Index (meka 1.9.1 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 _

A

A - Class in meka.core: A.java - Handy array operations
A() - Constructor for class meka.core.A
abs(double[][]) - Static method in class meka.core.MatrixUtils: absolute value
AbstractClassifyResultHistoryPlugin - Class in meka.gui.explorer.classify: Ancestor for plugins that work .
AbstractClassifyResultHistoryPlugin() - Constructor for class meka.gui.explorer.classify.AbstractClassifyResultHistoryPlugin
AbstractClassifyTabMenuItem - Class in meka.gui.explorer.classify: Ancestor to classes that can be added to a classify tab's custom menu.
AbstractClassifyTabMenuItem() - Constructor for class meka.gui.explorer.classify.AbstractClassifyTabMenuItem
AbstractConfigurableExtensionFileFilterFileChooser<R,W> - Class in meka.gui.choosers: A specialized JFileChooser that lists all available file Readers and Writers for spreadsheets and allows the user to invoke an options dialog to customize the reader/writer.
AbstractConfigurableExtensionFileFilterFileChooser() - Constructor for class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Constructs a FileChooser pointing to the user's default directory.
AbstractConfigurableExtensionFileFilterFileChooser(File) - Constructor for class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Constructs a FileChooser using the given File as the path.
AbstractConfigurableExtensionFileFilterFileChooser(String) - Constructor for class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Constructs a FileChooser using the given path.
AbstractDatasetProvider - Class in meka.experiment.datasetproviders: Loads local files from disk.
AbstractDatasetProvider() - Constructor for class meka.experiment.datasetproviders.AbstractDatasetProvider
AbstractDeepNeuralNet - Class in meka.classifiers.multilabel.NN: AbstractDeepNeuralNet.java - Extends AbstractNeuralNet with depth options.
AbstractDeepNeuralNet() - Constructor for class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
AbstractEvaluationStatisticsExporter - Class in meka.experiment.statisticsexporters: Ancestor for statistics exporters.
AbstractEvaluationStatisticsExporter() - Constructor for class meka.experiment.statisticsexporters.AbstractEvaluationStatisticsExporter
AbstractEvaluationStatisticsHandler - Class in meka.experiment.evaluationstatistics: Ancestor for handlers.
AbstractEvaluationStatisticsHandler() - Constructor for class meka.experiment.evaluationstatistics.AbstractEvaluationStatisticsHandler
AbstractEvaluator - Class in meka.experiment.evaluators: Ancestor for evaluators.
AbstractEvaluator() - Constructor for class meka.experiment.evaluators.AbstractEvaluator
AbstractExperimenterMenuItem - Class in meka.gui.experimenter.menu: Ancestor for menu items to be displayed in the Experimenter menu.
AbstractExperimenterMenuItem() - Constructor for class meka.gui.experimenter.menu.AbstractExperimenterMenuItem
AbstractExperimenterTab - Class in meka.gui.experimenter: Ancestor for experimenter tabs.
AbstractExperimenterTab() - Constructor for class meka.gui.experimenter.AbstractExperimenterTab
AbstractExperimentFileHandler - Class in meka.experiment.filehandlers: Ancestor for experiment file handler classes.
AbstractExperimentFileHandler() - Constructor for class meka.experiment.filehandlers.AbstractExperimentFileHandler
AbstractExplorerTab - Class in meka.gui.explorer: Ancestor for tabs in the Explorer.
AbstractExplorerTab() - Constructor for class meka.gui.explorer.AbstractExplorerTab
AbstractExtensionFileFilterFileChooser<F extends weka.gui.ExtensionFileFilter> - Class in meka.gui.choosers: A specialized JFileChooser that lists all available file Readers and Writers for reports.
AbstractExtensionFileFilterFileChooser() - Constructor for class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: onstructs a FileChooser pointing to the user's default directory.
AbstractExtensionFileFilterFileChooser(File) - Constructor for class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Constructs a FileChooser using the given File as the path.
AbstractExtensionFileFilterFileChooser(String) - Constructor for class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Constructs a FileChooser using the given path.
AbstractFileBasedEvaluationStatisticsExporter - Class in meka.experiment.statisticsexporters: Ancestor for file-based statistics exporters.
AbstractFileBasedEvaluationStatisticsExporter() - Constructor for class meka.experiment.statisticsexporters.AbstractFileBasedEvaluationStatisticsExporter
AbstractFileBasedEvaluationStatisticsHandler - Class in meka.experiment.evaluationstatistics: Ancestor for file-base handlers.
AbstractFileBasedEvaluationStatisticsHandler() - Constructor for class meka.experiment.evaluationstatistics.AbstractFileBasedEvaluationStatisticsHandler
AbstractMeasurementEvaluationStatisticsExporter - Class in meka.experiment.statisticsexporters: Ancestor for classes that export a single statistic.
AbstractMeasurementEvaluationStatisticsExporter() - Constructor for class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter
AbstractMenuItemDefinition - Class in meka.gui.guichooser: Defines menu items for the GUIChooser's menu.
AbstractMenuItemDefinition() - Constructor for class meka.gui.guichooser.AbstractMenuItemDefinition
AbstractMetaEvaluationStatisticsExporter - Class in meka.experiment.statisticsexporters: Wraps another exporter.
AbstractMetaEvaluationStatisticsExporter() - Constructor for class meka.experiment.statisticsexporters.AbstractMetaEvaluationStatisticsExporter
AbstractMetaEvaluator - Class in meka.experiment.evaluators: Ancestor for evaluators that wrap a base evaluator.
AbstractMetaEvaluator() - Constructor for class meka.experiment.evaluators.AbstractMetaEvaluator
AbstractMultiLabelClassifier - Class in meka.classifiers.multilabel: A Multilabel Classifier.
AbstractMultiLabelClassifier() - Constructor for class meka.classifiers.multilabel.AbstractMultiLabelClassifier
AbstractNeuralNet - Class in meka.classifiers.multilabel.NN: AbstractNeuralNet.java - Provides common options, constants, and other functions for NNs.
AbstractNeuralNet() - Constructor for class meka.classifiers.multilabel.NN.AbstractNeuralNet
AbstractObjectRenderer - Class in meka.gui.modelviewer.renderers: Ancestor for classes that render objects visually.
AbstractObjectRenderer() - Constructor for class meka.gui.modelviewer.renderers.AbstractObjectRenderer
AbstractRecentItemsHandler<M,T> - Class in meka.gui.core: Ancestor for classes that handle a list of recent items.
AbstractRecentItemsHandler(String, M) - Constructor for class meka.gui.core.AbstractRecentItemsHandler: Initializes the handler with a maximum of 5 items.
AbstractRecentItemsHandler(String, int, M) - Constructor for class meka.gui.core.AbstractRecentItemsHandler: Initializes the handler.
AbstractRecentItemsHandler(String, String, int, M) - Constructor for class meka.gui.core.AbstractRecentItemsHandler: Initializes the handler.
AbstractResultHistoryPlugin - Class in meka.gui.explorer: Ancestor for plugins that work .
AbstractResultHistoryPlugin() - Constructor for class meka.gui.explorer.AbstractResultHistoryPlugin
AbstractSetupTab - Class in meka.gui.experimenter: Ancestor for tabs that setup experiments.
AbstractSetupTab() - Constructor for class meka.gui.experimenter.AbstractSetupTab
AbstractShowThresholdCurve - Class in meka.gui.explorer.classify: Allows the user to display the threshold curves per label.
AbstractShowThresholdCurve() - Constructor for class meka.gui.explorer.classify.AbstractShowThresholdCurve
AbstractTabMenuItem<T extends AbstractExplorerTab> - Class in meka.gui.explorer: Ancestor to classes that can be added to a tab's custom menu.
AbstractTabMenuItem() - Constructor for class meka.gui.explorer.AbstractTabMenuItem
AbstractThreadedExplorerTab - Class in meka.gui.explorer: Supports long-running tasks in a separate thread.
AbstractThreadedExplorerTab() - Constructor for class meka.gui.explorer.AbstractThreadedExplorerTab
AbstractThreadedExplorerTab.WorkerThread - Class in meka.gui.explorer: For execution the long-running process.
ACCURACY - Static variable in class meka.gui.explorer.classify.IncrementalPerformance
ACCURACY - Static variable in class meka.gui.explorer.classify.ShowMacroCurve
ACCURACY - Static variable in class meka.gui.explorer.classify.ShowMicroCurve
actionPerformed(ActionEvent) - Method in class meka.gui.dataviewer.DataPanel: invoked when an action occurs
actionPerformed(ActionEvent) - Method in class meka.gui.dataviewer.DataViewerMainPanel: invoked when an action occurs
actionPerformed(ActionEvent) - Method in class meka.gui.goe.GenericObjectEditorDialog: Gets called when the one of the buttons in the GOE panel gets pressed.
activate(double[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARTCluster
activity_report - Variable in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkClass
activity_report - Variable in class meka.classifiers.multilabel.neurofuzzy.WvARAM
actuals - Variable in class meka.core.Result
add(double[][], double[][]) - Static method in class meka.core.MatrixUtils
add(double[][], double) - Static method in class meka.core.MatrixUtils
add(List<String>, char, int) - Static method in class meka.core.OptionUtils: Adds the int value to the options.
add(List<String>, String, int) - Static method in class meka.core.OptionUtils: Adds the int value to the options.
add(List<String>, char, long) - Static method in class meka.core.OptionUtils: Adds the long value to the options.
add(List<String>, String, long) - Static method in class meka.core.OptionUtils: Adds the long value to the options.
add(List<String>, char, float) - Static method in class meka.core.OptionUtils: Adds the float value to the options.
add(List<String>, String, float) - Static method in class meka.core.OptionUtils: Adds the float value to the options.
add(List<String>, char, double) - Static method in class meka.core.OptionUtils: Adds the double value to the options.
add(List<String>, String, double) - Static method in class meka.core.OptionUtils: Adds the double value to the options.
add(List<String>, char, String) - Static method in class meka.core.OptionUtils: Adds the String value to the options.
add(List<String>, String, String) - Static method in class meka.core.OptionUtils: Adds the String value to the options.
add(List<String>, char, boolean) - Static method in class meka.core.OptionUtils: Adds the boolean flag (if true) to the options.
add(List<String>, String, boolean) - Static method in class meka.core.OptionUtils: Adds the boolean flag (if true) to the options.
add(List<String>, char, File) - Static method in class meka.core.OptionUtils: Adds the File value to the options.
add(List<String>, String, File) - Static method in class meka.core.OptionUtils: Adds the File value to the options.
add(List<String>, char, OptionHandler) - Static method in class meka.core.OptionUtils: Adds the OptionHandler to the options.
add(List<String>, String, OptionHandler) - Static method in class meka.core.OptionUtils: Adds the OptionHandler to the options.
add(List<String>, char, Object) - Static method in class meka.core.OptionUtils: Adds the array to the options.
add(List<String>, String, Object) - Static method in class meka.core.OptionUtils: Adds the array to the options.
add(List<String>, String[]) - Static method in class meka.core.OptionUtils: Adds the "super" options to the current list.
add(Vector, Enumeration) - Static method in class meka.core.OptionUtils: Adds the option description of the super class.
add(Result, Object, String) - Method in class meka.gui.core.ResultHistory: Adds the item to the history.
addBias(double[]) - Static method in class meka.core.MatrixUtils
addBias(double[][]) - Static method in class meka.core.MatrixUtils
addBias(Matrix) - Static method in class meka.core.MatrixUtils
addChangeListener(ChangeListener) - Method in class meka.gui.dataviewer.DataPanel: Adds a ChangeListener to the panel
addChangeListener(ChangeListener) - Method in class meka.gui.dataviewer.DataTable: Adds a ChangeListener to the panel
addClassifier() - Method in class meka.gui.experimenter.BasicSetup: Lets the user add a classifier.
addClassifier() - Method in class meka.gui.experimenter.ExpertSetup: Lets the user add a classifier.
addDataset() - Method in class meka.gui.experimenter.BasicSetup: Lets the user add a dataset.
addElement(Result, Object, String) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel: Adds the element to the history.
addExecutionStageListener(ExecutionStageListener) - Method in class meka.experiment.DefaultExperiment: Adds the execution stage listener.
addExecutionStageListener(ExecutionStageListener) - Method in interface meka.experiment.Experiment: Adds the execution stage listener.
addFlag(Vector, String, char) - Static method in class meka.core.OptionUtils: Adds an Option for a flag to the list of options.
addFlag(Vector, String, String) - Static method in class meka.core.OptionUtils: Adds an Option for a flag to the list of options.
addInstance() - Method in class meka.gui.dataviewer.DataPanel: Add an instance at the currently selected index.
addInstanceAtEnd() - Method in class meka.gui.dataviewer.DataPanel: Add an instance at the end of the dataset
addIterationNotificationListener(IterationNotificationListener) - Method in class meka.experiment.DefaultExperiment: Adds the iteration listener.
addIterationNotificationListener(IterationNotificationListener) - Method in interface meka.experiment.Experiment: Adds the iteration listener.
addLogListener(LogListener) - Method in class meka.events.LogObject: Adds the log listener to use.
addLogListener(LogListener) - Method in interface meka.events.LogSupporter: Adds the log listener to use.
addLogListener(LogListener) - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Adds the log listener to use.
addLogListener(LogListener) - Method in class meka.experiment.evaluators.AbstractMetaEvaluator: Adds the log listener to use.
addLogListener(LogListener) - Method in class meka.experiment.statisticsexporters.AbstractMetaEvaluationStatisticsExporter: Adds the log listener to use.
addLogListener(LogListener) - Method in class meka.experiment.statisticsexporters.MultiExporter: Adds the log listener to use.
addMouseListenerToHeader(JTable) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Adds a mouselistener to the header: left-click on the header sorts in ascending manner, using shift-left-click in descending manner.
addOption(Vector, String, String, char) - Static method in class meka.core.OptionUtils: Adds an Option for a flag to the list of options.
addOption(Vector, String, String, String) - Static method in class meka.core.OptionUtils: Adds an Option for a flag to the list of options.
addParameter(String, Component) - Method in class meka.gui.core.ParameterPanel: Adds the label and component as new row at the end.
addParameter(int, String, Component) - Method in class meka.gui.core.ParameterPanel: Inserts the label and component as new row at the specified row.
addRecentItem(T) - Method in class meka.gui.core.AbstractRecentItemsHandler: Adds the item to the internal list.
addRecentItemListener(RecentItemListener) - Method in class meka.gui.core.AbstractRecentItemsHandler: Adds the listener to the internal list.
addResult(double[], Instance) - Method in class meka.core.Result: AddResult - Add an entry.
addResult(Result, Object, String) - Method in class meka.gui.core.ResultHistoryList: Adds the element to the history.
addResultToHistory(Result, Object, String) - Method in class meka.gui.explorer.ClassifyTab: Adds the result to the history.
addsample(double[], int, double) - Method in class meka.classifiers.multilabel.neurofuzzy.ARTCluster
addSearchListener(SearchListener) - Method in class meka.gui.core.SearchPanel: Adds the specified listener to the internal list of listeners.
addStatisticsNotificationListener(StatisticsNotificationListener) - Method in class meka.experiment.DefaultExperiment: Adds the statistics listener.
addStatisticsNotificationListener(StatisticsNotificationListener) - Method in interface meka.experiment.Experiment: Adds the statistics listener.
addTableModelListener(TableModelListener) - Method in class meka.gui.dataviewer.DataSortedTableModel: adds a listener to the list that is notified each time a change to data model occurs
addTableModelListener(TableModelListener) - Method in class meka.gui.dataviewer.DataTableModel: adds a listener to the list that is notified each time a change to data model occurs
addToButtonsPanel(Component) - Method in class meka.gui.core.MekaPanelWithButtons: Adds the component to the panel with the buttons.
addToWidgetsPanel(Component, int) - Method in class meka.gui.core.SearchPanel: Adds the component to the panel with the Widgets.
addToWidgetsPanel(Component) - Method in class meka.gui.core.SearchPanel: Adds the component to the panel with the Widgets.
addUndoPoint() - Method in class meka.gui.dataviewer.DataPanel: adds the current state of the instances to the undolist
addUndoPoint() - Method in class meka.gui.dataviewer.DataSortedTableModel: adds an undo point to the undo history
addUndoPoint() - Method in class meka.gui.dataviewer.DataTableModel: adds an undo point to the undo history, if the undo support is enabled
addUndoPoint() - Method in class meka.gui.explorer.Explorer: Adds an undo point.
afterHide() - Method in class meka.gui.core.MekaDialog: Hook method just after the dialog was hidden.
afterHide() - Method in class meka.gui.core.MekaFrame: Hook method just after the dialog was hidden.
afterShow() - Method in class meka.gui.core.MekaDialog: Hook method just after the dialog was made visible.
afterShow() - Method in class meka.gui.core.MekaFrame: Hook method just after the dialog was made visible.
aggregate(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter: Aggregates the stats and returns the "mean".
aggregate(List<EvaluationStatistics>) - Method in interface meka.experiment.statisticsexporters.AggregatedEvaluationStatisticsExporter: Aggregates the statistics and returns these.
aggregate(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Aggregates the statistics and returns these.
