ClassificationViaPLS: Set the label index to get the PLS matrices for.
setLabelMatch(String) - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Sets the label for the matching rows.
setLabelNonMatch(String) - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Sets the label for the non-matching rows.
setLabelRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Sets the regular expression for matching the labels to remove.
setLabelString(String) - Method in class weka.classifiers.functions.ClassificationViaPLS: Set the class attribute's label to get the PLS matrices for.
setLambda(double) - Method in class adams.data.instancesanalysis.pls.DIPLS: Sets the lambda.
setLambda(double) - Method in class adams.data.instancesanalysis.pls.SparsePLS: Sets sparsity parameter; determines sparseness.
setLambda(double) - Method in class adams.data.instancesanalysis.pls.VCPLS: Sets the lambda parameter.
setLambda(float) - Method in class weka.classifiers.trees.XGBoost: Sets the L2 regularisation term on weights.
setLenient(boolean) - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Sets whether to tolerate attributes that are missing in the incoming data.
setLimit(ActualVsPredictedPlot.LimitType) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets the limit to impose on the axes.
setListType(ListPackages.ListType) - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: Sets the type of list to generate.
setLoadingsCalculations(AbstractPLSAttributeEval.LoadingsCalculations) - Method in class weka.attributeSelection.AbstractPLSAttributeEval: sets the maximum number of attributes to use.
setLocal(BaseHostname) - Method in class weka.classifiers.meta.SocketFacade: Sets the return address for the remote process to use.
setLocale(Locale) - Method in class adams.ml.data.InstancesView: Sets the locale.
setLocations(BaseString[]) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Sets the locations of the data (indices/regular expressions on attribute name).
setLocations(BaseString[]) - Method in class adams.flow.transformer.WekaInstancesStatistic: Sets the locations of the data (indices/regular expressions on attribute name).
setLoClassifier(Classifier) - Method in class weka.classifiers.meta.HighLowSplit
setLog(Logger) - Method in class weka.gui.explorer.ExperimentPanel: Sets the Logger to receive informational messages.
setLog(Logger) - Method in class weka.gui.explorer.SqlPanel: Sets the Logger to receive informational messages
setLoggingLevel(LoggingLevel) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Sets the logging level.
setLoggingLevel(LoggingLevel) - Method in class adams.flow.transformer.WekaFilter: Sets the logging level.
setLoHipoint(double) - Method in class weka.classifiers.meta.HighLowSplit
setLoHipoint(double) - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier
setLower(LowerStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Sets the lower value to output.
setLower(LowerStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Sets the lower value to output.
setLower(LowerStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Sets the lower value to output.
setLower(LowerStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Sets the lower value to output.
setMainFilter(Filter) - Method in class weka.filters.FilteredFilter: Sets the main filter to use.
setMakeClassLast(boolean) - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Sets whether to make the class attribute the last attribute.
setMakeThreadSafe(boolean) - Method in class adams.flow.transformer.WekaModelReader: Sets whether to wrap classifier inside a threadsafe ThreadSafeClassifierWrapper wrapper.
setManualClassifier(Classifier) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Sets the manual classifier to use instead of obtaining it from the flow.
setManualClassifier(Classifier) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Sets the manual classifier to use instead of obtaining it from the flow.
setManualMax(double) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Sets the maximum to use when using manual binning with user-supplied max/max enabled.
setManualMin(double) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Sets the minimum to use when using manual binning with user-supplied min/max enabled.
setMarkerExtent(int) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Sets the extent (width and height of the shape around the plotted point).
setMarkersDisabled(boolean) - Method in class adams.gui.visualization.instance.InstanceLinePaintlet: Sets whether to draw markers or not.
setMatrix(String) - Method in class adams.flow.transformer.WekaGenericPLSMatrixAccess: Sets the name of matrix to extract.
setMatrix(Matrix) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilter
setMatrix(Matrix) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
setMatrixType(WekaExtractPLSMatrix.MatrixType) - Method in class adams.flow.transformer.WekaExtractPLSMatrix: Sets the type of matrix to extract.
setMatrixValues(ConfusionMatrix.MatrixValues) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Sets the type of values to generate.
setMax(double) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
setMax(double) - Method in class weka.filters.unsupervised.instance.Scale: Sets the maximum for the values.
setMax(int) - Method in class adams.flow.transformer.WekaClassifierRanker: Sets the maximum number of top-ranked classifiers to forward.
setMax(int) - Method in class weka.classifiers.trees.RandomModelTrees
setMaxAttributeNames(int) - Method in class adams.data.instancesanalysis.PCA: Sets the maximum number of attribute names.
setMaxAttributes(int) - Method in class adams.data.instancesanalysis.PCA: Sets the maximum attributes.
setMaxBin(int) - Method in class weka.classifiers.trees.XGBoost: Sets the maximum number of discrete bins to bucket continuous features.
setMaxClassRangePercentage(double) - Method in class weka.classifiers.meta.MinMaxLimits: Set the percentage of leeway to apply to the upper limit determaxed by the range of the class attribute in the training data.
setMaxDecimalPlaces(int) - Method in class weka.core.converters.SimpleArffSaver: Set the maximum number of decimal places to print
setMaxDepth(int) - Method in class weka.classifiers.trees.XGBoost: Sets the maximum depth of a tree.
setMaxDifference(String) - Method in class weka.classifiers.meta.AbstainAverage
setMaxDifference(String) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights
setMaxDifference(String) - Method in class weka.classifiers.meta.AbstainVote
setMaxDisplayItems(int) - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Sets the maximum number of array items to display via toString().
setMaxFactor(double) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Sets the upper limit for the multiplication factor for instances.
setMaxHandling(MinMaxLimits.LimitHandling) - Method in class weka.classifiers.meta.MinMaxLimits: Set how the upper limit is handled.
setMaximum(double) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Sets the maximum.
setMaximum(double) - Method in class adams.data.weka.rowfinder.ByNumericValue: Sets the maximum.
setMaximum(double) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Sets the maximum.
setMaximumAttributeNames(int) - Method in class adams.flow.transformer.WekaPrincipalComponents: Sets maximum number of attribute names.
setMaximumAttributeNames(int) - Method in class weka.core.neighboursearch.PCANNSearch: Sets maximum number of attributes to include in transformed attribute names.
setMaximumAttributeNames(int) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Sets maximum number of attributes to include in transformed attribute names.
setMaximumAttributes(int) - Method in class adams.flow.transformer.WekaPrincipalComponents: Sets maximum number of PC attributes to retain.
setMaximumAttributes(int) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Sets maximum number of PC attributes to retain.
setMaximumDeltaStep(float) - Method in class weka.classifiers.trees.XGBoost: Sets the maximum delta step we allow each leaf output to be.
setMaximumIncluded(boolean) - Method in class adams.data.weka.rowfinder.ByNumericValue: Sets whether to exclude the maximum.
setMaximumIncluded(boolean) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Sets whether to exclude the maximum.
setMaxIter(int) - Method in class adams.data.instancesanalysis.pls.KernelPLS: Sets the inner NIPALS loop improvement tolerance.
setMaxIter(int) - Method in class adams.data.instancesanalysis.pls.NIPALS: Sets the inner NIPALS loop maximum number of iterations.
setMaxIter(int) - Method in class adams.data.instancesanalysis.pls.PRM: Sets the inner NIPALS loop maximum number of iterations.
setMaxIter(int) - Method in class adams.data.instancesanalysis.pls.SparsePLS: Sets the inner NIPALS loop maximum number of iterations.
setMaxIterations(int) - Method in class weka.clusterers.SAXKMeans: set the maximum number of iterations to be executed.
setMaxIterations(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Sets the maximum number of cleansing iterations to perform - < 1 means go until fully cleansed
setMaxIterations(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Sets the maximum number of cleansing iterations to perform - < 1 means go until fully cleansed
setMaxLabels(int) - Method in class adams.data.conversion.SpreadSheetToWekaInstances: Sets the maximum number of labels a nominal attribute can have.
setMaxLabels(int) - Method in class adams.data.spreadsheet.filter.WekaFilter: Sets the maximum number of labels a nominal attribute can have.
setMaxLeaves(int) - Method in class weka.classifiers.trees.XGBoost: Sets the maximum number of nodes to be added.
setMaxLevels(int) - Method in class weka.classifiers.meta.ClassifierCascade: the maximum number of levels in the cascade.
setMaxManual(double) - Method in class weka.classifiers.meta.MinMaxLimits: Set the manual upper limit.
setMaxNeighbors(int) - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Sets the maximum number of neighbors to find.
setMaxSize(int) - Method in class adams.data.weka.predictions.RelativeNumericErrorScaler: Sets the maximum size for the errors.
setMaxTrainTime(int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Sets the maximum number of seconds to perform training.
setMeasure(WekaClassifierRanker.Measure) - Method in class adams.flow.transformer.WekaClassifierRanker: Sets the measure to use for ranking the classifiers.
setMeasure(Measure) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the measure used for evaluating the fitness.
setMeasure(AbstractWEKAFitnessFunction.Measure) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Sets the measure used for evaluating the fitness.
setMeasuresPrefix(String) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Sets the prefix for the measure attributes.
setMenuItemText(String) - Method in class adams.gui.visualization.instances.instancestable.AbstractPlotSelectedRows: Sets the (optional) custom menu item text.
setMenuItemText(String) - Method in class adams.gui.visualization.instances.instancestable.AbstractProcessSelectedRows: Sets the (optional) custom menu item text.
setMergedIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Sets the position for the merged attribute.
setMergedIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Sets the position for the merged attribute.
setMergeMethod(AbstractMerge) - Method in class adams.flow.transformer.WekaDatasetsMerge: Sets the merge method to use to perform the merge.
setMessage(String) - Method in class adams.flow.transformer.WekaChooseAttributes: Sets the message to display to the user (variables get expanded).
setMetaDataColor(AbstractMetaDataColor) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets the scheme for extracting the color from the meta-data.
setMetaLevelClassifier(Classifier) - Method in class weka.classifiers.meta.PartitionedStacking: Sets the meta-level classifier.
setMethodNamePrediction(String) - Method in class weka.classifiers.functions.PyroProxy: Sets the name of the method to call for predictions.
setMethodNameTrain(String) - Method in class weka.classifiers.functions.PyroProxy: Sets the name of the method to call for training.
setMin(double) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
setMin(double) - Method in class weka.filters.unsupervised.instance.Scale: Sets the minimum for the values.
setMin(int) - Method in class weka.classifiers.trees.RandomRegressionForest: Sets the leaf threshold.
setMinChildWeight(float) - Method in class weka.classifiers.trees.XGBoost: Sets the minimum sum of instance weights (hessian) needed in a child.
setMinClassRangePercentage(double) - Method in class weka.classifiers.meta.MinMaxLimits: Set the percentage of leeway to apply to the lower limit determined by the range of the class attribute in the training data.
setMinHandling(MinMaxLimits.LimitHandling) - Method in class weka.classifiers.meta.MinMaxLimits: Set how the lower limit is handled.
setMinimal(boolean) - Method in class weka.attributeSelection.LinearRegressionAttributeEval: Sets whether to be more memory conservative or being able to output the model as string.
setMinimal(boolean) - Method in class weka.classifiers.functions.LinearRegressionJ: Sets whether to be more memory conservative or being able to output the model as string.
setMinImprovement(double) - Method in class weka.classifiers.meta.ClassifierCascade: the minimum improvement between levels that the statistic must improve.
setMinimum(double) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Sets the minimum.
setMinimum(double) - Method in class adams.data.weka.rowfinder.ByNumericValue: Sets the minimum.
setMinimum(double) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Sets the minimum.
setMinimumIncluded(boolean) - Method in class adams.data.weka.rowfinder.ByNumericValue: Sets whether to exclude the minimum.
setMinimumIncluded(boolean) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange: Sets whether to exclude the minimum.
setMinManual(double) - Method in class weka.classifiers.meta.MinMaxLimits: Set the manual lower limit.
setMinMax(String, double, double) - Method in class adams.opt.optimise.genetic.PackDataDef
setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.M5Base2: Set the minimum number of instances to allow at a leaf node
setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.Rule2: Set the minumum number of instances to allow at a leaf node
setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.RuleNode2: Set the minumum number of instances to allow at a leaf node
setMinProbability(double) - Method in class weka.classifiers.meta.AbstainMinimumProbability: Sets the minimum probability that the chosen class label must meet.
setMinProbability(double) - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Sets the minimum probability for the selected label.
setMinSamples(int) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Sets the minimum number of samples that are required for calculating IQR stats.
setMissing() - Method in class adams.ml.data.DataCellView: Sets the cell to missing.
setMissing(int) - Method in class weka.core.AbstractHashableInstance: Sets a specific value to be "missing".
setMissing(PlaceholderFile) - Method in class adams.tools.CompareDatasets: Sets the first dataset for the comparison.
setMissing(Attribute) - Method in class weka.core.AbstractHashableInstance: Sets a specific value to be "missing".
SetMissingValue - Class in weka.filters.unsupervised.attribute: Attribute values in the given range are set to missing values.
NB: The class attribute is not excluded from this process.
SetMissingValue() - Constructor for class weka.filters.unsupervised.attribute.SetMissingValue
setModel(TableModel) - Method in class adams.gui.visualization.instances.InstancesPanel: Sets the model to use.
setModel(TableModel) - Method in class adams.gui.visualization.instances.InstancesTable: Sets the model to use.
setModel(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Sets the model to make available.
setModelActor(CallableActorReference) - Method in class adams.flow.condition.bool.WekaClassification: Sets the callable actor to obtain the model from if model file is pointing to a directory.
setModelActor(CallableActorReference) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Sets the filter source actor.
setModelActor(CallableActorReference) - Method in class adams.flow.transformer.WekaFilter: Sets the filter source actor.
setModelFile(PlaceholderFile) - Method in class adams.flow.condition.bool.WekaClassification: Sets the file to load the model from.
setModelFile(PlaceholderFile) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Sets the file to load the model from.
setModelFile(PlaceholderFile) - Method in class adams.flow.transformer.WekaFilter: Sets the file to load the model from.
setModelLoadingType(AbstractModelLoader.ModelLoadingType) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Sets the loading type.
setModelLoadingType(AbstractModelLoader.ModelLoadingType) - Method in class adams.flow.transformer.WekaFilter: Sets the loading type.
setModelName(String) - Method in class weka.classifiers.functions.PyroProxy: Sets the name of the model to use.
setModelResetVariable(VariableName) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Sets the variable to monitor for changes in order to reset the model.
setModelStorage(StorageName) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Sets the filter storage item.
setModelStorage(StorageName) - Method in class adams.flow.transformer.WekaFilter: Sets the filter storage item.
setModified(boolean) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Sets whether the data has been modified.
setModified(boolean) - Method in interface adams.gui.tools.wekainvestigator.data.DataContainer: Sets whether the data has been modified.
setModified(boolean) - Method in class adams.gui.tools.wekainvestigator.data.FileContainer: Sets whether the data has been modified.
setModified(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel: Sets the modified state.
setMorphologies(PredictionEccentricity.Morphology[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Sets the morphologies to apply.
setMultiplier(double) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorstStdDev: Sets the multiplier for the stdev.
setN(int) - Method in class weka.core.SAXDistance: Sets the nth point setting.
setN(int) - Method in class weka.filters.supervised.attribute.YGradientEPO: Sets the number of eigenvectors to keep.
setName(String) - Method in class adams.data.weka.classattribute.ByExactName: Sets the name to use.
setName(String) - Method in class adams.data.weka.columnfinder.ByExactName: Sets the name to use.
setName(String) - Method in class adams.ml.data.InstancesView: Sets the name of the spreadsheet.
setNames(BaseString[]) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Sets the names to use for the fusion subsets (corresponds to the subsets).
setNameServer(BaseHostname) - Method in class weka.classifiers.functions.PyroProxy: Sets the address of the Pyro nameserver.
setNameServer(BaseHostname) - Method in interface weka.core.PyroProxyObject: Sets the address of the Pyro nameserver.
setNameSuffix(String) - Method in class adams.gui.tools.wekainvestigator.output.AbstractNestableResultItem: Sets the optional name suffix.
setNative(Object) - Method in class adams.ml.data.DataCellView: Determines the best set-method based on the class of the provided object.
setNearestNeighbourSearchAlgorithm(NearestNeighbourSearch) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Sets the nearestNeighbourSearch algorithm to be used for finding nearest neighbour(s).
setNewFilter(Filter) - Method in class adams.data.conversion.SwapPLS: Sets the new PLS filter to replace with.
setNoAdditionalFieldsPrefix(boolean) - Method in interface adams.data.instances.InstanceGeneratorWithAdditionalFields: Sets whether to drop the prefix for the additional fields.
setNoCheck(boolean) - Method in class adams.flow.transformer.WekaExperiment: Sets whether to avoid the check at setUp time whether the experiment file is present or not.
setNoCleanUp(boolean) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList: Sets whether to suppress automatic clean ups.
setNoise(double) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Set the level of Gaussian Noise.
setNoise(double) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Set the level of Gaussian Noise.
setNoise(double) - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Set the level of Gaussian Noise.
setNoise(double) - Method in class weka.classifiers.functions.GPD: Set the level of Gaussian Noise.
setNominal(boolean) - Method in class weka.filters.unsupervised.attribute.SAX: Sets whether to output nominal or numeric values.
setNonInteractive(boolean) - Method in class adams.flow.source.WekaSelectDataset: Sets whether to enable/disable interactiveness.
setNonInteractive(boolean) - Method in class adams.flow.transformer.WekaChooseAttributes: Sets whether to enable/disable interactiveness.
setNoReplacement(boolean) - Method in class weka.classifiers.meta.VotedImbalance: Sets whether instances are drawn with or with out replacement.
setNormaliseType(XGBoost.NormaliseType) - Method in class weka.classifiers.trees.XGBoost: Sets the type of normalisation algorithm.
setNormalize(boolean) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Sets whether to normalize the data before generating the histogram.
setNormalPlotOptions(NormalPlotOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Set the options for the normal plot.
setNormYWeights(boolean) - Method in class adams.data.instancesanalysis.pls.NIPALS: Sets whether to normalize Y weights.
setNotes(BaseText) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets the notes for the experiment.
setNotificationEnabled(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel: sets whether the notification of changes is enabled
setNoUpdate(boolean) - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Sets whether to suppress updating the nearest-neighbor search algorithm when making predictions.
setNoUpdate(boolean) - Method in class weka.classifiers.lazy.LWLSynchro: Sets whether to suppress updating the nearest-neighbor search algorithm when making predictions.
setNoUpdate(boolean) - Method in class weka.classifiers.lazy.LWLSynchroPrefilter: Sets whether to suppress updating the nearest-neighbor search algorithm when making predictions.
setNoUpdate(boolean) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Sets whether to suppress updating the nearest-neighbor search algorithm when making predictions.
setNthPoint(int) - Method in class weka.filters.unsupervised.attribute.DownSample: Sets the nth point setting.
setNumattrs(int) - Method in class weka.classifiers.meta.Corr
setNumBalanced(int) - Method in class weka.classifiers.meta.VotedImbalance: Set the number of balanced datasets to generated (= #classifiers).
setNumberInSubset(int) - Method in class weka.filters.unsupervised.instance.KennardStone: Sets the number of rws to select in subset.
setNumberOfParallelTrees(int) - Method in class weka.classifiers.trees.XGBoost: Sets the number of parallel trees constructed during each iteration.
setNumberOfRounds(int) - Method in class weka.classifiers.trees.XGBoost: Sets the number of boosting rounds to perform.
setNumBins(int) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Sets the number of bins to use in manual calculation.
setNumChrom(int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Sets the number of chromosomes to use.
setNumClusters(int) - Method in class weka.clusterers.SAXKMeans: set the number of clusters to generate.
setNumCoefficients(int) - Method in class adams.data.instancesanalysis.pls.SIMPLS: Sets the number of coefficients of W matrix to keep (rest gets zeroed).
setNumComponents(int) - Method in class adams.data.instancesanalysis.pls.AbstractPLS: sets the maximum number of attributes to use.
setNumComponents(int) - Method in class weka.attributeSelection.AbstractPLSAttributeEval: sets the maximum number of attributes to use.
setNumComponents(int) - Method in class weka.core.neighboursearch.PLSNNSearch
setNumComponents(Object, int) - Method in class adams.data.conversion.SwapPLS: Sets the number of components in the filter.
setNumCycles(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionEccentricity: Sets the number of cycles to apply.
setNumDecimals(int) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Sets the number of decimals to show in the bin description.
setNumDecimals(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Sets the number of decimals to display.
setNumDecimals(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Sets the number of decimals to use for numeric values.
setNumDecimals(int) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Sets the number of decimals to use for numeric values.
setNumEvaluationBins(int) - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Sets the number of bints to use during evaluation.
setNumExecutionSlots(int) - Method in class weka.classifiers.meta.SubsetEnsemble: Set the number of execution slots (threads) to use for building the members of the ensemble.
setNumExecutionSlots(int) - Method in class weka.classifiers.meta.VotedImbalance: Set the number of execution slots (threads) to use for building the members of the ensemble.
setNumExecutionSlots(int) - Method in class weka.clusterers.SAXKMeans: Set the degree of parallelism to use.
setNumFolds(int) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Sets the number of folds to use.
setNumFolds(int) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Sets the number of folds to use.
setNumFolds(int) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Sets the number of folds to use.
setNumFolds(int) - Method in interface weka.classifiers.CrossValidationFoldGenerator: Sets the number of folds to use.
setNumFolds(int) - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Sets the number of folds to use.
setNumFolds(int) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Sets the number of folds to use.
setNumFolds(int) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Sets the number of folds to use.
setNumFolds(int) - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Sets the number of folds to use.
setNumFolds(int) - Method in class weka.classifiers.meta.ClassifierCascade: the number of folds for cross-validation.
setNumFolds(int) - Method in class weka.filters.supervised.instance.RemoveOutliers: Sets the number of folds to use.
setNumFolds(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Sets the number of cross-validation folds to use - < 2 means no cross-validation.
setNumFolds(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Sets the number of cross-validation folds to use - < 2 means no cross-validation.
setNumIterations(int) - Method in class weka.classifiers.trees.RandomModelTrees: Sets the number of iterations.
setNumIterations(int) - Method in class weka.classifiers.trees.RandomRegressionForest: Sets the number of iterations
setNumPoints(int) - Method in class weka.filters.unsupervised.attribute.AndrewsCurves: Sets the number of points to generate.
setNumPoints(int) - Method in class weka.filters.unsupervised.attribute.EquiDistance: Sets the number of points to use.
setNumPoints(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Sets the number of points to the left of a data point.
setNumPointsLeft(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Sets the number of points to the left of a data point.
setNumPointsRight(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Sets the number of points to the right of a data point.
setNumRandomFeatures(int) - Method in class weka.classifiers.meta.SubsetEnsemble: Set the number of additional random features to use.
setNumRegressions(int) - Method in class weka.classifiers.meta.AbstainLeastMedianSq: sets number of samples
setNumRegressions(int) - Method in class weka.classifiers.meta.LeastMedianSq: sets number of samples
setNumRows(int) - Method in class adams.data.conversion.WekaCapabilitiesToInstances: Sets the number of data rows to generate.
setNumSimplsCoefficients(int) - Method in class adams.data.instancesanalysis.pls.PRM: Sets the number of SIMPLS coefficients to keep.
setNumSubSamples(int) - Method in class adams.flow.transformer.WekaBootstrapping: Sets the number sub-samples to generate.
setNumThreads(int) - Method in class adams.flow.transformer.WekaClassifierRanker: Sets the number of threads to use.
setNumThreads(int) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Sets the number of threads to use for cross-validation.
setNumThreads(int) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Sets the number of threads to use for cross-validation.
setNumThreads(int) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets the number of threads to use for cross-validation (only used if no JobRunnerSetup/JobRunner set).
setNumThreads(int) - Method in class weka.classifiers.meta.ClassifierCascade: the number of threads to use.
setNumThreads(int) - Method in class weka.classifiers.trees.XGBoost: Sets the number of parallel threads used to run XGBoost.
setNumThreads(int) - Method in class weka.filters.supervised.instance.RemoveOutliers: Sets the number of threads to use for cross-validation.
setNumZeroes(double) - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Sets the number of zeroes a row must have at least in order to be removed.
setObject(Object) - Method in class adams.ml.data.DataCellView: Ignored.
setObjective(XGBoost.Objective) - Method in class weka.classifiers.trees.XGBoost: Sets the learning objective.
setOffline(boolean) - Method in class adams.data.instances.AbstractInstanceGenerator: Sets whether to operate in offline mode.
setOldFilter(Filter) - Method in class adams.data.conversion.SwapPLS: Sets the old PLS filter to replace.
setOneDrop(boolean) - Method in class weka.classifiers.trees.XGBoost: Sets whether at least one tree is always dropped during the dropout.
setOneMissing(SelectedTag) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Sets the type of strategy to apply if one of the values is missing.
setOneMissing(SelectedTag) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Sets the type of strategy to apply if one of the values is missing.
setOnlyFirstBatch(boolean) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Set whether to apply row finder during first batch.
setOnTheFly(boolean) - Method in class adams.flow.condition.bool.WekaClassification: Sets whether the model file gets built on the fly and might not be present at start up time.
setOnTheFly(boolean) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Sets whether the model file gets built on the fly and might not be present at start up time.
setOnTheFly(boolean) - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Sets whether the reference file gets built on the fly and might not be present at start up time.
setOperation(WekaInstanceBuffer.Operation) - Method in class adams.flow.transformer.WekaInstanceBuffer: Sets the way the buffer operates.
setOptimizer(Classifier) - Method in class adams.flow.transformer.WekaClassifierOptimizer: Sets the optimizer to use.
setOptional(boolean) - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Sets whether the callable sink is optional.
setOptions(Object, String[]) - Method in class adams.core.option.WekaCommandLineHandler: Sets the options of the specified object.
setOptions(String[]) - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.attributeSelection.LinearRegressionAttributeEval
setOptions(String[]) - Method in class weka.classifiers.functions.ClassificationViaPLS: Parses the options for this object.
setOptions(String[]) - Method in class weka.classifiers.functions.FakeClassifier: Parses the options for this object.
setOptions(String[]) - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.GeneticAlgorithm: Parses the options for this object.
setOptions(String[]) - Method in class weka.classifiers.functions.GPD: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.LinearRegressionJ: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.MathExpressionClassifier: Parses the options for this object.
setOptions(String[]) - Method in class weka.classifiers.functions.PLSClassifierWeighted: Parses the options for this object.
setOptions(String[]) - Method in class weka.classifiers.functions.PLSWeighted: Parses the options for this object.
setOptions(String[]) - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.lazy.LWLSynchro: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.lazy.LWLSynchroPrefilter: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.AbstainAttributePercentile: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.AbstainAverage: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.AbstainingCascade: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.AbstainMinimumProbability: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.AbstainVote: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.ClassifierCascade: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.Consensus: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.ConsensusOrVote: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.Corr: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.Fallback: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.FilteredClassifierExt: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.HighLowSplit: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.InputSmearing: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.LeastMedianSq: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.MinMaxLimits: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.PartitionedStacking: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.SocketFacade: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.SubsetEnsemble: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.SuppressModelOutput: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.Veto: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.meta.VotedImbalance: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.m5.M5Base2: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.M5P2: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.RandomModelTrees: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.RandomRegressionForest: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.SAXKMeans: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.AbstractSimpleOptionHandler: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.core.converters.SimpleArffLoader: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.core.converters.SimpleArffSaver: Parses the options for this object.
setOptions(String[]) - Method in class weka.core.converters.SpreadSheetLoader: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.converters.SpreadSheetSaver: Parses the options for this object.
setOptions(String[]) - Method in class weka.core.neighboursearch.FilteredSearch
setOptions(String[]) - Method in class weka.core.neighboursearch.NewNNSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.PCANNSearch
setOptions(String[]) - Method in class weka.core.neighboursearch.PLSNNSearch
setOptions(String[]) - Method in class weka.core.SAXDistance: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.core.tokenizers.cleaners.AbstractTokenCleaner: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.core.tokenizers.cleaners.MultiCleaner: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.core.tokenizers.cleaners.RemoveNonWordCharTokens: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.core.tokenizers.MultiTokenizer: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.core.tokenizers.PreCleanedTokenizer: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.core.WeightedEuclideanDistanceRidge: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.ResultMatrixMediaWiki: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.filters.FilteredFilter: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.FlowFilter: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.SerializedFilter: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.MultiPLS: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.PLS: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.YGradientEPO: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.YGradientGLSW: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.supervised.instance.RemoveOutliers: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AbstractColumnFinderApplier: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AndrewsCurves: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AnyToString: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.CorrelationMatrix: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Detrend: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.DownSample: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.EquiDistance: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.FastWavelet: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.FFT: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.InputSmearing: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.JoinAttributes: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.LogTransform: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PAA: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SAX: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SetMissingValue: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SimpleDetrend: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SpellChecker: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.StringToDate: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.AlignDataset: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.DatasetLabeler: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.KeepRange: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.KennardStone: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.LatestRecords: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.multirowprocessor.AbstractMultiRowProcessorPlugin: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveDuplicateIDs: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveInstancesWithMissingValue: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveWithWeights: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveWithZeroes: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.SafeRemoveRange: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.Scale: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.Sort: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.SortOnAttribute: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Parses a list of options for this object.
setOtherParameters(BaseKeyValuePair[]) - Method in class weka.classifiers.trees.XGBoost: Sets any additional XGBoost parameters.
setOutput(AbstractWekaRepeatedCrossValidationOutput) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationOutput: Sets the output generator to use.
setOutput(AbstractOutput) - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Sets the prediction output generator to use.
setOutput(AbstractOutput) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets the prediction output generator to use.
setOutputAdditionalStats(boolean) - Method in class weka.attributeSelection.LinearRegressionAttributeEval: Set whether to output additional statistics (such as std.
setOutputAdditionalStats(boolean) - Method in class weka.classifiers.functions.LinearRegressionJ: Set whether to output additional statistics (such as std.
setOutputAdditionalStats(boolean) - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Set whether to output additional statistics (such as std.
setOutputArray(boolean) - Method in class adams.flow.source.AbstractWekaSetupGenerator: Sets whether to output an array or a sequence of classifier setups.
setOutputBestSetup(boolean) - Method in class adams.flow.transformer.WekaClassifierRanker: Sets whether to output the best setup found for optimizers like GridSearch and MultiSearch.
setOutputContainer(boolean) - Method in class adams.flow.transformer.WekaFilter: Sets whether to output a container with the filter alongside the filtered data or just the filtered data.
setOutputDirectory(PlaceholderDirectory) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the directory for the generated ARFF files.
setOutputDirectory(PlaceholderDirectory) - Method in class adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction: Sets the directory for the generated ARFF files.
setOutputDistribution(boolean) - Method in class adams.flow.transformer.wekaclusterer.AddCluster: Sets whether to output the cluster distribution instead of the cluster index.
setOutputFile(PlaceholderFile) - Method in class adams.flow.sink.WekaExperimentGenerator: Sets the file to store the experiment setup in (the extensions determines the type).
setOutputFile(PlaceholderFile) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Set output file.
setOutputFile(PlaceholderFile) - Method in class adams.tools.CompareDatasets: Sets the first dataset for the comparison.
setOutputFormat(ListPackages.OutputFormat) - Method in class adams.flow.source.wekapackagemanageraction.ListPackages: Sets the type of output format to generate.
setOutputFormat(WekaInstanceDumper.OutputFormat) - Method in class adams.flow.transformer.WekaInstanceDumper: Sets the output format.
setOutputFormat(ResultMatrix) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Sets the output format to use for generating the output.
setOutputFormat(ResultMatrix) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Sets the output format to use for generating the output.
setOutputGenerator(AbstractOutputGenerator) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem: Sets the output generator.
setOutputGenerators(AbstractOutputGenerator[]) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Sets the output generators to use.
setOutputGenerators(AbstractOutputGenerator[]) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Sets the output generators to use.
setOutputGenerators(AbstractOutputGenerator[]) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Sets the output generators to use.
setOutputGenerators(AbstractOutputGenerator[]) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Sets the output generators to use.
setOutputGenerators(AbstractOutputGenerator[]) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Sets the output generators to use.
setOutputHeader(boolean) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Sets whether to output the header of the result matrix as well.
setOutputHeader(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Sets whether to output the header of the result matrix as well.
setOutputIndices(boolean) - Method in class adams.flow.transformer.WekaAttributeIterator: Sets whether to output 1-based indices of matches instead of the names.
setOutputInstance(boolean) - Method in class adams.flow.transformer.WekaClassifying: Sets whether to output Instance objects instead of PredictionContainer ones.
setOutputModel(boolean) - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Sets whether to output the clusterer model as well.
setOutputModel(boolean) - Method in class adams.flow.transformer.WekaTrainTestSetClustererEvaluator: Sets whether to output the clusterer model as well.
setOutputName(String) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Sets the name to use for the merged dataset.
setOutputOnlyModel(boolean) - Method in class adams.flow.transformer.AbstractWekaModelReader: Sets whether to output only the model instead of the container.