AggregatedEvaluationStatisticsExporter - Interface in meka.experiment.statisticsexporters: Interface for statistics exporter that aggregate their data first.
aggregationKeysTipText() - Method in interface meka.experiment.statisticsexporters.AggregatedEvaluationStatisticsExporter: Describes this property.
aggregationKeysTipText() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Describes this property.
align(int[], int[]) - Static method in class meka.core.Metrics: Helper function for missing values in the labels and missing predictions (i.e., from abstaining classifiers).
align(int[], double[]) - Static method in class meka.core.Metrics: Helper function for missing values in the labels and missing predictions (i.e., from abstaining classifiers).
ALL - Static variable in class meka.core.ThreadUtils: whether to use all available cores.
allMissing(int[]) - Static method in class meka.core.Metrics: Helper function for missing values in the labels.
allPredictions() - Method in class meka.core.Result: AllPredictions - Retrieve all prediction confidences in an L * N matrix (2d array).
allPredictions(double) - Method in class meka.core.Result: AllPredictions - Retrieve all predictions (according to threshold t) in an L * N matrix.
allTrueValues() - Method in class meka.core.Result: AllTrueValues - Retrieve all true values in an L x N matrix.
Animation(JLabel, int) - Constructor for class meka.gui.core.StatusBar.Animation: Initializes the runnable.
append(int, Double) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Puts a key/value pair into the array, optimizing for the case where the key is greater than all existing keys in the array.
append(int[], int) - Static method in class meka.core.A
append(List<EvaluationStatistics>) - Method in interface meka.experiment.evaluationstatistics.IncrementalEvaluationStatisticsHandler: Adds the given statistics.
append(List<EvaluationStatistics>) - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Adds the given statistics.
apply() - Method in class meka.gui.experimenter.AbstractSetupTab: Applies the settings to the experiment.
ApprovalDialog - Class in meka.gui.core: Base class for approval dialogs, i.e., dialogs that require the user to click on Yes, No or Cancel.
ApprovalDialog() - Constructor for class meka.gui.core.ApprovalDialog: Creates a modeless dialog without a title and without a specified Frame owner.
ApprovalDialog(Dialog) - Constructor for class meka.gui.core.ApprovalDialog: Creates a modeless dialog without a title with the specified Dialog as its owner.
ApprovalDialog(Dialog, Dialog.ModalityType) - Constructor for class meka.gui.core.ApprovalDialog: Creates a dialog with the specified owner Dialog and modality.
ApprovalDialog(Dialog, String) - Constructor for class meka.gui.core.ApprovalDialog: Creates a modeless dialog with the specified title and with the specified owner dialog.
ApprovalDialog(Dialog, String, Dialog.ModalityType) - Constructor for class meka.gui.core.ApprovalDialog: Creates a dialog with the specified title, modality and the specified owner Dialog.
ApprovalDialog(Frame) - Constructor for class meka.gui.core.ApprovalDialog: Creates a modeless dialog without a title with the specified Frame as its owner.
ApprovalDialog(Frame, boolean) - Constructor for class meka.gui.core.ApprovalDialog: Creates a dialog with the specified owner Frame, modality and an empty title.
ApprovalDialog(Frame, String) - Constructor for class meka.gui.core.ApprovalDialog: Creates a modeless dialog with the specified title and with the specified owner frame.
ApprovalDialog(Frame, String, boolean) - Constructor for class meka.gui.core.ApprovalDialog: Creates a dialog with the specified owner Frame, modality and title.
APPROVE_OPTION - Static variable in class meka.gui.core.ApprovalDialog: the approve option.
APPROVE_OPTION - Static variable in class meka.gui.dataviewer.DataViewerDialog: Signifies an OK property selection
APPROVE_OPTION - Static variable in class meka.gui.goe.GenericObjectEditorDialog: constant for dialog approval.
ARAMm_Ranking2Class(double[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
ARAMm_Ranking2Class(double[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast
ARAMm_Ranking2Class(double[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse
ARAMm_Ranking2Class(double[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH
ARAMm_Ranking2Class(double[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT
ARAMm_Ranking2Class(double[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange
ARAMm_Ranking2Class(double[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV
ARAMm_Ranking2Class(double[]) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
ARAMm_Ranking2Class(double[]) - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM
ARAMm_Ranking2Class(double[]) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
ARAMNetwork - Class in meka.classifiers.multilabel.neurofuzzy: ****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION.
ARAMNetwork(int, int, double, double) - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
ARAMNetwork() - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
ARAMNetworkClass - Class in meka.classifiers.multilabel.neurofuzzy: ****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION.
ARAMNetworkClass() - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkClass
ARAMNetworkfast - Class in meka.classifiers.multilabel.neurofuzzy: ****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION.
ARAMNetworkfast(int, int, double, double) - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast
ARAMNetworkfast() - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast
ARAMNetworkSparse - Class in meka.classifiers.multilabel.neurofuzzy: ****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION.
ARAMNetworkSparse(int, int, double, double) - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse
ARAMNetworkSparse() - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse
ARAMNetworkSparseH - Class in meka.classifiers.multilabel.neurofuzzy: ****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION.
ARAMNetworkSparseH(int, int, double, double) - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH
ARAMNetworkSparseH() - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH
ARAMNetworkSparseHT - Class in meka.classifiers.multilabel.neurofuzzy: ****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION.
ARAMNetworkSparseHT(int, int, double, double) - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT
ARAMNetworkSparseHT() - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT
ARAMNetworkSparseHT_Strange - Class in meka.classifiers.multilabel.neurofuzzy: ****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION.
ARAMNetworkSparseHT_Strange(int, int, double, double) - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange
ARAMNetworkSparseHT_Strange() - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange
ARAMNetworkSparseV - Class in meka.classifiers.multilabel.neurofuzzy: ****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION.
ARAMNetworkSparseV(int, int, double, double) - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV
ARAMNetworkSparseV() - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV
argmax(double[]) - Static method in class meka.core.A: Argmax
argmax(HashMap<?, Integer>) - Static method in class meka.core.MLUtils: maxItem - argmax function for a HashMap NOTE: same as above, but for integer (TODO: do something more clever than this)
ARTCluster - Class in meka.classifiers.multilabel.neurofuzzy
ARTCluster(int, double) - Constructor for class meka.classifiers.multilabel.neurofuzzy.ARTCluster
attributeAsClass() - Method in class meka.gui.dataviewer.DataPanel: sets the current attribute as class attribute, i.e.
attributeAsClass() - Method in class meka.gui.dataviewer.DataViewerMainPanel: sets the current selected Attribute as class attribute, i.e.
attributeAsClassAt(int) - Method in class meka.gui.dataviewer.DataSortedTableModel: sets the attribute at the given col index as the new class attribute
attributeAsClassAt(int) - Method in class meka.gui.dataviewer.DataTableModel: sets the attribute at the given col index as the new class attribute, i.e.
attributeIndicesTipText() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes: Returns the tip text for this property
AttributeSelectionPanel - Class in meka.gui.components: 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 meka.gui.components.AttributeSelectionPanel: Creates the attribute selection panel with no initial instances.
AttributeSelectionPanel(boolean, boolean, boolean, boolean) - Constructor for class meka.gui.components.AttributeSelectionPanel: Creates the attribute selection panel with no initial instances.
AttributeSelectionPanel.CellRenderer - Class in meka.gui.components: Cell renderer for the attributes.
attSizePercentTipText() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
availableMetrics() - Method in class meka.core.Result: Return the set of metrics for which measurements are available.
averageResults(Result[]) - Static method in class meka.core.MLEvalUtils: Deprecated.

B

backPropagate(double[][], double[][]) - Method in class meka.classifiers.multilabel.BPNN: Back Propagate - Do one round of Back Propagation on batch X_,Y_.
backQuoteChars(String, char[], String[]) - Static method in class meka.core.OptionUtils: Converts specified characters into the string equivalents.
backQuoteChars(String) - Static method in class meka.core.OptionUtils: Converts carriage returns and new lines in a string into \r and \n.
backupModelSettings(TableModel) - Method in class meka.gui.core.SortableAndSearchableTable: Backs up the settings from the old model.
BaggingML - Class in meka.classifiers.multilabel.meta: BaggingML.java - Combining several multi-label classifiers using Bootstrap AGGregatING.
BaggingML() - Constructor for class meka.classifiers.multilabel.meta.BaggingML
BaggingMLdup - Class in meka.classifiers.multilabel.meta: BaggingMLdup.java - A version of BaggingML where Instances are duplicated instead of assigned higher weighs.
BaggingMLdup() - Constructor for class meka.classifiers.multilabel.meta.BaggingMLdup
BaggingMLUpdateable - Class in meka.classifiers.multilabel.incremental.meta: BaggingMLUpdatable.java - Using the OzaBag scheme (see OzaBag.java from MOA)).
BaggingMLUpdateable() - Constructor for class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable
BaggingMT - Class in meka.classifiers.multitarget.meta: BaggingMT.java - The Multi-Target Version of BaggingML.
BaggingMT() - Constructor for class meka.classifiers.multitarget.meta.BaggingMT
bagSizePercentTipText() - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
BasicSetup - Class in meka.gui.experimenter: Tab for setting up a basic experiment.
BasicSetup() - Constructor for class meka.gui.experimenter.BasicSetup
batch - Variable in class meka.classifiers.multilabel.incremental.PSUpdateable
BayesNet - Static variable in interface meka.core.MultiLabelDrawable
BCC - Class in meka.classifiers.multilabel: BCC.java - Bayesian Classifier Chains.
BCC() - Constructor for class meka.classifiers.multilabel.BCC
BCC - Class in meka.classifiers.multitarget
BCC() - Constructor for class meka.classifiers.multitarget.BCC
beforeHide() - Method in class meka.gui.core.MekaDialog: Hook method just before the dialog is hidden.
beforeHide() - Method in class meka.gui.core.MekaFrame: Hook method just before the dialog is hidden.
beforeShow() - Method in class meka.gui.core.ApprovalDialog: Hook method just before the dialog is made visible.
beforeShow() - Method in class meka.gui.core.MekaDialog: Hook method just before the dialog is made visible.
beforeShow() - Method in class meka.gui.core.MekaFrame: Hook method just before the dialog is made visible.
beforeShow() - Method in class meka.gui.goe.GenericObjectEditorDialog: Hook method just before the dialog is made visible.
betaTipText() - Method in class meka.classifiers.multilabel.PMCC
bitCount(String) - Static method in class meka.core.MLUtils
bitDifference(String, String) - Static method in class meka.core.MLUtils
bitDifference(String[], String[]) - Static method in class meka.core.MLUtils
bitDifference(int[], int[]) - Static method in class meka.core.MLUtils
BPNN - Class in meka.classifiers.multilabel: BPNN.java - Back Propagation Neural Network.
BPNN() - Constructor for class meka.classifiers.multilabel.BPNN
BR - Class in meka.classifiers.multilabel
BR() - Constructor for class meka.classifiers.multilabel.BR
BRq - Class in meka.classifiers.multilabel: BRq.java - Random Subspace ('quick') Version.
BRq() - Constructor for class meka.classifiers.multilabel.BRq
BRUpdateable - Class in meka.classifiers.multilabel.incremental: BRUpdateable.java - Updateable BR.
BRUpdateable() - Constructor for class meka.classifiers.multilabel.incremental.BRUpdateable
build(Instances, Classifier) - Method in class meka.classifiers.multilabel.cc.CNode: Build - Create transformation for this node, and train classifier of type H upon it.
buildCC(int[], Instances) - Method in class meka.classifiers.multilabel.PMCC: BuildCC - Build a CC of chain-order 's' on dataset 'D'.
buildCC(int[], Instances, Classifier) - Static method in class meka.core.CCUtils: BuildCC - Given a base classifier 'g', build a new CC classifier on data D, given chain order 'chain'.
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.AbstractMultiLabelClassifier
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.BCC
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.BPNN
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.BR
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.BRq
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.CC
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.CCq
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.CDN
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.CDT
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.CT
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.DBPNN
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.FW
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.HASEL
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.incremental.CCUpdateable
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.LabelTransformationClassifier
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.LC
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.MajorityLabelset
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.MCC
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.meta.BaggingML
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.meta.BaggingMLdup
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.meta.CM
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.meta.DeepML
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.meta.EM
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.meta.EnsembleML
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.meta.MBR
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.meta.SubsetMapper
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.MULAN
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork: Generates the classifier.
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast: Generates the classifier.
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse: Generates the classifier.
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH: Generates the classifier.
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT: Generates the classifier.
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange: Generates the classifier.
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV: Generates the classifier.
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork: Generates the classifier.
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM: Generates the classifier.
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM: Generates the classifier.
BuildClassifier(ARAMNetworkClass) - Constructor for class meka.classifiers.multilabel.neurofuzzy.WvARAM.BuildClassifier
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.PMCC
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.ProblemTransformationMethod
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.PS
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.RAkEL
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.RAkELd
buildClassifier(Instances) - Method in class meka.classifiers.multilabel.RT
buildClassifier(Instances) - Method in class meka.classifiers.multitarget.CCp
buildClassifier(Instances) - Method in class meka.classifiers.multitarget.CR
buildClassifier(Instances) - Method in class meka.classifiers.multitarget.NSR
buildClassifier(Instances) - Method in class meka.classifiers.multitarget.RAkELd
buildClassifier(Instances) - Method in class meka.classifiers.multitarget.SCC

C

calcColumnWidth(int) - Method in class meka.gui.core.JTableHelper: calcs the optimal column width of the given column.
calcColumnWidth(JTable, int) - Static method in class meka.gui.core.JTableHelper: Calculates the optimal width for the column of the given table.
calcHeaderWidth(int) - Method in class meka.gui.core.JTableHelper: calcs the optimal header width of the given column.
calcHeaderWidth(JTable, int) - Static method in class meka.gui.core.JTableHelper: Calculates the optimal width for the header of the given table.
calculateError(Matrix) - Method in class rbms.RBM: Calculate the Error right now.
calibrateThreshold(ArrayList<double[]>, double) - Static method in class meka.core.ThresholdUtils: CalibrateThreshold - Calibrate a threshold using PCut: the threshold which results in the best approximation of the label cardinality of the training set.
calibrateThresholds(ArrayList<double[]>, double[]) - Static method in class meka.core.ThresholdUtils: CalibrateThreshold - Calibrate a vector of thresholds (one for each label) using PCut: the threshold t[j] which results in the best approximation of the frequency of the j-th label in the training data.
call() - Method in class meka.experiment.evaluators.EvaluatorJob: Performs the evaluation and stores the results.
CANCEL_OPTION - Static variable in class meka.gui.core.ApprovalDialog: the cancel option.
CANCEL_OPTION - Static variable in class meka.gui.dataviewer.DataViewerDialog: Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class meka.gui.goe.GenericObjectEditorDialog: constant for dialog cancellation.
canPasteFromClipboard(DataFlavor) - Static method in class meka.gui.core.GUIHelper: Checks whether the specified "flavor" can be obtained from the clipboard.
canPasteStringFromClipboard() - Static method in class meka.gui.core.GUIHelper: Checks whether a string can be obtained from the clipboard.
canUndo() - Method in class meka.gui.dataviewer.DataPanel: returns whether an undo is possible
canUndo() - Method in class meka.gui.dataviewer.DataSortedTableModel: returns whether an undo is possible, i.e.
canUndo() - Method in class meka.gui.dataviewer.DataTableModel: returns whether an undo is possible, i.e.
canUndo() - Method in class meka.gui.explorer.Explorer: Returns whether any operations can be undone currently.
CC - Class in meka.classifiers.multilabel: CC.java - The Classifier Chains Method.
CC() - Constructor for class meka.classifiers.multilabel.CC
CC - Class in meka.classifiers.multitarget
CC() - Constructor for class meka.classifiers.multitarget.CC
CCp - Class in meka.classifiers.multitarget: CCp.java - Multitarget CC with probabilistic output.
CCp() - Constructor for class meka.classifiers.multitarget.CCp
CCp.Link - Class in meka.classifiers.multitarget
CCq - Class in meka.classifiers.multilabel: The Classifier Chains Method - Random Subspace ('quick') Version.
CCq() - Constructor for class meka.classifiers.multilabel.CCq
CCq.QLink - Class in meka.classifiers.multilabel
CCUpdateable - Class in meka.classifiers.multilabel.incremental: CCUpdateable.java - Updateable version of CC.
CCUpdateable() - Constructor for class meka.classifiers.multilabel.incremental.CCUpdateable
CCUpdateable.ULink - Class in meka.classifiers.multilabel.incremental
CCUtils - Class in meka.core: CCUtils.java - Handy Utils for working with Classifier Chains (and Trees and Graphs)
CCUtils() - Constructor for class meka.core.CCUtils
CDN - Class in meka.classifiers.multilabel: CDN.java - Conditional Dependency Networks.
CDN() - Constructor for class meka.classifiers.multilabel.CDN
CDT - Class in meka.classifiers.multilabel: CDT.java - Conditional Dependency Trellis.
CDT() - Constructor for class meka.classifiers.multilabel.CDT
ceil(Key) - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Returns the smallest key in the symbol table greater than or equal to key.
CellRenderer() - Constructor for class meka.gui.components.AttributeSelectionPanel.CellRenderer
chainIterationsTipText() - Method in class meka.classifiers.multilabel.MCC
char2int(char) - Static method in class meka.core.MLUtils
check(T) - Method in class meka.gui.core.AbstractRecentItemsHandler: Checks the item after obtaining from the props file.
check(File) - Method in class meka.gui.core.RecentFilesHandler: Checks the item after obtaining from the props file.
check(RecentFilesHandlerWithCommandline.Setup) - Method in class meka.gui.core.RecentFilesHandlerWithCommandline: Checks the item after obtaining from the props file.
check() - Method in class meka.gui.core.RecentFilesHandlerWithCommandline.Setup: Performs a check whether this setup is valid.
chi2(Instances, int, int) - Static method in class meka.core.StatUtils: Chi^2 - Do the chi-squared test on the j-th and k-th labels in Y.
chi2(Instances) - Static method in class meka.core.StatUtils: Chi^2 - Do the chi-squared test on all pairs of labels.
chi2(double[][][], double[][][]) - Static method in class meka.core.StatUtils: Chi^2 - Chi-squared test.
classCombinationCounts(Instances) - Static method in class meka.core.MLUtils: ClassCombinationCounts - multi-target version of countCombinations(...).
classFreqs - Variable in class meka.classifiers.multilabel.MajorityLabelset
classifiers(List<EvaluationStatistics>, boolean) - Static method in class meka.experiment.evaluationstatistics.EvaluationStatisticsUtils: Returns all the unique classifiers of all the statistics.
classifiersTipText() - Method in class meka.experiment.DefaultExperiment: Describes this property.
classifiersTipText() - Method in interface meka.experiment.Experiment: Describes this property.
classify(Instance, double[]) - Method in class meka.classifiers.multilabel.cc.CNode: Return the argmax on #distribution(Instance, double[]).
classify(Instance) - Method in class meka.classifiers.multilabel.incremental.CCUpdateable.ULink
classify(Instance) - Method in class meka.classifiers.multitarget.CCp.Link
classifyInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork: Classifies the given test instance.
classifyInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast: Classifies the given test instance.
classifyInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse: Classifies the given test instance.
classifyInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH: Classifies the given test instance.
classifyInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT: Classifies the given test instance.
classifyInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange: Classifies the given test instance.
classifyInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV: Classifies the given test instance.
classifyInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork: Classifies the given test instance.
classifyInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM: Classifies the given test instance.
classifyInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM: Classifies the given test instance.
ClassifyTab - Class in meka.gui.explorer: Simple panel for performing classification.
ClassifyTab() - Constructor for class meka.gui.explorer.ClassifyTab
ClassifyTab.HistoryCustomizer - Class in meka.gui.explorer: Customizer for the history's popup menu.
ClassifyTabOptions - Class in meka.gui.explorer: Panel for options for classification.
ClassifyTabOptions() - Constructor for class meka.gui.explorer.ClassifyTabOptions
clear() - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Removes all key-value mappings from this SparseArray.
clear() - Method in class meka.gui.core.ResultHistory: Empties the history.
clear() - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel: Clears the history.
clear() - Method in class meka.gui.experimenter.AbstractSetupTab: Resets the interface.
clear() - Method in class meka.gui.experimenter.BasicSetup: Resets the interface.
clear() - Method in class meka.gui.experimenter.ExpertSetup: Resets the interface.
clear() - Method in class meka.gui.experimenter.LogTab: Removes the logging content.
clear() - Method in class meka.gui.explorer.LogTab: Removes the logging content.
clearButtonsPanel() - Method in class meka.gui.core.MekaPanelWithButtons: Removes all components from the panel holding the buttons.
clearLabels(Instance) - Static method in class meka.core.MLUtils: Clear Labels -- set the value of all label attributes to 0.0
clearParameters() - Method in class meka.gui.core.ParameterPanel: Removes all parameters.
clearSearch() - Method in class meka.gui.core.SearchPanel: Clears a previous search if the last search term had a non-zero length.
clearSearch() - Method in class meka.gui.dataviewer.DataPanel: clears the search, i.e.
clearSearch() - Method in class meka.gui.dataviewer.DataViewerMainPanel: clears the search, i.e.
clearStatus() - Method in class meka.gui.core.StatusBar: Clears status message.
clearStatus() - Method in class meka.gui.experimenter.AbstractExperimenterTab: Clears status message.
clearStatus() - Method in class meka.gui.explorer.AbstractExplorerTab: Clears status message.
clearUndo() - Method in class meka.gui.dataviewer.DataPanel: removes the undo history
clearUndo() - Method in class meka.gui.dataviewer.DataSortedTableModel: removes the undo history
clearUndo() - Method in class meka.gui.dataviewer.DataTableModel: removes the undo history
clearWidgetsPanel() - Method in class meka.gui.core.SearchPanel: Removes all components from the panel holding the Widgets.
clone() - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray
close() - Method in class meka.gui.dataviewer.DataViewerMainPanel: closes the window, i.e., if the parent is not null and implements the WindowListener interface it calls the windowClosing method
close() - Method in class meka.gui.experimenter.Experimenter: Closes the experimenter.
close() - Method in class meka.gui.explorer.Explorer: Closes the explorer.
close() - Method in class meka.gui.guichooser.GUIChooser: Closes the application.
close() - Method in class meka.gui.modelviewer.ModelViewer: Closes the viewer.
closeAllFiles() - Method in class meka.gui.dataviewer.DataViewerMainPanel: closes all open files
closeFile() - Method in class meka.gui.dataviewer.DataViewerMainPanel: closes the current tab
closeFile(boolean) - Method in class meka.gui.dataviewer.DataViewerMainPanel: closes the current tab
closeParent() - Method in class meka.gui.core.MekaPanel: Closes the parent dialog/frame.
closeQuietly(InputStream) - Static method in class meka.core.FileUtils: Closes the stream, if possible, suppressing any exception.
closeQuietly(OutputStream) - Static method in class meka.core.FileUtils: Closes the stream, if possible, suppressing any exception.
closeQuietly(Reader) - Static method in class meka.core.FileUtils: Closes the reader, if possible, suppressing any exception.
closeQuietly(Writer) - Static method in class meka.core.FileUtils: Closes the writer, if possible, suppressing any exception.
CM - Class in meka.classifiers.multilabel.meta: CM.java - Classification Maximization using any multi-label classifier.
CM() - Constructor for class meka.classifiers.multilabel.meta.CM
CNode - Class in meka.classifiers.multilabel.cc: CNode.java - A Classifier Node class (for CC-like clasifiers).
CNode(int, int[], int[]) - Constructor for class meka.classifiers.multilabel.cc.CNode: CNode - A Node 'j', taking inputs from all parents inX and paY.
colConfidence(int) - Method in class meka.core.Result: ColConfidence - Retrieve the prediction confidences for the j-th label (column).
collapse(Properties) - Static method in class meka.core.PropsUtils: Collapses all the inherited and current properties into a single Properties object and returns it.
combinations - Variable in class meka.classifiers.multilabel.incremental.PSUpdateable
combineInstances(Instances, Instances) - Static method in class meka.core.MLUtils: Stack two Instances together row-wise.
combinePredictions(Result[]) - Static method in class meka.core.MLEvalUtils: Combine Predictions - Combine together various results (for example, from cross-validation) into one, simply by appending predictions and true values together, and averaging together their 'vals'.
CombineStatisticsFiles - Class in meka.gui.experimenter.menu: Allows the user to combine several statistics files into one.
CombineStatisticsFiles() - Constructor for class meka.gui.experimenter.menu.CombineStatisticsFiles
CommandLineArgsHandler - Interface in meka.gui.core: Interface for GUI applications that handle commandline arguments.
commandLines(List<EvaluationStatistics>, boolean) - Static method in class meka.experiment.evaluationstatistics.EvaluationStatisticsUtils: Returns all the unique classifiers of all the statistics.
CommandLineSetup - Class in meka.experiment.filehandlers: Stores the setup of the experiment as a commandline.
CommandLineSetup() - Constructor for class meka.experiment.filehandlers.CommandLineSetup
compare(Object, Object) - Method in class meka.core.LabelSet
compare(Object, Object) - Method in class meka.core.LabelSetComparator
compare(Object, Object) - Method in class meka.core.LabelVector: multi-label suitable only
compare(EvaluationStatistics, EvaluationStatistics) - Method in class meka.experiment.evaluationstatistics.EvaluationStatisticsComparator: Compares the two statistics.
compare(ExtensionFileFilter, ExtensionFileFilter) - Method in class meka.gui.choosers.ExtensionFileFilterComparator: Compares the two filters.
compareTo(SortableAndSearchableWrapperTableModel.SortContainer) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel.SortContainer: Compares this object with the specified object for order.
compareTo(AbstractResultHistoryPlugin) - Method in class meka.gui.explorer.AbstractResultHistoryPlugin: Comparison on the group and name.
compareTo(AbstractTabMenuItem<T>) - Method in class meka.gui.explorer.AbstractTabMenuItem: Compares this item to another, using group and name.
compareTo(AbstractMenuItemDefinition) - Method in class meka.gui.guichooser.AbstractMenuItemDefinition: Comparison on the group and name.
compressedMatrix - Variable in class meka.classifiers.multilabel.MLCBMaD: The compressed matrix.
compression - Variable in class meka.classifiers.multilabel.Maniac: The compression factor, i.e.
compressionTipText() - Method in class meka.classifiers.multilabel.Maniac: Gives the tiptext for compression.
compressionToolTip() - Method in class meka.classifiers.multilabel.Maniac: Gives the tooltip for compression.
condDepMatrix(Instances, Result) - Static method in class meka.core.StatUtils: CondDepMatrix - Get a Conditional Dependency Matrix.
confidences - Variable in class meka.classifiers.multilabel.CC
confidences - Variable in class meka.classifiers.multitarget.CCp
configureCurrentHandlerHook(int) - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: configures the current converter.
configureCurrentHandlerHook(int) - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Configures the current handler.
configureCurrentHandlerHook(int) - Method in class meka.gui.choosers.EvaluationStatisticsExporterFileChooser: configures the current converter.
configureCurrentHandlerHook(int) - Method in class meka.gui.choosers.EvaluationStatisticsFileChooser: configures the current converter.
configureCurrentHandlerHook(int) - Method in class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser: configures the current converter.
contains(Key) - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Does this symbol table contain the given key?
contains(int) - Method in class meka.core.LabelSet
contains(int[]) - Method in class meka.core.LabelSet
convert(Instances, int, int) - Method in class meka.classifiers.multilabel.FW
convert(LabelSet[], HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils: Given N labelsets 'sparseY', use a count 'map' to
convertDistribution(double[], int) - Method in class meka.classifiers.multitarget.NSR
convertDistribution(double[], int, Instances) - Static method in class meka.core.PSUtils: Deprecated.
convertDistribution(double[], int, LabelSet[]) - Static method in class meka.core.PSUtils: Convert Distribution - Given the posterior across combinations, return the distribution across labels.
convertInstance(Instance, int) - Method in class meka.classifiers.multilabel.BRq
convertInstance(Instance) - Method in class meka.classifiers.multilabel.RT: ConvertInstance - Convert an Instance to multi-class format by deleting all but one of the label attributes.
convertInstance(Instance, int, Instances) - Static method in class meka.core.PSUtils: Convert a multi-label instance into a multi-class instance, according to a template.
convertInstances(Instances, int) - Method in class meka.classifiers.multitarget.NSR
convertListArrayTo2DArray(ArrayList<Integer>[]) - Static method in class meka.core.SuperLabelUtils
convertVotesToDistributionForInstance(HashMap<Integer, Double>[]) - Static method in class meka.core.SuperLabelUtils
copy(double[][]) - Static method in class meka.core.MatrixUtils: Copy a 2D array
copyContent() - Method in class meka.gui.dataviewer.DataPanel: copies the content of the selection to the clipboard
copyContent() - Method in class meka.gui.dataviewer.DataViewerMainPanel: copies the content of the selection to the clipboard
CopyModelSetup - Class in meka.gui.explorer.classify: Allows the user to copy the commandline string of the model to the clipboard.
CopyModelSetup() - Constructor for class meka.gui.explorer.classify.CopyModelSetup
copyToClipboard(Transferable) - Static method in class meka.gui.core.GUIHelper: Copies the given transferable to the system's clipboard.
copyToClipboard(String) - Static method in class meka.gui.core.GUIHelper: Copies the given string to the system's clipboard.
copyToClipboard(BufferedImage) - Static method in class meka.gui.core.GUIHelper: Copies the given image to the system's clipboard.
copyToClipboard() - Method in class meka.gui.core.MekaTable: Copies either the selected rows to the clipboard.
copyValues(Instance, Instance, int, int) - Static method in class meka.core.MLUtils: CopyValues - Set x_dest[j+offset] = x_src[i+from].
copyValues(Instance, Instance, int[]) - Static method in class meka.core.MLUtils: CopyValues - Set x_dest[i++] = x_src[j] for all j in indices[].