setOutputPrefix(PlaceholderFile) - Method in class adams.flow.transformer.WekaInstanceDumper: Sets the prefix for the output (path + partial filename).
setOutputPrefixType(OutputPrefixType) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the type of prefix to use for the output.
setOutputRelationName(boolean) - Method in class adams.flow.transformer.WekaEvaluationSummary: Sets whether to output the relation name as well.
setOutputType(WekaFileReader.OutputType) - Method in class adams.flow.transformer.WekaFileReader: Sets how to output the data.
setOutputType(OutputType) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the type of output to generate.
setOverlays(XYSequencePaintlet[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets the overlays to use in the plot.
setOverride(boolean) - Method in class adams.flow.transformer.WekaClassSelector: Sets whether to override any existing class index or nor.
setOverrideJobRunner(boolean) - Method in class adams.flow.transformer.WekaExperimentExecution: Sets whether to override the jobrunner of the experiment.
setOwner(Row) - Method in class adams.ml.data.DataCellView: Sets the row this cell belongs to.
setOwner(SpreadSheet) - Method in class adams.ml.data.InstancesHeaderRow: Sets the spreadsheet this row belongs to.
setOwner(SpreadSheet) - Method in class adams.ml.data.InstanceView: Sets the spreadsheet this row belongs to.
setOwner(InvestigatorPanel) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource: Sets the owner for this source.
setOwner(InvestigatorPanel) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Sets the owner for this tab.
setOwner(InvestigatorPanel) - Method in class adams.gui.tools.wekainvestigator.tab.LogTab: Sets the owner for this tab.
setOwner(AbstractInvestigatorTabWithEditableDataTable) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Sets the owner.
setOwner(PreprocessTab) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Sets the owner.
setOwner(ExperimenterPanel) - Method in class adams.gui.tools.wekamultiexperimenter.AbstractExperimenterPanel: Sets the experimenter this panel belongs to.
setOwner(AbstractSetupPanel) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel: Sets the setup panel this option panel belongs to.
setOwner(AbstractSetupPanel) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel: Sets the setup panel this option panel belongs to.
setOwner(AbstractClassifierBasedGeneticAlgorithm) - Method in class adams.gui.menu.AbstractClassifierBasedGeneticAlgorithmWizard.PerformancePlot: Sets the owner for the plot.
setOwner(T) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Sets the owner.
setOwner(T) - Method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem: Sets the owner.
setPadding(SelectedTag) - Method in class weka.filters.unsupervised.attribute.FastWavelet: Sets the type of Padding to use.
setPaintlet(AbstractInstancePaintlet) - Method in class adams.flow.sink.WekaInstanceViewer: Sets the paintlet to use.
setPaintlet(XYSequencePaintlet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.PredictionTrend: Sets the paintlet to use for the plot.
setPaintlet(XYSequencePaintlet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Sets the paintlet to use.
setPanel(BasePanel) - Method in class weka.gui.explorer.ExplorerEntryPanel: Sets the panel to display the results in.
setParameters(AbstractParameter[]) - Method in class adams.flow.source.AbstractWekaSetupGenerator: Sets the setup parameters.
setParentComponentActor(CallableActorReference) - Method in class adams.flow.source.WekaSelectDataset: Sets the (optional) callable actor to use as parent component instead of the flow panel.
setParentTitle(String) - Method in class weka.gui.explorer.ExplorerExt: Sets the new title for the parent.
setPassword(BasePassword) - Method in class adams.flow.sink.WekaDatabaseWriter: Sets the database password.
setPassword(BasePassword) - Method in class adams.flow.source.WekaDatabaseReader: Sets the database password.
setPct(int) - Method in class weka.classifiers.meta.AbstainLeastMedianSq
setPct(int) - Method in class weka.classifiers.meta.LeastMedianSq
setPercent(double) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.RemoveWorst: Sets the percentage to remove.
setPercentage(double) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Sets the split percentage.
setPercentage(double) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Sets the split percentage.
setPercentage(double) - Method in class adams.flow.transformer.WekaBootstrapping: Sets the percentage (0-1).
setPercentage(double) - Method in class adams.flow.transformer.WekaRandomSplit: Sets the percentage (0-1).
setPercentage(double) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: Sets the split percentage.
setPercentage(double) - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Sets the split percentage.
setPercentage(double) - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Sets the split percentage.
setPercentage(double) - Method in class weka.classifiers.DefaultRandomSplitGenerator: Sets the split percentage.
setPercentage(double) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Sets the split percentage.
setPercentage(double) - Method in class weka.classifiers.GroupedRandomSplitGenerator: Sets the split percentage.
setPercentage(double) - Method in interface weka.classifiers.RandomSplitGenerator: Sets the split percentage.
setPercentile(double) - Method in class weka.classifiers.meta.AbstainAttributePercentile
setPercentiles(BaseDouble[]) - Method in class adams.flow.transformer.WekaBootstrapping: Sets the percentiles to calculate for the errors.
setPerformTraining(boolean) - Method in class weka.classifiers.functions.PyroProxy: Sets whether to train the model as well.
setPlotName(String) - Method in class adams.flow.transformer.WekaAccumulatedError: Sets the plot name.
setPLS(int) - Method in class weka.classifiers.trees.RandomRegressionForest: Sets the number of PLS components to generate.
setPolynomialOrder(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay: Sets the polynomial order.
setPolynomialOrder(int) - Method in class weka.filters.unsupervised.attribute.SavitzkyGolay2: Sets the polynomial order.
setPostProcessor(AbstractClustererPostProcessor) - Method in class adams.flow.transformer.WekaClustererPostProcessor: Sets the post-processor to use.
setPostProcessor(AbstractClustererPostProcessor) - Method in class adams.flow.transformer.WekaTrainClusterer: Sets the post-processor to use.
setPostProcessor(AbstractWekaEvaluationPostProcessor) - Method in class adams.flow.transformer.WekaEvaluationPostProcessor: Sets the post-processor to use.
setPostProcessors(AbstractClustererPostProcessor[]) - Method in class adams.flow.transformer.wekaclusterer.MultiClustererPostProcessor: Sets the distance function to use.
setPostProcessors(AbstractWekaEvaluationPostProcessor[]) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.MultiPostProcessor: Sets the post-processors to use.
setPostTokenizer(Tokenizer) - Method in class weka.core.tokenizers.PreCleanedTokenizer: Sets the tokenizer to use for the final tokenization (after cleaning).
setPredicted(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Sets the column with the predicted values.
setPredicted(SpreadSheetColumnIndex) - Method in class weka.classifiers.functions.FromPredictions: Sets the column with the predicted values.
setPredictedMax(double) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets the upper limit in use for the predicted values.
setPredictedMin(double) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets the lower limit in use for the predicted values.
setPredictionsFile(PlaceholderFile) - Method in class weka.classifiers.functions.FromPredictions: Sets the file with the predictions.
setPredictionType(PredictionType) - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Sets the type of prediction to perform.
setPredictMax(double) - Method in class weka.classifiers.functions.FakeClassifier: Sets the maximum value to predict.
setPredictMin(double) - Method in class weka.classifiers.functions.FakeClassifier: Sets the minimum value to predict.
setPredictor(Index) - Method in class weka.classifiers.meta.Consensus: Sets the index of the classifier for making the actual predictions.
setPredictor(XGBoost.Predictor) - Method in class weka.classifiers.trees.XGBoost: Sets the type of predictor algorithm to use.
setPredictWait(int) - Method in class weka.classifiers.functions.FakeClassifier: Sets the time in msec to wait when calling classifyInstance.
setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaFilter: Sets whether to offload processing to a JobRunner instance if available.
setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaTestSetEvaluator: Sets whether to offload processing to a JobRunner instance if available.
setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaTrainAssociator: Sets whether to offload processing to a JobRunner instance if available.
setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaTrainClassifier: Sets whether to offload processing to a JobRunner instance if available.
setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaTrainClusterer: Sets whether to offload processing to a JobRunner instance if available.
setPreferJobRunner(boolean) - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator: Sets whether to offload processing to a JobRunner instance if available.
setPreFilter(Filter) - Method in class adams.data.weka.rowfinder.FilteredIQR: Sets the pre filter.
setPreFilter(Filter) - Method in class weka.filters.FilteredFilter: Sets the pre-filter to use.
setPreFilter(Filter) - Method in class weka.filters.unsupervised.instance.KennardStone: Sets the pre-filter to apply to the data to perform the search on.
setPrefix(String) - Method in class adams.flow.transformer.WekaInstancesMerge: Sets the optional prefix string.
setPrefix(String) - Method in class weka.filters.unsupervised.attribute.EquiDistance: Sets the prefix for the new attributes.
setPrefixDatasetsWithIndex(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets whether to prefix the datasets with the index.
setPrefixDatasetsWithIndex(boolean) - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ExperimentWithCustomizableRelationNames: Sets whether to prefix the datasets with the index.
setPrefixDatasetsWithIndex(boolean) - Method in class weka.experiment.ExtExperiment: Sets whether to prefix the datasets with the index.
setPrefixes(BaseString[]) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Sets the list of prefixes to use.
setPrefixes(BaseString[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Sets the list of prefixes to use.
setPrefixSeparator(String) - Method in class adams.flow.transformer.WekaInstancesMerge: Sets the prefix separator string.
setPreparation(AbstractDataPreparation) - Method in class weka.classifiers.meta.SocketFacade: Sets the data preparation scheme to use.
setPreprocessing(SelectedTag) - Method in class weka.core.neighboursearch.PCANNSearch: Sets the type of preprocessing to use
setPreprocessing(SelectedTag) - Method in class weka.core.neighboursearch.PLSNNSearch: Sets the type of preprocessing to use
setPreprocessingType(PreprocessingType) - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Sets the type of preprocessing to perform.
setPreprocessingType(PreprocessingType) - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Sets the type of preprocessing to perform.
setPreSelection(BaseRegExp) - Method in class adams.flow.transformer.WekaChooseAttributes: Sets the regular expression to pre-select attributes for the dialog.
setPreserveIDColumn(boolean) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Sets whether the first non-summary attribute should be treated as an ID and moved to the first attribute position.
setPreserveInstancesOrder(boolean) - Method in class weka.clusterers.SAXKMeans: Sets whether order of instances must be preserved.
setPreserveOrder(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Sets whether to preserve the order.
setPreserveOrder(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Sets whether to preserve the order.
setPreserveOrder(boolean) - Method in class adams.flow.transformer.WekaRandomSplit: Sets whether to preserve order and suppress randomization.
setPreserveOrder(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment: Sets whether to preserve the order.
setPreserveOrder(boolean) - Method in class weka.classifiers.BestBinnedNumericClassRandomSplitGenerator: Sets whether to preserve the order.
setPreserveOrder(boolean) - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Sets whether to preserve the order.
setPreserveOrder(boolean) - Method in class weka.classifiers.DefaultRandomSplitGenerator: Sets whether to preserve the order.
setPreserveOrder(boolean) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Sets whether to preserve the order.
setPreserveOrder(boolean) - Method in class weka.classifiers.GroupedRandomSplitGenerator: Sets whether to preserve the order.
setPreserveOrder(boolean) - Method in interface weka.classifiers.RandomSplitGenerator: Sets whether to preserve the order.
setPreTokenizer(Tokenizer) - Method in class weka.core.tokenizers.PreCleanedTokenizer: Sets the tokenizer to use for the initial tokenization (before cleaning).
setProcessor(AbstractClassifierSetupProcessor) - Method in class adams.flow.transformer.WekaClassifierSetupProcessor: Sets the processor the incoming classifier arrays.
setProcessType(XGBoost.ProcessType) - Method in class weka.classifiers.trees.XGBoost: Sets the type of boosting process to run.
setProperties(Properties) - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: Sets the properties to base the properties on.
setProperties(Properties) - Method in class adams.gui.wizard.WekaSelectDatasetPage: Sets the content of the page (ie parameters) as properties.
setProperties(Properties) - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: Sets the content of the page (ie parameters) as properties.
setProperty(String) - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Sets the property to manage.
setProperty(String) - Method in class adams.core.discovery.genetic.GenericFloatResolution: Sets the property to manage.
setProperty(String) - Method in class adams.core.discovery.genetic.GenericInteger: Sets the property to manage.
setProperty(String) - Method in class adams.core.discovery.genetic.GenericString: Sets the property to manage.
setQuery(SQLStatement) - Method in class adams.flow.source.WekaDatabaseReader: Sets the query to execute.
setRandomize(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Sets whether to randomize the data.
setRandomize(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Sets whether to randomize the data.
setRandomize(boolean) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Sets whether to randomize the data.
setRandomize(boolean) - Method in interface weka.classifiers.CrossValidationFoldGenerator: Sets whether to randomize the data.
setRandomize(boolean) - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Sets whether to randomize the data.
setRandomize(boolean) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Sets whether to randomize the data.
setRandomize(boolean) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Sets whether to randomize the data.
setRandomize(boolean) - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Sets whether to randomize the data.
setRandomize(boolean) - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Sets whether to randomize the data.
setRandomize(boolean) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Sets whether to include the class attribute in the comparison.
setRandomSeed(long) - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Set the seed for the random number generator
setRandomSeed(long) - Method in class weka.classifiers.meta.LeastMedianSq: Set the seed for the random number generator
setRange(Range) - Method in class adams.flow.transformer.WekaAttributeIterator: Sets the range of attributes to operate on.
setRange(Range) - Method in class weka.filters.unsupervised.attribute.EquiDistance: Sets the attribute range.
setRange(WekaAttributeRange) - Method in class adams.flow.sink.WekaAttributeSummary: Sets the ranges of attributes to visualize.
setRange(WekaAttributeRange) - Method in class weka.filters.unsupervised.attribute.AnyToString: Sets the attribute range to use.
setRange(WekaAttributeRange) - Method in class weka.filters.unsupervised.attribute.StringToDate: Sets the first attribute range to use (regular expression on attribute names).
setRange(WekaAttributeRange) - Method in class weka.filters.unsupervised.instance.multirowprocessor.processor.AbstractRangeBasedSelectionProcessor: Sets the attribute range to work on.
setRange(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetIndexer: Sets the range of attributes to use.
setRange1(Range) - Method in class adams.tools.CompareDatasets: Sets the range of attributes of the first dataset.
setRange2(Range) - Method in class adams.tools.CompareDatasets: Sets the range of attributes of the second dataset.
setRangePaintlet(AbstractErrorPaintlet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Sets the paintlet to use for the lower/upper statistics.
setRanges(BaseInterval[]) - Method in class adams.data.weka.rowfinder.ByNumericRange: Sets the intervals.
setRanges(BaseInterval[]) - Method in class adams.flow.transformer.wekaevaluationpostprocessor.SubRange: Sets the ranges to include.
setRanges(BaseInterval[]) - Method in class weka.filters.unsupervised.attribute.detrend.RangeBased: Sets the wave number ranges.
setRanges(BaseInterval[]) - Method in class weka.filters.unsupervised.attribute.multiplicativescattercorrection.RangeBased: Sets the wave number ranges.
setRanges(Range[]) - Method in class weka.classifiers.meta.PartitionedStacking: Sets the attribute ranges for the base-classifiers.
setRanges(Range[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Sets the list of possible Ranges to choose from.
setRateDrop(float) - Method in class weka.classifiers.trees.XGBoost: Sets the dropout rate (a fraction of previous trees to drop during the dropout).
setReader(SpreadSheetReader) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Sets the spreadsheet reader to use.
setReader(SpreadSheetReader) - Method in class weka.classifiers.functions.FromPredictions: Sets the spreadsheet reader to use.
setReader(SpreadSheetReader) - Method in class weka.core.converters.SpreadSheetLoader: Sets the spreadsheet reader to use.
setReadOnly(boolean) - Method in class adams.gui.visualization.instances.InstancesTable: sets whether the model is read-only
setReadOnly(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel: sets whether the model is read-only
setReal(boolean) - Method in class weka.filters.unsupervised.attribute.FFT: Sets whether to return real or imaginary part.
setReduceNumberOfDistanceCalcsViaCanopies(boolean) - Method in class weka.clusterers.SAXKMeans: Set whether to use canopies to reduce the number of distance computations required
setReferenceActor(CallableActorReference) - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Sets the callable actor to obtain the reference dataset from if reference file is pointing to a directory.
setReferenceDataset(File) - Method in class weka.filters.unsupervised.instance.AlignDataset: Sets the file containing the reference dataset.
setReferenceError(double) - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference: Sets the absolute value of the reference error.
setReferenceFile(PlaceholderFile) - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Sets the file to load the reference dataset from.
setReferenceSize(int) - Method in class adams.data.weka.predictions.NumericErrorScalerWithReference: Sets the size for the reference error.
setRegex(String) - Method in class adams.flow.transformer.WekaRegexToRange: Sets the regular expression for attribute matching.
setRegexName(BaseRegExp) - Method in class adams.flow.transformer.WekaClassSelector: Sets the regular expression for selecting the attributes.
setRegExp(BaseRegExp) - Method in class adams.data.weka.classattribute.ByName: Sets the index of the attribute to select.
setRegExp(BaseRegExp) - Method in class adams.data.weka.columnfinder.ByName: Sets the regular expression to use.
setRegExp(BaseRegExp) - Method in class adams.data.weka.rowfinder.ByLabel: Sets the regular expression to use.
setRegExp(BaseRegExp) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
setRegExp(BaseRegExp) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
setRegExp(BaseRegExp) - Method in class adams.flow.transformer.WekaAttributeIterator: Sets the regular expression for the names.
setRegExp(BaseRegExp) - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Sets the regular expression to match the strings against.
setRegExp(BaseRegExp) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
setRegExp(BaseRegExp) - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
setRegExp(BaseRegExp) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
setRegExp(BaseRegExp) - Method in class weka.classifiers.GroupedRandomSplitGenerator: Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
setRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.EquiDistance: Sets the regular expression for identifying attributes.
setRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.instance.multirowprocessor.selection.GroupExpression: Sets the regular expression for identifying the group (eg '^(.*)-([0-9]+)-(.*)$').
setRegExp(BaseRegExp[]) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Sets the list of possible regular expressions.
setRegExps(BaseRegExp[]) - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Sets the regular expression to apply to the attribute names for identifying the fusion subsets (incl class).
setRegExps(BaseRegExp[]) - Method in class weka.classifiers.MultiLevelSplitGenerator: Sets the regular expressions to use for extracting the groups.
setRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.Rule2: Set the value of regressionTree.
setRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.RuleNode2: Set the value of regressionTree.
setRelationName(String) - Method in class adams.flow.source.WekaNewInstances: Sets the name of the relation.
setRelationName(String) - Method in class adams.flow.transformer.WekaCrossValidationSplit: Sets the pattern to use for renaming the relation.
setRelationName(String) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Sets the template for the relation name.
setRelationName(String) - Method in interface weka.classifiers.CrossValidationFoldGenerator: Sets the template for the relation name.
setRelationName(String) - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Sets the template for the relation name.
setRelationName(String) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Sets the template for the relation name.
setRelationName(String) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Sets the template for the relation name.
setRelationName(String) - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Sets the template for the relation name.
setRelationName(String) - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Sets the template for the relation name.
setRelationNameHeuristic(AbstractRelationNameHeuristic) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Sets the relation name heuristic.
setRelativeWidths(boolean) - Method in class adams.data.weka.evaluator.IntervalEstimatorBased: Sets whether to divide the calculated widths by the class value.
setRemote(BaseHostname) - Method in class weka.classifiers.meta.SocketFacade: Sets address of the remote process.
setRemoteObjectName(String) - Method in class weka.classifiers.functions.PyroProxy: Sets the name of the remote object to use.
setRemoteObjectName(String) - Method in interface weka.core.PyroProxyObject: Sets the name of the remote object to use.
setRemove(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge: Sets whether to remove if not all present
setRemoveAttributeIndices(String) - Method in class weka.classifiers.meta.FilteredClassifierExt: Sets the attribute indices to remove before applying the actual filter.
setRemoveChars(String) - Method in class weka.filters.unsupervised.attribute.MergeManyAttributes: Sets the characters to remove from start/end of the generated name.
setRemoveChars(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Sets the characters to remove from start/end of the generated name.
setRemoveTrain(boolean) - Method in class weka.classifiers.meta.AbstainAttributePercentile
setRemoveUnused(boolean) - Method in class weka.filters.unsupervised.attribute.MetaPartitionedMultiFilter: Sets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.
setRemoveUnused(boolean) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: Sets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.
setReplace(String) - Method in class adams.flow.transformer.WekaRenameRelation: Sets the replacement string.
setReplace(String) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Sets the expression to use for assembling the numeric part.
setReplaceMissing(boolean) - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Sets whether to replace missing values.
setReplaceMissing(boolean) - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Sets whether to replace missing values.
setReport(Report) - Method in class adams.data.instance.Instance: Sets a new report.
setResetResults(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets whether to clear the results before starting the experiment.
setResetResults(boolean) - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ResettableExperiment: Sets whether to clear the results before starting the experiment.
setResultFile(PlaceholderFile) - Method in class adams.flow.sink.WekaExperimentGenerator: Sets the file to store the experimental results in.
setResultFormat(WekaExperimentGenerator.ResultFormat) - Method in class adams.flow.sink.WekaExperimentGenerator: Sets the data format the results are stored in.
setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.AbstractOutputPanel: Sets the ResultListener.
setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.ArffOutputPanel: Sets the ResultListener.
setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CsvOutputPanel: Sets the ResultListener.
setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.CustomOutputPanel: Sets the ResultListener.
setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel: Sets the ResultListener.
setResultListener(ResultListener) - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.OutputPanel: Sets the ResultListener.
setResultMatrix(ResultMatrix) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Sets the matrix to use.
setResults(Instances) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel: Sets the results to analyze.
setResults(Instances) - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel: Sets the results to use for analysis.
setResultsHandler(AbstractResultsHandler) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets the results handler to use.
setRetainStringValues(boolean) - Method in class weka.core.converters.AArffLoader.AArffReader: Sets whether to retain string values (safe) or not.
setReverse(boolean) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Sets whether to reverse the sorting.
setReverse(boolean) - Method in class weka.classifiers.AggregateEvaluations: Sets whether to reverse the sorting.
setRidge(double) - Method in class adams.data.baseline.AbstractLinearRegressionBased: Sets the ridge parameter.
setRidge(double) - Method in class weka.attributeSelection.LinearRegressionAttributeEval: Set the value of Ridge.
setRidge(double) - Method in class weka.classifiers.functions.LinearRegressionJ: Set the value of Ridge.
setRidge(double) - Method in class weka.classifiers.trees.RandomModelTrees
setRidge(double) - Method in class weka.core.WeightedEuclideanDistanceRidge: Set the value of Ridge.
setRow(BaseString[]) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Sets the list of fields that identify a row.
setRow(BaseString[]) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Sets the list of fields that identify a row.
setRow(Index) - Method in class adams.flow.transformer.WekaGetInstancesValue: Sets the 1-based index of the row.
setRow(Index) - Method in class adams.flow.transformer.WekaSetInstancesValue: Sets the 1-based index of the row.
setRowAttribute1(String) - Method in class adams.tools.CompareDatasets: Sets the index of the attribute used for identifying rows to compare against each other (first dataset).
setRowAttribute2(String) - Method in class adams.tools.CompareDatasets: Sets the index of the attribute used for identifying rows to compare against each other (second dataset).
setRowFinder(RowFinder) - Method in class adams.data.weka.columnfinder.RowFilteredColumnFinder: Sets the row finder to use.
setRowFinder(RowFinder) - Method in class adams.data.weka.datasetsplitter.RowSplitter: Sets the row-finder to use to select rows for the first dataset.
setRowFinder(RowFinder) - Method in class adams.data.weka.rowfinder.AbstractFilteredRowFinder: Sets the row finder to use.
setRowFinder(RowFinder) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Sets the training data row selector.
setRowFinder(RowFinder) - Method in class weka.filters.unsupervised.instance.AbstractRowFinderApplier: Sets the row finder to use.
setRowFinder(RowFinder) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Sets the row finder scheme.
setRowFinderEnabled(boolean) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Sets the whether to use the row finder.
setRowIndex(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Sets the index of the attribute to use for matching rows (only works if dataset already loaded).
setRowRange(String) - Method in class weka.filters.unsupervised.instance.KeepRange: Sets the unordered range of rows to keep.
setRows(int) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Sets the size of array.
setRows(int) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
setRows(BaseInteger[]) - Method in class adams.data.weka.rowfinder.Constant: Sets the constant set of rows to find.
setRowSelection(AbstractRowSelection) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Sets the row selection scheme to use.
setRunInformation(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics: Sets whether the run information is output as well.
setRunInformation(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics: Sets whether the run information is output as well.
setRunInformation(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics: Sets whether the run information is output as well.
setRunInformation(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Sets whether the run information is output as well.
setRuns(int) - Method in class adams.flow.sink.WekaExperimentGenerator: Sets the number of runs to perform.
setRuns(int) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Sets the number of runs to perform.
setRuns(int) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets the number of runs.
setSampleSize(int) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Sets the sample size to use.
setSampleType(XGBoost.SampleType) - Method in class weka.classifiers.trees.XGBoost: Sets the type of sampling algorithm.
setSaveInstances(boolean) - Method in class weka.classifiers.trees.m5.Rule2: Sets whether instances at each node in an M5 tree should be saved for visualization purposes.
setSaveInstances(boolean) - Method in class weka.classifiers.trees.m5.RuleNode2: Set whether to save instances for visualization purposes.
setSaveInstances(boolean) - Method in class weka.classifiers.trees.M5P2: Set whether to save instance data at each node in the tree for visualization purposes
setScale(double) - Method in class weka.filters.unsupervised.attribute.NormalizeAdaptive
setScalePositiveWeights(float) - Method in class weka.classifiers.trees.XGBoost: Sets the positive-weights scale factor.
setScaler(AbstractErrorScaler) - Method in class adams.data.weka.predictions.AutoScaler: Sets the scaler to use for numeric data.
setSearch(ASSearch) - Method in class adams.flow.transformer.WekaAttributeSelection: Sets the evaluation method to use.
setSearch(NearestNeighbourSearch) - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Sets the search algorithm.
setSearchAlgorithm(NearestNeighbourSearch) - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Sets the nearestNeighbourSearch algorithm to be used for finding nearest neighbour(s).
setSecondAttribute(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoAttributes: Sets the name of the second attribute.
setSecondAttributeRange(String) - Method in class adams.gui.InstanceCompare: Sets the second attribute range ('second' and 'last' can be used as well).
setSecondAttributeRange(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel: Sets the second attribute range ('second' and 'last' can be used as well).
setSecondCrossValidationSeed(int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Sets the seed value to use for cross-validation (second evaluation).
setSecondDataset(PlaceholderFile) - Method in class adams.gui.InstanceCompare: Sets the second dataset.
setSecondDataset(File) - Method in class adams.gui.visualization.instance.InstanceComparePanel: Sets the second dataset.
setSecondFolds(int) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Sets the number of folds to use in cross-validation (second evaluation).
setSecondNewFitness(double, Object, int, int[]) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Sets a fitness and keep it if better (second evaluation).
setSecondRange(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.OuterProductAnalysis: Sets the prefix to use for the generated attributes.
setSecondRowIndex(String) - Method in class adams.gui.InstanceCompare: Sets the second row index ('second' and 'last' can be used as well).
setSecondRowIndex(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel: Sets the second row index ('second' and 'last' can be used as well).
setSeed(int) - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator: Sets the seed value for cross-validation.
setSeed(int) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Sets the seed value to use, resets the random number generator.
setSeed(int) - Method in class weka.classifiers.functions.FakeClassifier: Sets the seed value for the random values.
setSeed(int) - Method in class weka.classifiers.trees.XGBoost: Sets the random number seed.
setSeed(int) - Method in class weka.filters.supervised.instance.RemoveOutliers: Sets the seed value.
setSeed(int) - Method in class weka.filters.unsupervised.attribute.InputSmearing: Set the seed for random number generation.
setSeed(int) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Set the seed for random number generation.
setSeed(int) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Set the seed for random number generation.
setSeed(long) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Sets the seed value.
setSeed(long) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Sets the seed value.
setSeed(long) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedRandomSplitGenerator: Sets the seed value.
setSeed(long) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesRandomSplitGenerator: Sets the seed value.
setSeed(long) - Method in class adams.flow.transformer.WekaAttributeSelection: Sets the seed value.
setSeed(long) - Method in class adams.flow.transformer.WekaBootstrapping: Sets the seed value.
setSeed(long) - Method in class adams.flow.transformer.WekaClassifierRanker: Sets the seed value.
setSeed(long) - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator: Sets the seed value.
setSeed(long) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Sets the seed value.
setSeed(long) - Method in class adams.flow.transformer.WekaCrossValidationSplit: Sets the seed value.
setSeed(long) - Method in class adams.flow.transformer.WekaRandomSplit: Sets the seed value.
setSeed(long) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets the seed value.
setSeed(long) - Method in class weka.classifiers.AbstractSplitGenerator: Sets the seed value.
setSelectionProcessor(AbstractSelectionProcessor) - Method in class weka.filters.unsupervised.instance.MultiRowProcessor: Sets the selection processor scheme to use.
setSeparateFolds(boolean) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets whether to separate the folds, an Evaluation object per fold.
setSerialized(PlaceholderFile) - Method in class weka.filters.SerializedFilter: Sets the serialized filter file.
setSetup(String) - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Sets the property in the incoming properties that contains the commandline of the genetic algorithm.
setSetup(Classifier) - Method in class adams.flow.source.WekaClassifierGenerator: Sets the base classifier.
setSetup(Clusterer) - Method in class adams.flow.source.WekaClustererGenerator: Sets the base clusterer.
setSetup(Filter) - Method in class adams.flow.source.WekaFilterGenerator: Sets the base clusterer.
setSetupUpload(AbstractSetupUpload) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the scheme for uploading the currently best job setup.
setShowAboutBox(boolean) - Method in class adams.gui.wizard.WekaPropertySheetPanelPage.CustomPropertySheetPanel: Sets whether to show the about box or not.
setShowAttributeIndex(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel: Sets whether to display the attribute index in the header.
setShowAttributeWeights(boolean) - Method in class adams.gui.visualization.instances.InstancesTable: Sets whether to display attribute weights.
setShowAttributeWeights(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel: Sets whether to display attribute weights.
setShowDistribution(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Sets whether to show the class distribution as well.
setShowDistribution(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Sets whether to show the class distribution as well.
setShowError(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Sets whether to show the error as well.
setShowError(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Sets whether to show the error as well.
setShowProbability(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Sets whether to show the probability of the prediction as well.
setShowProbability(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Sets whether to show the probability of the prediction as well.
setShowWeight(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Sets whether to show the weight as well.
setShowWeight(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Sets whether to show the weight as well.
setShowWeightsColumn(boolean) - Method in class adams.gui.visualization.instances.InstancesTable: Sets whether to display a weights column.
setShowWeightsColumn(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel: Sets whether to display a weights column.
setShowZeroInstancesAsUnknown(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.InstancesSummaryPanel: Set whether to show zero instances as unknown (i.e.
setSidePanelVisible(boolean) - Method in class adams.gui.visualization.instance.InstanceExplorer: Whether to display the side panel or not.
setSignificance(double) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Sets the significance level (0-1).
setSignificance(double) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Sets the significance level (0-1).
setSilent(boolean) - Method in class weka.classifiers.MultiLevelSplitGenerator: Sets whether to suppress error messages.
setSimpleAttributeNames(boolean) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Set whether to just number the attributes rather than compiling names.
setSize(int) - Method in class adams.data.weka.predictions.FixedSizeErrorScaler: Sets the size for the errors.
setSizeLimit(double) - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Sets the size limit for the final dataset.
setSkipBuild(boolean) - Method in class adams.flow.transformer.WekaTrainClassifier: Sets whether to skip the buildClassifier call for incremental classifiers.
setSkipDrop(float) - Method in class weka.classifiers.trees.XGBoost: Sets the probability of skipping the dropout procedure during a boosting iteration.
setSkipHistory(boolean) - Method in class weka.gui.explorer.AbstractExplorerPanelHandler: Sets whether to skip history panels.
setSkipIdentical(boolean) - Method in class weka.core.neighboursearch.NewNNSearch: Sets the property to skip identical instances (with distance zero from the target) from the set of neighbours returned.
setSkipNominal(boolean) - Method in class adams.data.instancesanalysis.PCA: Sets whether to skip NOMINAL attributes from the PCA process by turning them into STRING attributes.
setSkipTrain(boolean) - Method in class weka.classifiers.meta.SocketFacade: Sets whether to skip training, eg when using a pre-built model.
setSmoothing(boolean) - Method in class weka.classifiers.trees.m5.Rule2: Smooth predictions
setSortAttributeNames(boolean) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Sets whether to sort the attribute names.
setSortAttributes(boolean) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTable: Sets whether to sort the attributes alphabetically for the dropdown list.
setSortAttributes(boolean) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableWithButtons: Sets whether to sort the attributes alphabetically for the dropdown list.
setSortLabels(boolean) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Sets whether to sort the labels with the specified comparator.
setSortLabels(boolean) - Method in class weka.classifiers.AggregateEvaluations: Sets whether to sort the labels with the specified comparator.
setSource(File) - Method in class weka.core.converters.SimpleArffLoader: Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(File) - Method in class weka.core.converters.SpreadSheetLoader: Resets the Loader object and sets the source of the data set to be the supplied File object.
setSourceCodeClass(String) - Method in class adams.flow.transformer.WekaClassifierInfo: Sets the class name for the generated source code.
setSparseFormat(boolean) - Method in class adams.flow.source.WekaDatabaseReader: Sets whether to output the data in sparse format.
setSplitPercentage(double) - Method in class adams.flow.sink.WekaExperimentGenerator: Sets the split percentage (only train/test splits).
setSplitpoint(double) - Method in class weka.classifiers.meta.HighLowSplit
setSplitpoint(double) - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier
setSplits(int) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Sets the splits.
setSplits(int) - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
setSplitter(AbstractSplitter) - Method in class adams.flow.transformer.WekaDatasetSplit: Sets the splitter to use.
setSpreadSheetType(SpreadSheet) - Method in class adams.data.conversion.WekaInstancesToSpreadSheet: Sets the type of spreadsheet to use.
setSpreadSheetWriter(SpreadSheetWriter) - Method in class weka.core.converters.SpreadSheetSaver: Sets the spreadsheet writer to use.
setStatement(SQLStatement) - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Sets the SQL statement.
setStatistic(AbstractArrayStatistic) - Method in class adams.flow.transformer.WekaInstancesStatistic: Sets the statistic to use.
setStatistic(EvaluationStatistic) - Method in class weka.classifiers.meta.ClassifierCascade: the statistic to use for termination.
setStatistic(CenterStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Sets the statistic to output.
setStatistic(CenterStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Sets the statistic to output.
setStatistic(CenterStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Sets the statistic to output.
setStatistic(CenterStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Sets the statistic to output.
setStatistics(EvaluationStatistic[]) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Sets the statistics to output.
setStatistics(EvaluationStatistic[]) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Sets the statistics to output.
setStatisticValue(EvaluationStatistic) - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Sets the value to extract.
setStatisticValues(EvaluationStatistic[]) - Method in class adams.flow.transformer.WekaBootstrapping: Sets the values to extract.
setStatisticValues(EvaluationStatistic[]) - Method in class adams.flow.transformer.WekaEvaluationValues: Sets the values to extract.
setStatusMessageHandler(StatusMessageHandler) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets the status message handler to use.
setStatusMessageHandler(StatusMessageHandler) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets the status message handler for outputting notifications.
setStdDev(double) - Method in class weka.classifiers.meta.InputSmearing: Sets the multiplier for the standard deviation to use for input smearing.
setStdDev(double) - Method in class weka.filters.unsupervised.attribute.InputSmearing: Sets the multiplier for the standard deviation to use for input smearing.
setStopFlowIfCanceled(boolean) - Method in class adams.flow.source.WekaSelectDataset: Sets whether to stop the flow if dialog canceled.
setStopMode(StopMode) - Method in class adams.flow.source.WekaSelectDataset: Sets the stop mode.
setStorage(StorageName) - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Sets the data storage item.
setStorageName(StorageName) - Method in class adams.data.conversion.MapToWekaInstance: Sets the name of the stored Instances object to use as template.
setStorageName(StorageName) - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Sets the name for the data in the internal storage.
setStoreFilename(boolean) - Method in class adams.flow.transformer.WekaTextDirectoryReader: Sets whether to store the filename in extra attribute.
setStratify(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Sets whether to stratify the data (nominal class).
setStratify(boolean) - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Sets whether to stratify the data (nominal class).
setStratify(boolean) - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Sets whether to stratify the data (nominal class).
setStratify(boolean) - Method in interface weka.classifiers.CrossValidationFoldGenerator: Sets whether to stratify the data (nominal class).
setStratify(boolean) - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Sets whether to stratify the data (nominal class).
setStratify(boolean) - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Sets whether to stratify the data (nominal class).
setStratify(boolean) - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Sets whether to stratify the data (nominal class).
setStratify(boolean) - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Sets whether to stratify the data (nominal class).
setStrict(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge: Sets whether to enforce uniqueness in IDs.
setSubsampleRatio(float) - Method in class weka.classifiers.trees.XGBoost: Sets the sub-sample ratio of the training instances.
setSummaryFilter(Filter) - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Sets the filter to use to summarise the attributes.
setSuppliedPrefix(String) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the prefix to use in case of OutputPrefixType.SUPPLIED.
setSuppliedReferenceDataset(Instances) - Method in class weka.filters.unsupervised.instance.AlignDataset: Sets the reference dataset to use instead of loading one from disk.
setSuppliedTestSet(Instances) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Sets the test set to use instead of loading one from disk.
setSupport(double) - Method in class weka.classifiers.meta.ConsensusOrVote: Sets the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.
setSupport(double) - Method in class weka.classifiers.meta.Veto: Sets the percentage (0-1 excl) or number of base-classifiers (>= 1) that need to chose the label in order to predict it.
setSuppressErrorMessage(boolean) - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Turn off the error message that is reported when no useful attribute is found.
setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.AbstainingCascade: Sets whether to output the model with the toString() method or not.
setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.ConsensusOrVote: Sets whether to output the model with the toString() method or not.
setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.SuppressModelOutput: Sets whether to output the model with the toString() method or not.
setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Sets whether to output the model with the toString() method or not.
setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.Veto: Sets whether to output the model with the toString() method or not.
setSuppressModelOutput(boolean) - Method in class weka.classifiers.meta.VotedImbalance: Sets whether to output the model with the toString() method or not.
setSuppressModelOutput(boolean) - Method in interface weka.core.ModelOutputHandler: Sets whether to output the model with the toString() method or not.
setSwapAxes(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets whether to swap the axes.
setSwapRowsAndColumns(boolean) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Sets whether to swap rows and columns.
setSwapRowsAndColumns(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Sets whether to swap rows and columns.
setTableName(String) - Method in class adams.flow.sink.WekaDatabaseWriter: Sets the table name to store the data in.
setTarget(Object) - Method in class adams.gui.wizard.WekaPropertySheetPanelPage: Sets the object to display the properties for.
setTemplate(Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Sets the stored template object.
setTemplate(Vote) - Method in class adams.flow.transformer.wekaensemblegenerator.VotedModels: Sets the Vote template to use.
setTemplate(Vote) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds: Sets the Vote template to use.
setTemplate(MultipleClassifiersCombiner) - Method in class adams.flow.transformer.wekaensemblegenerator.MultiClassifiersCombinerModels: Sets the MultipleClassifiersCombiner template to use.
setTemplate(Clusterer) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Sets the stored template object.
setTest(CallableActorReference) - Method in class adams.flow.transformer.WekaClassifierRanker: Sets the name of the callable actor to obtain the test set.
setTestAttributes(WekaAttributeRange) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Sets the range of attributes from the test to add to the output.
setTestBase(int) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Sets the index of the test base.
setTestBase(int) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Sets the index of the test base.
setTestData(StorageName) - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Sets the (optional) storage item that contains the test data; cross-validation is performed if not present.
setTester(Tester) - Method in class adams.flow.transformer.WekaExperimentEvaluation: Sets the Tester to use.
setTester(Tester) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Sets the Tester to use.
setTester(Tester) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Sets the tester to use.
setTestInstances(Instances) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Sets the currently set test set (if null, cross-validation is used).
setTestset(CallableActorReference) - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Sets the name of the callable clusterer to use.
setTestset(CallableActorReference) - Method in class adams.flow.transformer.WekaTestSetEvaluator: Sets the name of the callable classifier to use.
setTestSet(File) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Sets the file containing the test set to remove from the data passing through the filter.
setTestSplitName(String) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Sets the name of the split to use for testing.
setTestSplitName(String) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Sets the name of the split to use for testing, ie generating predictions.
setThreshold(double) - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator: Sets the threshold.
setThreshold(double) - Method in class adams.tools.CompareDatasets: Sets the threshold for the correlation coefficient.
setThreshold(double) - Method in class weka.classifiers.meta.ClassifierCascade: the threshold for the statistic for termination.
setThreshold(double) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Sets the threshold for the max error when predicting a numeric class.
setThreshold(double) - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Sets the threshold for the max error when predicting a numeric class.
setThresholdCheck(ClassifierCascade.ThresholdCheck) - Method in class weka.classifiers.meta.ClassifierCascade: whether to go below or above the threshold.
setThresholds(String) - Method in class weka.classifiers.meta.VotedImbalance: Set the pairs of threshold/number of resampled models.
setTimeLenient(boolean) - Method in class adams.ml.data.InstancesView: Sets whether parsing of times is to be lenient or not.
setTimeMsecLenient(boolean) - Method in class adams.ml.data.InstancesView: Sets whether parsing of times/msec is to be lenient or not.
setTimeout(int) - Method in class weka.classifiers.meta.SocketFacade: Sets the timeout in milli-second to wait for new connections.
setTimeZone(TimeZone) - Method in class adams.ml.data.InstancesView: Sets the timezone to use.
setTitle(String) - Method in class weka.gui.explorer.ExplorerExt: Sets the base title to use for the title generator.
setTitleClassDetails(String) - Method in class adams.flow.transformer.WekaEvaluationSummary: Sets the title to use for the class details.
setTitleMatrix(String) - Method in class adams.flow.transformer.WekaEvaluationSummary: Sets the title to use for the confusion matrix.
setTitleNameColumn(String) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Sets the title of the "Name" column, i.e., the first column.
setTitleSummary(String) - Method in class adams.flow.transformer.WekaEvaluationSummary: Sets the title to use for the summary.
setTitleValueColumn(String) - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Sets the title of the "Value" column, i.e., the first column.
setTokenizers(Tokenizer[]) - Method in class weka.core.tokenizers.MultiTokenizer: Sets the tokenizers to use.
setTol(double) - Method in class adams.data.instancesanalysis.pls.KernelPLS: Sets the inner NIPALS loop maximum number of iterations.
setTol(double) - Method in class adams.data.instancesanalysis.pls.NIPALS: Sets the inner NIPALS loop improvement tolerance.
setTol(double) - Method in class adams.data.instancesanalysis.pls.PRM: Sets the inner NIPALS loop improvement tolerance.
setTol(double) - Method in class adams.data.instancesanalysis.pls.SparsePLS: Sets the inner NIPALS loop improvement tolerance.
setTolerateHeaderChanges(boolean) - Method in class adams.data.instances.AbstractInstanceGenerator: Sets whether to tolerate header changes and merely re-generating the header instead of throwing an exception.
setToolTipsEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Sets whether to show tool tips.
setToolTipsEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Sets whether to show tool tips.
setToolTipsEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Sets whether to show tool tips.
setToolTipsEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Sets whether to show tool tips.
setToolTipsEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Sets whether to show tool tips.
setTopK(int) - Method in class weka.classifiers.trees.XGBoost: Sets the number of top features to select when using the greedy or thrifty feature selector.
setTrain(CallableActorReference) - Method in class adams.flow.transformer.WekaClassifierRanker: Sets the name of the callable actor to obtain the training set.
setTrain(Instances) - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Sets the training data to use.
setTrainSplitName(String) - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Sets the name of the split to use for training.
setTrainSplitName(String) - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Sets the name of the split to use for training.
setTreeMethod(XGBoost.TreeMethod) - Method in class weka.classifiers.trees.XGBoost: Sets the tree construction algorithm used in XGBoost.
setTrials(int) - Method in class weka.classifiers.trees.RandomModelTrees
setTurnOffAbstaining(boolean) - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: Sets whether to turn off abstaining of the base classifier.
setTweedieVariancePower(float) - Method in class weka.classifiers.trees.XGBoost: Sets the parameter that controls the variance of the Tweedie distribution.
setType(WekaClassifierInfo.InfoType) - Method in class adams.flow.transformer.WekaClassifierInfo: Sets the type of information to generate.
setType(WekaClustererInfo.InfoType) - Method in class adams.flow.transformer.WekaClustererInfo: Sets the type of information to generate.
setType(WekaEvaluationInfo.InfoType) - Method in class adams.flow.transformer.WekaEvaluationInfo: Sets the type of information to generate.
setType(WekaExtractArray.ExtractionType) - Method in class adams.flow.transformer.WekaExtractArray: Sets the type of extraction to perform.
setType(WekaInstancesInfo.InfoType) - Method in class adams.flow.transformer.WekaInstancesInfo: Sets the type of information to generate.
setType(NominalToNumeric.ConversionType) - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Sets the conversion type to use.
setUndo(Undo) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Sets the undo manager to use, can be null if no undo-support wanted.
setUndo(Undo) - Method in class adams.gui.visualization.instance.InstancePanel: Sets the undo manager to use, can be null if no undo-support wanted.
setUndoEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.data.DataContainerList: Sets whether undo is enabled.
setUndoEnabled(boolean) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Sets the undo state.
setUndoEnabled(boolean) - Method in class adams.gui.visualization.instances.InstancesTable: sets whether undo support is enabled
setUndoEnabled(boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel: sets whether undo support is enabled
setUndoHandler(UndoHandlerWithQuickAccess) - Method in class adams.gui.visualization.instances.InstancesTable: Sets the undo handler to use.
setUndoHandler(UndoHandlerWithQuickAccess) - Method in class adams.gui.visualization.instances.InstancesTableModel: Sets the undo handler to use.
setUniqueID(String) - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Sets the name of the unique ID attribute that the merge is joining on.
setUniqueID(String) - Method in class adams.flow.transformer.WekaInstancesMerge: Sets the attribute (string/numeric) to use for uniquely identifying rows.
setUnpruned(boolean) - Method in class weka.classifiers.trees.m5.M5Base2: Use unpruned tree/rules
setUnpruned(boolean) - Method in class weka.classifiers.trees.m5.Rule2: Use unpruned tree/rules
setUnset(boolean) - Method in class adams.flow.transformer.WekaClassSelector: Sets whether to unset the class attribute.
setup(Instances) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Initializes the filter with the given input data.
setUp() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator: Performs necessary initializations before being able to evaluate.
setUp() - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Performs necessary initializations before being able to evaluate.
setUp() - Method in class adams.flow.transformer.AbstractCallableWekaClassifierEvaluator: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.AbstractCallableWekaClustererEvaluator: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.AbstractInstanceGenerator: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaClassifierRanker: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaCrossValidationClustererEvaluator
setUp() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaExperiment: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaFilter: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaInstanceDumper: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaStoreInstance: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaTrainAssociator: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaTrainClassifier: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaTrainClusterer: Initializes the item for flow execution.
setUp() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator: Initializes the item for flow execution.
setUp(Actor) - Method in class adams.flow.condition.bool.AbstractAttributeCapabilities: Configures the condition.
setUp(Actor) - Method in class adams.flow.condition.bool.WekaClassification: Initializes the item for flow execution.
setUp(Instances) - Method in class weka.classifiers.lazy.LWLSynchroPrefilter
SETUP - adams.opt.genetic.OutputType: only the setup.
setUpCallableActor() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Configures the callable actor.
setUpdateContainerColor(boolean) - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet: Sets whether to update the container's color with the color determined by this paintlet.
setUpdateHeader(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Sets whether to remove the labels also from the attribute definition.
setUpdateInterval(int) - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater: Sets the number of tokens after which the display is being updated.
setUpdater(AbstractInstancePanelUpdater) - Method in class adams.flow.sink.WekaInstanceViewer: Sets the updater to use.
setUpdater(XGBoost.Updater) - Method in class weka.classifiers.trees.XGBoost: Sets the choice of algorithm to fit the linear model.
setUpdateRelationName(boolean) - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Sets whether to update the relation name with the new class attribute.
setUpdateWait(int) - Method in class weka.classifiers.functions.FakeClassifier: Sets the time in msec to wait when calling updateClassifier.
SetupDialog(Dialog, Dialog.ModalityType) - Constructor for class adams.gui.visualization.instance.HistogramFactory.SetupDialog: Initializes the dialog.
SetupDialog(Frame, boolean) - Constructor for class adams.gui.visualization.instance.HistogramFactory.SetupDialog: Initializes the dialog.
setUpEvaluator() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Initializes the evaluator.
setUpModel() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Loads the model from the model file.
setUpModel(Actor) - Method in class adams.flow.condition.bool.WekaClassification: Loads the model from the model file.
setupModified() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: Sends an event that the setup was modified.
setUpper(UpperStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Sets the upper value to output.
setUpper(UpperStatistic) - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Sets the upper value to output.
setUpper(UpperStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Sets the upper value to output.
setUpper(UpperStatistic) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Sets the upper value to output.
setUpReference() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Loads the reference data.
setupTipText() - Method in class adams.flow.source.WekaClassifierGenerator: Returns the tip text for this property.
setupTipText() - Method in class adams.flow.source.WekaClustererGenerator: Returns the tip text for this property.
setupTipText() - Method in class adams.flow.source.WekaFilterGenerator: Returns the tip text for this property.
setupTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Returns the tip text for this property.
setupUploadTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
setURL(String) - Method in class adams.flow.sink.WekaDatabaseWriter: Sets the database URL to query.
setURL(String) - Method in class adams.flow.source.WekaDatabaseReader: Sets the database URL to query.
setUseAbsoluteError(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Sets whether to use an absolute error (ie no direction).
setUseAbsoluteError(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Sets whether to use an absolute error (ie no direction).
setUseColumnNamesAsClassLabels(boolean) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Sets whether to use the names of the class distribution columns as labels in the fake evaluation.
setUseCustomLoader(boolean) - Method in class adams.flow.transformer.WekaFileReader: Sets whether to use a custom loader or not.
setUseCustomLoader(boolean) - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Sets whether to use a custom loader or not.
setUseCustomLoader(boolean) - Method in class weka.filters.unsupervised.instance.AlignDataset: Sets whether to use a custom loader or automatic loading.
setUseCustomLoader(boolean) - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Sets whether to use a custom loader or automatic loading.
setUseCustomPaintlet(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets whether to use the custom paintlet.
setUseCustomSaver(boolean) - Method in class adams.flow.sink.WekaFileWriter: Sets whether to use a custom saver or not.
setUseError(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Sets whether to use the numeric error for the cross size.
setUseFilename(boolean) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Sets whether to use the filename (w/o path) instead of the relationname.
setUseFilename(boolean) - Method in interface adams.gui.tools.wekamultiexperimenter.experiment.ExperimentWithCustomizableRelationNames: Sets whether to use the filename (w/o path) instead of the relationname.
setUseFilename(boolean) - Method in class weka.experiment.ExtExperiment: Sets whether to use the filename (w/o path) instead of the relationname.
setUseFixedMinMax(boolean) - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Sets whether to use user-supplied min/max for bin calculation rather than obtain min/max from data.
setUseMedian(boolean) - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters: Sets whether to use the median instead of the mean.
setUseModelResetVariable(boolean) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Sets the whether to use a variable to monitor for changes in order to reset the model.
setUseOriginalIndices(boolean) - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Sets whether to align with original data (requires: WekaEvaluationContainer as input and original indices in container).
setUseOuterWindow(boolean) - Method in class adams.flow.source.WekaSelectDataset: Sets whether to use the outer window as parent.
setUsePrefix(boolean) - Method in class adams.flow.transformer.WekaInstancesMerge: Sets whether to use prefixes.
setUseProbabilities(boolean) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Sets whether to use probabilities instead of 0 and 1 for the counts.
setUser(String) - Method in class adams.flow.sink.WekaDatabaseWriter: Sets the database user.
setUser(String) - Method in class adams.flow.source.WekaDatabaseReader: Sets the database user.
setUseRelationNameAsFilename(boolean) - Method in class adams.flow.sink.WekaFileWriter: Sets whether to use the relation name as filename instead.
setUseRelationNameAsFilename(boolean) - Method in class adams.flow.transformer.WekaInstanceDumper: Sets whether to use the relation name as filename instead.
setUseRelationNameAsTable(boolean) - Method in class adams.flow.sink.WekaDatabaseWriter: Sets whether to output single Instance objects or just one Instances object.
setUseRelativePath(boolean) - Method in class weka.core.converters.SimpleArffLoader: Ignored.
setUseSaveDialog(boolean) - Method in class adams.gui.wizard.WekaSelectDatasetPage: Sets whether to use the save or open dialog.
setUseSecondEvaluation(boolean) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Sets whether to use the second evaluation.
setUseTree(boolean) - Method in class weka.classifiers.trees.m5.Rule2: Use an m5 tree rather than generate rules
setUseUnsmoothed(boolean) - Method in class weka.classifiers.trees.m5.M5Base2: Use unsmoothed predictions
setUseViews(boolean) - Method in interface adams.data.weka.InstancesViewSupporter: Sets whether to uses views.
setUseViews(boolean) - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Sets whether to use views instead of dataset copies, in order to conserve memory.
setUseViews(boolean) - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Sets whether to use views instead of dataset copies, in order to conserve memory.
setUseViews(boolean) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets whether to use views instead of dataset copies, in order to conserve memory.
setUseViews(boolean) - Method in class weka.classifiers.AbstractSplitGenerator: Sets whether to uses views only.
setValue(int, double) - Method in class weka.core.AbstractHashableInstance: Sets a specific value in the instance to the given value (internal floating-point format).
setValue(int, String) - Method in class weka.core.AbstractHashableInstance: Sets a value of a nominal or string attribute to the given value.
setValue(PropertyPath.PropertyContainer, double) - Method in class adams.core.discovery.genetic.GenericDoubleResolution: Sets the double value in the property container.
setValue(PropertyPath.PropertyContainer, double) - Method in class adams.core.discovery.genetic.GPDGamma: Sets the double value in the property container.
setValue(PropertyPath.PropertyContainer, double) - Method in class adams.core.discovery.genetic.GPDNoise: Sets the double value in the property container.
setValue(PropertyPath.PropertyContainer, float) - Method in class adams.core.discovery.genetic.GenericFloatResolution: Sets the float value in the property container.
setValue(PropertyPath.PropertyContainer, int) - Method in class adams.core.discovery.genetic.GenericInteger: Sets the double value in the property container.
setValue(PropertyPath.PropertyContainer, int) - Method in class adams.core.discovery.genetic.PLSFilterNumComponents: Sets the integer value in the property container.
setValue(PropertyPath.PropertyContainer, int) - Method in class adams.core.discovery.genetic.SavitzkyGolay2NumPoints: Sets the integer value in the property container.
setValue(PropertyPath.PropertyContainer, String) - Method in class adams.core.discovery.genetic.GenericString: Sets the string value in the property container.
setValue(PropertyPath.PropertyContainer, Matrix) - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Sets the integer value in the property container.
setValue(PropertyPath.PropertyContainer, Matrix) - Method in class adams.core.discovery.genetic.SIMPLSWeightsMatrix: Sets the integer value in the property container.
setValue(PropertyEditor, Object) - Method in class adams.gui.goe.WekaGenericObjectEditorHandler: Sets the editor value.
setValue(String) - Method in class adams.flow.transformer.WekaSetInstancesValue: Sets the value to set in the report.
setValue(String) - Method in class adams.flow.transformer.WekaSetInstanceValue: Sets the value to set in the report.
setValue(Attribute, double) - Method in class weka.core.AbstractHashableInstance: Sets a specific value in the instance to the given value (internal floating-point format).
setValue(Attribute, String) - Method in class weka.core.AbstractHashableInstance: Sets a value of an nominal or string attribute to the given value.
setValue(Instance, int, Object) - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge: Sets the value of the given attribute in the given instance to the given value (handles object conversion).
setValueAt(Object, int, int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: Sets the value at the specified position, if possible.
setValueAt(Object, int, int) - Method in class adams.gui.visualization.instances.InstancesTableModel: sets the value in the cell at columnIndex and rowIndex to aValue.
setValueAt(Object, int, int, boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel: Sets the value in the cell at columnIndex and rowIndex to aValue.
setValueSparse(int, double) - Method in class weka.core.AbstractHashableInstance: Sets a specific value in the instance to the given value (internal floating-point format), given an index into the sparse representation.
setVariableName(VariableName) - Method in class adams.flow.template.InstanceDumperVariable: Sets the variable name to generate the sub-flow for.
setVariableName(VariableName) - Method in class adams.flow.transformer.WekaInstanceBuffer: Sets the name of the variable to monitor.
setVariableName(VariableName) - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Sets the name of the variable to monitor.
setVariance(double) - Method in class adams.data.instancesanalysis.PCA: Sets the variance.
setVariance(double) - Method in class weka.classifiers.meta.AbstainLeastMedianSq
setVarianceCovered(double) - Method in class adams.flow.transformer.WekaPrincipalComponents: Sets the amount of variance to account for when retaining principal components.
setVarianceCovered(double) - Method in class weka.core.neighboursearch.PCANNSearch: Sets the amount of variance to account for when retaining principal components.
setVarianceCovered(double) - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Sets the amount of variance to account for when retaining principal components.
setVector(Matrix, Matrix, int) - Static method in class weka.core.matrix.MatrixHelper: stores the data from the (column) vector in the matrix at the specified index
setVerbosity(XGBoost.Verbosity) - Method in class weka.classifiers.trees.XGBoost: Sets the verbosity level.
setVersusFitOptions(VersusFitOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Set the options for the vsfit plot.
setVersusOrderOptions(VersusOrderOptions) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Set the options for the vs order plot.
setVisible(boolean) - Method in class adams.gui.visualization.instance.InstanceContainer: Sets the instance's visibility.
setVisible(int, boolean) - Method in class adams.gui.visualization.instance.InstanceContainerManager: Sets the specified container's visibility.
setVotingType(VotedPairs.VotingType) - Method in class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs: Sets the type of voting to use.
setWaitForJobs(boolean) - Method in class adams.multiprocess.WekaCrossValidationExecution: Sets whether to wait for jobs to finish when terminating.
setWaveNoRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.Detrend: Sets the regular expression used for extracting the wave number from the attribute name (using the first group).
setWaveNoRegExp(BaseRegExp) - Method in class weka.filters.unsupervised.attribute.MultiplicativeScatterCorrection: Sets the regular expression used for extracting the wave number from the attribute name (using the first group).
setWeight(double) - Method in class weka.core.AbstractHashableInstance: Sets the weight of an instance.
setWeight(SpreadSheetColumnIndex) - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Sets the (optional) column with the instance weight values.
setWeight(SpreadSheetColumnIndex) - Method in class weka.classifiers.functions.FromPredictions: Sets the column with the weight values.
setWeightingKernel(int) - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Sets the kernel weighting method to use.
setWeightingKernel(int) - Method in class weka.filters.unsupervised.instance.AccumulatedLWLWeights: Sets the kernel weighting method to use.
setWeights(String) - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Sets the optional property in the incoming properties for the initial weights to use.
setWindows(int) - Method in class weka.filters.unsupervised.attribute.PAA: Sets the nth point setting.
setWindows(int) - Method in class weka.filters.unsupervised.attribute.SAX: Sets the nth point setting.
setWithReplacement(boolean) - Method in class adams.flow.transformer.WekaBootstrapping: Sets whether to draw predictions using replacement.
setWriter(SpreadSheetWriter) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Sets the spreadsheet writer to use.
setX(Integer) - Method in class adams.data.instance.InstancePoint: Sets the X value.
setXRegExp(BaseRegExp) - Method in class weka.filters.supervised.attribute.MultiPLS: Sets the regular expression to identify the X attributes.
setY(Double) - Method in class adams.data.instance.InstancePoint: Sets the Y value.
setYRegExp(BaseRegExp) - Method in class weka.filters.supervised.attribute.MultiPLS: Sets the regular expression to identify the Y attributes.
setZoomOverview(boolean) - Method in class adams.flow.sink.WekaInstanceViewer: Sets whether to display the zoom overview.
setZoomOverviewPanelVisible(boolean) - Method in class adams.gui.visualization.instance.InstanceExplorer: Sets the zoom overview panel visible or not.
setZoomOverviewPanelVisible(boolean) - Method in class adams.gui.visualization.instance.InstancePanel: Sets the zoom overview panel visible or hides it.
SF_ENTROPY_GAIN - adams.flow.core.EvaluationStatistic
SF_ENTROPY_GAIN - adams.flow.core.ExperimentStatistic
SF_MEAN_ENTROPY_GAIN - adams.flow.core.EvaluationStatistic
SF_MEAN_ENTROPY_GAIN - adams.flow.core.ExperimentStatistic
SF_MEAN_PRIOR_ENTROPY - adams.flow.core.EvaluationStatistic
SF_MEAN_PRIOR_ENTROPY - adams.flow.core.ExperimentStatistic
SF_MEAN_SCHEME_ENTROPY - adams.flow.core.EvaluationStatistic
SF_MEAN_SCHEME_ENTROPY - adams.flow.core.ExperimentStatistic
SF_PRIOR_ENTROPY - adams.flow.core.EvaluationStatistic
SF_PRIOR_ENTROPY - adams.flow.core.ExperimentStatistic
SF_SCHEME_ENTROPY - adams.flow.core.EvaluationStatistic
SF_SCHEME_ENTROPY - adams.flow.core.ExperimentStatistic
shallowCopy() - Method in class adams.data.instances.AbstractInstanceGenerator: Returns a shallow copy of itself, i.e., based on the commandline options.
shallowCopy() - Method in class adams.data.weka.columnfinder.AbstractColumnFinder: Returns a shallow copy of itself, i.e., based on the commandline options.
shallowCopy() - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Returns a shallow copy of itself, i.e., based on the commandline options.
shallowCopy() - Method in class adams.data.weka.predictions.AbstractErrorScaler: Returns a shallow copy of itself, i.e., based on the commandline options.
shallowCopy() - Method in class adams.data.weka.rowfinder.AbstractRowFinder: Returns a shallow copy of itself, i.e., based on the commandline options.
shallowCopy(boolean) - Method in class adams.data.instances.AbstractInstanceGenerator: Returns a shallow copy of itself, i.e., based on the commandline options.
shallowCopy(boolean) - Method in class adams.data.weka.columnfinder.AbstractColumnFinder: Returns a shallow copy of itself, i.e., based on the commandline options.
shallowCopy(boolean) - Method in class adams.data.weka.evaluator.AbstractInstanceEvaluator: Returns a shallow copy of itself, i.e., based on the commandline options.
shallowCopy(boolean) - Method in class adams.data.weka.predictions.AbstractErrorScaler: Returns a shallow copy of itself, i.e., based on the commandline options.
shallowCopy(boolean) - Method in class adams.data.weka.rowfinder.AbstractRowFinder: Returns a shallow copy of itself, i.e., based on the commandline options.
shortenCommandLine(Classifier) - Static method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns a shortened commandline string for the classifier.
SHOTGUN - weka.classifiers.trees.XGBoost.Updater
showCellPopup(MouseEvent) - Method in class adams.gui.visualization.instances.InstancesTable: Shows a popup menu for the cells.
showCredentials() - Method in class adams.gui.tools.wekamultiexperimenter.setup.weka.JdbcOutputPanel: Displays a dialog for the user credentials.
showDataTablePopup(MouseEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: Displays popup for table.
showDialog() - Method in class adams.flow.source.WekaSelectObjects: Displays the dialog, prompting the user to select classes.
showDistributionTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the tip text for this property.
showDistributionTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Returns the tip text for this property.
showErrorTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the tip text for this property.
showErrorTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Returns the tip text for this property.
showHeaderPopup(MouseEvent) - Method in class adams.gui.visualization.instances.InstancesTable: Shows a popup menu for the header.
showHelp() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Displays the help for the queries.
showHistogram(List<InstanceContainer>) - Method in class adams.gui.visualization.instance.InstancePanel: Displays the histograms for the given instances.
showInstanceExplorer() - Method in class weka.gui.explorer.ExplorerExt: Displays the data in the Instance Explorer.
showListPopup(MouseEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: Displays the popup for the list.
showOutputGeneratorsFavorites() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Shows the favorites popup menu for the output generators.
showOutputGeneratorsFavorites() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Shows the favorites popup menu for the output generators.
showOutputGeneratorsFavorites() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Shows the favorites popup menu for the output generators.
showOutputGeneratorsFavorites() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Shows the favorites popup menu for the output generators.
showOutputGeneratorsFavorites() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Shows the favorites popup menu for the output generators.
showPopup(String, int, int) - Method in class weka.gui.explorer.ExperimentPanel: Handles constructing a popup menu with visualization options.
showProbabilityTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the tip text for this property.
showProbabilityTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Returns the tip text for this property.
showProgress() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Updates the progress of the experiment.
showProgress(String) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Displays a progresss message.
showStatus(String) - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekainvestigator.source.AbstractSource: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Displays a message.
showStatus(String) - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Displays a message.
showStatus(String) - Method in class adams.gui.visualization.instance.InstanceComparePanel: Displays a message.
showStatus(String) - Method in class adams.gui.visualization.instance.InstanceExplorer: Displays a message.
showWeightTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the tip text for this property.
showWeightTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.Predictions: Returns the tip text for this property.
SHUFFLE - weka.classifiers.trees.XGBoost.FeatureSelector
significanceTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the tip text for this property.
significanceTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the tip text for this property.
SILENT - weka.classifiers.trees.XGBoost.Verbosity
silentTipText() - Method in class weka.classifiers.MultiLevelSplitGenerator: Returns the tip text for this property.
Simple - Class in adams.flow.transformer.wekadatasetsmerge: Just merges the datasets side by side.
Simple - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel: Simply builds the classifier on the full dataset.
Simple - Class in weka.classifiers.meta.socketfacade: Simple preparation scheme, using JSON with the actual data in CSV format.
Simple() - Constructor for class adams.flow.transformer.wekadatasetsmerge.Simple
Simple() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.Simple
Simple() - Constructor for class weka.classifiers.meta.socketfacade.Simple
Simple.SimpleRowSetIterator - Class in adams.flow.transformer.wekadatasetsmerge: Enumeration class which just returns the concatenation of the source data rows in order.
SimpleArffLoader - Class in weka.core.converters: A simple ARFF loader, only supports batch loading.
SimpleArffLoader() - Constructor for class weka.core.converters.SimpleArffLoader: Initializes the loader.
SimpleArffSaver - Class in weka.core.converters: Writes the Instances to an ARFF file in batch mode.
SimpleArffSaver() - Constructor for class weka.core.converters.SimpleArffSaver: Constructor
simpleAttributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Returns the tip text for this property
SimpleDetrend - Class in weka.filters.unsupervised.attribute: Performs Detrend, using the specified correction scheme.
SimpleDetrend() - Constructor for class weka.filters.unsupervised.attribute.SimpleDetrend
SimpleInstanceLinePaintlet - Class in adams.gui.visualization.instance: Paintlet for generating a line plot for Instance objects (no markers).
SimpleInstanceLinePaintlet() - Constructor for class adams.gui.visualization.instance.SimpleInstanceLinePaintlet
SimpleInstancePanelUpdater - Class in adams.gui.visualization.instance: Updates the flow after the specified number of tokens have been processed.
SimpleInstancePanelUpdater() - Constructor for class adams.gui.visualization.instance.SimpleInstancePanelUpdater
SimpleJsonCommunicationProcessor - Class in adams.data.wekapyroproxy: Turns Instances/Instance into simple JSON.
SimpleJsonCommunicationProcessor() - Constructor for class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor
SimpleLinearRegressionIntervalEstimator - Class in weka.classifiers.functions: Learns a simple linear regression model.
SimpleLinearRegressionIntervalEstimator() - Constructor for class weka.classifiers.functions.SimpleLinearRegressionIntervalEstimator
SimpleLinearRegressionWithAccess - Class in weka.classifiers.functions: Learns a simple linear regression model.
SimpleLinearRegressionWithAccess() - Constructor for class weka.classifiers.functions.SimpleLinearRegressionWithAccess
SimplePlot - Class in adams.gui.visualization.instances.instancestable: Allows to perform a simple plot of a column or row.
SimplePlot() - Constructor for class adams.gui.visualization.instances.instancestable.SimplePlot
SimpleSetupDialog(Dialog) - Constructor for class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog: Initializes the dialog.
SimpleSetupDialog(Frame) - Constructor for class adams.gui.goe.WekaExperimentFileEditor.SimpleSetupDialog: Initializes the dialog.
SimpleSubRange - Class in adams.flow.transformer.wekaevaluationpostprocessor: Generates an Evaluation object based on the actual class values that fall within the specified interval ranges.
SimpleSubRange() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.SimpleSubRange
SIMPLS - Class in adams.data.instancesanalysis.pls: Implementation of SIMPLS algorithm.