COST - Variable in class rbms.RBM
countCombinations(Instances, int) - Static method in class meka.core.MLUtils: CountCombinations - return a mapping of each distinct label combination and its count.
countCombinationsSparse(Instances, int) - Static method in class meka.core.MLUtils: CountCombinations in a sparse way.
countCombinationsSparse(Instances, int) - Static method in class meka.core.PSUtils: CountCombinationsSparse - return a mapping of each distinct label combination and its count.
countCombinationsSparseSubset(Instances, int[]) - Static method in class meka.core.PSUtils: CountCombinationsSparseSubset - like CountCombinationsSparse, but only interested in 'indices[]' wrt 'D'.
countSubsets(LabelSet, Set<LabelSet>) - Static method in class meka.core.PSUtils: Count Subsets - returns the number of times labelset 'ysub' exists as a subset in 'Y'.
cover(LabelSet, HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils: Cover - cover 'y' completely (or as best as possible) with sets from 'map'.
cover(LabelSet, SortedSet<LabelSet>, Comparator) - Static method in class meka.core.PSUtils
CR - Class in meka.classifiers.multitarget
CR() - Constructor for class meka.classifiers.multitarget.CR
createAccessoryPanel() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Creates an accessory panel displayed next to the files.
createAccessoryPanel() - Method in class meka.gui.choosers.MekaFileChooser: Creates an accessory panel displayed next to the files.
createAnimation() - Method in class meka.gui.core.StatusBar
createDBM(int) - Method in class meka.classifiers.multilabel.meta.DeepML: CreateDBM - make a RBM if N=1 or a DBM otherwise.
createDialog() - Method in class meka.gui.dataviewer.DataViewerDialog: creates all the elements of the dialog
createDialog(Container) - Static method in class meka.gui.goe.GenericObjectEditorDialog: Creates a modal dialog for the parent.
createDialog(Container, PropertyEditor) - Static method in class meka.gui.goe.GenericObjectEditorDialog: Creates a modal dialog for the parent with the provided editor.
createDialog(Container, PropertyEditor, Object) - Static method in class meka.gui.goe.GenericObjectEditorDialog: Creates a modal dialog for the parent with the provided editor and initial value.
createFrame() - Method in class meka.gui.dataviewer.DataViewer: creates all the components in the frame
createMenuItemText(int, T) - Method in class meka.gui.core.AbstractRecentItemsHandler: Generates the text for the menuitem.
createMenuItemText(int, File) - Method in class meka.gui.core.RecentFilesHandler: Generates the text for the menuitem.
createMenuItemText(int, RecentFilesHandlerWithCommandline.Setup) - Method in class meka.gui.core.RecentFilesHandlerWithCommandline: Generates the text for the menuitem.
createPanel() - Method in class meka.gui.dataviewer.DataPanel: creates all the components in the frame
createPanel() - Method in class meka.gui.dataviewer.DataViewerMainPanel: creates all the components in the panel
createPanel(Instances, String) - Method in class meka.gui.explorer.classify.AbstractShowThresholdCurve: Creates a panel displaying the ROC data.
createPanel(Instances) - Method in class meka.gui.explorer.classify.IncrementalPerformance: Creates a panel displaying the data.
createPanel(Instances) - Method in class meka.gui.explorer.classify.ShowMacroCurve: Creates a panel displaying the data.
createPanel(Instances) - Method in class meka.gui.explorer.classify.ShowMicroCurve: Creates a panel displaying the data.
createPanel(Instances, String) - Method in class meka.gui.explorer.classify.ShowPrecisionRecall: Creates a panel displaying the ROC data.
createPanel(Instances, String) - Method in class meka.gui.explorer.classify.ShowROC: Creates a panel displaying the ROC data.
createPartialFilename(File, int) - Static method in class meka.core.FileUtils: Creates a partial filename for the given file, based on how many parent directories should be included.
createPopup(MouseEvent) - Method in class meka.gui.core.ResultHistoryList: Creates a popup menu for the selected item.
CRITICAL - Static variable in class meka.core.StatUtils: Critical value used for Chi^2 test.
CrossValidation - Class in meka.experiment.evaluators: Evaluates the classifier using cross-validation.
CrossValidation() - Constructor for class meka.experiment.evaluators.CrossValidation
CT - Class in meka.classifiers.multilabel: CT - Classifier Trellis.
CT() - Constructor for class meka.classifiers.multilabel.CT
CURVE_DATA - Static variable in class meka.gui.explorer.classify.AbstractShowThresholdCurve
CURVE_DATA_MACRO - Static variable in class meka.gui.explorer.classify.ShowMacroCurve
CURVE_DATA_MICRO - Static variable in class meka.gui.explorer.classify.ShowMicroCurve
curveData(int[], double[]) - Static method in class meka.core.Metrics: Get Data for Plotting PR and ROC curves.
curveData(int[][], double[][]) - Static method in class meka.core.Metrics: Get Data for Plotting PR and ROC curves.
curveDataMacroAveraged(int[][], double[][]) - Static method in class meka.core.Metrics: Get Data for Plotting PR and ROC curves.
curveDataMicroAveraged(int[][], double[][]) - Static method in class meka.core.Metrics: Get Data for Plotting PR and ROC curves.
customizePopupMenu(ResultHistoryList, int, JPopupMenu) - Method in interface meka.gui.core.ResultHistoryList.ResultHistoryPopupMenuCustomizer: Allows to customize the popup menu for the result history.
customizePopupMenu(ResultHistoryList, int, JPopupMenu) - Method in class meka.gui.explorer.AbstractResultHistoryPlugin: Allows to customize the popup menu for the result history.
customizePopupMenu(ResultHistoryList, int, JPopupMenu) - Method in class meka.gui.explorer.ClassifyTab.HistoryCustomizer: Allows to customize the popup menu for the result history.
cvModel(MultiLabelClassifier, Instances, int, String) - Static method in class meka.classifiers.multilabel.Evaluation: CVModel - Split D into train/test folds, and then train and evaluate on each one.
cvModel(MultiLabelClassifier, Instances, int, String, String) - Static method in class meka.classifiers.multilabel.Evaluation: CVModel - Split D into train/test folds, and then train and evaluate on each one.

D

D_ - Variable in class meka.classifiers.multilabel.meta.EM
D_templates - Variable in class meka.classifiers.multilabel.CDN
DataPanel - Class in meka.gui.dataviewer: A Panel representing an Data-Table and the associated filename.
DataPanel() - Constructor for class meka.gui.dataviewer.DataPanel: initializes the panel with no data
DataPanel(String, AbstractFileLoader...) - Constructor for class meka.gui.dataviewer.DataPanel: initializes the panel and loads the specified file
DataPanel(Instances) - Constructor for class meka.gui.dataviewer.DataPanel: initializes the panel with the given data
DatasetProvider - Interface in meka.experiment.datasetproviders: Interface for classes that provide datasets for the experiment.
datasetProviderTipText() - Method in class meka.experiment.DefaultExperiment: Describes this property.
datasetProviderTipText() - Method in interface meka.experiment.Experiment: Describes this property.
datasetsTipText() - Method in class meka.experiment.datasetproviders.LocalDatasetProvider: Describes this property.
DataSortedTableModel - Class in meka.gui.dataviewer: A sorter for the Data-Viewer - necessary because of the custom CellRenderer.
DataSortedTableModel(String, AbstractFileLoader...) - Constructor for class meka.gui.dataviewer.DataSortedTableModel: initializes the sorter w/o a model, but loads the given file and creates from that a model
DataSortedTableModel(Instances) - Constructor for class meka.gui.dataviewer.DataSortedTableModel: initializes the sorter w/o a model, but uses the given data to create a model from that
DataSortedTableModel(TableModel) - Constructor for class meka.gui.dataviewer.DataSortedTableModel: initializes the sorter with the given model
DataTable - Class in meka.gui.dataviewer: A specialized JTable for the Data-Viewer.
DataTable() - Constructor for class meka.gui.dataviewer.DataTable: initializes with no model
DataTable(TableModel) - Constructor for class meka.gui.dataviewer.DataTable: initializes with the given model
DataTable.RelationalCellEditor - Class in meka.gui.dataviewer: a special Editor for editing the relation attribute.
DataTableCellRenderer - Class in meka.gui.dataviewer: Handles the background colors for missing values differently than the DefaultTableCellRenderer.
DataTableCellRenderer() - Constructor for class meka.gui.dataviewer.DataTableCellRenderer: initializes the Renderer with a standard color
DataTableCellRenderer(Color, Color) - Constructor for class meka.gui.dataviewer.DataTableCellRenderer: initializes the Renderer with the given colors
DataTableCellRenderer(Color, Color, Color, Color) - Constructor for class meka.gui.dataviewer.DataTableCellRenderer: initializes the Renderer with the given colors
DataTableModel - Class in meka.gui.dataviewer: The model for the Data-Viewer.
DataTableModel(String, AbstractFileLoader...) - Constructor for class meka.gui.dataviewer.DataTableModel: initializes the object and loads the given file
DataTableModel(Instances) - Constructor for class meka.gui.dataviewer.DataTableModel: initializes the model with the given data
DataViewer - Class in meka.gui.dataviewer: A little tool for viewing ARFF files.
DataViewer() - Constructor for class meka.gui.dataviewer.DataViewer: initializes the object
DataViewerDefinition - Class in meka.gui.guichooser: Launches the Data Viewer.
DataViewerDefinition() - Constructor for class meka.gui.guichooser.DataViewerDefinition
DataViewerDialog - Class in meka.gui.dataviewer: A downsized version of the DataViewer, displaying only one Instances-Object.
DataViewerDialog(Frame) - Constructor for class meka.gui.dataviewer.DataViewerDialog: initializes the dialog with the given parent.
DataViewerDialog(Frame, Dialog.ModalityType) - Constructor for class meka.gui.dataviewer.DataViewerDialog: initializes the dialog with the given parent
DataViewerDialog(Dialog) - Constructor for class meka.gui.dataviewer.DataViewerDialog: initializes the dialog with the given parent.
DataViewerDialog(Dialog, boolean) - Constructor for class meka.gui.dataviewer.DataViewerDialog: initializes the dialog with the given parent.
DataViewerMainPanel - Class in meka.gui.dataviewer: The main panel of the DataViewer.
DataViewerMainPanel(Container) - Constructor for class meka.gui.dataviewer.DataViewerMainPanel: initializes the object
dbm - Variable in class meka.classifiers.multilabel.DBPNN
dbm - Variable in class meka.classifiers.multilabel.meta.DeepML
DBM - Class in rbms: DBM - Stacked Restricted Boltzmann Machines.
DBM(String[]) - Constructor for class rbms.DBM: DBM - Create a DBM with 'options' (we use WEKA-style option processing).
DBPNN - Class in meka.classifiers.multilabel: DBPNN.java - Deep Back-Propagation Neural Network.
DBPNN() - Constructor for class meka.classifiers.multilabel.DBPNN
DEBUG - Static variable in class meka.core.PropsUtils: whether to output some debug information.
debug(String) - Method in class meka.events.LogObject: For debugging messages.
DEBUG - Static variable in class meka.gui.goe.GenericObjectEditor: whether to output some debugging information.
DEBUG - Static variable in class meka.gui.goe.GenericPropertiesCreator: whether to output some debugging information.
debugTipText() - Method in interface meka.classifiers.multilabel.MultiLabelClassifier: Returns the tip text for this property
debugTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
debugTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM
debugTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
debugTipText() - Method in interface meka.classifiers.multitarget.MultiTargetClassifier: Returns the tip text for this property
decodeClass(String) - Static method in class meka.core.SuperLabelUtils: Decode a string into sparse list of indices
decodeClass(String) - Static method in class meka.filters.multilabel.SuperNodeFilter: ("c_3",'_') -> 3
decodeClasses(String) - Static method in class meka.filters.multilabel.SuperNodeFilter: ("c_3+1") -> [3,1]
decodeValue(String) - Static method in class meka.classifiers.multitarget.NSR
decodeValue(String) - Static method in class meka.core.MLUtils: Deprecated.
decodeValue(String) - Static method in class meka.core.SuperLabelUtils
decodeValue(String) - Static method in class meka.filters.multilabel.SuperNodeFilter: "C+A+B" -> ["C","A","B"]
deep_copy() - Method in class meka.core.LabelSet
deep_copy(int[][]) - Static method in class meka.core.MatrixUtils: Deep Copy - Make a deep copy of M[][].
deepCopy(Object) - Static method in class meka.core.ObjectUtils: Creates a deep copy of the given object (must be serializable!).
DeepML - Class in meka.classifiers.multilabel.meta: DeepML.java - Deep Multi-label Classification.
DeepML() - Constructor for class meka.classifiers.multilabel.meta.DeepML
DEFAULT_KEYS - Static variable in class meka.experiment.evaluationstatistics.EvaluationStatisticsComparator: the default keys.
defaultClassifierString() - Method in class meka.classifiers.multilabel.incremental.BRUpdateable
defaultClassifierString() - Method in class meka.classifiers.multilabel.incremental.CCUpdateable
defaultClassifierString() - Method in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable
defaultClassifierString() - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
defaultClassifierString() - Method in class meka.classifiers.multilabel.incremental.RTUpdateable
defaultClassifierString() - Method in class meka.classifiers.multilabel.LabelTransformationClassifier
defaultClassifierString() - Method in class meka.classifiers.multilabel.meta.DeepML
defaultClassifierString() - Method in class meka.classifiers.multilabel.meta.EM
defaultClassifierString() - Method in class meka.classifiers.multilabel.meta.FilteredClassifier: String describing default classifier.
defaultClassifierString() - Method in class meka.classifiers.multilabel.meta.MBR
defaultClassifierString() - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
defaultClassifierString() - Method in class meka.classifiers.multilabel.meta.SubsetMapper
defaultClassifierString() - Method in class meka.classifiers.multilabel.ProblemTransformationMethod
defaultClassifierString() - Method in class meka.classifiers.multitarget.BCC
defaultClassifierString() - Method in class meka.classifiers.multitarget.CC
defaultClassifierString() - Method in class meka.classifiers.multitarget.CR
defaultClassifierString() - Method in class meka.classifiers.multitarget.meta.BaggingMT
defaultClassifierString() - Method in class meka.classifiers.multitarget.meta.EnsembleMT
defaultClassifierString() - Method in class meka.classifiers.multitarget.meta.FilteredClassifier: String describing default classifier.
defaultClassifierString() - Method in class meka.classifiers.multitarget.NSR
defaultClassifierString() - Method in class meka.classifiers.multitarget.SCC
DefaultExperiment - Class in meka.experiment: Default experiment which executes experiments on the local machine.
DefaultExperiment() - Constructor for class meka.experiment.DefaultExperiment
delete(int) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Removes the mapping from the specified key, if there was any.
delete(Key) - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Removes the key and associated value from the symbol table (if the key is in the symbol table).
delete(int[], int) - Static method in class meka.core.A
delete(int[], int[]) - Static method in class meka.core.A
deleteAttribute() - Method in class meka.gui.dataviewer.DataPanel: deletes the currently selected attribute
deleteAttribute(boolean) - Method in class meka.gui.dataviewer.DataViewerMainPanel: deletes the current selected Attribute or several chosen ones
deleteAttributeAt(int) - Method in class meka.gui.dataviewer.DataSortedTableModel: deletes the attribute at the given col index
deleteAttributeAt(int) - Method in class meka.gui.dataviewer.DataTableModel: deletes the attribute at the given col index.
deleteAttributeAt(int, boolean) - Method in class meka.gui.dataviewer.DataTableModel: deletes the attribute at the given col index
deleteAttributes() - Method in class meka.gui.dataviewer.DataPanel: deletes the chosen attributes
deleteAttributes(int[]) - Method in class meka.gui.dataviewer.DataSortedTableModel: deletes the attributes at the given indices
deleteAttributes(int[]) - Method in class meka.gui.dataviewer.DataTableModel: deletes the attributes at the given indices
deleteAttributesAt(Instance, int[]) - Static method in class meka.core.MLUtils: Delete attributes from an instance 'x' indexed by 'indicesToRemove[]'.
deleteAttributesAt(Instances, int[]) - Static method in class meka.core.MLUtils: Delete attributes from a dataset 'D' indexed by 'indicesToRemove[]'.
deleteInstance() - Method in class meka.gui.dataviewer.DataPanel: deletes the currently selected instance
deleteInstance(boolean) - Method in class meka.gui.dataviewer.DataViewerMainPanel: deletes the current selected Instance or several chosen ones
deleteInstanceAt(int) - Method in class meka.gui.dataviewer.DataSortedTableModel: deletes the instance at the given index
deleteInstanceAt(int) - Method in class meka.gui.dataviewer.DataTableModel: deletes the instance at the given index
deleteInstanceAt(int, boolean) - Method in class meka.gui.dataviewer.DataTableModel: deletes the instance at the given index
deleteInstances() - Method in class meka.gui.dataviewer.DataPanel: deletes all the currently selected instances
deleteInstances(int[]) - Method in class meka.gui.dataviewer.DataSortedTableModel: deletes the instances at the given positions
deleteInstances(int[]) - Method in class meka.gui.dataviewer.DataTableModel: deletes the instances at the given positions
densityTipText() - Method in class meka.classifiers.multilabel.CDT
densityTipText() - Method in class meka.classifiers.multilabel.CT
dependencyMetricTipText() - Method in class meka.classifiers.multilabel.CDT
dependencyMetricTipText() - Method in class meka.classifiers.multilabel.CT
dependencyTypeTipText() - Method in class meka.classifiers.multilabel.BCC
destroy() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
destroy() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM.DistributionCalc
determineAllClasses() - Static method in class meka.gui.goe.GenericObjectEditor
determineMinimumNumberOfParentDirs() - Method in class meka.gui.core.RecentFilesHandler: Determines the minimum number of parent directories that need to be included in the filename to make the filenames in the menu distinguishable.
determineMinimumNumberOfParentDirs() - Method in class meka.gui.core.RecentFilesHandlerWithCommandline: Determines the minimum number of parent directories that need to be included in the filename to make the filenames in the menu distinguishable.
determineOutputFormat(Instances) - Method in class meka.filters.multilabel.SuperNodeFilter
determineOutputFormat(Instances) - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes: Determines the output format based on the input format and returns this.
DIR_UNIX - Static variable in class meka.core.Project: the unix directory.
DIR_WINDOWS - Static variable in class meka.core.Project: the windows directory.
DISCARD_OPTION - Static variable in class meka.gui.core.ApprovalDialog: the discard option.
displayResults() - Method in class meka.gui.explorer.ClassifyTab: Displays the selected results.
distance(LabelSet) - Method in class meka.core.LabelSet
distribution(Instance, double[]) - Method in class meka.classifiers.multilabel.cc.CNode: The distribution this this node, given input x.
DistributionCalc(ARAMNetworkClass) - Constructor for class meka.classifiers.multilabel.neurofuzzy.WvARAM.DistributionCalc
DistributionCalcM(ARAMNetworkClass) - Constructor for class meka.classifiers.multilabel.neurofuzzy.WvARAM.DistributionCalcM
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.AbstractMultiLabelClassifier
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.BPNN
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.BR
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.BRq
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.CC
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.CCq
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.CDN
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.CDT
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.DBPNN
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.FW
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.incremental.CCUpdateable
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.LabelTransformationClassifier
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.LC
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.MajorityLabelset
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.MCC
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.meta.DeepML
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.meta.EM
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.meta.MBR
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.meta.SubsetMapper
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.MULAN
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.PCC
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.PMCC
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.ProblemTransformationMethod
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.PSt
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.RAkELd
distributionForInstance(Instance) - Method in class meka.classifiers.multilabel.RT
distributionForInstance(Instance) - Method in class meka.classifiers.multitarget.BCC
distributionForInstance(Instance) - Method in class meka.classifiers.multitarget.CC
distributionForInstance(Instance) - Method in class meka.classifiers.multitarget.CCp
distributionForInstance(Instance) - Method in class meka.classifiers.multitarget.CR
distributionForInstance(Instance) - Method in class meka.classifiers.multitarget.meta.BaggingMT
distributionForInstance(Instance) - Method in class meka.classifiers.multitarget.meta.EnsembleMT
distributionForInstance(Instance) - Method in class meka.classifiers.multitarget.NSR
distributionForInstance(Instance) - Method in class meka.classifiers.multitarget.RAkELd
distributionForInstance(Instance) - Method in class meka.classifiers.multitarget.SCC
distributionForInstanceM(Instances) - Method in interface meka.classifiers.multilabel.MultiLabelClassifierThreaded
distributionForInstanceM(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
distributionForInstanceM(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast
distributionForInstanceM(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse
distributionForInstanceM(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH
distributionForInstanceM(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT
distributionForInstanceM(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange
distributionForInstanceM(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV
distributionForInstanceM(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
distributionForInstanceM(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM
distributionForInstanceM(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
distributionT(Instance) - Method in class meka.classifiers.multilabel.cc.CNode: Same as #distribution(Instance, double[]), but the Instance is pre-transformed with ypred inside.
doAggregate(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Calculates the actual aggregates.
doCall() - Method in class meka.experiment.evaluators.EvaluatorJob: Performs the actual evaluation.
doExport(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.AbstractEvaluationStatisticsExporter: Exports the statistics.
doExport(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter: Exports the statistics.
doExport(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.InMemory: Exports the statistics.
doExport(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.MultiExporter: Exports the statistics.
doExport(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Exports the statistics.
doExport(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.TabSeparated: Exports the statistics.
doExport(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.WekaFilter: Exports the statistics.
doExportAggregated(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter: Exports the aggregated statistics.
doExportAggregated(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.LatexMeasurement: Exports the aggregated statistics.
doExportAggregated(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.TabSeparatedMeasurement: Exports the aggregated statistics.
doInitializeFilters() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Performs the actual initialization of the filters.
doInitializeFilters() - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Performs the actual initialization of the filters.
doInitializeFilters() - Method in class meka.gui.choosers.EvaluationStatisticsExporterFileChooser: Performs the actual initialization of the filters.
doInitializeFilters() - Method in class meka.gui.choosers.EvaluationStatisticsFileChooser: Performs the actual initialization of the filters.
doInitializeFilters() - Method in class meka.gui.choosers.ExperimentFileChooser: Performs the actual initialization of the filters.
doInitializeFilters() - Method in class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser: Performs the actual initialization of the filters.
doNotify() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM.DistributionCalc
doRender(Object, JPanel) - Method in class meka.gui.modelviewer.renderers.AbstractObjectRenderer: Performs the actual rendering.
doRender(Object, JPanel) - Method in class meka.gui.modelviewer.renderers.InstancesRenderer: Performs the actual rendering.
doRender(Object, JPanel) - Method in class meka.gui.modelviewer.renderers.MultiLabelClassifierRenderer: Performs the actual rendering.
doRender(Object, JPanel) - Method in class meka.gui.modelviewer.renderers.PlainTextRenderer: Performs the actual rendering.
dot(SparseVector) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseVector
dot(double[], double[]) - Static method in class meka.core.MatrixUtils: dot product of two vectors
doUpdateMenu() - Method in class meka.gui.core.AbstractRecentItemsHandler: Updates the menu.
downSampleRatioTipText() - Method in class meka.classifiers.multilabel.BRq
downSampleRatioTipText() - Method in class meka.classifiers.multilabel.CCq
dsigma(double) - Static method in class meka.core.MatrixUtils: Derivative of the sigmoid function applied to scalar
dsigma(double[]) - Static method in class meka.core.MatrixUtils: Derivative of the sigmoid function applied to vector
dsigma(double[][]) - Static method in class meka.core.MatrixUtils: Derivative of the sigmoid function applied to Matrix
dsigma(Matrix) - Static method in class meka.core.MatrixUtils: Derivative of the sigmoid function applied to Jama Matrix
dW_ - Variable in class meka.classifiers.multilabel.BPNN
dW_ - Variable in class rbms.RBM

E

edit() - Method in class meka.gui.explorer.Explorer: edits the current instances object in the viewer
editClassifier() - Method in class meka.gui.experimenter.BasicSetup: Lets the user edit a classifier.
editClassifier() - Method in class meka.gui.experimenter.ExpertSetup: Lets the user edit a classifier.
editNotes() - Method in class meka.gui.experimenter.BasicSetup: Displays dialog for entering notes in Markdown.
editNotes() - Method in class meka.gui.experimenter.ExpertSetup: Displays dialog for entering notes in Markdown.
EditTestData - Class in meka.gui.explorer.classify: Menu item for loading a model from disk.
EditTestData() - Constructor for class meka.gui.explorer.classify.EditTestData
EM - Class in meka.classifiers.multilabel.meta: EM.java - Expectation Maximization using any multi-label classifier.
EM() - Constructor for class meka.classifiers.multilabel.meta.EM
EMPTY_ICON - Static variable in class meka.gui.core.GUIHelper: the empty icon name.
emptyVectors(int[][]) - Static method in class meka.core.MLUtils: EmptyVectors - percentage of empty vectors sum(y[i])==0 in Y.
encodeClass(int[]) - Static method in class meka.core.SuperLabelUtils: Encode a sparse list of indices to a string
encodeClass(int) - Static method in class meka.filters.multilabel.SuperNodeFilter: (3,'_') -> "c_3"
encodeClass(String, String) - Static method in class meka.filters.multilabel.SuperNodeFilter: (["c_3","c_1"]) -> "c_3+1"
encodeClass(int[]) - Static method in class meka.filters.multilabel.SuperNodeFilter: ([3,1]) -> "c_3+1"
encodeValue(int[]) - Static method in class meka.core.MLUtils: Deprecated.
encodeValue(Instance, int[]) - Static method in class meka.core.SuperLabelUtils: Encode a vector of integer values to a string
encodeValue(String, String) - Static method in class meka.filters.multilabel.SuperNodeFilter: (3,1) -> "3+1"
encodeValue(Instance, int[]) - Static method in class meka.filters.multilabel.SuperNodeFilter: (3,1,2) -> "3+1+2"
EnsembleML - Class in meka.classifiers.multilabel.meta: EnsembleML.java - Combines several multi-label classifiers in a simple-subset ensemble.
EnsembleML() - Constructor for class meka.classifiers.multilabel.meta.EnsembleML
EnsembleMT - Class in meka.classifiers.multitarget.meta: The Multi-Target Version of EnsembleML.
EnsembleMT() - Constructor for class meka.classifiers.multitarget.meta.EnsembleMT
ensureThreadSafety(Experiment, Evaluator) - Static method in class meka.experiment.ExperimentUtils: Makes sure that the experiment uses a threadsafe setup.
ensureThreadSafety(Experiment) - Static method in class meka.experiment.ExperimentUtils: Makes sure that the experiment uses a threadsafe setup.
epoch(Matrix) - Method in class rbms.RBM: Epoch - Run X through one epcho of CD of the RBM.
equals(Object) - Method in class meka.core.LabelSet
equals(Object) - Method in class meka.core.LabelVector
equals(Object) - Method in class meka.gui.core.RecentFilesHandlerWithCommandline.Setup: Returns true if the other object is also a RecentFilesHandlerWithCommandline.Setup instance and contains the same file.
equals(Object) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel.SortContainer: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class meka.gui.explorer.AbstractResultHistoryPlugin: Checks equality using the name of the plugin.
equals(Object) - Method in class meka.gui.guichooser.AbstractMenuItemDefinition: Checks equality using the name of the plugin.
escape(String) - Static method in class meka.core.LatexUtils: Ensures that the string is LaTeX compliant.
escape(String, LatexUtils.Characters[]) - Static method in class meka.core.LatexUtils: Ensures that the string is LaTeX compliant.
eTipText() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
evaluate(MultiLabelClassifier, Instances) - Method in class meka.experiment.evaluators.CrossValidation: Returns the evaluation statistics generated for the dataset.
evaluate(MultiLabelClassifier, Instances) - Method in interface meka.experiment.evaluators.Evaluator: Returns the evaluation statistics generated for the dataset.
evaluate(MultiLabelClassifier, Instances) - Method in class meka.experiment.evaluators.PercentageSplit: Returns the evaluation statistics generated for the dataset.
evaluate(MultiLabelClassifier, Instances) - Method in class meka.experiment.evaluators.RepeatedRuns: Returns the evaluation statistics generated for the dataset.
evaluateModel(MultiLabelClassifier, Instances, Instances, String) - Static method in class meka.classifiers.multilabel.Evaluation: EvaluateModel - Build model 'h' on 'D_train', test it on 'D_test', threshold it according to 'top', using default verbosity option.
evaluateModel(MultiLabelClassifier, Instances, Instances, String, String) - Static method in class meka.classifiers.multilabel.Evaluation: EvaluateModel - Build model 'h' on 'D_train', test it on 'D_test', threshold it according to 'top', verbosity 'vop'.
evaluateModel(MultiLabelClassifier, Instances, String, String) - Static method in class meka.classifiers.multilabel.Evaluation: EvaluateModel - Assume 'h' is already built, test it on 'D_test', threshold it according to 'top', verbosity 'vop'.
evaluateModel(MultiLabelClassifier, Instances, Instances) - Static method in class meka.classifiers.multilabel.Evaluation: EvaluateModel - Build model 'h' on 'D_train', test it on 'D_test'.
evaluateModel(MultiLabelClassifier, String[]) - Static method in class meka.classifiers.multilabel.incremental.IncrementalEvaluation: EvaluateModel - Build and evaluate.
evaluateModel(MultiLabelClassifier, Instances) - Static method in class meka.classifiers.multilabel.incremental.IncrementalEvaluation: EvaluateModel - over 20 windows.
evaluateModelBatchWindow(MultiLabelClassifier, Instances, int, double, String, String) - Static method in class meka.classifiers.multilabel.incremental.IncrementalEvaluation: EvaluateModelBatchWindow - Evaluate a multi-label data-stream model over windows.
evaluateModelM(MultiLabelClassifier, Instances, Instances, String, String) - Static method in class meka.classifiers.multilabel.Evaluation
evaluateModelPrequentialBasic(MultiLabelClassifier, Instances, int, double, String, String) - Static method in class meka.classifiers.multilabel.incremental.IncrementalEvaluation: Prequential Evaluation - Accuracy since the start of evaluation.
evaluateParallel(MultiLabelClassifier, Instances) - Method in class meka.experiment.evaluators.CrossValidation: Returns the evaluation statistics generated for the dataset (parallel execution).
evaluateParallel(MultiLabelClassifier, Instances) - Method in class meka.experiment.evaluators.RepeatedRuns: Executes the runs in sequential order.
evaluateSequential(MultiLabelClassifier, Instances) - Method in class meka.experiment.evaluators.CrossValidation: Returns the evaluation statistics generated for the dataset (sequential execution).
evaluateSequential(MultiLabelClassifier, Instances) - Method in class meka.experiment.evaluators.RepeatedRuns: Executes the runs in sequential order.
evaluation(MultiLabelClassifier, String[]) - Static method in class meka.classifiers.multilabel.AbstractMultiLabelClassifier: Called by classifier's main() method upon initialisation from the command line.
Evaluation - Class in meka.classifiers.multilabel: Evaluation.java - Evaluation functionality.
Evaluation() - Constructor for class meka.classifiers.multilabel.Evaluation
evaluation(MultiLabelClassifier, String[]) - Static method in class meka.classifiers.multilabel.ProblemTransformationMethod: Called by classifier's main() method upon initialisation from the command line.
EvaluationStatistics - Class in meka.experiment.evaluationstatistics: Stores evaluation statistics.
EvaluationStatistics() - Constructor for class meka.experiment.evaluationstatistics.EvaluationStatistics: Default constructor.
EvaluationStatistics(MultiLabelClassifier, Instances, Result) - Constructor for class meka.experiment.evaluationstatistics.EvaluationStatistics: Extracts the statistics from the Result object.
EvaluationStatistics(MultiLabelClassifier, String, Result) - Constructor for class meka.experiment.evaluationstatistics.EvaluationStatistics: Extracts the statistics from the Result object.
EvaluationStatisticsComparator - Class in meka.experiment.evaluationstatistics: Comparator for statistics.
EvaluationStatisticsComparator() - Constructor for class meka.experiment.evaluationstatistics.EvaluationStatisticsComparator: Initializes the comparator with the default keys.
EvaluationStatisticsComparator(String[]) - Constructor for class meka.experiment.evaluationstatistics.EvaluationStatisticsComparator: Initializes the comparator with the specified keys.
EvaluationStatisticsExporter - Interface in meka.experiment.statisticsexporters: Interface for classes that export statistics into other formats.
EvaluationStatisticsExporterFileChooser - Class in meka.gui.choosers: File chooser for evaluation statistics exporters (only writers, no readers!).
EvaluationStatisticsExporterFileChooser() - Constructor for class meka.gui.choosers.EvaluationStatisticsExporterFileChooser
EvaluationStatisticsFileChooser - Class in meka.gui.choosers: File chooser for evaluation statistics files.
EvaluationStatisticsFileChooser() - Constructor for class meka.gui.choosers.EvaluationStatisticsFileChooser
EvaluationStatisticsHandler - Interface in meka.experiment.evaluationstatistics: Interface for classes that load and save collected EvaluationStatistics in some form.