Available matrices: W, B

For more information see:

Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002).
SIMPLS() - Constructor for class adams.data.instancesanalysis.pls.SIMPLS
SIMPLS_B - adams.flow.transformer.WekaExtractPLSMatrix.MatrixType: the B matrix for SIMPLS (used for prediction)
SIMPLS_W - adams.flow.transformer.WekaExtractPLSMatrix.MatrixType: the W matrix for SIMPLS
SIMPLSAttributeEval - Class in weka.attributeSelection: Uses the first component of SIMPLS to determine the importance of the attributes (defaults: no preprocessing, missing values not replaced, and 20 components)
SIMPLSAttributeEval() - Constructor for class weka.attributeSelection.SIMPLSAttributeEval
SIMPLSMatrixFilter - Class in weka.filters.supervised.attribute: Runs Partial Least Square Regression over the given instances and computes the resulting beta matrix for prediction.
By default it replaces missing values and centers the data.

Allows access to the internal matrices.

For more information see:

Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002).
SIMPLSMatrixFilter() - Constructor for class weka.filters.supervised.attribute.SIMPLSMatrixFilter
SIMPLSMatrixFilterFromGeneticString - Class in weka.filters.supervised.attribute: Runs Partial Least Square Regression over the given instances and computes the resulting beta matrix for prediction.
By default it replaces missing values and centers the data.

Allows access to the internal matrices.

For more information see:

Tormod Naes, Tomas Isaksson, Tom Fearn, Tony Davies (2002).
SIMPLSMatrixFilterFromGeneticString() - Constructor for class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
SIMPLSWeightsMatrix - Class in adams.core.discovery.genetic: SIMPLS pls internal weights handler.
SIMPLSWeightsMatrix() - Constructor for class adams.core.discovery.genetic.SIMPLSWeightsMatrix
size() - Method in class adams.opt.optimise.genetic.PackDataDef
size() - Method in class weka.core.InstanceGrouping: Returns the number of groups.
size() - Method in class weka.core.InstancesView: Returns the number of instances in the dataset.
sizeLimitTipText() - Method in class weka.filters.unsupervised.instance.WeightsBasedResample: Returns the tip text for this property.
sizeTipText() - Method in class adams.data.weka.predictions.FixedSizeErrorScaler: Returns the tip text for this property.
skipBuildTipText() - Method in class adams.flow.transformer.WekaTrainClassifier: Returns the tip text for this property.
skipDropTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the skipDrop option.
skipIdenticalTipText() - Method in class weka.core.neighboursearch.NewNNSearch: Returns the tip text for this property.
skipNominalTipText() - Method in class adams.data.instancesanalysis.PCA: Returns the tip text for this property.
skipTrainTipText() - Method in class weka.classifiers.meta.SocketFacade: Returns the tip text for this property.
slim(Matrix) - Method in class adams.data.instancesanalysis.pls.SIMPLS: Zeroes the coefficients of the W matrix beyond the specified number of coefficients.
smoothingOriginal(double, double, double) - Static method in class weka.classifiers.trees.m5.RuleNode2: Applies the m5 smoothing procedure to a prediction
SocketFacade - Class in weka.classifiers.meta: Uses sockets to communicate with a process for training and making predictions.
SocketFacade() - Constructor for class weka.classifiers.meta.SocketFacade
SOFTMAX_MULTICLASS_CLASSIFICATION - weka.classifiers.trees.XGBoost.Objective
SOFTPROB_MULTICLASS_CLASSIFICATION - weka.classifiers.trees.XGBoost.Objective
solveChol(double[][], double[]) - Method in class weka.classifiers.functions.GPD: specialised to solve A * x = b, where x and b are one-dimensional
sort() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Sorts genes and fitness arrays according to fitness.
sort(int) - Method in class weka.core.InstancesView: Sorts the instances based on an attribute.
sort(int, boolean) - Method in class adams.ml.data.InstancesView: Sorts the rows based on the values in the specified column.
sort(InstanceComparator) - Method in class adams.gui.visualization.instances.InstancesTable: Sorts the data with the given comparator.
sort(RowComparator) - Method in class adams.ml.data.InstancesView: Sorts the rows using the given comparator.
sort(RowComparator, boolean) - Method in class adams.ml.data.InstancesView: Sorts the rows using the given comparator.
Sort - Class in weka.filters.unsupervised.instance: Sorts the instances.
Sort() - Constructor for class weka.filters.unsupervised.instance.Sort
SortablePrediction(Prediction) - Constructor for class adams.flow.transformer.WekaAccumulatedError.SortablePrediction: Initializes the container.
sortBasedOnNominalAttribute(int) - Method in class weka.core.InstancesView: Sorts a nominal attribute (stable, linear-time sort).
SortContainer(int, double) - Constructor for class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer: Initializes the container.
SortedInterval(Instance, double[][], boolean) - Constructor for class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval: Initializes the intervals.
sortInstances(int) - Method in class adams.gui.visualization.instances.InstancesTableModel: sorts the instances via the given attribute
sortInstances(int, boolean) - Method in class adams.gui.visualization.instances.InstancesTableModel: sorts the instances via the given attribute
sortLabelsTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the tip text for this property.
SortOnAttribute - Class in weka.filters.unsupervised.instance: Sorts the instances on a particular attribute.
SortOnAttribute() - Constructor for class weka.filters.unsupervised.instance.SortOnAttribute
sortResults() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment
sortRowKeys() - Method in class adams.ml.data.InstancesView: Sorts the rows according to the row keys.
sortRowKeys(Comparator<String>) - Method in class adams.ml.data.InstancesView: Sorts the rows according to the row keys.
sortSetupChanged(InstancesSortSetupEvent) - Method in interface adams.gui.event.InstancesSortSetupListener: Gets triggered whenever the sort setup changes.
SOURCE_CODE - adams.flow.transformer.WekaClassifierInfo.InfoType: source code (if available).
SourceAttribute(int, int, String) - Constructor for class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute: Standard constructor.
SourceCode - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Outputs source code from the model (if classifier implements Sourcable).
SourceCode() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.SourceCode
sourceCodeClassTipText() - Method in class adams.flow.transformer.WekaClassifierInfo: Returns the tip text for this property.
sparseFormatTipText() - Method in class adams.flow.source.WekaDatabaseReader: Returns the tip text for this property.
SparsePLS - Class in adams.data.instancesanalysis.pls
SparsePLS() - Constructor for class adams.data.instancesanalysis.pls.SparsePLS
SpellChecker - Class in weka.filters.unsupervised.attribute: A simple filter that merges misspelled labels into a single correct one.
SpellChecker() - Constructor for class weka.filters.unsupervised.attribute.SpellChecker
split() - Method in class weka.classifiers.trees.m5.RuleNode2: Finds an attribute and split point for this node
split(Instances) - Method in class adams.data.weka.datasetsplitter.AbstractSplitter: Splits the given dataset into a number of other datasets.
split(Instances) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter: Splits the given dataset into a number of other datasets.
split(Instances) - Method in class adams.data.weka.datasetsplitter.RowSplitter: Splits the given dataset into a number of other datasets.
split(Instances, double) - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator: Splits the dataset into two separate ones, according to the specified percentage (0-1).
Split - Class in adams.gui.tools.wekainvestigator.datatable.action: Creates train/test splits from a dataset and inserts these as new datasets.
Split() - Constructor for class adams.gui.tools.wekainvestigator.datatable.action.Split: Instantiates the action.
splitAtt() - Method in class weka.classifiers.trees.m5.RuleNode2: Get the index of the splitting attribute for this node
splitAttributes(Instances) - Method in class adams.data.weka.datasetsplitter.ColumnSplitter: Creates the attribute lists for the two datasets resulting from this split.
SplitGenerator - Interface in weka.classifiers: Interface for helper classes that generate dataset splits.
splitOptions(String) - Method in class adams.core.option.WekaCommandLineHandler: Splits the commandline into an array.
splitPercentageTipText() - Method in class adams.flow.sink.WekaExperimentGenerator: Returns the tip text for this property.
splitpointTipText() - Method in class weka.classifiers.meta.HighLowSplit
splitpointTipText() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier
SPLITS - Static variable in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
splitsTipText() - Method in class adams.core.discovery.genetic.AbstractGeneticDoubleMatrixDiscoveryHandler: Returns the tip text for this property.
splitsTipText() - Method in class weka.filters.supervised.attribute.SIMPLSMatrixFilterFromGeneticString
splitterTipText() - Method in class adams.flow.transformer.WekaDatasetSplit: Gets the tip-text for the splitter option.
splitVal() - Method in class weka.classifiers.trees.m5.RuleNode2: Get the split point for this node
SpreadSheet - Class in adams.gui.tools.wekainvestigator.source: For loading ADAMS spreadsheets.
SpreadSheet() - Constructor for class adams.gui.tools.wekainvestigator.source.SpreadSheet: Instantiates the action.
SPREADSHEET - adams.flow.source.wekapackagemanageraction.ListPackages.OutputFormat
spreadSheetColumnInserted(SpreadSheetColumnInsertionEvent) - Method in class adams.ml.data.InstanceView: A column got inserted.
SpreadSheetContainer - Class in adams.gui.tools.wekainvestigator.data: SpreadSheet-based dataset.
SpreadSheetContainer(SpreadSheetReader, PlaceholderFile) - Constructor for class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer: Loads the data using the specified reader.
SpreadSheetContainer(SpreadSheetReader, File) - Constructor for class adams.gui.tools.wekainvestigator.data.SpreadSheetContainer: Loads the data using the specified reader.
SpreadSheetLoader - Class in weka.core.converters: Loads a CSV file using an ADAMS spreadsheet reader and converts it into an Instances object.
SpreadSheetLoader() - Constructor for class weka.core.converters.SpreadSheetLoader: default constructor
SpreadSheetSaver - Class in weka.core.converters: Writes the Instances to a spreadsheet file using the specified ADAMS spreadsheet writer.
SpreadSheetSaver() - Constructor for class weka.core.converters.SpreadSheetSaver: Constructor
SpreadSheetToWekaInstances - Class in adams.data.conversion: Generates a weka.core.Instances object from a SpreadSheet object.
If there are too many unique lables for a NOMINAL attribute, it gets turned into a STRING attribute (see 'maxLabels' property).
SpreadSheetToWekaInstances() - Constructor for class adams.data.conversion.SpreadSheetToWekaInstances
spreadSheetTypeTipText() - Method in class adams.data.conversion.WekaInstancesToSpreadSheet: Returns the tip text for this property.
spreadSheetWriterTipText() - Method in class weka.core.converters.SpreadSheetSaver: Returns the tip text for this property
sqDifference(int, double, double) - Method in class weka.core.SAXDistance: Returns the squared difference of two values of an attribute.
sqDifference(int, double, double) - Method in class weka.core.WeightedEuclideanDistance: Returns the squared difference of two values of an attribute.
sqDifference(int, double, double) - Method in class weka.core.WeightedEuclideanDistanceRidge: Returns the squared difference of two values of an attribute.
SqlPanel - Class in weka.gui.explorer: A simple demonstration for extending the Explorer by another tab, in this case the SqlViewer (as an extra tab instead of only the button in the PreprocessPanel).
SqlPanel() - Constructor for class weka.gui.explorer.SqlPanel: initializes the panel
SqlViewer - Class in adams.gui.menu: Opens the SQL viewer.
SqlViewer() - Constructor for class adams.gui.menu.SqlViewer: Initializes the menu item with no owner.
SqlViewer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.SqlViewer: Initializes the menu item.
squaredDistance(double[], double[]) - Method in class weka.classifiers.functions.GPD: Computes the squared distance.
stableSort(int) - Method in class weka.core.InstancesView: Sorts the instances based on an attribute, using a stable sort.
STANDARDIZE - adams.data.instancesanalysis.pls.PreprocessingType
startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Starts the evaluation.
startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Starts the evaluation.
startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Starts the evaluation.
startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Starts the evaluation.
startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Starts the evaluation.
startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Generates PCA visualization.
startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Generates PLS visualization.
startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Starts the filtering.
startExecution() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Generates PCA visualization.
startExecution() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Starts the execution.
startExecution(InvestigatorJob) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Starts a job.
startExecution(InvestigatorTabJob) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Starts the job.
startExecutorPool() - Method in class weka.classifiers.meta.SubsetEnsemble: Start the pool of execution threads.
startExecutorPool() - Method in class weka.classifiers.meta.VotedImbalance: Start the pool of execution threads.
startExecutorPool() - Method in class weka.clusterers.SAXKMeans: Start the pool of execution threads
startExperiment() - Method in class weka.gui.explorer.ExperimentPanel: Starts running the currently configured classifier with the current settings in an experiment.
stateChanged(ChangeEvent) - Method in class adams.gui.tools.wekainvestigator.tab.DataTab: Gets called when the data in the table changed.
stateChanged(ChangeEvent) - Method in class adams.gui.tools.wekainvestigator.tab.ScatterPlotTab: Gets called when the data in the table changed.
stateChanged(ChangeEvent) - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupPanel.ModificationChangeListener
STATISTIC - Static variable in class weka.classifiers.meta.ClassifierCascade
statisticIsMaximisable(String) - Method in class weka.classifiers.evaluation.Bias: True if the optimum value of the named metric is a maximum value; false if the optimim value is a minimum value.
statisticIsMaximisable(String) - Method in class weka.classifiers.evaluation.MSLE: True if the optimum value of the named metric is a maximum value; false if the optimim value is a minimum value.
statisticIsMaximisable(String) - Method in class weka.classifiers.evaluation.SDR: True if the optimum value of the named metric is a maximum value; false if the optimim value is a minimum value.
Statistics - Class in adams.flow.transformer.wekarepeatedcrossvalidationoutput: Generates mean/stddev for the specified statistics.
Statistics - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated: Generates statistics for repeated cross-validation runs.
Statistics() - Constructor for class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics
Statistics() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics
StatisticsTable() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.StatisticsTable
statisticsTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Statistics: Returns the tip text for this property.
statisticsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Statistics: Returns the tip text for this property.
statisticTipText() - Method in class adams.flow.transformer.WekaInstancesStatistic: Returns the tip text for this property.
statisticTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Returns the tip text for this property.
statisticTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Returns the tip text for this property.
statisticTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Returns the tip text for this property.
statisticTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the tip text for this property.
statisticTipText() - Method in class weka.classifiers.meta.ClassifierCascade: Returns the tip text for this property.
statisticValuesTipText() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the tip text for this property.
statisticValuesTipText() - Method in class adams.flow.transformer.WekaEvaluationValues: Returns the tip text for this property.
statisticValueTipText() - Method in class adams.flow.transformer.WekaEvaluationValuePicker: Returns the tip text for this property.
stdDev(int, Instances) - Static method in class weka.classifiers.trees.m5.Rule2: Returns the standard deviation value of the supplied attribute index.
stdDevs() - Method in class weka.filters.supervised.attribute.PLSFilterExtended: the standard deviation of the class
stdDevTipText() - Method in class weka.classifiers.meta.InputSmearing: Returns the tip text for this property
stdDevTipText() - Method in class weka.filters.unsupervised.attribute.InputSmearing: Returns the tip text for this property
STDEV - adams.flow.transformer.WekaInstancesInfo.InfoType: the stdev (selected attribute, only numeric).
stop() - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Stops the execution of the algorithm.
stopExecution() - Method in class adams.flow.source.WekaSelectObjects: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaClassifierRanker: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaExperimentExecution: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaRandomSplit: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaSplitGenerator: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaTestSetEvaluator: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: Stops the execution.
stopExecution() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Stops the evaluation.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Stops the evaluation.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Stops the evaluation.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.AbstractExperimentSetup: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Stops the evaluation.
stopExecution() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.CrossValidationExperiment.CrossValidationExperimentJob: Stops the execution.
stopExecution() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Stops the execution.
stopExecution() - Method in class adams.multiprocess.WekaCrossValidationExecution: Stops the execution.
stopExecution() - Method in class adams.multiprocess.WekaCrossValidationJob: Stops the execution.
stopExecution() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Stops the execution of the algorithm.
stopExecution() - Method in class weka.classifiers.evaluation.StoppableEvaluation: Stops the execution.
stopExecution() - Method in class weka.classifiers.MultiLevelSplitGenerator: Stops the execution.
stopExecution() - Method in class weka.classifiers.StoppableClassifier: Stops the execution.
stopExecution() - Method in class weka.classifiers.StoppableEvaluation: Stops the execution.
stopExecution() - Method in class weka.classifiers.StoppableRandomizableClassifier: Stops the execution.
stopExecution() - Method in class weka.classifiers.StoppableSingleClassifierEnhancer: Stops the execution.
stopExperiment() - Method in class weka.gui.explorer.ExperimentPanel: Stops the currently running experiment (if any).
stopFlowIfCanceledTipText() - Method in class adams.flow.source.WekaSelectDataset: Returns the tip text for this property.
stopModeTipText() - Method in class adams.flow.source.WekaSelectDataset: Returns the tip text for this property.
StoppableClassifier - Class in weka.classifiers: Ancestor for classifiers that can be stopped.
StoppableClassifier() - Constructor for class weka.classifiers.StoppableClassifier
StoppableEvaluation - Class in weka.classifiers.evaluation: Extended Evaluation class that can stop its evaluation processes better.
StoppableEvaluation - Class in weka.classifiers: Extended Evaluation class that can stop its evaluation processes better.
StoppableEvaluation(Instances) - Constructor for class weka.classifiers.evaluation.StoppableEvaluation: Initializes all the counters for the evaluation.
StoppableEvaluation(Instances) - Constructor for class weka.classifiers.StoppableEvaluation: Initializes all the counters for the evaluation.
StoppableEvaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.evaluation.StoppableEvaluation: Initializes all the counters for the evaluation and also takes a cost matrix as parameter.
StoppableEvaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.StoppableEvaluation: Initializes all the counters for the evaluation and also takes a cost matrix as parameter.
StoppableRandomizableClassifier - Class in weka.classifiers: Ancestor for randomizable classifiers that can be stopped.
StoppableRandomizableClassifier() - Constructor for class weka.classifiers.StoppableRandomizableClassifier
StoppableSingleClassifierEnhancer - Class in weka.classifiers: Stops the base classifier if it implements Stoppable.
StoppableSingleClassifierEnhancer() - Constructor for class weka.classifiers.StoppableSingleClassifierEnhancer
storageNameTipText() - Method in class adams.data.conversion.MapToWekaInstance: Returns the tip text for this property.
storageNameTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithmInitializer: Returns the tip text for this property.
storageTipText() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns the tip text for this property.
storeColorInReport(int[], String) - Method in class adams.gui.visualization.instance.InstancePanel: Stores the color of the container in the report of container's data object.
storeFilenameTipText() - Method in class adams.flow.transformer.WekaTextDirectoryReader: Returns the tip text for this property.
storeSetup(Instances) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Generates a Properties file that stores information on the setup of the genetic algorithm.
storeSetup(Instances, AbstractGeneticAlgorithm.GeneticAlgorithmJob) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Generates a Properties file that stores information on the setup of the genetic algorithm.
storeSetup(Instances, AbstractGeneticAlgorithm.GeneticAlgorithmJob) - Method in class adams.opt.genetic.DarkLord: Generates a Properties file that stores information on the setup of the genetic algorithm.
storeValueInReport(int[], AbstractField, Object) - Method in class adams.gui.visualization.instance.InstancePanel: Stores the value in the report of container's data object.
stratifyTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesCrossValidationFoldGenerator: Returns the tip text for this property.
stratifyTipText() - Method in class adams.flow.transformer.indexedsplitsrunsgenerator.InstancesGroupedCrossValidationFoldGenerator: Returns the tip text for this property.
stratifyTipText() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
stratifyTipText() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns the tip text for this property.
stratifyTipText() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns the tip text for this property.
stratifyTipText() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns the tip text for this property.
stratStep(int) - Method in class weka.core.InstancesView: Help function needed for stratification of set.
strictTipText() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the tip text for this property.
STRING_ATTRIBUTES - adams.flow.core.Capability: can handle string attributes.
STRING_CLASS - adams.flow.core.Capability: can handle string classes.
StringAttributeGroupExtractor(int, String, String) - Constructor for class adams.data.binning.BinnableInstances.StringAttributeGroupExtractor: Initializes the extractor.
stringFreeStructure() - Method in class weka.core.InstancesView: Create a copy of the structure.
StringToDate - Class in weka.filters.unsupervised.attribute: Parses the selected range of string attributes using the specified format and turns them into date ones.
StringToDate() - Constructor for class weka.filters.unsupervised.attribute.StringToDate
stringToIntArray(String) - Method in class adams.opt.genetic.Hermione: Converts the bit string into an int array.
stringValue(int) - Method in class weka.core.AbstractHashableInstance: Returns the value of a nominal, string, date, or relational attribute for the instance as a string.
stringValue(Attribute) - Method in class weka.core.AbstractHashableInstance: Returns the value of a nominal, string, date, or relational attribute for the instance as a string.
submitJob(Runnable) - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Submits the job.
SubRange - Class in adams.flow.transformer.wekaevaluationpostprocessor: Generates an Evaluation object based on the actual class values that fall within the specified interval ranges.
SubRange() - Constructor for class adams.flow.transformer.wekaevaluationpostprocessor.SubRange
SubRangeEvaluation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.history: Generates a fake evaluation using only predictions with an actual class value that fits in the specified sub-range.
SubRangeEvaluation - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold: Generates a fake evaluation using only predictions with an actual class value that fits in the specified sub-range.
SubRangeEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.history.SubRangeEvaluation
SubRangeEvaluation() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.SubRangeEvaluation
subsampleRatioTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the subsampleRatio option.
subset(double[], int[]) - Method in class adams.gui.visualization.instances.instancestable.ArrayStatistic: Returns the subset of the values.
subset(List<Instances>, int, boolean) - Method in class weka.classifiers.MultiLevelSplitGenerator: Generates the subset: either the specified index of the rest.
SubsetEnsemble - Class in weka.classifiers.meta: Generates an ensemble using the following approach:
- for each attribute apart from class attribute do:
* create new dataset with only this feature and the class attribute
* remove all instances that contain a missing value
* if no instances left in subset, don't build a classifier for this feature
* if at least 1 instance is left in subset, build base classifier with it
If no classifier gets built at all, use ZeroR as backup model, built on the full dataset.
In addition to the default feature for a subset, a number of random features can be added to the subset before the classifier is trained.
At prediction time, the Vote meta-classifier (using the pre-built classifiers) is used to determing the class probabilities or regression value.
SubsetEnsemble() - Constructor for class weka.classifiers.meta.SubsetEnsemble
subsetSizesOK(Instances, int) - Method in class weka.classifiers.trees.RandomRegressionForest.Node: tests whether the leaf threshold is OK
SUFFIX_NAME - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator
SUFFIX_TYPE - Static variable in interface adams.flow.transformer.indexedsplitsrunsgenerator.InstancesIndexedSplitsRunsGenerator
summaryFilterTipText() - Method in class weka.filters.unsupervised.attribute.AttributeSummaryTransferFilter: Gets the tip-text for the pca-filter option.
SumTransformed - Class in weka.classifiers.meta: Finds the base classifier with the best least median squared error.
SumTransformed() - Constructor for class weka.classifiers.meta.SumTransformed
sumXY(Instances) - Method in class weka.classifiers.meta.Corr
Supplementary - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output: Outputs the supplementary data if available.
Supplementary() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.Supplementary
SUPPLIED - adams.opt.genetic.OutputPrefixType: the supplied prefix.
suppliedPrefixTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns the tip text for this property.
supplyComponent() - Method in class adams.flow.sink.WekaAttributeSummary: Returns the current component.
supplyComponent() - Method in class adams.flow.sink.WekaGraphVisualizer: Returns the current component.
supplyComponent() - Method in class adams.flow.sink.WekaInstancesDisplay: Supplies the component.
supplyComponent() - Method in class adams.flow.sink.WekaTreeVisualizer: Returns the current component.
supplyText() - Method in class adams.flow.sink.WekaInstancesDisplay: Supplies the text.
supplyText() - Method in class adams.flow.sink.WekaInstanceViewer: Supplies the text.
supplyText() - Method in class adams.gui.tools.wekainvestigator.output.TextualContentPanel: Supplies the text.
supplyText(InstancePanel) - Static method in class adams.flow.sink.WekaInstanceViewer: Returns the displayed instances as ARFF.
SUPPORT - Static variable in class weka.classifiers.meta.ConsensusOrVote
SUPPORT - Static variable in class weka.classifiers.meta.Veto
supportsBatchPredictions() - Method in class adams.data.wekapyroproxy.AbstractCommunicationProcessor: Returns whether batch predictions are supported.
supportsBatchPredictions() - Method in class adams.data.wekapyroproxy.FusionJsonCommunicationProcessor: Returns whether batch predictions are supported.
supportsBatchPredictions() - Method in class adams.data.wekapyroproxy.NullCommunicationProcessor: Returns whether batch predictions are supported.
supportsBatchPredictions() - Method in class adams.data.wekapyroproxy.SimpleJsonCommunicationProcessor: Returns whether batch predictions are supported.
supportsClear() - Method in class adams.flow.sink.WekaAttributeSummary: Whether "clear" is supported and shows up in the menu.
supportsClear() - Method in class adams.flow.sink.WekaClassifierErrors: Whether "clear" is supported and shows up in the menu.
supportsClear() - Method in class adams.flow.sink.WekaCostCurve: Whether "clear" is supported and shows up in the menu.
supportsClear() - Method in class adams.flow.sink.WekaGraphVisualizer: Whether "clear" is supported and shows up in the menu.
supportsClear() - Method in class adams.flow.sink.WekaInstancesDisplay: Whether "clear" is supported and shows up in the menu.
supportsClear() - Method in class adams.flow.sink.WekaInstancesPlot: Whether "clear" is supported and shows up in the menu.
supportsClear() - Method in class adams.flow.sink.WekaInstanceViewer: Whether "clear" is supported and shows up in the menu.
supportsClear() - Method in class adams.flow.sink.WekaMarginCurve: Whether "clear" is supported and shows up in the menu.
supportsClear() - Method in class adams.flow.sink.WekaThresholdCurve: Whether "clear" is supported and shows up in the menu.
supportsClear() - Method in class adams.flow.sink.WekaTreeVisualizer: Whether "clear" is supported and shows up in the menu.
supportsFavorites() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Whether the favorites button is shown or not.
supportsFavorites() - Method in class adams.gui.goe.WekaGenericObjectEditorPanel: Whether the favorites button is shown or not.
supportsHeadlessInteraction() - Method in class adams.flow.source.WekaSelectDataset: Returns whether headless interaction is supported.
supportsLimit(Object) - Method in class adams.gui.visualization.debug.objectrenderer.WekaInstancesRenderer: Returns whether a limit is supported by the renderer.
supportsStoreColorInReport() - Method in class adams.gui.visualization.instance.InstancePanel: Returns true if storing the color in the report of container's data object is supported.
supportsStoreValueInReport() - Method in class adams.gui.visualization.instance.InstancePanel: Returns true if storing a value in the report of container's data object is supported.
supportTipText() - Method in class weka.classifiers.meta.ConsensusOrVote: Returns the tip text for this property.
supportTipText() - Method in class weka.classifiers.meta.Veto: Returns the tip text for this property.
SUPPRESS_MODEL_OUTPUT - Static variable in class weka.classifiers.meta.AbstainingCascade
SUPPRESS_MODEL_OUTPUT - Static variable in class weka.classifiers.meta.ConsensusOrVote
SUPPRESS_MODEL_OUTPUT - Static variable in class weka.classifiers.meta.SuppressModelOutput
SUPPRESS_MODEL_OUTPUT - Static variable in class weka.classifiers.meta.ThresholdedBinaryClassification
SUPPRESS_MODEL_OUTPUT - Static variable in class weka.classifiers.meta.Veto
SuppressModelOutput - Class in weka.classifiers.meta: Meta-classifier that enables the user to suppress the model output.
Useful for ensembles, since their output can be extremely long.
SuppressModelOutput() - Constructor for class weka.classifiers.meta.SuppressModelOutput
suppressModelOutputTipText() - Method in class weka.classifiers.meta.AbstainingCascade: Returns the tip text for this property.
suppressModelOutputTipText() - Method in class weka.classifiers.meta.ConsensusOrVote: Returns the tip text for this property.
suppressModelOutputTipText() - Method in class weka.classifiers.meta.SuppressModelOutput: Returns the tip text for this property.
suppressModelOutputTipText() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Returns the tip text for this property.
suppressModelOutputTipText() - Method in class weka.classifiers.meta.Veto: Returns the tip text for this property.
suppressModelOutputTipText() - Method in class weka.classifiers.meta.VotedImbalance: Returns the tip text for this property.
suppressModelOutputTipText() - Method in interface weka.core.ModelOutputHandler: Returns the tip text for this property.
SVMLightSpreadSheetReader - Class in adams.data.io.input: Reads WEKA datasets in ARFF format and turns them into spreadsheets.
SVMLightSpreadSheetReader() - Constructor for class adams.data.io.input.SVMLightSpreadSheetReader
SVMLightSpreadSheetWriter - Class in adams.data.io.output: Writes a spreadsheet in SVMLight file format.
SVMLightSpreadSheetWriter() - Constructor for class adams.data.io.output.SVMLightSpreadSheetWriter
swap(int, int) - Method in class adams.gui.tools.wekainvestigator.datatable.DataTableModel: Swaps the two rows.
swap(int, int) - Method in class weka.core.InstancesView: Swaps two instances in the set.
swapAxesTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
SwapPLS - Class in adams.data.conversion: Swaps one PLS filter for another.
SwapPLS() - Constructor for class adams.data.conversion.SwapPLS
swapRowsAndColumnsTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the tip text for this property.
swapRowsAndColumnsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the tip text for this property.