EvaluationStatisticsTableModel - Class in meka.gui.core: The table model for evaluation statistics.
EvaluationStatisticsTableModel() - Constructor for class meka.gui.core.EvaluationStatisticsTableModel: Initializes the model with no statistics.
EvaluationStatisticsTableModel(List<EvaluationStatistics>) - Constructor for class meka.gui.core.EvaluationStatisticsTableModel: Initializes the model with the statistics.
EvaluationStatisticsUtils - Class in meka.experiment.evaluationstatistics: Helper class for stats related operations.
EvaluationStatisticsUtils() - Constructor for class meka.experiment.evaluationstatistics.EvaluationStatisticsUtils
Evaluator - Interface in meka.experiment.evaluators: Interface for classes that evaluate on a dataset.
EvaluatorJob - Class in meka.experiment.evaluators: Job to be used in parallel execution.
EvaluatorJob() - Constructor for class meka.experiment.evaluators.EvaluatorJob
evaluatorTipText() - Method in class meka.experiment.DefaultExperiment: Describes this property.
evaluatorTipText() - Method in class meka.experiment.evaluators.AbstractMetaEvaluator: Describes this property.
evaluatorTipText() - Method in interface meka.experiment.Experiment: Describes this property.
ExceptionUtils - Class in meka.core: Helper class for throwables and exceptions.
ExceptionUtils() - Constructor for class meka.core.ExceptionUtils
executionFinalized() - Method in class meka.gui.explorer.AbstractThreadedExplorerTab: Gets called when the thread has finished completely.
executionFinished(Throwable) - Method in class meka.gui.explorer.AbstractThreadedExplorerTab: Gets called when the thread finishes or gets stopped.
executionFinished(Throwable) - Method in class meka.gui.explorer.ClassifyTab: Gets called when the thread finishes or gets stopped.
executionFinished(Throwable) - Method in class meka.gui.explorer.PreprocessTab: Gets called when the thread finishes or gets stopped.
ExecutionStageEvent - Class in meka.experiment.events: Event that gets sent by an experiment when it enters a new stage in the execution.
ExecutionStageEvent(Experiment, ExecutionStageEvent.Stage) - Constructor for class meka.experiment.events.ExecutionStageEvent: Gets called when the experiment enters a new stage.
ExecutionStageEvent.Stage - Enum in meka.experiment.events: The stages of an experiment.
ExecutionStageListener - Interface in meka.experiment.events: Interface for classes that want to be notified whenever an experiment enters a new stage.
executionStarted() - Method in class meka.gui.explorer.AbstractThreadedExplorerTab: Gets called when the thread starts.
executionStarted() - Method in class meka.gui.explorer.ClassifyTab: Gets called when the thread starts.
executionStarted() - Method in class meka.gui.explorer.PreprocessTab: Gets called when the thread starts.
expand(String) - Method in class meka.gui.core.AbstractRecentItemsHandler: Adds the prefix to the property name if provided.
expandFile(String) - Static method in class meka.core.Project: Adds the home directory to the file.
Experiment - Interface in meka.experiment: Interface for experiments.
Experimenter - Class in meka.gui.experimenter: Experimenter interface.
Experimenter() - Constructor for class meka.gui.experimenter.Experimenter
ExperimenterDefinition - Class in meka.gui.guichooser: Launches the Experimenter.
ExperimenterDefinition() - Constructor for class meka.gui.guichooser.ExperimenterDefinition
ExperimentFileChooser - Class in meka.gui.choosers: File chooser for experiment files.
ExperimentFileChooser() - Constructor for class meka.gui.choosers.ExperimentFileChooser
ExperimentFileHandler - Interface in meka.experiment.filehandlers: Interface for classes load/save experiments.
experimentStage(ExecutionStageEvent) - Method in interface meka.experiment.events.ExecutionStageListener: Gets called when the experiment enters a new stage.
experimentStage(ExecutionStageEvent) - Method in class meka.gui.experimenter.AbstractExperimenterTab: Gets called when the experiment enters a new stage.
experimentStage(ExecutionStageEvent) - Method in class meka.gui.experimenter.AbstractSetupTab: Gets called when the experiment enters a new stage.
experimentStage(ExecutionStageEvent) - Method in class meka.gui.experimenter.Experimenter: Gets called when the experiment enters a new stage.
experimentStage(ExecutionStageEvent) - Method in class meka.gui.experimenter.LogTab: Gets called when the experiment enters a new stage.
experimentStage(ExecutionStageEvent) - Method in class meka.gui.experimenter.Statistics: Gets called when the experiment enters a new stage.
ExperimentUtils - Class in meka.experiment: Experiment related methods.
ExperimentUtils() - Constructor for class meka.experiment.ExperimentUtils
ExpertSetup - Class in meka.gui.experimenter: Tab for setting up a experiment in expert mode.
ExpertSetup() - Constructor for class meka.gui.experimenter.ExpertSetup
Explorer - Class in meka.gui.explorer: Explorer GUI for MEKA.
Explorer() - Constructor for class meka.gui.explorer.Explorer
ExplorerDefinition - Class in meka.gui.guichooser: Launches the Explorer.
ExplorerDefinition() - Constructor for class meka.gui.guichooser.ExplorerDefinition
export(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.AbstractEvaluationStatisticsExporter: Exports the statistics.
export(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.AbstractFileBasedEvaluationStatisticsExporter: Exports the statistics.
export(List<EvaluationStatistics>) - Method in interface meka.experiment.statisticsexporters.EvaluationStatisticsExporter: Exports the statistics.
export() - Method in class meka.gui.dataviewer.DataViewerDialog: Exports the data to a file.
exportersTipText() - Method in class meka.experiment.statisticsexporters.MultiExporter: Describes this property.
exporterTipText() - Method in class meka.experiment.statisticsexporters.AbstractMetaEvaluationStatisticsExporter: Describes this property.
ExtensionFileFilterComparator - Class in meka.gui.choosers: Comparator for file filters.
ExtensionFileFilterComparator() - Constructor for class meka.gui.choosers.ExtensionFileFilterComparator
ExtensionFileFilterWithClass - Class in meka.gui.choosers: A custom filter class that stores the associated class along the description and extensions.
ExtensionFileFilterWithClass(String, String, String) - Constructor for class meka.gui.choosers.ExtensionFileFilterWithClass: Constructs a filter that matches files with the given extension, not case-sensitive.
ExtensionFileFilterWithClass(String[], String, String) - Constructor for class meka.gui.choosers.ExtensionFileFilterWithClass: Constructs a filter that matches files with the given extension, not case-sensitive.
extractPart(Instances, boolean) - Method in class meka.classifiers.multilabel.LabelTransformationClassifier: Returns a new set of instances either only with the labels (labels = true) or only the features (labels = false)
extractValues(Instances) - Static method in class meka.core.SuperLabelUtils: Returns a map of values for this multi-class Instances.

F

F - Class in meka.core: F.java - transform/Filter Operations on instances.
F() - Constructor for class meka.core.F
F(Instances) - Static method in class meka.core.StatUtils: F - Relative frequency matrix (between p(j),p(k) and p(j,k)) in dataset D.
F1(int[], int[]) - Static method in class meka.core.Metrics: F1 - the F1 measure for two sets.
fastLearnTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
FileBasedEvaluationStatisticsExporter - Interface in meka.experiment.statisticsexporters: Interface for file-based statistics exporters.
FileBasedEvaluationStatisticsHandler - Interface in meka.experiment.evaluationstatistics: Interface for file-based statistics handlers.
FileBasedMeasurementEvaluationStatisticsExporter - Interface in meka.experiment.statisticsexporters: Interface for file-based statistics exporters for a single measurement.
FileChooserBookmarksFactory() - Constructor for class meka.gui.core.FileChooserBookmarksPanel.FileChooserBookmarksFactory
FileChooserBookmarksPanel - Class in meka.gui.core: Panel for bookmarking directories in a JFileChooser.
FileChooserBookmarksPanel() - Constructor for class meka.gui.core.FileChooserBookmarksPanel
FileChooserBookmarksPanel.FileChooserBookmarksFactory - Class in meka.gui.core: MEKA-specific factory.
FileChooserBookmarksPanel.FileChooserBookmarksPropertiesHandler - Class in meka.gui.core: The MEKA-specific properties handler.
FileChooserBookmarksPropertiesHandler() - Constructor for class meka.gui.core.FileChooserBookmarksPanel.FileChooserBookmarksPropertiesHandler
FileFormatSupporter - Interface in meka.core: For classes that support file formats.
FILENAME - Static variable in class meka.core.Version: the file name.
FILENAME - Static variable in class meka.gui.core.FileChooserBookmarksPanel: the properties to store the bookmarks in.
FILENAME - Static variable in class meka.gui.core.GUIHelper: the name of the props file.
fileTipText() - Method in class meka.experiment.evaluationstatistics.AbstractFileBasedEvaluationStatisticsHandler: Describes this property.
fileTipText() - Method in interface meka.experiment.evaluationstatistics.FileBasedEvaluationStatisticsHandler: Describes this property.
fileTipText() - Method in class meka.experiment.statisticsexporters.AbstractFileBasedEvaluationStatisticsExporter: Describes this property.
fileTipText() - Method in interface meka.experiment.statisticsexporters.FileBasedEvaluationStatisticsExporter: Describes this property.
FileTypeDeterminingFileChooser<R,W> - Interface in meka.gui.choosers: Interface for file choosers that support the determination of readers and writers based on filenames (namely extensions).
FileUtils - Class in meka.core: Utility class for I/O related actions.
FileUtils() - Constructor for class meka.core.FileUtils
fillCol(double[][], int, double) - Static method in class meka.core.MatrixUtils
fillRow(double[][], int, double) - Static method in class meka.core.MatrixUtils
filter(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.WekaFilter: Filters the statistics using the specified filter.
filterData(Filter, String) - Method in class meka.gui.explorer.PreprocessTab: Filters the data with the specified filter.
FilteredClassifier - Class in meka.classifiers.multilabel.meta: Allows the application of a filter in conjunction with a multi-label classifier.
FilteredClassifier() - Constructor for class meka.classifiers.multilabel.meta.FilteredClassifier: Default constructor.
FilteredClassifier - Class in meka.classifiers.multitarget.meta: Allows the application of a filter in conjunction with a multi-target classifier.
FilteredClassifier() - Constructor for class meka.classifiers.multitarget.meta.FilteredClassifier: Default constructor.
filterTipText() - Method in class meka.experiment.statisticsexporters.WekaFilter: Describes this property.
find(String) - Static method in class meka.core.PropsUtils: Locates the properties file in the current classpath.
findView(PropertyEditor) - Static method in class meka.gui.goe.GenericObjectEditor: Tries to determine a view for the editor.
finish() - Method in class meka.experiment.datasetproviders.AbstractDatasetProvider: Gets called after the experiment finishes.
finish() - Method in interface meka.experiment.datasetproviders.DatasetProvider: Gets called after the experiment finishes.
finish() - Method in class meka.experiment.DefaultExperiment: Finishes the experiment.
finish() - Method in class meka.experiment.evaluationstatistics.AbstractEvaluationStatisticsHandler: Gets called after the experiment finished.
finish() - Method in interface meka.experiment.evaluationstatistics.EvaluationStatisticsHandler: Gets called after the experiment finished.
finish() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Gets called after the experiment finished.
finish() - Method in class meka.experiment.evaluationstatistics.Serialized: Gets called after the experiment finished.
finish() - Method in interface meka.experiment.Experiment: Finishes the experiment.
finishBusy() - Method in class meka.gui.core.StatusBar: Stops the animated icon, without setting status message.
finishBusy(String) - Method in class meka.gui.core.StatusBar: Stops the animated icon, setting the specified status message.
finishBusy() - Method in class meka.gui.experimenter.AbstractExperimenterTab: Stops the animated icon, without setting status message.
finishBusy(String) - Method in class meka.gui.experimenter.AbstractExperimenterTab: Stops the animated icon, setting the specified status message.
finishBusy() - Method in class meka.gui.explorer.AbstractExplorerTab: Stops the animated icon, without setting status message.
finishBusy(String) - Method in class meka.gui.explorer.AbstractExplorerTab: Stops the animated icon, setting the specified status message.
finishInit() - Method in class meka.gui.core.MekaDialog: finishes the initialization, by setting size/location.
finishInit() - Method in class meka.gui.core.MekaFrame: finishes the initialization, by setting size/location.
finishInit() - Method in class meka.gui.core.MekaPanel: Finishes the initialization.
finishInit() - Method in class meka.gui.experimenter.AbstractSetupTab: Finishes the GUI setup.
finishInit() - Method in class meka.gui.experimenter.Experimenter: Finishes the initialization.
finishInit() - Method in class meka.gui.explorer.Explorer: Finishes the initialization.
fixRelationName(Instances) - Static method in class meka.core.MLUtils: Fixes the relation name by adding the "-C" attribute to it if necessary.
fixRelationName(Instances, int) - Static method in class meka.core.MLUtils: Fixes the relation name by adding the "-C" attribute to it if necessary.
flatten(int[][]) - Static method in class meka.core.MatrixUtils: Flatten - turn Matrix [0 1; 2 3] into vector [0 1 2 3].
flatten(double[][]) - Static method in class meka.core.MatrixUtils: Flatten - turn Matrix [0.
flatten(List, String) - Static method in class meka.core.ObjectUtils: Flattens the list into a single, long string.
flatten(Object[], String) - Static method in class meka.core.ObjectUtils: Flattens the array into a single, long string.
floor(Key) - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Returns the largest key in the symbol table less than or equal to key.
forwardPass(double[][]) - Method in class meka.classifiers.multilabel.BPNN: Forward Pass - Given input X_, get output of all layers Z[0]...
freeNetworks() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
fromBitString(String) - Static method in class meka.core.MLUtils: FromBitString - returns a double[] representation of s.
fromCommandLine(Class<T>, String) - Static method in class meka.core.OptionUtils: Turns a commandline into an object.
fromExperiment() - Method in class meka.gui.experimenter.AbstractSetupTab: Maps the experiment onto the parameters.
fromExperiment() - Method in class meka.gui.experimenter.BasicSetup: Maps the experiment onto the parameters.
fromExperiment() - Method in class meka.gui.experimenter.ExpertSetup: Maps the experiment onto the parameters.
fromInstances(Instances) - Method in class meka.experiment.statisticsexporters.WekaFilter: Converts the Instances back into statistics.
fromSparseString(String) - Static method in class meka.core.MLUtils: From Sparse String - From a sparse String representation, e.g., [1,34,73], to a binary int[] where those indices are set to 1.
fromString(String) - Method in class meka.gui.core.AbstractRecentItemsHandler: Turns the string obtained from the props into an object again.
fromString(String) - Method in class meka.gui.core.RecentFilesHandler: Turns the string obtained from the props into an object again.
fromString(String) - Method in class meka.gui.core.RecentFilesHandlerWithCommandline: Turns the string obtained from the props into an object again.
FW - Class in meka.classifiers.multilabel: FW.java Four-class pairWise classification.
FW() - Constructor for class meka.classifiers.multilabel.FW

G

gen_indices(int) - Static method in class meka.core.MLUtils: Deprecated.
generatePartition(int) - Static method in class meka.core.SuperLabelUtils: generatePartition - return [[0],...,[L-1]].
generatePartition(int[], Random) - Static method in class meka.core.SuperLabelUtils: generatePartition - .
generatePartition(int[], int, Random) - Static method in class meka.core.SuperLabelUtils: Generate a random Partition.
generatePartition(int[], int, Random, boolean) - Static method in class meka.core.SuperLabelUtils: Generate Random Partition
GenericObjectEditor - Class in meka.gui.goe: An extended GOE to cater for the multi-label classifiers.
GenericObjectEditor() - Constructor for class meka.gui.goe.GenericObjectEditor: Default constructor.
GenericObjectEditor(boolean) - Constructor for class meka.gui.goe.GenericObjectEditor: Constructor that allows specifying whether it is possible to change the class within the editor dialog.
GenericObjectEditorDialog - Class in meka.gui.goe: Displays a GenericObjectEditor.