T

TAB - adams.flow.transformer.WekaInstanceDumper.OutputFormat: tab-separated.
table - Variable in class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState: the table.
Table() - Constructor for class adams.gui.visualization.instance.InstanceReportFactory.Table: Initializes the table.
Table(Report) - Constructor for class adams.gui.visualization.instance.InstanceReportFactory.Table: Initializes the table.
Table(TableModel) - Constructor for class adams.gui.visualization.instance.InstanceReportFactory.Table: Initializes the table.
TABLE_CHANGED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent: the whole table changed.
tableChanged(TableModelEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: This fine grain notification tells listeners the exact range of cells, rows, or columns that changed.
TableContentPanel - Class in adams.gui.tools.wekainvestigator.output: Panel for exporting the table as spreadsheet.
TableContentPanel(BaseTable, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TableContentPanel: Initializes the panel with the specified textual component.
TableContentPanel(BaseTableWithButtons, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TableContentPanel: Initializes the panel with the specified textual component.
TableContentPanel(SortableAndSearchableTable, boolean, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TableContentPanel: Initializes the panel with the specified textual component.
TableContentPanel(SortableAndSearchableTableWithButtons, boolean, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TableContentPanel: Initializes the panel with the specified textual component.
TableContentPanel(JTable, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TableContentPanel: Initializes the panel with the specified textual component.
tableNameTipText() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the tip text for this property.
TableResultsPanel - Class in adams.gui.tools.wekamultiexperimenter.analysis: Displays the results in a table.
TableResultsPanel() - Constructor for class adams.gui.tools.wekamultiexperimenter.analysis.TableResultsPanel
TableState() - Constructor for class adams.gui.visualization.instances.instancestable.InstancesTablePopupMenuItemHelper.TableState
TAGS_ALGORITHM - Static variable in class weka.filters.unsupervised.attribute.FastWavelet: the types of algorithm.
TAGS_FILTER - Static variable in class weka.classifiers.functions.GaussianProcessesAdaptive: The filter to apply to the training data
TAGS_FILTER - Static variable in class weka.classifiers.functions.GaussianProcessesNoWeights: The filter to apply to the training data
TAGS_FILTER - Static variable in class weka.classifiers.functions.GaussianProcessesWeighted: The filter to apply to the training data
TAGS_FILTER - Static variable in class weka.classifiers.functions.GPD: The filter to apply to the training data
TAGS_ONEMISSING - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes
TAGS_ONEMISSING - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes
TAGS_PADDING - Static variable in class weka.filters.unsupervised.attribute.FastWavelet: the types of padding.
TAGS_RULES - Static variable in class weka.classifiers.meta.AbstainVote: combination rules
TAGS_SELECTION - Static variable in class weka.classifiers.functions.LinearRegressionJ: Attribute selection methods
TAGS_SELECTION - Static variable in class weka.clusterers.SAXKMeans: Initialization methods
TAGS_VALUESDIFFER - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes: the types of how to handle differing values.
TAGS_VALUESDIFFER - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: the types of how to handle differing values.
testAttributesTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the tip text for this property.
testBaseTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the tip text for this property.
testBaseTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the tip text for this property.
testDataTipText() - Method in class adams.flow.transformer.WekaGeneticAlgorithm: Returns the tip text for this property.
testerTipText() - Method in class adams.flow.transformer.WekaExperimentEvaluation: Returns the tip text for this property.
testerTipText() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput: Returns the tip text for this property.
TestingHelper - Class in weka.classifiers: Helper class for evaluating models on test data.
TestingHelper() - Constructor for class weka.classifiers.TestingHelper
TestingHelper.TestingUpdateListener - Interface in weka.classifiers: The interface for objects that listen for testing updates.
testingUpdateRequested(Instances, int, int) - Method in interface weka.classifiers.TestingHelper.TestingUpdateListener: Gets called when the testing interval reached or all instances processed.
testInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter2: tests the data whether the filter can actually handle it.
testsetTipText() - Method in class adams.flow.transformer.WekaTestSetClustererEvaluator: Returns the tip text for this property.
testsetTipText() - Method in class adams.flow.transformer.WekaTestSetEvaluator: Returns the tip text for this property.
testSetTipText() - Method in class weka.filters.unsupervised.instance.AlignDataset: Returns the tip text for this property.
testSetTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the tip text for this property.
testSplitNameTipText() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns the tip text for this property.
testSplitNameTipText() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Returns the tip text for this property.
testTipText() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the tip text for this property.
TextDirectory - Class in adams.gui.tools.wekainvestigator.source: Uses the TextDirectoryLoader to load text documents.
TextDirectory() - Constructor for class adams.gui.tools.wekainvestigator.source.TextDirectory: Instantiates the action.
TextDirectoryLoaderContainer - Class in adams.gui.tools.wekainvestigator.data: Dataset generated by TextDirectoryLoader.
TextDirectoryLoaderContainer(TextDirectoryLoader) - Constructor for class adams.gui.tools.wekainvestigator.data.TextDirectoryLoaderContainer: Loads the data using the specified loader.
TextOutput - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.output: Generates textual output.
TextOutput() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.output.TextOutput
TextStatistics - Class in adams.gui.tools.wekainvestigator.tab.attseltab.output: Generates basic text statistic.
TextStatistics - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Generates basic text statistic.
TextStatistics - Class in adams.gui.tools.wekainvestigator.tab.clustertab.output: Generates basic text statistic.
TextStatistics() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.output.TextStatistics
TextStatistics() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.TextStatistics
TextStatistics() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.output.TextStatistics
TextualContentPanel - Class in adams.gui.tools.wekainvestigator.output: Panel for exporting the textual component as text.
TextualContentPanel(BaseTextAreaWithButtons, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TextualContentPanel: Initializes the panel with the specified textual component.
TextualContentPanel(BaseTextPaneWithButtons, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TextualContentPanel: Initializes the panel with the specified textual component.
TextualContentPanel(JTextComponent, boolean) - Constructor for class adams.gui.tools.wekainvestigator.output.TextualContentPanel: Initializes the panel with the specified textual component.
ThreadSafeClassifier - Interface in weka.classifiers: Indicator interface for thread-safe classifiers.
ThreadSafeClassifierWrapper - Class in weka.classifiers.meta: Wraps an abstaining classifier and allows turning on/of abstaining.
ThreadSafeClassifierWrapper() - Constructor for class weka.classifiers.meta.ThreadSafeClassifierWrapper
THRESHOLD - adams.flow.sink.WekaThresholdCurve.AttributeName
THRESHOLD - Static variable in class weka.classifiers.meta.ClassifierCascade
THRESHOLD_CHECK - Static variable in class weka.classifiers.meta.ClassifierCascade
thresholdCheckTipText() - Method in class weka.classifiers.meta.ClassifierCascade: Returns the tip text for this property.
ThresholdCurves - Class in weka.gui.visualize.plugins: Displays all the threshold curves (ROC) in a single plot.
ThresholdCurves() - Constructor for class weka.gui.visualize.plugins.ThresholdCurves
ThresholdedBinaryClassification - Class in weka.classifiers.meta: Meta classifier for binary classification problems that allows to specify a minimum probability threshold for one of the labels.
ThresholdedBinaryClassification() - Constructor for class weka.classifiers.meta.ThresholdedBinaryClassification
thresholdsTipText() - Method in class weka.classifiers.meta.VotedImbalance: Returns the tip text for this property.
thresholdTipText() - Method in class adams.data.weka.evaluator.AbstractDatasetInstanceEvaluator: Returns the tip text for this property.
thresholdTipText() - Method in class adams.tools.CompareDatasets: Returns the tip text for this property.
thresholdTipText() - Method in class weka.classifiers.meta.ClassifierCascade: Returns the tip text for this property.
thresholdTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedAbs: Returns the tip text for this property.
thresholdTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassifiedRel: Returns the tip text for this property.
THRIFTY - weka.classifiers.trees.XGBoost.FeatureSelector
timeoutTipText() - Method in class weka.classifiers.meta.SocketFacade: Returns the tip text for this property.
titleClassDetailsTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the tip text for this property.
titleMatrixTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the tip text for this property.
titleNameColumnTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the tip text for this property.
titleSummaryTipText() - Method in class adams.flow.transformer.WekaEvaluationSummary: Returns the tip text for this property.
titleValueColumnTipText() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet: Returns the tip text for this property.
toAdams(Capabilities.Capability) - Static method in enum adams.flow.core.Capability: Turns the WEKA capability into an ADAMS one.
toAnyDateType() - Method in class adams.ml.data.DataCellView: Returns the date content, null if not a date, time or date/time.
toArray() - Method in class weka.experiment.ResultMatrixAdamsCSV: returns a 2-dimensional array with the prepared data.
toArray(Object) - Method in class adams.core.option.WekaCommandLineHandler: Generates an options array from the specified object.
toArray(List<String>) - Static method in class weka.core.WekaOptionUtils: Turns the list of options into an array.
toBinnableUsingClass(Instances) - Static method in class adams.data.binning.BinnableInstances: Turns Instances into a list of binnables using the class value.
toBinnableUsingIndex(Instances) - Static method in class adams.data.binning.BinnableInstances: Turns Instances into a list of binnables using the instance index.
toBits(double) - Method in class adams.opt.optimise.genetic.PackDataDef.DataInfo
toBoolean() - Method in class adams.ml.data.DataCellView: Checks whether the cell represents a boolean value.
toBufferedImage() - Method in class adams.gui.tools.wekainvestigator.output.ComponentContentPanel: Returns a buffered image.
toBytes(JsonObject) - Method in class weka.classifiers.meta.socketfacade.Simple: Turns the JSON object into bytes.
toCommandLine(Object) - Method in class adams.core.option.WekaCommandLineHandler: Generates a commandline from the specified object.
toCommandLine(Object) - Static method in class weka.core.WekaOptionUtils: Returns the commandline string for the object.
toCSV(Instance) - Method in class weka.classifiers.meta.socketfacade.Simple: Turns the instance into CSV.
toCSV(Instances) - Method in class weka.classifiers.meta.socketfacade.Simple: Turns the instances into CSV.
toCustomStringRepresentation(Object) - Method in class adams.gui.goe.WekaAttributeRangeEditor: Returns a custom string representation of the object.
toCustomStringRepresentation(Object) - Method in class adams.gui.goe.WekaExperimentFileEditor: Returns a custom string representation of the object.
toCustomStringRepresentation(Object) - Method in class adams.gui.goe.WekaUnorderedAttributeRangeEditor: Returns a custom string representation of the object.
toDataset(Instances) - Static method in class adams.ml.data.WekaConverter: Converts a Weka Instances object into an ADAMS Dataset.
toDate() - Method in class adams.ml.data.DataCellView: Returns the date content, null if not a date.
toDateTime() - Method in class adams.ml.data.DataCellView: Returns the date/time content, null if not a date/time.
toDateTimeMsec() - Method in class adams.ml.data.DataCellView: Returns the date/time msec content, null if not a date/time.
toDisplay() - Method in enum adams.flow.core.EvaluationStatistic: Returns the display string, including nominal/numeric if it applies.
toDisplay() - Method in enum adams.flow.core.ExperimentStatistic: Returns the display string.
toDisplay() - Method in enum adams.flow.sink.WekaThresholdCurve.AttributeName: Returns the display string.
toDisplay() - Method in enum adams.flow.transformer.WekaClassifierRanker.Measure: Returns the display string.
toDisplayShort() - Method in enum adams.flow.core.EvaluationStatistic: Returns the display string.
toDouble() - Method in class adams.ml.data.DataCellView: Returns the content as double, if possible.
toDoubleArray() - Method in class adams.data.instance.Instance: Returns the y values as double array.
toDoubleArray() - Method in class weka.core.AbstractHashableInstance: Returns the values of each attribute as an array of doubles.
toDoubleArray(Instance) - Static method in class adams.data.instance.InstanceUtils: Returns the points as double array.
toDoubleArray(List<InstancePoint>) - Static method in class adams.data.instance.InstanceUtils: Returns the points as double array.
toEnumeration(Vector) - Static method in class weka.core.WekaOptionUtils: Returns the option descriptions as an enumeration.
toEvaluationStatistic() - Method in enum adams.opt.genetic.Measure: Converts the measure into EvaluationStatistic.
toFile() - Method in class adams.data.WekaExperimentFile: Returns a file object.
toggleSortAttributeNames() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Toggles the "sort attribute names" option.
toggleUndo() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Toggles the undo state.
toGraphml(String, MessageCollection) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML: Converts the dotty string and saves it as graphml file.
toHTML(SpreadSheet) - Static method in class adams.gui.tools.wekainvestigator.output.RunInformationHelper: Turns the run information into an html table.
toInstance() - Method in class adams.data.instance.Instance: Generates a weka instance, if a dataset header is available.
toInstance(Instances, Row) - Static method in class adams.ml.data.WekaConverter: Turns an ADAMS dataset row into a Weka Instance.
toInstances() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the collected results.
toInstances(SpreadSheet) - Method in class adams.data.spreadsheet.filter.WekaFilter: Converts the spreadsheet into an Instances object.
toInstances(TableRowRange) - Method in class adams.gui.visualization.instances.InstancesTable: Returns the data.
toInstances(TableRowRange, boolean) - Method in class adams.gui.visualization.instances.InstancesTable: Returns the data.
toInstances(Dataset) - Static method in class adams.ml.data.WekaConverter: Converts an ADAMS Dataset to Weka Instances.
toInstances(List<Binnable<Instance>>) - Static method in class adams.data.binning.BinnableInstances: Turns a binnable list back into Instances.
toInstances(Instances, Matrix, Matrix) - Static method in class weka.core.matrix.MatrixHelper: returns the X and Y matrix again as Instances object, based on the given header (must have a class attribute set).
toInstances(Instances, Matrix, Matrix) - Method in class weka.filters.supervised.attribute.PLSFilterExtended: Override superclass method, as this cannot deal with multiple y attributes Returns the X and Y matrix again as Instances object, based on the given header (must have a class attribute set).
TokenCleaner - Interface in weka.core.tokenizers.cleaners: Interface for token cleaners.
tokenize(String) - Method in class weka.core.tokenizers.MultiTokenizer: Sets the string to tokenize.
tokenize(String) - Method in class weka.core.tokenizers.PreCleanedTokenizer: Sets the string to tokenize.
TOKENIZER - Static variable in class weka.core.tokenizers.MultiTokenizer
tokenizersTipText() - Method in class weka.core.tokenizers.MultiTokenizer: Returns the tip text for this property.
tolerateHeaderChangesTipText() - Method in class adams.data.instances.AbstractInstanceGenerator: Returns the tip text for this property.
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
toMap(Package) - Static method in class weka.core.WekaPackageUtils: Turns the package into a map.
toMatrix() - Method in class adams.ml.data.InstancesView: Returns the spreadsheet as matrix, with the header as the first row.
toMatrixString(int, int[][], int[], Instances) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Returns a "confusion" style matrix of classes to clusters assignments
toParamsArray(Object) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab: Turns a parameter object into a string array.
topKTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the topK option.
topOfTree() - Method in class weka.classifiers.trees.m5.Rule2: Returns the top of the tree.
toRaw() - Method in enum adams.flow.core.EvaluationStatistic: Returns the raw enum string.
toRaw() - Method in enum adams.flow.core.ExperimentStatistic: Returns the raw enum string.
toRaw() - Method in enum adams.flow.sink.WekaThresholdCurve.AttributeName: Returns the raw enum string.
toRaw() - Method in enum adams.flow.transformer.WekaClassifierRanker.Measure: Returns the raw enum string.
toShortCommandLine(Object) - Method in class adams.core.option.WekaCommandLineHandler: Generates a commandline from the specified object.
toSpreadSheet() - Method in class adams.data.instance.Instance: Returns the content as spreadsheet.
toSpreadSheet() - Method in class adams.gui.tools.wekainvestigator.output.TableContentPanel: Returns the content as spreadsheet.
toSpreadSheet() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the collected results.
toSpreadSheet() - Method in class adams.gui.visualization.instances.InstancesTableModel: Returns the content as spreadsheet.
toSpreadSheet(LoggingSupporter, MessageCollection, ResultItem, boolean, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.PredictionHelper: Turns the result item into a spreadsheet with the predictions.
toSpreadSheet(LoggingSupporter, MessageCollection, ResultItem, boolean, boolean, boolean, boolean, boolean, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.PredictionHelper: Turns the result item into a spreadsheet with the predictions.
toSpreadSheet(LoggingSupporter, MessageCollection, Evaluation, int[], SpreadSheet, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.PredictionHelper: Turns the result item into a spreadsheet with the predictions.
toSpreadSheet(LoggingSupporter, MessageCollection, Evaluation, int[], SpreadSheet, boolean, boolean, boolean, boolean, boolean) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.PredictionHelper: Turns the result item into a spreadsheet with the predictions.
toSpreadSheet(Instances) - Method in class adams.data.spreadsheet.filter.WekaFilter: Converts the Instances into a SpreadSheet object.
toString() - Method in class adams.data.conversion.WekaPredictionContainerToSpreadSheet.SortContainer: Returns a short string description of the container.
toString() - Method in class adams.data.instance.InstancePoint: Returns a string representation of the point.
toString() - Method in class adams.data.instances.InstanceComparator: Returns a short description of the comparator.
toString() - Method in class adams.data.weka.evaluator.AbstractCrossvalidatedInstanceEvaluator.EvaluationContainer: Returns a string representation of the stored data.
toString() - Method in class adams.data.weka.evaluator.IntervalEstimatorBased.SortedInterval: Returns the intervals as string.
toString() - Method in class adams.data.weka.predictions.AbstractErrorScaler: Returns the commandline of this object.
toString() - Method in enum adams.flow.core.EvaluationStatistic: Returns the displays string.
toString() - Method in enum adams.flow.core.ExperimentStatistic: Returns the displays string.
toString() - Method in enum adams.flow.sink.WekaThresholdCurve.AttributeName: Returns the display string.
toString() - Method in class adams.flow.transformer.WekaAccumulatedError.SortablePrediction: Returns a string representation of the wrapped prediction.
toString() - Method in enum adams.flow.transformer.WekaClassifierRanker.Measure: Returns the display string.
toString() - Method in class adams.flow.transformer.WekaClassifierRanker.RankingJob: Returns a string representation of the job.
toString() - Method in class adams.flow.transformer.wekadatasetsmerge.AbstractMerge.SourceAttribute
toString() - Method in class adams.flow.transformer.WekaFilter.BatchFilterJob: Returns a string representation of this job.
toString() - Method in class adams.flow.transformer.WekaTestSetEvaluator.EvaluateJob: Returns a string representation of this job.
toString() - Method in class adams.flow.transformer.WekaTrainAssociator.TrainJob: Returns a string representation of this job.
toString() - Method in class adams.flow.transformer.WekaTrainClassifier.BatchTrainJob: Returns a string representation of this job.
toString() - Method in class adams.flow.transformer.WekaTrainClusterer.BatchTrainJob: Returns a string representation of this job.
toString() - Method in class adams.flow.transformer.WekaTrainTestSetEvaluator.EvaluateJob: Returns a string representation of this job.
toString() - Method in class adams.gui.event.InstancesSortSetupEvent: Returns a short description of the object.
toString() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Returns a short description of the container.
toString() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Returns just the name of the evaluation.
toString() - Method in class adams.gui.tools.wekainvestigator.output.AbstractResultItem: Returns a short description of the container.
toString() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: Returns a short description of the container.
toString() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Returns a short description of the container.
toString() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Returns a short description of the container.
toString() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Returns a short description of the container.
toString() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: Returns a short description of the container.
toString() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel: Returns the name of the panel.
toString() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractResultsPanel: Just returns the name of the panel.
toString() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment.AbstractExperimentJob: Returns a string representation of this job.
toString() - Method in class adams.gui.visualization.instance.InstanceContainer: Returns a short string representation of the container.
toString() - Method in class adams.gui.visualization.instances.InstancesColumnComboBox.ColumnContainer: Returns the name and index of the column as string representation.
toString() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: Returns a short description of the current setup.
toString() - Method in class adams.ml.data.InstancesHeaderRow: Simply returns the internal hashtable of cells as string.
toString() - Method in class adams.multiprocess.WekaCrossValidationJob: Returns a string representation of this job.
toString() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Returns a short string of the algorithm with the currently best fitness.
toString() - Method in class adams.opt.optimise.genetic.PackData
toString() - Method in class adams.opt.optimise.GeneticAlgorithm.GAJob
toString() - Method in class weka.attributeSelection.AbstractPLSAttributeEval: Outputs the underlying linear regression model.
toString() - Method in class weka.attributeSelection.LinearRegressionAttributeEval: Outputs the underlying linear regression model.
toString() - Method in class weka.classifiers.AbstractSplitGenerator: Returns a short description of the generator.
toString() - Method in class weka.classifiers.AggregateEvaluations: Returns a short description of current state.
toString() - Method in class weka.classifiers.BinnedNumericClassCrossValidationFoldGenerator: Returns a short description of the generator.
toString() - Method in class weka.classifiers.BinnedNumericClassRandomSplitGenerator: Returns a short description of the generator.
toString() - Method in class weka.classifiers.DefaultCrossValidationFoldGenerator: Returns a short description of the generator.
toString() - Method in class weka.classifiers.DefaultRandomSplitGenerator: Returns a short description of the generator.
toString() - Method in class weka.classifiers.functions.ClassificationViaPLS: Returns a string representation of the built model.
toString() - Method in class weka.classifiers.functions.FakeClassifier: Returns a string representation of the built model.
toString() - Method in class weka.classifiers.functions.GaussianProcessesAdaptive: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.GaussianProcessesNoWeights: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.GaussianProcessesWeighted: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.GeneticAlgorithm: Returns a string representation of the built model.
toString() - Method in class weka.classifiers.functions.GPD: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.LinearRegressionJ: Outputs the linear regression model as a string.
toString() - Method in class weka.classifiers.functions.MathExpressionClassifier: Returns a string representation of the built model.
toString() - Method in class weka.classifiers.functions.PLSClassifierWeighted: returns a string representation of the classifier
toString() - Method in class weka.classifiers.functions.PLSWeighted: returns a string representation of the classifier
toString() - Method in class weka.classifiers.functions.PyroProxy: Returns a short description of the classifier.
toString() - Method in class weka.classifiers.functions.SimpleLinearRegressionWithAccess: Returns a description of this classifier as a string
toString() - Method in class weka.classifiers.GroupedBinnedNumericClassCrossValidationFoldGenerator: Returns a short description of the generator.
toString() - Method in class weka.classifiers.GroupedBinnedNumericClassRandomSplitGenerator: Returns a short description of the generator.
toString() - Method in class weka.classifiers.GroupedCrossValidationFoldGenerator: Returns a short description of the generator.
toString() - Method in class weka.classifiers.GroupedCrossValidationFoldGeneratorUsingNumericClassValues: Returns a short description of the generator.
toString() - Method in class weka.classifiers.GroupedRandomSplitGenerator: Returns a short description of the generator.
toString() - Method in class weka.classifiers.lazy.AbstainingLWL: Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.LWLDatasetBuilder.LWLContainer: Outputs distances and original indices.
toString() - Method in class weka.classifiers.lazy.LWLDatasetBuilder: Returns a short string description of the setup.
toString() - Method in class weka.classifiers.lazy.LWLSynchro: Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.LWLSynchroPrefilter: Returns a description of this classifier.
toString() - Method in class weka.classifiers.LeaveOneOutByValueGenerator: Returns a short description of the generator.
toString() - Method in class weka.classifiers.meta.AbstainAttributePercentile: Returns description of classifier.
toString() - Method in class weka.classifiers.meta.AbstainAverage: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.AbstainAverageWithClassifierWeights: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.AbstainingCascade: Outputs the ensemble model.
toString() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: Returns the model.
toString() - Method in class weka.classifiers.meta.AbstainLeastMedianSq: Returns description of classifier.
toString() - Method in class weka.classifiers.meta.AbstainMinimumProbability: Returns the model.
toString() - Method in class weka.classifiers.meta.AbstainVote: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.ClassificationViaRegressionD: Prints the classifiers.
toString() - Method in class weka.classifiers.meta.ClassifierCascade: Outputs a short description of the classifier model.
toString() - Method in class weka.classifiers.meta.ConsensusOrVote: Outputs the ensemble model.
toString() - Method in class weka.classifiers.meta.Corr: Returns description of classifier.
toString() - Method in class weka.classifiers.meta.Fallback: Returns a description of the model.
toString() - Method in class weka.classifiers.meta.HighLowSplit: Returns description of classifier.
toString() - Method in class weka.classifiers.meta.HighLowSplitSingleClassifier: Returns description of classifier.
toString() - Method in class weka.classifiers.meta.LeastMedianSq: Returns description of classifier.
toString() - Method in class weka.classifiers.meta.LogClassRegressor: Returns description of classifier.
toString() - Method in class weka.classifiers.meta.LogTargetRegressor: Returns description of classifier.
toString() - Method in class weka.classifiers.meta.MinMaxLimits: Returns description of classifier.
toString() - Method in class weka.classifiers.meta.PeakTransformed: Returns description of classifier.
toString() - Method in class weka.classifiers.meta.RangeCheck: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.SocketFacade: Just returns the commandline options.
toString() - Method in class weka.classifiers.meta.SubsetEnsemble: Returns a string representation of the classifier.
toString() - Method in class weka.classifiers.meta.SumTransformed: Returns description of classifier.
toString() - Method in class weka.classifiers.meta.SuppressModelOutput: Returns a string representation of the model.
toString() - Method in class weka.classifiers.meta.ThreadSafeClassifierWrapper: Returns the model.
toString() - Method in class weka.classifiers.meta.ThresholdedBinaryClassification: Returns the classifier's model.
toString() - Method in class weka.classifiers.meta.Veto: Outputs the ensemble model.
toString() - Method in class weka.classifiers.meta.VotedImbalance: Returns a string representation of the classifier.
toString() - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Returns a string representation of the base classifier.
toString() - Method in class weka.classifiers.MultiLevelSplitGenerator: Returns a short description of the generator.
toString() - Method in interface weka.classifiers.SplitGenerator: Returns a short description of the generator.
toString() - Method in class weka.classifiers.trees.m5.M5Base2: Returns a description of the classifier
toString() - Method in class weka.classifiers.trees.m5.Rule2: Return a description of the m5 tree or rule
toString() - Method in class weka.classifiers.trees.m5.RuleNode2: print the linear model at this node
toString() - Method in class weka.classifiers.trees.RandomModelTrees
toString() - Method in class weka.classifiers.trees.RandomRegressionForest: Returns description of the classifier.
toString() - Method in class weka.classifiers.trees.XGBoost: Returns a description of this classifier.
toString() - Method in class weka.clusterers.SAXKMeans: return a string describing this clusterer.
toString() - Method in class weka.core.AbstractHashableInstance: Returns the value of the Instance's toString() method.
toString() - Method in class weka.core.InstanceGrouping: Returns the groups and their indices.
toString(int) - Method in class weka.core.AbstractHashableInstance: Returns the description of one value of the instance as a string.
toString(int, int) - Method in class weka.core.AbstractHashableInstance: Returns the description of one value of the instance as a string.
toString(int, StringBuffer, List<String>) - Method in class weka.classifiers.trees.RandomRegressionForest.Node: Generates a string representation of the node.
toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaAttributeIndexParsing: Returns the object as string.
toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaAttributeRangeParsing: Returns the object as string.
toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaExperimentFileParsing: Returns the file as string.
toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaLabelIndexParsing: Returns the object as string.
toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaLabelRangeParsing: Returns the object as string.
toString(AbstractOption, Object) - Static method in class adams.core.option.parsing.WekaUnorderedAttributeRangeParsing: Returns the object as string.
toString(AbstractOption, Object) - Static method in enum adams.flow.core.EvaluationStatistic: Returns the enum as string.
toString(AbstractOption, Object) - Static method in enum adams.flow.core.ExperimentStatistic: Returns the enum as string.
toString(AbstractOption, Object) - Static method in enum adams.flow.sink.WekaThresholdCurve.AttributeName: Returns the enum as string.
toString(AbstractOption, Object) - Static method in enum adams.flow.transformer.WekaClassifierRanker.Measure: Returns the enum as string.
toString(SpreadSheet) - Static method in class adams.gui.tools.wekainvestigator.output.RunInformationHelper: Turns the run information into a string representation.
toString(SpreadSheet) - Method in class weka.experiment.ResultMatrixAdamsCSV: Turns the spreadsheet into a string.
toString(Object) - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Not used.
toString(Object) - Method in class adams.gui.goe.WekaGenericObjectEditorPanel: Converts the value into its string representation.
toString(Attribute) - Method in class weka.core.AbstractHashableInstance: Returns the description of one value of the instance as a string.
toString(Attribute, int) - Method in class weka.core.AbstractHashableInstance: Returns the description of one value of the instance as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixAdamsCSV: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixMediaWiki: returns the header of the matrix as a string.
toStringKey() - Method in class weka.experiment.ResultMatrixAdamsCSV: returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixMediaWiki: returns a key for all the col names, for better readability if the names got cut off.
toStringMatrix() - Method in class weka.experiment.ResultMatrixAdamsCSV: returns the matrix in CSV format.
toStringMatrix() - Method in class weka.experiment.ResultMatrixMediaWiki: returns the matrix in CSV format.
toStringMaxDecimalDigits(int) - Method in class weka.core.AbstractHashableInstance: Returns the description of one instance with any numeric values printed at the supplied maximum number of decimal places.
toStringNoWeight() - Method in class weka.core.AbstractHashableInstance: Returns the description of one instance (without weight appended).
toStringNoWeight(int) - Method in class weka.core.AbstractHashableInstance: Returns the description of one instance (without weight appended).
toStringOLD() - Method in class weka.classifiers.trees.RandomModelTrees: Returns description of the bagged classifier.
toStringRanking() - Method in class weka.experiment.ResultMatrixAdamsCSV: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixMediaWiki: returns the ranking in a string representation.
toStringSummary() - Method in class weka.experiment.ResultMatrixAdamsCSV: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixMediaWiki: returns the summary as string.
toSummaryString() - Method in class weka.classifiers.evaluation.Bias: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toSummaryString() - Method in class weka.classifiers.evaluation.Dice: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toSummaryString() - Method in class weka.classifiers.evaluation.MSLE: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toSummaryString() - Method in class weka.classifiers.evaluation.RPD: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toSummaryString() - Method in class weka.classifiers.evaluation.RSquared: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toSummaryString() - Method in class weka.classifiers.evaluation.SDR: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toTime() - Method in class adams.ml.data.DataCellView: Returns the time content, null if not a time.
toTimeMsec() - Method in class adams.ml.data.DataCellView: Returns the time/msec content, null if not a time/msec.
toView(int[], int[]) - Method in class adams.ml.data.InstancesView: Creates a view of the spreadsheet with the specified rows/columns.
toWeka(Capability) - Static method in enum adams.flow.core.Capability: Turns the ADAMS capability into a WEKA one.
TP_RATE - adams.flow.sink.WekaThresholdCurve.AttributeName
Train - Class in adams.gui.tools.wekainvestigator.tab.associatetab.evaluation: Builds an associator on a dataset.
Train - Class in adams.gui.tools.wekainvestigator.tab.attseltab.evaluation: Performs attribute selection on the train data.
Train() - Constructor for class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train
Train() - Constructor for class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train
TRAIN_TEST_SPLIT_ORDER_PRESERVED - adams.flow.sink.WekaExperimentGenerator.EvaluationType: train/test split order preserved.
TRAIN_TEST_SPLIT_RANDOMIZED - adams.flow.sink.WekaExperimentGenerator.EvaluationType: train/test split randomized.
TrainableColumnFinder - Interface in adams.data.weka.columnfinder: Interface for ColumnFinder algorithms that can be trained.
TrainableRowFinder - Interface in adams.data.weka.rowfinder: Interface for RowFinder algorithms that can be trained.
trainColumnFinder(Instances) - Method in class adams.data.weka.columnfinder.AbstractTrainableColumnFinder: Trains the column finder with the specified dataset.
trainColumnFinder(Instances) - Method in interface adams.data.weka.columnfinder.TrainableColumnFinder: Trains the column finder with the specified dataset.
TrainJob(Associator, Instances) - Constructor for class adams.flow.transformer.WekaTrainAssociator.TrainJob: Initializes the job.
trainRowFinder(Instances) - Method in class adams.data.weka.rowfinder.AbstractTrainableRowFinder: Trains the row finder with the specified dataset.
trainRowFinder(Instances) - Method in interface adams.data.weka.rowfinder.TrainableRowFinder: Trains the row finder with the specified dataset.
trainSplitNameTipText() - Method in class adams.flow.transformer.indexedsplitsrunsevaluation.InstancesIndexedSplitsRunsEvaluation: Returns the tip text for this property.
trainSplitNameTipText() - Method in class adams.flow.transformer.indexedsplitsrunspredictions.InstancesIndexedSplitsRunsPredictions: Returns the tip text for this property.
TrainTestSet - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation: Uses dedicated train/test sets.
TrainTestSet - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation: Uses dedicated train/test sets.
TrainTestSet() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet
TrainTestSet() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet
TrainTestSplit - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation: Uses a (random) percentage split to generate train/test.
TrainTestSplit - Class in adams.gui.tools.wekainvestigator.tab.clustertab.evaluation: Uses a (random) percentage split to generate train/test.
TrainTestSplit() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit
TrainTestSplit() - Constructor for class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit
TrainTestSplitExperiment - Class in adams.gui.tools.wekamultiexperimenter.experiment: Performs train-test splits.
TrainTestSplitExperiment() - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment
TrainTestSplitExperiment.TrainTestSplitExperimentJob - Class in adams.gui.tools.wekamultiexperimenter.experiment
TrainTestSplitExperimentJob(TrainTestSplitExperiment, int, Classifier, Instances) - Constructor for class adams.gui.tools.wekamultiexperimenter.experiment.TrainTestSplitExperiment.TrainTestSplitExperimentJob: Initializes the run.
TrainTestSplitSetup - Class in adams.gui.tools.wekainvestigator.tab.experimenttab.setup: Setup for a train/test-split experiment.
TrainTestSplitSetup() - Constructor for class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup
trainTipText() - Method in class adams.flow.transformer.WekaClassifierRanker: Returns the tip text for this property.
TrainValidateTestSet - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation: Uses dedicated train/validate/test sets.
TrainValidateTestSet() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet
transferAdditionalAttributes(SelectOptionPanel, Instances) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.AbstractClassifierEvaluation: Transfers the additional attributes into a spreadsheet.
transferCapability(Capabilities, Capabilities.Capability, Capabilities, Capability) - Static method in class adams.ml.data.WekaConverter: Transfers the specified capability if enabled.
transform(Instance) - Method in class weka.classifiers.meta.LogClassRegressor: Transform instance.
transform(Instance) - Method in class weka.classifiers.meta.LogTargetRegressor: Transform instance.
transform(Instance) - Method in class weka.core.SAXDistance
transform(Instance) - Method in class weka.core.WeightedEuclideanDistance
transform(Instance) - Method in class weka.core.WeightedEuclideanDistanceRidge
transform(Instances) - Method in class adams.data.instancesanalysis.pls.AbstractPLS: Transforms the data, initializes if necessary.
transformInstance(Instance) - Method in class weka.classifiers.meta.PeakTransformed: Just finds the maximum peak.
transformInstance(Instance) - Method in class weka.classifiers.meta.SumTransformed: Just sums up all the peaks.
transformInstance(Instance) - Method in class weka.core.neighboursearch.FilteredSearch
transformInstance(Instance) - Method in class weka.core.neighboursearch.PCANNSearch
transformInstance(Instance) - Method in class weka.core.neighboursearch.PLSNNSearch
transformInstance(Instance) - Method in class weka.core.neighboursearch.TransformNNSearch
transformInstances(Instances) - Method in class weka.core.neighboursearch.FilteredSearch
transformInstances(Instances) - Method in class weka.core.neighboursearch.PCANNSearch
transformInstances(Instances) - Method in class weka.core.neighboursearch.PLSNNSearch
TransformNNSearch - Class in weka.core.neighboursearch
TransformNNSearch() - Constructor for class weka.core.neighboursearch.TransformNNSearch
TransformNNSearch(Instances) - Constructor for class weka.core.neighboursearch.TransformNNSearch
TREE - weka.classifiers.trees.XGBoost.NormaliseType
TreeGraphML - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Displays the GraphML source code of the tree graph.
TreeGraphML() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeGraphML
treeMethodTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the treeMethod option.
treeToString(int) - Method in class weka.classifiers.trees.m5.RuleNode2: Recursively builds a textual description of the tree
TreeVisualizer - Class in adams.gui.menu: Displays data in the tree visualizer.
TreeVisualizer - Class in adams.gui.tools.previewbrowser: Displays trees in dot notation.
TreeVisualizer - Class in adams.gui.tools.wekainvestigator.tab.classifytab.output: Displays the tree that the model generated.
TreeVisualizer() - Constructor for class adams.gui.menu.TreeVisualizer: Initializes the menu item with no owner.
TreeVisualizer() - Constructor for class adams.gui.tools.previewbrowser.TreeVisualizer
TreeVisualizer() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.output.TreeVisualizer
TreeVisualizer(AbstractApplicationFrame) - Constructor for class adams.gui.menu.TreeVisualizer: Initializes the menu item.
trialsTipText() - Method in class weka.classifiers.trees.RandomModelTrees: Returns the tip text for this property.
TRIANGLE - adams.gui.visualization.instance.InstanceLinePaintlet.MarkerShape: a triangle.
trimIDs(List<String>) - Method in class adams.gui.visualization.instance.InstanceComparePanel: Removes the leading 0s.
TRUE_NEG - adams.flow.sink.WekaThresholdCurve.AttributeName
TRUE_NEG_RATE - adams.opt.genetic.Measure: true negative rate.
TRUE_NEGATIVE_RATE - adams.flow.core.EvaluationStatistic
TRUE_NEGATIVE_RATE - adams.flow.core.ExperimentStatistic
TRUE_POS - adams.flow.sink.WekaThresholdCurve.AttributeName
TRUE_POS_RATE - adams.opt.genetic.Measure: true positive rate.
TRUE_POSITIVE_RATE - adams.flow.core.EvaluationStatistic
TRUE_POSITIVE_RATE - adams.flow.core.ExperimentStatistic
TURN_OFF_ABSTAINING - Static variable in class weka.classifiers.meta.AbstainingClassifierWrapper
turnChecksOff() - Method in class weka.classifiers.functions.LinearRegressionJ: Turns off checks for missing values, etc.
turnChecksOn() - Method in class weka.classifiers.functions.LinearRegressionJ: Turns on checks for missing values, etc.
turnIntoLeaf(Instances) - Method in class weka.classifiers.trees.RandomRegressionForest.Node: turns the node into a leaf
turnOffAbstainingTipText() - Method in class weka.classifiers.meta.AbstainingClassifierWrapper: Returns the tip text for this property
TWEEDIE_REGRESSION - weka.classifiers.trees.XGBoost.Objective
tweedieVariancePowerTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the tweedieVariancePower option.
TYPE - Static variable in class weka.filters.unsupervised.attribute.NominalToNumeric
typeTipText() - Method in class adams.flow.transformer.WekaClassifierInfo: Returns the tip text for this property.
typeTipText() - Method in class adams.flow.transformer.WekaClustererInfo: Returns the tip text for this property.
typeTipText() - Method in class adams.flow.transformer.WekaEvaluationInfo: Returns the tip text for this property.
typeTipText() - Method in class adams.flow.transformer.WekaExtractArray: Returns the tip text for this property.
typeTipText() - Method in class adams.flow.transformer.WekaInstancesInfo: Returns the tip text for this property.
typeTipText() - Method in class weka.filters.unsupervised.attribute.NominalToNumeric: Returns the tip text for this property.