GenericObjectEditorDialog(Dialog) - Constructor for class meka.gui.goe.GenericObjectEditorDialog: Creates a modeless dialog without a title with the specified Dialog as its owner.
GenericObjectEditorDialog(Dialog, Dialog.ModalityType) - Constructor for class meka.gui.goe.GenericObjectEditorDialog: Creates a dialog with the specified owner Dialog and modality.
GenericObjectEditorDialog(Dialog, String) - Constructor for class meka.gui.goe.GenericObjectEditorDialog: Creates a modeless dialog with the specified title and with the specified owner dialog.
GenericObjectEditorDialog(Dialog, String, Dialog.ModalityType) - Constructor for class meka.gui.goe.GenericObjectEditorDialog: Creates a dialog with the specified title, modality and the specified owner Dialog.
GenericObjectEditorDialog(Frame) - Constructor for class meka.gui.goe.GenericObjectEditorDialog: Creates a modeless dialog without a title with the specified Frame as its owner.
GenericObjectEditorDialog(Frame, boolean) - Constructor for class meka.gui.goe.GenericObjectEditorDialog: Creates a dialog with the specified owner Frame, modality and an empty title.
GenericObjectEditorDialog(Frame, String) - Constructor for class meka.gui.goe.GenericObjectEditorDialog: Creates a modeless dialog with the specified title and with the specified owner frame.
GenericObjectEditorDialog(Frame, String, boolean) - Constructor for class meka.gui.goe.GenericObjectEditorDialog: Creates a dialog with the specified owner Frame, modality and title.
GenericPropertiesCreator - Class in meka.gui.goe: Custom GOE props creator, to include the MEKA classes.
GenericPropertiesCreator() - Constructor for class meka.gui.goe.GenericPropertiesCreator: initializes the creator, locates the props file with the Utils class.
get(int) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Gets the Object mapped from the specified key, or null if no such mapping has been made.
get(int, Double) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Gets the Object mapped from the specified key, or the specified Object if no such mapping has been made.
get(int) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseVector
get(Key) - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Returns the value associated with the given key.
get(int) - Method in class meka.gui.core.ResultHistory: Returns the specified history item.
get_k_subset(int, int, Random) - Static method in class meka.core.SuperLabelUtils: Get k subset - return a set of k label indices (of L possible labels).
getAction() - Method in class meka.gui.experimenter.menu.AbstractExperimenterMenuItem: Returns the action.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.AbstractResultHistoryPlugin: Returns the action lister to use in the menu.
getActionListener(T) - Method in class meka.gui.explorer.AbstractTabMenuItem: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.AbstractShowThresholdCurve: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.CopyModelSetup: Returns the action lister to use in the menu.
getActionListener(ClassifyTab) - Method in class meka.gui.explorer.classify.EditTestData: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.IncrementalPerformance: Returns the action lister to use in the menu.
getActionListener(ClassifyTab) - Method in class meka.gui.explorer.classify.OpenModel: Returns the action lister to use in the menu.
getActionListener(ClassifyTab) - Method in class meka.gui.explorer.classify.OpenTestData: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.PredictionsOnTestset: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.ReevaluateModelOnTestset: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.SaveCSV: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.SaveGraphs: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.SaveModel: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.SavePredictions: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.ShowGraphs: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.ShowMacroCurve: Returns the action lister to use in the menu.
getActionListener(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.ShowMicroCurve: Returns the action lister to use in the menu.
getActualNumThreads(int, int) - Static method in class meka.core.ThreadUtils: Calculates the number of threads to use.
getActualRow(int) - Method in interface meka.gui.core.SearchableTable: Returns the actual row in the model.
getActualRow(int) - Method in interface meka.gui.core.SearchableTableModel: Returns the actual row in the model.
getActualRow(int) - Method in class meka.gui.core.SortableAndSearchableTable: Returns the actual underlying row the given visible one represents.
getActualRow(int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the actual underlying row the given visible one represents.
getActualRow(int) - Method in interface meka.gui.core.SortableTableModel: Returns the actual underlying row the given visible one represents.
getActualRowCount() - Method in interface meka.gui.core.SearchableTable: Returns the actual row count in the model.
getActualRowCount() - Method in interface meka.gui.core.SearchableTableModel: Returns the actual row count in the model.
getActualRowCount() - Method in class meka.gui.core.SortableAndSearchableTable: Returns the actual row count in the model.
getActualRowCount() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the actual row count in the model.
getAggregationKeys() - Method in interface meka.experiment.statisticsexporters.AggregatedEvaluationStatisticsExporter: Returns the blank-separated list of keys used for aggregating.
getAggregationKeys() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns the blank-separated list of keys used for aggregating.
getAllSubsets(LabelSet, HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils: GetAllSubsets - Get all frequent subsets of 'y' according to 'map'.
getApproveButton() - Method in class meka.gui.core.ApprovalDialog: Returns the approve button.
getApproveCaption() - Method in class meka.gui.core.ApprovalDialog: Returns the caption/text of the approve button.
getApproveMnemonic() - Method in class meka.gui.core.ApprovalDialog: Returns the mnemonic of the approve button.
getApproxC(Instances) - Static method in class meka.core.StatUtils: GetApproxP - A fast version of getC(D), based on frequent sets.
getApproxP(Instances) - Static method in class meka.core.StatUtils: GetApproxP - A fast version of getP(D), based on frequent sets.
getAttributeAt(int) - Method in class meka.gui.dataviewer.DataSortedTableModel: returns the attribute at the given index, can be NULL if not an attribute column
getAttributeAt(int) - Method in class meka.gui.dataviewer.DataTableModel: returns the attribute at the given index, can be NULL if not an attribute column
getAttributeColumn(String) - Method in class meka.gui.dataviewer.DataSortedTableModel: returns the column of the given attribute name, -1 if not found
getAttributeColumn(String) - Method in class meka.gui.dataviewer.DataTableModel: returns the column of the given attribute name, -1 if not found
getAttributeIndices() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes: Get the current range selection
getAttributes() - Method in class meka.gui.dataviewer.DataPanel: returns a list with the attributes
getAttSizePercent() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML: Gets the percentage of attributes to sample from the original set.
getAvailableProcessors() - Static method in class meka.core.ThreadUtils: Returns the available number of processors on the machine.
getBagSizePercent() - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
getBeta() - Method in class meka.classifiers.multilabel.PMCC: Get the temperature factor
getBitness() - Static method in class meka.core.OS: Returns the "bitness", ie 32 or 64 bit of the underlying OS.
getButton() - Method in class meka.gui.guichooser.AbstractMenuItemDefinition: Returns the shortcut button.
getButtonCaption() - Method in class meka.gui.core.SearchPanel: Returns the current caption of the search button (incl.
getC(Instances) - Static method in class meka.core.StatUtils: GetC - Get pairwise co-ocurrence counts from the training data D.
getCancelButton() - Method in class meka.gui.core.ApprovalDialog: Returns the cancel button.
getCancelCaption() - Method in class meka.gui.core.ApprovalDialog: Returns the caption/text of the Cancel button.
getCancelMnemonic() - Method in class meka.gui.core.ApprovalDialog: Returns the mnemonic of the Cancel button.
getCapabilities() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
getCapabilities() - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM
getCapabilities() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getCapabilities() - Method in class meka.classifiers.multilabel.ProblemTransformationMethod
getCapabilities() - Method in class meka.classifiers.multitarget.NSR
getCapabilities() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes: Returns the Capabilities of this filter.
getCaretPosition() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Returns the current caret position.
getCaretPosition() - Method in class meka.gui.core.MarkdownTextPane: Returns the current position of the cursor.
getCellEditor(int, int) - Method in class meka.gui.dataviewer.DataTable: returns the cell editor for the given cell
getCellEditorValue() - Method in class meka.gui.dataviewer.DataTable.RelationalCellEditor: Returns the value contained in the editor.
getCenteredLeft() - Method in class meka.gui.dataviewer.DataViewer: returns the left coordinate if the frame would be centered
getCenteredTop() - Method in class meka.gui.dataviewer.DataViewer: returns the top coordinate if the frame would be centered
getChainIterations() - Method in class meka.classifiers.multilabel.MCC: Get the iterations of s (chain order)
getChooseClassPopupMenu() - Method in class meka.gui.goe.GenericObjectEditor: Returns a popup menu that allows the user to change the class of object.
getClassesFromProperties() - Method in class meka.gui.goe.GenericObjectEditor: Called when the class of object being edited changes.
getClassifier() - Method in class meka.classifiers.multilabel.cc.CNode: Returns the underlying classifier.
getClassifier() - Method in class meka.experiment.evaluationstatistics.EvaluationStatistics: Returns the classifier for these statistics.
getClassifier() - Method in class meka.experiment.events.IterationNotificationEvent: Returns the classifier.
getClassifier(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.AbstractClassifyResultHistoryPlugin: Returns the classifier from the history list.
getClassifier() - Method in class meka.gui.explorer.ClassifyTab: Returns the current classifier.
getClassifiers() - Method in class meka.experiment.DefaultExperiment: Returns the classifiers to be evaluated.
getClassifiers() - Method in interface meka.experiment.Experiment: Returns the classifiers to be evaluated.
getClassname() - Method in class meka.gui.choosers.ExtensionFileFilterWithClass: Returns the associated classname.
getClassType() - Method in class meka.gui.goe.GenericObjectEditor: Returns the class of values that can be edited.
getClosest(HashMap<String, CC>, String) - Static method in class meka.classifiers.multilabel.PMCC: GetClosest - returns the 'CC' in 'map' which is built on the sequence most matched to 'sequence'.
getClusterVigilance() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
getCol(double[][], int) - Static method in class meka.core.MatrixUtils: GetCol - return the k-th column of M (as a vector).
getCol(int[][], int) - Static method in class meka.core.MatrixUtils: GetCol - return the k-th column of M (as a vector).
getColumnClass(int) - Method in class meka.gui.core.EvaluationStatisticsTableModel: Returns the type of the column.
getColumnClass(int) - Method in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: Returns the type of the column.
getColumnClass(int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the most specific superclass for all the cell values in the column.
getColumnClass(int) - Method in class meka.gui.dataviewer.DataTableModel: returns the most specific superclass for all the cell values in the column (always String)
getColumnClassForComparison(int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the class of the column.
getColumnCount() - Method in class meka.gui.core.EvaluationStatisticsTableModel: The number of columns in this model.
getColumnCount() - Method in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: The number of columns in this model.
getColumnCount() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the number of columns in the model.
getColumnCount() - Method in class meka.gui.dataviewer.DataTableModel: returns the number of columns in the model
getColumnName(int) - Method in class meka.gui.core.EvaluationStatisticsTableModel: Returns the name of the column.
getColumnName(int) - Method in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: Returns the name of the column.
getColumnName(int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the name of the column at columnIndex.
getColumnName(int) - Method in class meka.gui.dataviewer.DataTableModel: returns the name of the column at columnIndex
getColumns() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Returns the columns.
getCommandLine() - Method in class meka.experiment.evaluationstatistics.EvaluationStatistics: Returns the commandline of the classifier for these statistics.
getCompression() - Method in class meka.classifiers.multilabel.Maniac: Get the Compression value.
getConfidences() - Method in class meka.classifiers.multilabel.CC: GetConfidences - get the posterior probabilities of the previous prediction (after calling distributionForInstance(x)).
getConfirmationDialog(Dialog) - Static method in class meka.gui.core.ApprovalDialog: Returns a basic (modal) confirmation dialog (yes/no/cancel).
getConfirmationDialog(Dialog, Dialog.ModalityType) - Static method in class meka.gui.core.ApprovalDialog: Returns a basic confirmation dialog (yes/no/cancel).
getConfirmationDialog(Frame) - Static method in class meka.gui.core.ApprovalDialog: Returns a basic (modal) confirmation dialog (yes/no/cancel).
getConfirmationDialog(Frame, boolean) - Static method in class meka.gui.core.ApprovalDialog: Returns a basic confirmation dialog (yes/no/cancel).
getConfirmExit() - Method in class meka.gui.dataviewer.DataViewer: returns the setting of whether to display a confirm messagebox or not on exit
getConfirmExit() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the setting of whether to display a confirm messagebox or not on exit
getContentPanel() - Method in class meka.gui.core.ApprovalDialog: Returns the panel to add the content to.
getCountKey() - Method in class meka.gui.core.AbstractRecentItemsHandler: Returns the key to use for the counts in the props file.
getCountKey() - Method in class meka.gui.core.RecentFilesHandler: Returns the key to use for the counts in the props file.
getCountKey() - Method in class meka.gui.core.RecentFilesHandlerWithCommandline: Returns the key to use for the counts in the props file.
getCounts(Instances, int[], int) - Static method in class meka.core.SuperLabelUtils: Return a set of all the combinations of attributes at 'indices' in 'D', pruned by 'p'; AND THEIR COUNTS, e.g., {(00:3),(01:8),(11:3))}.
getCounts(Instances, int[], int) - Static method in class meka.filters.multilabel.SuperNodeFilter: Return a set of all the combinations of attributes at 'indices' in 'D', pruned by 'p'; AND THEIR COUNTS, e.g., {(00:3),(01:8),(11:3))}.
getCurrent() - Method in class meka.gui.goe.GenericObjectEditorDialog: Returns the current object.
getCurrentData() - Method in class meka.gui.explorer.Explorer: Returns the currently loaded data.
getCurrentExperiment() - Method in class meka.gui.experimenter.Experimenter: Returns the current experiment, null if not available.
getCurrentFile() - Method in class meka.gui.experimenter.Experimenter: Returns the filename of the currently loaded data.
getCurrentFile() - Method in class meka.gui.explorer.Explorer: Returns the filename of the currently loaded data.
getCurrentFilename() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the filename of the current tab
getCurrentIndex() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the currently selected tab index
getCurrentPanel() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the currently selected panel
getData() - Method in class meka.gui.explorer.AbstractExplorerTab: Returns the current data.
getDataset() - Method in class meka.experiment.events.IterationNotificationEvent: Returns the dataset.
getDatasetName(Instances) - Static method in class meka.core.MLUtils: GetDataSetName - Look for name in the 'relationName' in format 'dataset-name: options'
getDatasetOptions(Instances) - Static method in class meka.core.MLUtils: GetDataSetOptions - Look for options in the 'relationName' in format 'dataset-name: options'
getDatasetProvider() - Method in class meka.experiment.DefaultExperiment: Returns the dataset provider in use.
getDatasetProvider() - Method in interface meka.experiment.Experiment: Returns the dataset provider in use.
getDatasets() - Method in class meka.experiment.datasetproviders.LocalDatasetProvider: Returns the datasets to use in the experiment.
getDebug() - Method in interface meka.classifiers.multilabel.MultiLabelClassifier: Get whether debugging is turned on.
getDebug() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
getDebug() - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM
getDebug() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getDebug() - Method in interface meka.classifiers.multitarget.MultiTargetClassifier: Get whether debugging is turned on.
getDefaultAggregationKeys() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns the default keys used for aggregation.
getDefaultClassifier() - Method in class meka.classifiers.multilabel.LabelTransformationClassifier
getDefaultClassifier() - Method in class meka.classifiers.multilabel.Maniac: Change default classifier to CR with Linear Regression as base as this classifier uses numeric values in the compressed labels.
getDefaultClassifier() - Method in class meka.classifiers.multilabel.PLST: Change default classifier to CR with Linear Regression as base as this classifier uses numeric values in the compressed labels.
getDefaultCompression() - Method in class meka.classifiers.multilabel.Maniac: Returns the default compression, 0.85 seems to be a good value for most settings.
getDefaultDatasetProvider() - Method in class meka.experiment.DefaultExperiment: Returns the default dataset provider.
getDefaultDimensions(String, int, int) - Static method in class meka.gui.core.GUIHelper: Returns the default dimensions for this prefix.
getDefaultEvaluator() - Method in class meka.experiment.DefaultExperiment: Returns the default evaluator to use.
getDefaultEvaluator() - Method in class meka.experiment.evaluators.AbstractMetaEvaluator: Returns the default evaluator to use.
getDefaultEvaluator() - Method in class meka.experiment.evaluators.RepeatedRuns: Returns the default evaluator to use.