U

UI_DIVIDERLOCATION - Static variable in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.PerFoldMultiPagePane
UNARY_ATTRIBUTES - adams.flow.core.Capability: can handle unary attributes.
UNARY_CLASS - adams.flow.core.Capability: can handle unary classes.
undo() - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: Performs an undo if possible.
undo() - Method in class adams.gui.visualization.instances.InstancesTable: undoes the last action
undo() - Method in class adams.gui.visualization.instances.InstancesTableModel: undoes the last action
undo() - Method in class weka.gui.explorer.ExplorerExt: Performs an undo.
undo(int[]) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithDataTable: Performs undo on the selected rows.
UNDO_DISABLED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent: undo disabled.
UNDO_ENABLED - Static variable in class adams.gui.event.WekaInvestigatorDataEvent: undo enabled.
undoOccurred(UndoEvent) - Method in class adams.gui.tools.wekainvestigator.data.AbstractDataContainer: An undo event, like add or remove, has occurred.
undoOccurred(UndoEvent) - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: An undo event, like add or remove, has occurred.
unhandledInputType(Object, MessageCollection) - Method in class adams.flow.transformer.wekapackagemanageraction.AbstractWekaPackageManagerAction: Adds an error message that the input type is not supported.
UNIFORM - weka.classifiers.trees.XGBoost.SampleType
Uninstall - Class in adams.flow.transformer.wekapackagemanageraction: Action that removes installed packages.
Uninstall() - Constructor for class adams.flow.transformer.wekapackagemanageraction.Uninstall
uniqueIDTipText() - Method in class adams.flow.transformer.wekadatasetsmerge.JoinOnID: Gets the tip-text for the unique ID option.
uniqueIDTipText() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the tip text for this property.
unprunedTipText() - Method in class weka.classifiers.trees.m5.M5Base2: Returns the tip text for this property
unquoteAttribute(String) - Method in class weka.core.converters.SimpleArffLoader: Unquotes the attribute name.
unsetTipText() - Method in class adams.flow.transformer.WekaClassSelector: Returns the tip text for this property.
UNWEIGHTED_MACRO_F_MEASURE - adams.flow.core.EvaluationStatistic
UNWEIGHTED_MICRO_F_MEASURE - adams.flow.core.EvaluationStatistic
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.AbstractEditableDataTableAction: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Append: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Compatibility: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Copy: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Merge: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Randomize: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.RandomSubset: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.RemoveTestSet: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Rename: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Revert: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Save: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.SaveIndexedSplitsRuns: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.datatable.action.Split: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.evaluation.AbstractEvaluation: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.evaluation.Train: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.CrossValidation: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.evaluation.Train: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.BuildModel: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.CrossValidation: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.FromPredictions: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.IndexedSplitsRunsEvaluation: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.ReevaluateModel: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.RepeatedCrossValidation: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSet: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainTestSplit: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.TrainValidateTestSet: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.BuildModel: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ClassesToClusters: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.CrossValidation: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.ReevaluateModel: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSet: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.evaluation.TrainTestSplit: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.CrossValidationSetup: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.setup.TrainTestSplitSetup: Updates the settings panel.
update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.AbstractSelectedAttributesAction: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToDate: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToNominal: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ConvertToString: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.Remove: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.Rename: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.ReorderAttributes: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.UseAsClass: Updates the action.
update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeSummaryPanel: Updates the display.
update() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.MultiAttributeVisualizationPanel: Updates the display.
update() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.AbstractAnalysisPanel: Updates the GUI.
update() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Updates the GUI.
update() - Method in class adams.gui.tools.wekamultiexperimenter.runner.AbstractExperimentRunner: Updates the owner's state.
update() - Method in class adams.gui.tools.wekamultiexperimenter.setup.AbstractSetupOptionPanel: Performs GUI updates.
update() - Method in class adams.gui.tools.wekamultiexperimenter.setup.ClassifierPanel: Updates the buttons.
update() - Method in class adams.gui.tools.wekamultiexperimenter.setup.DatasetPanel: Updates the buttons.
update() - Method in class adams.gui.visualization.instance.InstanceComparePanel.DatasetPanel: Updates buttons, etc.
update() - Method in class adams.gui.visualization.instances.InstancesColumnComboBox: Updates the content of the combobox.
update() - Method in class adams.gui.visualization.instances.InstancesPanel: Updates the combobox.
update() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: Resets the comboboxes.
update() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortPanel: Updates the display.
update() - Method in class weka.gui.explorer.ExplorerExt: Updates title and menu items.
update(AbstractEnvironment) - Method in class adams.env.InstanceCompareDefinition: Updates the environment object with its definition for the props file (whether to add/replace/etc the values).
update(AbstractEnvironment) - Method in class adams.env.InstanceExplorerDefinition: Updates the environment object with its definition for the props file (whether to add/replace/etc the values).
update(AbstractEnvironment) - Method in class adams.env.WekaInvestigatorDefinition: Updates the environment object with its definition for the props file (whether to add/replace/etc the values).
update(AbstractEnvironment) - Method in class adams.env.WekaInvestigatorShortcutsDefinition: Updates the environment object with its definition for the props file (whether to add/replace/etc the values).
update(WekaExperimentContainer) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: Updates the item.
update(WekaExperimentContainer, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.experimenttab.ResultItem: Updates the item.
update(String, Serializable, Clusterer, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Updates the item.
update(AssociatorEvaluation, Associator, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.associatetab.ResultItem: Updates the item.
update(AttributeSelection, int, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Updates the item.
update(AttributeSelection, int, Instances, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Updates the item.
update(AttributeSelection, Instances, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.attseltab.ResultItem: Updates the item.
update(Evaluation, Classifier) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Updates the item.
update(Evaluation, Classifier, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Updates the item.
update(Evaluation, Classifier, MetaData, int[], SpreadSheet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Updates the item.
update(Evaluation, Evaluation[], Classifier, Classifier[], MetaData, int[], SpreadSheet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Updates the item.
update(Evaluation, Evaluation[], Evaluation[], Classifier, Classifier[], Classifier[], MetaData, int[], int[][], SpreadSheet) - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.ResultItem: Updates the item.
update(ClusterEvaluation, String, Serializable, Clusterer, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Updates the item.
update(ClusterEvaluation, Clusterer, MetaData) - Method in class adams.gui.tools.wekainvestigator.tab.clustertab.ResultItem: Updates the item.
update(Instance) - Method in class weka.core.neighboursearch.FilteredSearch: Updates the LinearNNSearch to cater for the new added instance.
update(Instance) - Method in class weka.core.neighboursearch.NewNNSearch: Updates the LinearNNSearch to cater for the new added instance.
update(Instance) - Method in class weka.core.neighboursearch.PCANNSearch: Updates the LinearNNSearch to cater for the new added instance.
update(Instance) - Method in class weka.core.neighboursearch.PLSNNSearch: Updates the LinearNNSearch to cater for the new added instance.
UPDATE - weka.classifiers.trees.XGBoost.ProcessType
UPDATE_HEADER - Static variable in class weka.filters.unsupervised.instance.RemoveWithLabels
updateActions() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Updates the actions.
updateAttributes() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Updates the attributes model.
updateAttributeSelection() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: For updating the state of the selected attributes text field and button.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTabWithEditableDataTable: Updates the state of the buttons.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab: Updates the buttons.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab: Updates the buttons.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab: Updates the buttons.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab: Updates the buttons.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.DataQueryTab: Updates the state of the buttons.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab: Updates the buttons.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.IndependentComponentsTab: Updates the buttons.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Updates the buttons.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.PartialLeastSquaresTab: Updates the buttons.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.PreprocessTab: Updates the buttons.
updateButtons() - Method in class adams.gui.tools.wekainvestigator.tab.PrincipalComponentsTab: Updates the buttons.
updateButtons() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Updates the buttons.
updateButtons() - Method in class adams.gui.visualization.instances.instancestable.InstancesSortDefinitionPanel: Updates the enabled status of the buttons.
updateButtons() - Method in class weka.gui.explorer.MultiExplorer: Updates the enabled state of the buttons.
updateCapabilitiesFilter(Capabilities) - Method in class weka.gui.explorer.ExperimentPanel: updates the capabilities filter of the GOE.
updateClassAttribute(Instances) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Updates the class attribute, if not set.
updateClassifier(Instance) - Method in class weka.classifiers.functions.FakeClassifier: Does nothing.
updateClassifier(Instance) - Method in class weka.classifiers.functions.MathExpressionClassifier: Does nothing.
updateComparisonBase() - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel: Updates the base of comparison.
updateContainerColorTipText() - Method in class adams.gui.visualization.instance.ReportColorInstancePaintlet: Returns the tip text for this property.
updateDataTable() - Method in class adams.gui.visualization.weka.AbstractInstanceInfoFrame: Updates the data in the data table.
updateDisplay() - Method in class adams.gui.goe.WekaGenericArrayEditorPanel: Updates the display.
updateDistance(double, double) - Method in class weka.core.SAXDistance: Updates the current distance calculated so far with the new difference between two attributes.
updateDistance(double, double) - Method in class weka.core.WeightedEuclideanDistance: Updates the current distance calculated so far with the new difference between two attributes.
updateDistance(double, double) - Method in class weka.core.WeightedEuclideanDistanceRidge: Updates the current distance calculated so far with the new difference between two attributes.
updateEditor(PropertyEditor, JComponent, String) - Method in class adams.gui.goe.WekaGenericObjectEditorPopupMenu: Updates the editor using the string.
updateEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.AssociateTab.HistoryPanel: Displays the specified entry.
updateEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Displays the specified entry.
updateEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClassifyTab.HistoryPanel: Displays the specified entry.
updateEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ClusterTab.HistoryPanel: Displays the specified entry.
updateEntry(String) - Method in class adams.gui.tools.wekainvestigator.tab.ExperimentTab.HistoryPanel: Displays the specified entry.
updateEntry(String) - Method in class adams.gui.tools.wekamultiexperimenter.analysis.DefaultAnalysisPanel.HistoryPanel: Displays the specified entry.
updateEntry(String) - Method in class weka.gui.explorer.ExplorerEntryPanel: Displays the specified entry.
updateEnvironment(List<String>) - Method in class adams.core.management.WekaHomeEnvironmentModifier: Updates the environment variables that the Launcher uses for launching the ADAMS process.
updateExperimentFromMenu(Object) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Updates the experiment using the state of some menu items.
updateFileChooserAccessory(JFileChooser) - Static method in class weka.gui.AdamsHelper: Updates the accessory panel of the filechooser.
updateHeader(Instances) - Method in class adams.opt.optimise.genetic.AbstractGeneticAlgorithm: Creates a new dataset, with the setup as the new relation name.
updateHeader(Instances, AbstractGeneticAlgorithm.GeneticAlgorithmJob) - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithm: Creates a new dataset, with the setup as the new relation name.
updateHeaderTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithLabels: Returns the tip text for this property.
updateIDs() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Updates the list with IDs.
updateIDs(int, Instances, HashSet) - Method in class adams.flow.transformer.WekaInstancesMerge: Updates the IDs in the hashset with the ones stored in the ID attribute of the provided dataset.
updateIntervalTipText() - Method in class adams.gui.visualization.instance.SimpleInstancePanelUpdater: Returns the tip text for this property.
updateLabels(Attribute) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel: Sets the labels for fields we can determine just from the instance header.
updateListButtons() - Method in class adams.gui.wizard.WekaSelectMultipleDatasetsPage: Updates the enabled state of the buttons.
updateMenu() - Method in class adams.gui.tools.DatasetCompatibilityPanel: updates the enabled state of the menu items.
updateMenu() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: updates the enabled state of the menu items.
updateMenu() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: updates the enabled state of the menu items.
updateMenu() - Method in class adams.gui.visualization.instance.InstanceComparePanel: updates the enabled state of the menu items.
updateMenu() - Method in class adams.gui.visualization.instance.InstanceExplorer: updates the enabled state of the menu items.
updateMenu() - Method in class weka.gui.explorer.ExplorerExt: updates the enabled state of the menu items.
updateMenu(JMenuBar) - Method in class weka.gui.explorer.ExplorerEntryPanel: Updates the menu bar.
updateMenuFromExperiment(Object) - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Updates some menu items from the experiment.
updatePanel() - Method in class weka.gui.explorer.ExplorerEntryPanel: Revalidates the panel to make changes visible.
updatePanel(AbstractAnalysisPanel) - Method in class adams.gui.tools.wekamultiexperimenter.AnalysisPanel: Sets the panel as the new analysis panel.
updatePopupMenu(AbstractNamedHistoryPanel, AbstractInvestigatorTab, int[], JPopupMenu, Class) - Static method in class adams.gui.tools.wekainvestigator.history.AbstractHistoryPopupMenuItem: Updates the menu for the specified superclass of menu items.
updatePopupMenu(PerFoldMultiPagePane, AbstractOutputGenerator, int[], JPopupMenu) - Static method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.perfold.AbstractPerFoldPopupMenuItem: Updates the menu.
updateRelationName(File, Instances) - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Updates the relation name.
updateRelationNameTipText() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Returns the tip text for this property.
updateRows() - Method in class adams.gui.visualization.instance.InstanceComparePanel: Updates the combobox with the rows.
updaterTipText() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the tip text for this property.
updaterTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the updater option.
updateStatistics(AttributeStats) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.AttributeInfoPanel: Sets the gui elements for fields that are stored in the AttributeStats structure.
updateStatistics(AttributeStats, Attribute, boolean) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSummaryPanel.StatisticsTable: Creates a tablemodel for the attribute being displayed
updateStatsForClassifier(double[], Instance) - Method in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure: Ignored.
updateStatsForClassifier(double[], Instance) - Method in class weka.classifiers.evaluation.Dice: Updates the statistics about a classifiers performance for the current test instance.
updateStatsForPredictor(double, Instance) - Method in class weka.classifiers.evaluation.AbstractSimpleRegressionMeasure: Updates the statistics about a predictors performance for the current test instance.
updateStatsForPredictor(double, Instance) - Method in class weka.classifiers.evaluation.Dice: Updates the statistics about a predictors performance for the current test instance.
updateTitle() - Method in class adams.gui.tools.wekainvestigator.InvestigatorPanel: Updates the title of the dialog.
updateTitle() - Method in class adams.gui.tools.wekamultiexperimenter.ExperimenterPanel: Updates the title of the dialog.
updateTitle() - Method in class weka.gui.explorer.ExplorerExt: Updates the title of the dialog.
updateVariables() - Method in class adams.flow.transformer.WekaInstanceDumper: Gets called when the actor needs to be re-setUp when a variable changes.
updateWaitTipText() - Method in class weka.classifiers.functions.FakeClassifier: Returns the tip text for this property.
updateWidgets() - Method in class adams.gui.tools.wekainvestigator.tab.CompareTab: Updates the state of the widgets.
updateWidgets() - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Updates the enabled state of the buttons/combobox.
UpperStatistic - Enum in adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated: Enumeration of upper statistics to compute.
upperTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.Predictions: Returns the tip text for this property.
upperTipText() - Method in class adams.flow.transformer.wekarepeatedcrossvalidationoutput.SamplePlot: Returns the tip text for this property.
upperTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.Predictions: Returns the tip text for this property.
upperTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.SamplePlot: Returns the tip text for this property.
URLTipText() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the tip text for this property.
URLTipText() - Method in class adams.flow.source.WekaDatabaseReader: Returns the tip text for this property.
USE_FIRST_COMPONENT - weka.attributeSelection.AbstractPLSAttributeEval.LoadingsCalculations
useAbsoluteErrorTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the tip text for this property.
useAbsoluteErrorTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Returns the tip text for this property.
UseAsClass - Class in adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction: Uses the selected attribute as class attribute.
UseAsClass() - Constructor for class adams.gui.tools.wekainvestigator.tab.preprocesstab.attributeselaction.UseAsClass: Instantiates the action.
useColumnNamesAsClassLabelsTipText() - Method in class adams.flow.transformer.WekaSpreadSheetToPredictions: Returns the tip text for this property.
useCustomLoaderTipText() - Method in class adams.flow.transformer.WekaFileReader: Returns the tip text for this property.
useCustomLoaderTipText() - Method in class adams.flow.transformer.WekaReorderAttributesToReference: Returns the tip text for this property.
useCustomLoaderTipText() - Method in class weka.filters.unsupervised.instance.AlignDataset: Returns the tip text for this property.
useCustomLoaderTipText() - Method in class weka.filters.unsupervised.instance.RemoveTestInstances: Returns the tip text for this property.
useCustomPaintletTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
useCustomSaverTipText() - Method in class adams.flow.sink.WekaFileWriter: Returns the tip text for this property.
useErrorTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ClassifierErrors: Returns the tip text for this property.
useFilenameTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractExperiment: Returns the tip text for this property.
useFixedMinMaxTipText() - Method in class adams.flow.transformer.WekaInstancesHistogramRanges: Returns the tip text for this property.
useMedianTipText() - Method in class adams.flow.transformer.wekaclusterer.ClusterCenters: Returns the tip text for this property.
useModelResetVariableTipText() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Returns the tip text for this property.
useOriginalIndicesTipText() - Method in class adams.flow.transformer.AbstractWekaPredictionsTransformer: Returns the tip text for this property.
useOuterWindowTipText() - Method in class adams.flow.source.WekaSelectDataset: Returns the tip text for this property.
usePrefixTipText() - Method in class adams.flow.transformer.WekaInstancesMerge: Returns the tip text for this property.
useProbabilitiesTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.ConfusionMatrix: Returns the tip text for this property.
USERCPU_TIME_TESTING - adams.flow.core.ExperimentStatistic
USERCPU_TIME_TRAINING - adams.flow.core.ExperimentStatistic
useReducedData(ResultItem) - Method in class adams.gui.tools.wekainvestigator.tab.AttributeSelectionTab.HistoryPanel: Makes the reduced data available as data container.
useRelationNameAsFilenameTipText() - Method in class adams.flow.sink.WekaFileWriter: Returns the tip text for this property.
useRelationNameAsFilenameTipText() - Method in class adams.flow.transformer.WekaInstanceDumper: Returns the tip text for this property.
useRelationNameAsTableTipText() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the tip text for this property.
userTipText() - Method in class adams.flow.sink.WekaDatabaseWriter: Returns the tip text for this property.
userTipText() - Method in class adams.flow.source.WekaDatabaseReader: Returns the tip text for this property.
useSecondEvaluationTipText() - Method in class adams.opt.genetic.AbstractClassifierBasedGeneticAlgorithmWithSecondEvaluation: Returns the tip text for this property.
useUndoHandler() - Method in class adams.gui.visualization.instances.InstancesTableModel: Returns whether to use the undo handler.
useUnsmoothedTipText() - Method in class weka.classifiers.trees.m5.M5Base2: Returns the tip text for this property
useViewsTipText() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Returns the tip text for this property.
useViewsTipText() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Returns the tip text for this property.
useViewsTipText() - Method in class weka.classifiers.AbstractSplitGenerator: Returns the tip text for this property.
useWekaEditors() - Static method in class adams.gui.goe.WekaEditorsRegistration: Returns whether Weka editors should be used.

V

value() - Method in annotation type weka.classifiers.trees.XGBoost.XGBoostParameter: The name of the parameter this field corresponds to.
value(int) - Method in class weka.core.AbstractHashableInstance: Returns an instance's attribute value in internal format.
value(Attribute) - Method in class weka.core.AbstractHashableInstance: Returns an instance's attribute value in internal format.
VALUE_ABSTENTION_CLASSIFICATION - Static variable in class adams.flow.container.WekaPredictionContainer: the identifier for the classification of an abstaining classifier.
VALUE_ABSTENTION_CLASSIFICATION_LABEL - Static variable in class adams.flow.container.WekaPredictionContainer: the identifier for the classification label of an abstaining classifier.
VALUE_ABSTENTION_DISTRIBUTION - Static variable in class adams.flow.container.WekaPredictionContainer: the identifier for the distribution of an abstaining classifier.
VALUE_ALGORITHM - Static variable in class adams.flow.container.WekaGeneticAlgorithmInitializationContainer: the identifier for the algorithm instance.
VALUE_AVERAGE_SILHOUETTE_COEFFICIENT - Static variable in class adams.flow.transformer.wekaclusterer.AverageSilhouetteCoefficient: the key in the container.
VALUE_CLASSES_TO_CLUSTERS - Static variable in class weka.gui.explorer.ClustererHandler
VALUE_CLASSIFICATION - Static variable in class adams.flow.container.WekaPredictionContainer: the identifier for the Classification.
VALUE_CLASSIFICATION_LABEL - Static variable in class adams.flow.container.WekaPredictionContainer: the identifier for the Classification's label.
VALUE_CLUSTER - Static variable in class adams.flow.container.WekaClusteringContainer: the identifier for the Cluster.
VALUE_CLUSTERED_DATASET - Static variable in class adams.flow.transformer.wekaclusterer.AbstractClusterMembershipPostProcessor: the clustered full dataset.
VALUE_CROSS_VALIDATION - Static variable in class weka.gui.explorer.AttributeSelectionHandler
VALUE_CROSS_VALIDATION - Static variable in class weka.gui.explorer.ClassifierHandler
VALUE_DATA - Static variable in class adams.flow.container.WekaFilterContainer: the identifier for the Data.
VALUE_DATA - Static variable in class adams.flow.container.WekaGeneticAlgorithmInitializationContainer: the identifier for the data.
VALUE_DATASET - Static variable in class adams.flow.container.WekaModelContainer: the identifier for the full dataset.
VALUE_DISTANCES - Static variable in class adams.flow.container.WekaNearestNeighborSearchContainer: the identifier for the distances.
VALUE_DISTRIBUTION - Static variable in class adams.flow.container.WekaClusteringContainer: the identifier for the Distribution.
VALUE_DISTRIBUTION - Static variable in class adams.flow.container.WekaPredictionContainer: the identifier for the Distribution.
VALUE_EVALUATION - Static variable in class adams.flow.container.WekaAttributeSelectionContainer: the identifier for the evaluation object.
VALUE_EVALUATION - Static variable in class adams.flow.container.WekaClusterEvaluationContainer: the identifier for the ClusterEvaluation.
VALUE_EVALUATION - Static variable in class adams.flow.container.WekaEvaluationContainer: the identifier for the Evaluation.
VALUE_EXPERIMENT - Static variable in class adams.flow.container.WekaExperimentContainer: the identifier for the experiment.
VALUE_FILTER - Static variable in class adams.flow.container.WekaFilterContainer: the identifier for the Filter.
VALUE_FITNESS - Static variable in class adams.flow.container.WekaGeneticAlgorithmContainer: the identifier for the fitness.
VALUE_FOLD_COUNT - Static variable in class adams.flow.container.WekaAttributeSelectionContainer: the identifier for the fold count.
VALUE_FOLD_COUNT - Static variable in class adams.flow.container.WekaTrainTestSetContainer: the identifier for the fold count.
VALUE_FOLD_NUMBER - Static variable in class adams.flow.container.WekaTrainTestSetContainer: the identifier for the fold number.
VALUE_HEADER - Static variable in class adams.flow.container.WekaModelContainer: the identifier for the Header.
VALUE_INPUT - Static variable in class adams.flow.container.WekaFilterContainer: the identifier for the Input Data.
VALUE_INSTANCE - Static variable in class adams.flow.container.WekaClusteringContainer: the identifier for the Instance.
VALUE_INSTANCE - Static variable in class adams.flow.container.WekaNearestNeighborSearchContainer: the identifier for the Instance.
VALUE_INSTANCE - Static variable in class adams.flow.container.WekaPredictionContainer: the identifier for the Instance.
VALUE_INSTANCES - Static variable in class adams.flow.container.WekaExperimentContainer: the identifier for the results (instances).
VALUE_LOGDENSITY - Static variable in class adams.flow.container.WekaClusteringContainer: the identifier for the LogDensity.
VALUE_LOGDENSITYPERCLUSTER - Static variable in class adams.flow.container.WekaClusteringContainer: the identifier for the LogDensityPerCluster.
VALUE_LOGJOINTDENSITIES - Static variable in class adams.flow.container.WekaClusteringContainer: the identifier for the LogJointDensities.
VALUE_LOGLIKELIHOOD - Static variable in class adams.flow.container.WekaClusterEvaluationContainer: the identifier for the log-likelihood.
VALUE_MEASURE - Static variable in class adams.flow.container.WekaGeneticAlgorithmContainer: the identifier for the measure.
VALUE_MODEL - Static variable in class adams.flow.container.WekaClusterEvaluationContainer: the identifier for the Model.
VALUE_MODEL - Static variable in class adams.flow.container.WekaEvaluationContainer: the identifier for the Model.
VALUE_MODEL - Static variable in class adams.flow.container.WekaModelContainer: the identifier for the Model.
VALUE_NEIGHBORHOOD - Static variable in class adams.flow.container.WekaNearestNeighborSearchContainer: the identifier for the neighborhood.
VALUE_ORIGINALINDICES - Static variable in class adams.flow.container.WekaEvaluationContainer: the identifier for the original indices.
VALUE_PERCENTAGE_SPLIT - Static variable in class weka.gui.explorer.ClassifierHandler
VALUE_PERCENTAGE_SPLIT - Static variable in class weka.gui.explorer.ClustererHandler
VALUE_PREDICTIONOUTPUT - Static variable in class adams.flow.container.WekaEvaluationContainer: the identifier for the prediction output.
VALUE_RANGECHECK - Static variable in class adams.flow.container.WekaPredictionContainer: the identifier for the Range check.
VALUE_REDUCED - Static variable in class adams.flow.container.WekaAttributeSelectionContainer: the identifier for the reduced data.
VALUE_RULES - Static variable in class adams.flow.container.WekaAssociatorContainer: the identifier for the rules.
VALUE_SEED - Static variable in class adams.flow.container.WekaAttributeSelectionContainer: the identifier for the random seed.
VALUE_SEED - Static variable in class adams.flow.container.WekaTrainTestSetContainer: the identifier for the random seed.
VALUE_SELECTEDATTRIBUTES - Static variable in class adams.flow.container.WekaAttributeSelectionContainer: the identifier for the Remove filter setup.
VALUE_SETUP - Static variable in class adams.flow.container.WekaGeneticAlgorithmContainer: the identifier for the setup.
VALUE_SPREADSHEET - Static variable in class adams.flow.container.WekaExperimentContainer: the identifier for the results (spreadsheet).
VALUE_STATISTICS - Static variable in class adams.flow.container.WekaAttributeSelectionContainer: the identifier for the statistics object.
VALUE_SUPPLIED_TEST_SET - Static variable in class weka.gui.explorer.ClassifierHandler
VALUE_SUPPLIED_TEST_SET - Static variable in class weka.gui.explorer.ClustererHandler
VALUE_TEST - Static variable in class adams.flow.container.WekaAttributeSelectionContainer: the identifier for the test data.
VALUE_TEST - Static variable in class adams.flow.container.WekaTrainTestSetContainer: the identifier for the test data.
VALUE_TEST_ORIGINALINDICES - Static variable in class adams.flow.container.WekaTrainTestSetContainer: the identifier for the original indices (test).
VALUE_TEST_REDUCED - Static variable in class adams.flow.container.WekaAttributeSelectionContainer: the identifier for the reduced data.
VALUE_TEST_TRANSFORMED - Static variable in class adams.flow.container.WekaAttributeSelectionContainer: the identifier for the transformed data.
VALUE_TESTDATA - Static variable in class adams.flow.container.WekaEvaluationContainer: the identifier for the original data.
VALUE_TRAIN - Static variable in class adams.flow.container.WekaAttributeSelectionContainer: the identifier for the training data.
VALUE_TRAIN - Static variable in class adams.flow.container.WekaTrainTestSetContainer: the identifier for the training data.
VALUE_TRAIN_ORIGINALINDICES - Static variable in class adams.flow.container.WekaTrainTestSetContainer: the identifier for the original indices (train).
VALUE_TRAINING_SET - Static variable in class weka.gui.explorer.AttributeSelectionHandler
VALUE_TRAINING_SET - Static variable in class weka.gui.explorer.ClassifierHandler
VALUE_TRAINING_SET - Static variable in class weka.gui.explorer.ClustererHandler
VALUE_TRANSFORMED - Static variable in class adams.flow.container.WekaAttributeSelectionContainer: the identifier for the transformed data.
VALUE_WEIGHTS - Static variable in class adams.flow.container.WekaGeneticAlgorithmContainer: the identifier for the weights.
VALUE_WEIGHTSSTR - Static variable in class adams.flow.container.WekaGeneticAlgorithmContainer: the identifier for the weights string.
valueAtPct(double[], double) - Method in class weka.filters.unsupervised.attribute.InterquartileRangeSamp: Calculates the value at the specified percentage.
valueChanged(ListSelectionEvent) - Method in class adams.gui.tools.wekainvestigator.tab.preprocesstab.AttributeSelectionPanel: Called whenever the value of the selection changes.
valueIsSmallerEqual(Instance, int, double) - Method in class weka.core.SAXDistance: Returns true if the value of the given dimension is smaller or equal the value to be compared with.
valueIsSmallerEqual(Instance, int, double) - Method in class weka.core.WeightedEuclideanDistance: Returns true if the value of the given dimension is smaller or equal the value to be compared with.
valueIsSmallerEqual(Instance, int, double) - Method in class weka.core.WeightedEuclideanDistanceRidge: Returns true if the value of the given dimension is smaller or equal the value to be compared with.
valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaAttributeIndexParsing: Returns a object generated from the string.
valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaAttributeRangeParsing: Returns a object generated from the string.
valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaExperimentFileParsing: Returns a file generated from the string.
valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaLabelIndexParsing: Returns a object generated from the string.
valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaLabelRangeParsing: Returns a object generated from the string.
valueOf(AbstractOption, String) - Static method in class adams.core.option.parsing.WekaUnorderedAttributeRangeParsing: Returns a object generated from the string.
valueOf(AbstractOption, String) - Static method in enum adams.flow.core.EvaluationStatistic: Returns an enum generated from the string.
valueOf(AbstractOption, String) - Static method in enum adams.flow.core.ExperimentStatistic: Returns an enum generated from the string.
valueOf(AbstractOption, String) - Static method in enum adams.flow.sink.WekaThresholdCurve.AttributeName: Returns an enum generated from the string.
valueOf(AbstractOption, String) - Static method in enum adams.flow.transformer.WekaClassifierRanker.Measure: Returns an enum generated from the string.
valueOf(String) - Static method in enum adams.data.conversion.WekaPredictionContainerToSpreadSheet.Sorting: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.data.instancesanalysis.pls.PredictionType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.data.instancesanalysis.pls.PreprocessingType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.data.weka.columnfinder.MultiColumnFinder.Combination: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.data.weka.rowfinder.MultiRowFinder.Combination: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.core.Capability: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.core.EvaluationStatistic: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.core.ExperimentStatistic: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.sink.WekaExperimentGenerator.EvaluationType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.sink.WekaExperimentGenerator.ExperimentType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.sink.WekaExperimentGenerator.ResultFormat: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.sink.WekaThresholdCurve.AttributeName: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.source.wekapackagemanageraction.ListPackages.ListType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.source.wekapackagemanageraction.ListPackages.OutputFormat: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaBootstrapping.ErrorCalculation: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaClassifierInfo.InfoType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaClassifierRanker.Measure: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaClustererInfo.InfoType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaEvaluationInfo.InfoType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaExtractArray.ExtractionType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaExtractPLSMatrix.MatrixType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaFileReader.OutputType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaInstanceBuffer.Operation: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaInstanceDumper.OutputFormat: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaInstancesInfo.InfoType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.flow.transformer.WekaInstancesStatisticDataType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.gui.event.InstancesSortSetupEvent.EventType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.CenterStatistic: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.LowerStatistic: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.UpperStatistic: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.gui.visualization.instance.InstanceLinePaintlet.MarkerShape: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.opt.genetic.Measure: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.opt.genetic.OutputPrefixType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.opt.genetic.OutputType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.attributeSelection.AbstractPLSAttributeEval.LoadingsCalculations: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.meta.ClassifierCascade.Combination: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.meta.ClassifierCascade.ThresholdCheck: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.meta.MinMaxLimits.LimitHandling: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.BoosterType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.FeatureSelector: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.GrowPolicy: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.NormaliseType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.Objective: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.Predictor: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.ProcessType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.SampleType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.TreeMethod: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.Updater: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.classifiers.trees.XGBoost.Verbosity: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.filters.unsupervised.attribute.EquiDistance.AttributeSelection: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.filters.unsupervised.attribute.NominalToNumeric.ConversionType: Returns the enum constant of this type with the specified name.
values() - Static method in enum adams.data.conversion.WekaPredictionContainerToSpreadSheet.Sorting: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.data.instancesanalysis.pls.PredictionType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.data.instancesanalysis.pls.PreprocessingType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.data.weka.columnfinder.MultiColumnFinder.Combination: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.data.weka.rowfinder.MultiRowFinder.Combination: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.core.Capability: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.core.EvaluationStatistic: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.core.ExperimentStatistic: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.sink.WekaExperimentGenerator.EvaluationType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.sink.WekaExperimentGenerator.ExperimentType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.sink.WekaExperimentGenerator.ResultFormat: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.sink.WekaThresholdCurve.AttributeName: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.source.wekapackagemanageraction.ListPackages.ListType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.source.wekapackagemanageraction.ListPackages.OutputFormat: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaBootstrapping.ErrorCalculation: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaClassifierInfo.InfoType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaClassifierRanker.Measure: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs.VotingType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaClustererInfo.InfoType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaEvaluationInfo.InfoType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaExtractArray.ExtractionType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaExtractPLSMatrix.MatrixType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaFileReader.OutputType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaInstanceBuffer.Operation: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaInstanceDumper.OutputFormat: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaInstancesInfo.InfoType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.flow.transformer.WekaInstancesStatisticDataType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.gui.event.InstancesSortSetupEvent.EventType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.gui.tools.wekainvestigator.tab.AbstractInvestigatorTab.SerializationOption: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.CenterStatistic: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.LowerStatistic: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.gui.tools.wekainvestigator.tab.classifytab.output.repeated.UpperStatistic: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.gui.visualization.instance.InstanceLinePaintlet.MarkerShape: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.opt.genetic.Measure: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.opt.genetic.OutputPrefixType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.opt.genetic.OutputType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum adams.opt.optimise.genetic.fitnessfunctions.AbstractWEKAFitnessFunction.Measure: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.attributeSelection.AbstractPLSAttributeEval.LoadingsCalculations: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.meta.ClassifierCascade.Combination: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.meta.ClassifierCascade.ThresholdCheck: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.meta.MinMaxLimits.LimitHandling: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.trees.XGBoost.BoosterType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.trees.XGBoost.FeatureSelector: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.trees.XGBoost.GrowPolicy: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.trees.XGBoost.NormaliseType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.trees.XGBoost.Objective: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.trees.XGBoost.Predictor: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.trees.XGBoost.ProcessType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.trees.XGBoost.SampleType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.trees.XGBoost.TreeMethod: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.trees.XGBoost.Updater: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.classifiers.trees.XGBoost.Verbosity: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.filters.unsupervised.attribute.EquiDistance.AttributeSelection: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.filters.unsupervised.attribute.NominalToNumeric.ConversionType: Returns an array containing the constants of this enum type, in the order they are declared.
VALUESDIFFER_AVERAGE - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes: how to handle differing values: average.
VALUESDIFFER_AVERAGE - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: how to handle differing values: average.
VALUESDIFFER_FIRST - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: how to handle differing values: first.
VALUESDIFFER_MISSING - Static variable in class weka.filters.unsupervised.attribute.MergeManyAttributes: how to handle differing values: missing.
VALUESDIFFER_MISSING - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: how to handle differing values: missing.
VALUESDIFFER_SECOND - Static variable in class weka.filters.unsupervised.attribute.MergeTwoAttributes: how to handle differing values: SECOND.
valueSparse(int) - Method in class weka.core.AbstractHashableInstance: Returns an instance's attribute value in internal format, given an index in the sparse representation.
valueTipText() - Method in class adams.flow.transformer.WekaSetInstancesValue: Returns the tip text for this property.
valueTipText() - Method in class adams.flow.transformer.WekaSetInstanceValue: Returns the tip text for this property.
variableChanged(VariableChangeEvent) - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Gets triggered when a variable changed (added, modified, removed).
variableChanged(VariableChangeEvent) - Method in class adams.flow.transformer.WekaInstanceBuffer: Gets triggered when a variable changed (added, modified, removed).
variableChanged(VariableChangeEvent) - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Gets triggered when a variable changed (added, modified, removed).
variableNameTipText() - Method in class adams.flow.template.InstanceDumperVariable: Returns the tip text for this property.
variableNameTipText() - Method in class adams.flow.transformer.WekaInstanceBuffer: Returns the tip text for this property.
variableNameTipText() - Method in class adams.flow.transformer.WekaNearestNeighborSearch: Returns the tip text for this property.
varianceCoveredTipText() - Method in class adams.flow.transformer.WekaPrincipalComponents: Returns the tip text for this property.
varianceCoveredTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponentsJ: Returns the tip text for this property.
varianceTipText() - Method in class adams.data.instancesanalysis.PCA: Returns the tip text for this property.
varianceTipText() - Method in class weka.classifiers.meta.AbstainLeastMedianSq
VCPLS - Class in adams.data.instancesanalysis.pls
VCPLS() - Constructor for class adams.data.instancesanalysis.pls.VCPLS
verbosityTipText() - Method in class weka.classifiers.trees.XGBoost: Gets the tip-text for the verbosity option.
versusFitOptionsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Tip text for the vs fit options property.
versusOrderOptionsTipText() - Method in class adams.gui.tools.wekainvestigator.tab.classifytab.output.FourInOnePlot: Tip text for the vsorder options property.
Veto - Class in weka.classifiers.meta: If the specified label is predicted by the required minimum number of classifiers of the ensemble, then this label is predicted.
Veto() - Constructor for class weka.classifiers.meta.Veto
ViewAsTable - Class in adams.gui.visualization.instance.containerlistpopup: Views the selected instance as table.
ViewAsTable() - Constructor for class adams.gui.visualization.instance.containerlistpopup.ViewAsTable
ViewCell - Class in adams.gui.visualization.instances.instancestable: For viewing the cell content.
ViewCell() - Constructor for class adams.gui.visualization.instances.instancestable.ViewCell
viewInstance(InstanceContainer) - Method in class adams.gui.visualization.instance.InstancePanel: Views the specified instance in a table.
Viewport - Class in adams.gui.visualization.instance.plotpopup: Allows the user to perform operations on the instances visible in the current viewport.
Viewport() - Constructor for class adams.gui.visualization.instance.plotpopup.Viewport
visualize() - Method in class adams.gui.tools.wekainvestigator.tab.InstanceTab: Updates the visualization.
VotedFolds - Class in adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel: Generates a Vote meta-classifier from the models from the cross-validation folds.
VotedFolds() - Constructor for class adams.gui.tools.wekainvestigator.tab.classifytab.evaluation.finalmodel.VotedFolds
VotedImbalance - Class in weka.classifiers.meta: Generates an ensemble using the following approach:
- do x times:
* create new dataset, resampled with specified bias
* build base classifier with it
If no classifier gets built at all, use ZeroR as backup model, built on the full dataset.
At prediction time, the Vote meta-classifier (using the pre-built classifiers) is used to determining the class probabilities or regression value.
Instead of just using a fixed number of resampled models, you can also specify thresholds (= probability that the minority class does not meet) with associated number of resampled models to use.
VotedImbalance() - Constructor for class weka.classifiers.meta.VotedImbalance
VotedModels - Class in adams.flow.transformer.wekaensemblegenerator: Generates a Vote meta-classifier from the incoming pre-built classifier models.
VotedModels() - Constructor for class adams.flow.transformer.wekaensemblegenerator.VotedModels
VotedPairs - Class in adams.flow.transformer.wekaclassifiersetupprocessor: Generates an array of classifiers that contains the original ones, but also all possible classifier pairs encapsulated in the Vote meta-classifier.
VotedPairs() - Constructor for class adams.flow.transformer.wekaclassifiersetupprocessor.VotedPairs
VotedPairs.VotingType - Enum in adams.flow.transformer.wekaclassifiersetupprocessor: How the voting is done.
voteTipText() - Method in class adams.flow.transformer.wekaensemblegenerator.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
WekaPackageManagerAction - Class in adams.flow.source: Executes the specified action and forwards the generated output.
WekaPackageManagerAction - Class in adams.flow.standalone: Executes the specified action and forwards the generated output.
WekaPackageManagerAction - Class in adams.flow.transformer: Applies the selected Weka Package Manager action to the incoming data and forwards the generated output.
WekaPackageManagerAction() - Constructor for class adams.flow.source.WekaPackageManagerAction
WekaPackageManagerAction() - Constructor for class adams.flow.standalone.WekaPackageManagerAction
WekaPackageManagerAction() - Constructor for class adams.flow.transformer.WekaPackageManagerAction
WekaPackagesClassPathAugmenter - Class in adams.core.management: Returns the classpath augmentations for all the installed WEKA packages.
WekaPackagesClassPathAugmenter() - Constructor for class adams.core.management.WekaPackagesClassPathAugmenter
WekaPackageToMap - Class in adams.data.conversion: Turns the Weka Package into a Map.
WekaPackageToMap() - Constructor for class adams.data.conversion.WekaPackageToMap
WekaPackageUtils - Class in weka.core: Utility functions for Weka packages.
WekaPackageUtils() - Constructor for class weka.core.WekaPackageUtils
WekaPluginManagerExtensions - Class in adams.gui.application: Enables further extensions through Weka's PluginManager.
WekaPluginManagerExtensions() - Constructor for class adams.gui.application.WekaPluginManagerExtensions
WekaPredictionContainer - Class in adams.flow.container: A container for predictions made by a classifier.
WekaPredictionContainer() - Constructor for class adams.flow.container.WekaPredictionContainer: Initializes the container.
WekaPredictionContainer(Instance, double, double[]) - Constructor for class adams.flow.container.WekaPredictionContainer: Initializes the container.
WekaPredictionContainer(Instance, double, double[], String) - Constructor for class adams.flow.container.WekaPredictionContainer: Initializes the container.
WekaPredictionContainerToSpreadSheet - Class in adams.data.conversion: Turns a WEKA prediction container into a SpreadSheet object.
WekaPredictionContainerToSpreadSheet() - Constructor for class adams.data.conversion.WekaPredictionContainerToSpreadSheet
WekaPredictionContainerToSpreadSheet.SortContainer - Class in adams.data.conversion: Helper class for sorting the distribution.
WekaPredictionContainerToSpreadSheet.Sorting - Enum in adams.data.conversion: How to sort the distribution.
WekaPredictionsToInstances - Class in adams.flow.transformer: Generates weka.core.Instances from the predictions of an Evaluation object.
WekaPredictionsToInstances() - Constructor for class adams.flow.transformer.WekaPredictionsToInstances
WekaPredictionsToSpreadSheet - Class in adams.flow.transformer: Generates a SpreadSheet object from the predictions of an Evaluation object.

See also:
adams.flow.transformer.WekaSpreadSheetToPredictions

Input/output:
- accepts:
   weka.classifiers.Evaluation
   adams.flow.container.WekaEvaluationContainer
- generates:
   adams.data.spreadsheet.SpreadSheet

Container information:
- adams.flow.container.WekaEvaluationContainer: Evaluation, Model, Prediction output, Original indices
WekaPredictionsToSpreadSheet() - Constructor for class adams.flow.transformer.WekaPredictionsToSpreadSheet
WekaPrincipalComponents - Class in adams.flow.transformer: Performs principal components analysis on the incoming data and outputs the loadings and the transformed data as spreadsheet array.
Automatically filters out attributes that cannot be handled by PCA.
WekaPrincipalComponents() - Constructor for class adams.flow.transformer.WekaPrincipalComponents
WekaPropertySheetPanelPage - Class in adams.gui.wizard: Wizard page that use a PropertySheetPanel for displaying the properties of an object.
WekaPropertySheetPanelPage() - Constructor for class adams.gui.wizard.WekaPropertySheetPanelPage: Default constructor.
WekaPropertySheetPanelPage(String) - Constructor for class adams.gui.wizard.WekaPropertySheetPanelPage: Initializes the page with the given page name.
WekaPropertySheetPanelPage.CustomPropertySheetPanel - Class in adams.gui.wizard: Allowing better access to property sheet panel.
WekaPropertyValueConverter - Class in adams.flow.core: Handler for WEKA classes.
WekaPropertyValueConverter() - Constructor for class adams.flow.core.WekaPropertyValueConverter
WekaRandomSplit - Class in adams.flow.transformer: Splits a dataset into a training and test set according to a specified split percentage.
WekaRandomSplit() - Constructor for class adams.flow.transformer.WekaRandomSplit
WekaRegexToRange - Class in adams.flow.transformer: Produces a range string from a regular expression describing attributes.
WekaRegexToRange() - Constructor for class adams.flow.transformer.WekaRegexToRange
WekaRegressionModel - Class in adams.ml.model.regression: Regression model for Weka classifiers.
WekaRegressionModel(Classifier, Dataset, Instances) - Constructor for class adams.ml.model.regression.WekaRegressionModel: Initializes the model.
WekaRegressor - Class in adams.ml.model.regression: Wraps around a Weka classifier that handles numeric classes (= regression).
WekaRegressor() - Constructor for class adams.ml.model.regression.WekaRegressor
WekaRelationName - Class in adams.flow.transformer: Deprecated.
WekaRelationName() - Constructor for class adams.flow.transformer.WekaRelationName: Deprecated.
WekaRenameRelation - Class in adams.flow.transformer: Modifies relation names.
WekaRenameRelation() - Constructor for class adams.flow.transformer.WekaRenameRelation
WekaReorderAttributesToReference - Class in adams.flow.transformer: Reorders the attributes of the Instance/Instances passing through according to the provided reference dataset (callable actor or reference file).
This ensures that the generated data always has the same structure as the reference dataset.
WekaReorderAttributesToReference() - Constructor for class adams.flow.transformer.WekaReorderAttributesToReference
WekaRepeatedCrossValidationEvaluator - Class in adams.flow.transformer: Performs repeated cross-validation a classifier on an incoming dataset.
WekaRepeatedCrossValidationEvaluator() - Constructor for class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator
WekaRepeatedCrossValidationOutput - Class in adams.flow.transformer: Generates output from the incoming repeated cross-validation data.
WekaRepeatedCrossValidationOutput() - Constructor for class adams.flow.transformer.WekaRepeatedCrossValidationOutput
WekaSelectDataset - Class in adams.flow.source: Pops up a file chooser dialog, prompting the user to select one or more datasets.
WekaSelectDataset() - Constructor for class adams.flow.source.WekaSelectDataset
WekaSelectDatasetPage - Class in adams.gui.wizard: Wizard page that allows the user to select a Weka dataset.
WekaSelectDatasetPage() - Constructor for class adams.gui.wizard.WekaSelectDatasetPage: whether to show the /** Default constructor.
WekaSelectDatasetPage(String) - Constructor for class adams.gui.wizard.WekaSelectDatasetPage: Initializes the page with the given page name.
WekaSelectMultipleDatasetsPage - Class in adams.gui.wizard: Wizard page that allows the user to select multiple datasets.
WekaSelectMultipleDatasetsPage() - Constructor for class adams.gui.wizard.WekaSelectMultipleDatasetsPage: Default constructor.
WekaSelectMultipleDatasetsPage(String) - Constructor for class adams.gui.wizard.WekaSelectMultipleDatasetsPage: Initializes the page with the given page name.
WekaSelectObjects - Class in adams.flow.source: Allows the user to select an arbitrary number of Weka objects from the specified class hierarchy using the GenericObjectArray.
WekaSelectObjects() - Constructor for class adams.flow.source.WekaSelectObjects
WekaSetInstancesValue - Class in adams.flow.transformer: Sets a value in a WEKA Instances object.
Notes:
- relational values cannot be set
- '?' (without single quotes) is interpreted as missing value

Input/output:
- accepts:
weka.core.Instances
- generates:
weka.core.Instances
WekaSetInstancesValue() - Constructor for class adams.flow.transformer.WekaSetInstancesValue
WekaSetInstanceValue - Class in adams.flow.transformer: Sets a value in a WEKA Instance.
Notes:
- relational values cannot be set
- '?' (without single quotes) is interpreted as missing value

Input/output:
- accepts:
weka.core.Instance
- generates:
weka.core.Instance

Valid options are:
WekaSetInstanceValue() - Constructor for class adams.flow.transformer.WekaSetInstanceValue
WekaSimpleCLI - Class in adams.gui.menu: Opens the WEKA SimpleCLI.
WekaSimpleCLI() - Constructor for class adams.gui.menu.WekaSimpleCLI: Initializes the menu item with no owner.
WekaSimpleCLI(AbstractApplicationFrame) - Constructor for class adams.gui.menu.WekaSimpleCLI: Initializes the menu item.
WekaSplitGenerator - Class in adams.flow.transformer
WekaSplitGenerator() - Constructor for class adams.flow.transformer.WekaSplitGenerator
WekaSpreadSheetToPredictions - Class in adams.flow.transformer: Turns the predictions stored in the incoming spreadsheet (actual and predicted) into a Weka weka.classifiers.Evaluation object.
For recreating the predictions of a nominal class, the class distributions must be present in the spreadsheet as well.

See also:
adams.flow.transformer.WekaPredictionsToSpreadSheet

Input/output:
- accepts:
adams.data.spreadsheet.SpreadSheet
- generates:
weka.classifiers.Evaluation
WekaSpreadSheetToPredictions() - Constructor for class adams.flow.transformer.WekaSpreadSheetToPredictions
WekaStoreInstance - Class in adams.flow.transformer: Appends the incoming weka.core.Instance to the dataset in storage.
WekaStoreInstance() - Constructor for class adams.flow.transformer.WekaStoreInstance
WekaStreamEvaluator - Class in adams.flow.transformer: Evaluates an incremental classifier on a data stream using prequential evaluation (first evaluate, then train).
WekaStreamEvaluator() - Constructor for class adams.flow.transformer.WekaStreamEvaluator
WekaStreamFilter - Class in adams.flow.transformer: Filters Instance objects using the specified filter.
WekaStreamFilter() - Constructor for class adams.flow.transformer.WekaStreamFilter
WekaSubsets - Class in adams.flow.transformer: Splits the dataset based on the unique values of the specified attribute: all rows with the same unique value form a subset.
WekaSubsets() - Constructor for class adams.flow.transformer.WekaSubsets
WekaSystemProperties - Class in adams.gui.application: Sets some Weka-specific system properties to improve performance.
WekaSystemProperties() - Constructor for class adams.gui.application.WekaSystemProperties
WekaTestSetClustererEvaluator - Class in adams.flow.transformer: Evaluates a trained clusterer (obtained from input) on the dataset obtained from the callable actor.
If a class attribute is set, a classes-to-clusters evaluation is performed automatically

Input/output:
- accepts:
   weka.clusterers.Clusterer
   adams.flow.container.WekaModelContainer
- generates:
   adams.flow.container.WekaClusterEvaluationContainer

Container information:
- adams.flow.container.WekaModelContainer: Model, Header, Dataset
- adams.flow.container.WekaClusterEvaluationContainer: Evaluation, Model, Log-likelohood
WekaTestSetClustererEvaluator() - Constructor for class adams.flow.transformer.WekaTestSetClustererEvaluator
WekaTestSetEvaluator - Class in adams.flow.transformer: Evaluates a trained classifier (obtained from input) on the dataset obtained from the callable actor.
WekaTestSetEvaluator() - Constructor for class adams.flow.transformer.WekaTestSetEvaluator
WekaTestSetEvaluator.EvaluateJob - Class in adams.flow.transformer
WekaTextDirectoryReader - Class in adams.flow.transformer: Loads all text files in a directory and uses the subdirectory names as class labels.
WekaTextDirectoryReader() - Constructor for class adams.flow.transformer.WekaTextDirectoryReader
WekaThresholdCurve - Class in adams.flow.sink: Actor for displaying threshold curves, like ROC or precision/recall.
WekaThresholdCurve() - Constructor for class adams.flow.sink.WekaThresholdCurve
WekaThresholdCurve.AttributeName - Enum in adams.flow.sink: The type of the fields.
wekaToJama(Matrix) - Static method in class adams.data.instancesanalysis.pls.MatrixHelper: Turns a Weka matrix into a Jama one.
wekaToMatrixAlgo(Matrix) - Static method in class adams.data.instancesanalysis.pls.MatrixHelper: Turns a Weka matrix into a matrix-algorithm one.
WekaTrainAssociator - Class in adams.flow.transformer: Trains an associator based on the incoming dataset and outputs the built associator alongside the training header and rules (in a model container)..
WekaTrainAssociator() - Constructor for class adams.flow.transformer.WekaTrainAssociator
WekaTrainAssociator.TrainJob - Class in adams.flow.transformer
WekaTrainClassifier - Class in adams.flow.transformer: Trains a classifier based on the incoming dataset and outputs the built classifier alongside the training header (in a model container).
Incremental training is performed, if the input are weka.core.Instance objects and the classifier implements weka.classifiers.UpdateableClassifier.
WekaTrainClassifier() - Constructor for class adams.flow.transformer.WekaTrainClassifier
WekaTrainClassifier.BatchTrainJob - Class in adams.flow.transformer
WekaTrainClusterer - Class in adams.flow.transformer: Trains a clusterer based on the incoming dataset and output the built clusterer alongside the training header (in a model container).
Incremental training is performed, if the input are weka.core.Instance objects and the clusterer implements weka.clusterers.UpdateableClusterer.
WekaTrainClusterer() - Constructor for class adams.flow.transformer.WekaTrainClusterer
WekaTrainClusterer.BatchTrainJob - Class in adams.flow.transformer
WekaTrainTestSetClustererEvaluator - Class in adams.flow.transformer: Trains a clusterer on an incoming training dataset (from a container) and then evaluates it on the test set (also from a container).
The clusterer setup being used in the evaluation is a callable 'Clusterer' actor.
If a class attribute is set, a classes-to-clusters evaluation is performed automatically

Input/output:
- accepts:
adams.flow.container.WekaTrainTestSetContainer
- generates:
adams.flow.container.WekaClusterEvaluationContainer

Container information:
- adams.flow.container.WekaTrainTestSetContainer: Train, Test, Seed, FoldNumber, FoldCount
- adams.flow.container.WekaClusterEvaluationContainer: Evaluation, Model, Log-likelohood
WekaTrainTestSetClustererEvaluator() - Constructor for class adams.flow.transformer.WekaTrainTestSetClustererEvaluator
WekaTrainTestSetContainer - Class in adams.flow.container: A container for storing train and test set.
WekaTrainTestSetContainer() - Constructor for class adams.flow.container.WekaTrainTestSetContainer: Initializes the container.
WekaTrainTestSetContainer(Instances, Instances) - Constructor for class adams.flow.container.WekaTrainTestSetContainer: Initializes the container.
WekaTrainTestSetContainer(Instances, Instances, Long) - Constructor for class adams.flow.container.WekaTrainTestSetContainer: Initializes the container.
WekaTrainTestSetContainer(Instances, Instances, Long, Integer, Integer) - Constructor for class adams.flow.container.WekaTrainTestSetContainer: Initializes the container.
WekaTrainTestSetContainer(Instances, Instances, Long, Integer, Integer, int[], int[]) - Constructor for class adams.flow.container.WekaTrainTestSetContainer: Initializes the container.
WekaTrainTestSetEvaluator - Class in adams.flow.transformer: Trains a classifier on an incoming training dataset (from a container) and then evaluates it on the test set (also from a container).
The classifier setup being used in the evaluation is a callable 'Classifier' actor.
WekaTrainTestSetEvaluator() - Constructor for class adams.flow.transformer.WekaTrainTestSetEvaluator
WekaTrainTestSetEvaluator.EvaluateJob - Class in adams.flow.transformer
WekaTreeVisualizer - Class in adams.flow.sink: Displays trees in dot notation.
WekaTreeVisualizer() - Constructor for class adams.flow.sink.WekaTreeVisualizer
WekaUnorderedAttributeRange - Class in adams.data.weka: Extended UnorderedRange class that also allows attribute names for specifying attribute positions (names are case-insensitive, just like placeholders for 'first', 'second', etc).
WekaUnorderedAttributeRange() - Constructor for class adams.data.weka.WekaUnorderedAttributeRange: Initializes with no range.
WekaUnorderedAttributeRange(String) - Constructor for class adams.data.weka.WekaUnorderedAttributeRange: Initializes with the given range, but no maximum.
WekaUnorderedAttributeRange(String, int) - Constructor for class adams.data.weka.WekaUnorderedAttributeRange: Initializes with the given range and maximum.
WekaUnorderedAttributeRangeEditor - Class in adams.gui.goe: A PropertyEditor for WekaAttributeRange objects.
WekaUnorderedAttributeRangeEditor() - Constructor for class adams.gui.goe.WekaUnorderedAttributeRangeEditor
WekaUnorderedAttributeRangeParsing - Class in adams.core.option.parsing: For parsing WekaUnorderedAttributeRange options.
WekaUnorderedAttributeRangeParsing() - Constructor for class adams.core.option.parsing.WekaUnorderedAttributeRangeParsing
windowsPointTipText() - Method in class weka.filters.unsupervised.attribute.PAA: Returns the tip text for this property.
windowsPointTipText() - Method in class weka.filters.unsupervised.attribute.SAX: Returns the tip text for this property.
withReplacementTipText() - Method in class adams.flow.transformer.WekaBootstrapping: Returns the tip text for this property.
Workbench - Class in adams.gui.menu: Opens the WEKA Workbench.
Workbench() - Constructor for class adams.gui.menu.Workbench: Initializes the menu item with no owner.
Workbench(AbstractApplicationFrame) - Constructor for class adams.gui.menu.Workbench: Initializes the menu item.
WorkspaceHelper - Class in weka.gui.explorer: Helper class for loading/saving workspaces.
WorkspaceHelper() - Constructor for class weka.gui.explorer.WorkspaceHelper
wrapUp() - Method in class adams.flow.sink.WekaDatabaseWriter: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.sink.WekaInstanceViewer: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.source.AbstractWekaSetupGenerator: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.source.WekaDatabaseReader: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.source.WekaSelectObjects: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.AbstractProcessWekaInstanceWithModel: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.AbstractWekaClassifierEvaluator: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaAccumulatedError: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaCrossValidationEvaluator: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaCrossValidationSplit: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaFileReader: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaInstanceBuffer: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaInstanceDumper: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaInstanceEvaluator: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaMultiLabelSplitter: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaRepeatedCrossValidationEvaluator: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaSubsets: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaTrainClassifier: Cleans up after the execution has finished.
wrapUp() - Method in class adams.flow.transformer.WekaTrainClusterer: Cleans up after the execution has finished.
write(PlaceholderFile, AbstractExperiment) - Method in class adams.data.io.output.AbstractAdamsExperimentWriter: Writes the experiment file.
write(SpreadSheet) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.AbstractResultsHandler: Stores the results.
write(SpreadSheet) - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Stores the results.
write(MultiExplorer, File) - Static method in class weka.gui.explorer.WorkspaceHelper: Saves the explorer session to the given file.
writeBatch() - Method in class weka.core.converters.SimpleArffSaver: Writes a Batch of instances
writeBatch() - Method in class weka.core.converters.SpreadSheetSaver: Writes a Batch of instances
writerForFile(File) - Static method in class adams.gui.chooser.AdamsExperimentFileChooser: Returns the writer for the specified file.
writerForFile(File) - Static method in class adams.gui.chooser.WekaFileChooser: Returns the writer for the specified file.
writerTipText() - Method in class adams.gui.tools.wekamultiexperimenter.experiment.FileResultsHandler: Returns the tip text for this property.
writeToDisk(boolean) - Method in class adams.flow.transformer.WekaInstanceDumper: Writes the content of the buffer to disk.

X

XGBoost - Class in weka.classifiers.trees: Classifier implementing XGBoost.
XGBoost() - Constructor for class weka.classifiers.trees.XGBoost
XGBoost.BoosterType - Enum in weka.classifiers.trees: The available types of booster.
XGBoost.FeatureSelector - Enum in weka.classifiers.trees: Available feature selectors.
XGBoost.GrowPolicy - Enum in weka.classifiers.trees: Available grow policy settings.
XGBoost.NormaliseType - Enum in weka.classifiers.trees: Available normalisation-type settings.
XGBoost.Objective - Enum in weka.classifiers.trees: The set of possible learning objectives.
XGBoost.ParamValueProvider - Interface in weka.classifiers.trees: Provides a value suitable as a proxy for the XGBoost parameter system.
XGBoost.Predictor - Enum in weka.classifiers.trees: Available predictors.
XGBoost.ProcessType - Enum in weka.classifiers.trees: Available process-type settings.
XGBoost.SampleType - Enum in weka.classifiers.trees: Available sample-type settings.
XGBoost.TreeMethod - Enum in weka.classifiers.trees: Possible tree-method settings.
XGBoost.Updater - Enum in weka.classifiers.trees: Available updaters.
XGBoost.Verbosity - Enum in weka.classifiers.trees: The possible verbosity levels.
XGBoost.XGBoostParameter - Annotation Type in weka.classifiers.trees: Marks a field as participating in the XGBoost parameter system.
XRegExpTipText() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the tip text for this property
XrffSpreadSheetReader - Class in adams.data.io.input: Reads WEKA datasets in ARFF format and turns them into spreadsheets.
XrffSpreadSheetReader() - Constructor for class adams.data.io.input.XrffSpreadSheetReader
XrffSpreadSheetWriter - Class in adams.data.io.output: Writes a spreadsheet in XRFF file format.
XrffSpreadSheetWriter() - Constructor for class adams.data.io.output.XrffSpreadSheetWriter

Y

YGradientEPO - Class in weka.filters.supervised.attribute: Applies the External Parameter Orthogonalization (EPO) algorithm to the data.

For more information see:
http://wiki.eigenvector.com/index.php?title=Advanced_Preprocessing:_Multivariate_Filtering#External_Parameter_Orthogonalization_.28EPO.29

Valid options are:
YGradientEPO() - Constructor for class weka.filters.supervised.attribute.YGradientEPO
YGradientGLSW - Class in weka.filters.supervised.attribute: Applies the Generalized Least Squares Weighting (GLSW) algorithm to the data.

For more information see:
http://wiki.eigenvector.com/index.php?title=Advanced_Preprocessing:_Multivariate_Filtering#Y-Gradient_GLSW

Valid options are:
YGradientGLSW() - Constructor for class weka.filters.supervised.attribute.YGradientGLSW
YRegExpTipText() - Method in class weka.filters.supervised.attribute.MultiPLS: Returns the tip text for this property

Z

zoomOverviewTipText() - Method in class adams.flow.sink.WekaInstanceViewer: Returns the tip text for this property.

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
All Classes All Packages