getDefaultExporter() - Method in class meka.experiment.statisticsexporters.AbstractMetaEvaluationStatisticsExporter: Returns the default exporter to use.
getDefaultExporter() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns the default exporter to use.
getDefaultExporter() - Method in class meka.experiment.statisticsexporters.WekaFilter: Returns the default exporter to use.
getDefaultExporters() - Method in class meka.experiment.statisticsexporters.MultiExporter: Returns the default exporters to use.
getDefaultFile() - Method in class meka.experiment.evaluationstatistics.AbstractFileBasedEvaluationStatisticsHandler: Returns the default file.
getDefaultFile() - Method in class meka.experiment.statisticsexporters.AbstractFileBasedEvaluationStatisticsExporter: Returns the default file.
getDefaultFileFilter(int) - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Returns the default file filter to use.
getDefaultFileFilter(int) - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Returns the default file filter to use.
getDefaultFilter() - Method in class meka.experiment.statisticsexporters.WekaFilter: Returns the default keys used for aggregation.
getDefaultFrameDimensions() - Static method in class meka.gui.core.GUIHelper: Returns the default frame dimensions.
getDefaultFrameDimensions(Class) - Static method in class meka.gui.core.GUIHelper: Returns the default frame dimensions for this class.
getDefaultFrameIcon(Class) - Static method in class meka.gui.core.GUIHelper: Returns the default icon name for this frame class.
getDefaultLowerRuns() - Method in class meka.experiment.evaluators.RepeatedRuns: Returns the default lower number of runs to perform.
getDefaultMeasurement() - Method in class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter: Returns the default exporters to use.
getDefaultNumberAutoencoders() - Method in class meka.classifiers.multilabel.Maniac: Returns the default number of autoencoders, set to 4, which seems to be good choice for most problems.
getDefaultNumFolds() - Method in class meka.experiment.evaluators.CrossValidation: Gets the number of folds.
getDefaultNumThreads() - Method in class meka.experiment.evaluators.CrossValidation: Returns the default number of threads to use.
getDefaultNumThreads() - Method in class meka.experiment.evaluators.RepeatedRuns: Returns the default number of threads to use.
getDefaultOptimizeAE() - Method in class meka.classifiers.multilabel.Maniac: Tge default setting for optimizing the autoencoders.
getDefaultProviders() - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Returns the default dataset providers to use.
getDefaultReader() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Returns the default reader.
getDefaultReader() - Method in class meka.gui.choosers.EvaluationStatisticsExporterFileChooser: Returns the default reader.
getDefaultReader() - Method in class meka.gui.choosers.EvaluationStatisticsFileChooser: Returns the default reader.
getDefaultReader() - Method in class meka.gui.choosers.ExperimentFileChooser: Returns the default reader.
getDefaultReader() - Method in class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser: Returns the default reader.
getDefaultSeed() - Method in class meka.classifiers.multilabel.CC
getDefaultSeed() - Method in class meka.experiment.evaluators.CrossValidation: Gets the default seed for the random number generations
getDefaultSeed() - Method in class meka.experiment.evaluators.PercentageSplit: Gets the default seed for the random number generations
getDefaultSize() - Method in class meka.classifiers.multilabel.MLCBMaD: Default size = 20, seems to be a good choice for most data sets.
getDefaultSize() - Method in class meka.classifiers.multilabel.PLST: The default size, set to 5.
getDefaultStatisticsHandler() - Method in class meka.experiment.DefaultExperiment: Returns the default statistics handler.
getDefaultSuffixCount() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns the default suffix for the count.
getDefaultSuffixMean() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns the default suffix for the mean.
getDefaultSuffixStdDev() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns the default suffix for the stddev.
getDefaultThreshold() - Method in class meka.classifiers.multilabel.MLCBMaD: Default threshold = 0.5, has to be in at least half of the rows.
getDefaultThreshold() - Method in class meka.experiment.evaluators.CrossValidation: Gets the default threshold option.
getDefaultThreshold() - Method in class meka.experiment.evaluators.PercentageSplit: Gets the default threshold option.
getDefaultTrainPercentage() - Method in class meka.experiment.evaluators.PercentageSplit: Gets the default percentage to use for training.
getDefaultUpperRuns() - Method in class meka.experiment.evaluators.RepeatedRuns: Returns the default upper number of runs to perform.
getDefaultVerbosity() - Method in class meka.experiment.evaluators.CrossValidation: Gets the default threshold option.
getDefaultVerbosity() - Method in class meka.experiment.evaluators.PercentageSplit: Gets the default threshold option.
getDefaultWriter() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Returns the default writer.
getDefaultWriter() - Method in class meka.gui.choosers.EvaluationStatisticsExporterFileChooser: Returns the default writer.
getDefaultWriter() - Method in class meka.gui.choosers.EvaluationStatisticsFileChooser: Returns the default writer.
getDefaultWriter() - Method in class meka.gui.choosers.ExperimentFileChooser: Returns the default writer.
getDefaultWriter() - Method in class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser: Returns the default writer.
getDefaultXColumn() - Method in class meka.gui.explorer.classify.AbstractShowThresholdCurve: Returns the name of the default X column to display.
getDefaultXColumn() - Method in class meka.gui.explorer.classify.ShowMacroCurve: Returns the name of the default X column to display.
getDefaultXColumn() - Method in class meka.gui.explorer.classify.ShowMicroCurve: Returns the name of the default X column to display.
getDefaultXColumn() - Method in class meka.gui.explorer.classify.ShowPrecisionRecall: Returns the name of the default X column to display.
getDefaultXColumn() - Method in class meka.gui.explorer.classify.ShowROC: Returns the name of the default X column to display.
getDefaultYColumn() - Method in class meka.gui.explorer.classify.AbstractShowThresholdCurve: Returns the name of the default Y column to display.
getDefaultYColumn() - Method in class meka.gui.explorer.classify.ShowMacroCurve: Returns the name of the default Y column to display.
getDefaultYColumn() - Method in class meka.gui.explorer.classify.ShowMicroCurve: Returns the name of the default Y column to display.
getDefaultYColumn() - Method in class meka.gui.explorer.classify.ShowPrecisionRecall: Returns the name of the default Y column to display.
getDefaultYColumn() - Method in class meka.gui.explorer.classify.ShowROC: Returns the name of the default Y column to display.
getDefinitions() - Static method in class meka.gui.guichooser.AbstractMenuItemDefinition: Returns all the available menu items.
getDensity() - Method in class meka.classifiers.multilabel.CDT: GetDensity - Get the neighbourhood density (number of neighbours for each node).
getDensity() - Method in class meka.classifiers.multilabel.CT: GetDensity - Get the neighbourhood density (number of neighbours for each node).
getDependencyMetric() - Method in class meka.classifiers.multilabel.CDT: GetDependency - Get the type of depependency to use in rearranging the trellis (None by default)
getDependencyMetric() - Method in class meka.classifiers.multilabel.CT: GetDependency - Get the type of depependency to use in rearranging the trellis
getDependencyType() - Method in class meka.classifiers.multilabel.BCC
getDialogType() - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Returns the current dialog type.
getDim(double[][]) - Static method in class meka.core.MatrixUtils
getDim(Matrix) - Static method in class meka.core.MatrixUtils
getDirectoryDepth(File) - Static method in class meka.core.FileUtils: Returns the number of directories that this file object contains.
getDiscardButton() - Method in class meka.gui.core.ApprovalDialog: Returns the discard button.
getDiscardCaption() - Method in class meka.gui.core.ApprovalDialog: Returns the caption/text of the discard button.
getDiscardMnemonic() - Method in class meka.gui.core.ApprovalDialog: Returns the mnemonic of the discard button.
getDisplayRow(int) - Method in class meka.gui.core.SortableAndSearchableTable: Returns the "visible" row derived from row in the actual table model.
getDisplayRow(int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the "visible" row derived from row in the actual table model.
getDisplayRow(int) - Method in interface meka.gui.core.SortableTableModel: Returns the "visible" row derived from row in the actual table model.
getDocument() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Returns the underlying document.
getDocument() - Method in class meka.gui.core.MarkdownTextPane: Returns the underlying document.
getDownSampleRatio() - Method in class meka.classifiers.multilabel.BRq
getDownSampleRatio() - Method in class meka.classifiers.multilabel.CCq: Get the downsample ratio
getE() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
getE() - Method in class rbms.RBM
getEditor() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Returns the GOE, initializes it if necessary.
getEditor() - Method in class meka.gui.goe.GenericObjectEditorDialog: Returns the underlying editor.
getElementAt(int) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel: Returns the element at the specified location.
getEmptyIcon() - Static method in class meka.gui.core.GUIHelper: Returns the ImageIcon for the empty icon.
getEvaluator() - Method in class meka.experiment.DefaultExperiment: Returns the evaluator in use.
getEvaluator() - Method in class meka.experiment.evaluators.AbstractMetaEvaluator: Returns the evaluator in use.
getEvaluator() - Method in interface meka.experiment.Experiment: Returns the evaluator in use.
getExitOnClose() - Method in class meka.gui.dataviewer.DataViewer: returns TRUE if a System.exit(0) is done on a close
getExitOnClose() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns TRUE if a System.exit(0) is done on a close
getExperiment() - Method in class meka.experiment.events.ExecutionStageEvent: Returns the associated experiment.
getExperiment() - Method in class meka.experiment.events.IterationNotificationEvent: Returns the associated experiment.
getExperiment() - Method in class meka.experiment.events.StatisticsNotificationEvent: Returns the associated experiment.
getExperiment() - Method in class meka.gui.experimenter.AbstractExperimenterTab: Returns the current experiment.
getExporter() - Method in class meka.experiment.statisticsexporters.AbstractMetaEvaluationStatisticsExporter: Returns the exporter in use.
getExporters() - Method in class meka.experiment.statisticsexporters.MultiExporter: Returns the exporter in use.
getExtension(File) - Static method in class meka.core.FileUtils: Returns the extension of the file, if any.
getExtension(String) - Static method in class meka.core.FileUtils: Returns the extension of the file, if any.
getExternalIcon(String) - Static method in class meka.gui.core.GUIHelper: Returns an ImageIcon from the given name.
getFastLearn() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getFile() - Method in class meka.experiment.evaluationstatistics.AbstractFileBasedEvaluationStatisticsHandler: Returns the file to read from/write to.
getFile() - Method in interface meka.experiment.evaluationstatistics.FileBasedEvaluationStatisticsHandler: Returns the file to read from/write to.
getFile() - Method in class meka.experiment.statisticsexporters.AbstractFileBasedEvaluationStatisticsExporter: Returns the file to read from/write to.
getFile() - Method in interface meka.experiment.statisticsexporters.FileBasedEvaluationStatisticsExporter: Returns the file to read from/write to.
getFile() - Method in class meka.gui.core.RecentFilesHandlerWithCommandline.Setup: Returns the file.
getFileChooser() - Method in class meka.gui.explorer.classify.SaveCSV: Returns the file chooser to use for the data.
getFileChooser() - Method in class meka.gui.explorer.classify.SaveGraphs: Returns the file chooser to use for the graphs.
getFileChooser() - Method in class meka.gui.explorer.classify.SaveModel: Returns the file chooser to use for the models.
getFileChooser() - Method in class meka.gui.explorer.classify.SavePredictions: Returns the file chooser to use for the results.
getFileMustExist() - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Returns whether the selected file must exist (only open dialog).
getFilename() - Method in class meka.gui.core.FileChooserBookmarksPanel.FileChooserBookmarksPropertiesHandler: The properties file in the $HOME/.meka directory.
getFilename() - Method in class meka.gui.dataviewer.DataPanel: returns the filename
getFilename(int) - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the filename of the specified panel
getFilter() - Method in class meka.experiment.statisticsexporters.WekaFilter: Returns the filter to use.
getFiltersInitialized() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Returns whether the filters have already been initialized.
getFiltersInitialized() - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Returns whether the filters have already been initialized.
getFiltersInitialized() - Method in class meka.gui.choosers.EvaluationStatisticsExporterFileChooser: Returns whether the filters have already been initialized.
getFiltersInitialized() - Method in class meka.gui.choosers.EvaluationStatisticsFileChooser: Returns whether the filters have already been initialized.
getFiltersInitialized() - Method in class meka.gui.choosers.ExperimentFileChooser: Returns whether the filters have already been initialized.
getFiltersInitialized() - Method in class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser: Returns whether the filters have already been initialized.
getFolds() - Method in class meka.gui.explorer.ClassifyTabOptions: Returns the currently set folds value.
getFormatDescription() - Method in interface meka.core.FileFormatSupporter: Returns the format description.
getFormatDescription() - Method in interface meka.experiment.evaluationstatistics.FileBasedEvaluationStatisticsHandler: Returns the format description.
getFormatDescription() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Returns the format description.
getFormatDescription() - Method in class meka.experiment.evaluationstatistics.Serialized: Returns the format description.
getFormatDescription() - Method in class meka.experiment.filehandlers.CommandLineSetup: A description of the file format.
getFormatDescription() - Method in interface meka.experiment.filehandlers.ExperimentFileHandler: A description of the file format.
getFormatDescription() - Method in class meka.experiment.filehandlers.SerializedExperiment: A description of the file format.
getFormatDescription() - Method in interface meka.experiment.statisticsexporters.FileBasedEvaluationStatisticsExporter: Returns the format description.
getFormatDescription() - Method in class meka.experiment.statisticsexporters.LatexMeasurement: Returns the format description.
getFormatDescription() - Method in class meka.experiment.statisticsexporters.TabSeparated: Returns the format description.
getFormatDescription() - Method in class meka.experiment.statisticsexporters.TabSeparatedMeasurement: Returns the format description.
getFormatExtensions() - Method in interface meka.core.FileFormatSupporter: Returns the format extension(s).
getFormatExtensions() - Method in interface meka.experiment.evaluationstatistics.FileBasedEvaluationStatisticsHandler: Returns the format extension(s).
getFormatExtensions() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Returns the format extension(s).
getFormatExtensions() - Method in class meka.experiment.evaluationstatistics.Serialized: Returns the format extension(s).
getFormatExtensions() - Method in class meka.experiment.filehandlers.CommandLineSetup: Returns the format extensions.
getFormatExtensions() - Method in interface meka.experiment.filehandlers.ExperimentFileHandler: Returns the format extensions.
getFormatExtensions() - Method in class meka.experiment.filehandlers.SerializedExperiment: Returns the format extensions.
getFormatExtensions() - Method in interface meka.experiment.statisticsexporters.FileBasedEvaluationStatisticsExporter: Returns the format extension(s).
getFormatExtensions() - Method in class meka.experiment.statisticsexporters.LatexMeasurement: Returns the format extension(s).
getFormatExtensions() - Method in class meka.experiment.statisticsexporters.TabSeparated: Returns the format extension(s).
getFormatExtensions() - Method in class meka.experiment.statisticsexporters.TabSeparatedMeasurement: Returns the format extension(s).
getFrameTitle() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the title (incl.
getGOEDialog(Class, Object) - Method in class meka.gui.experimenter.AbstractSetupTab: Returns a GOE dialog.
getGOEEditor() - Method in class meka.gui.goe.GenericObjectEditorDialog: Returns the underlying GOE editor.
getGroup() - Method in class meka.gui.explorer.AbstractResultHistoryPlugin: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.AbstractTabMenuItem: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.AbstractShowThresholdCurve: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.CopyModelSetup: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.EditTestData: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.IncrementalPerformance: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.OpenModel: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.OpenTestData: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.PredictionsOnTestset: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.ReevaluateModelOnTestset: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.SaveCSV: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.SaveGraphs: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.SaveModel: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.SavePredictions: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.ShowGraphs: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.ShowMacroCurve: Returns the group of the plugin.
getGroup() - Method in class meka.gui.explorer.classify.ShowMicroCurve: Returns the group of the plugin.
getGroup() - Method in class meka.gui.guichooser.AbstractMenuItemDefinition: The name of the menu this item belongs to.
getGroup() - Method in class meka.gui.guichooser.DataViewerDefinition: The name of the menu this item belongs to.
getGroup() - Method in class meka.gui.guichooser.ExperimenterDefinition: The name of the menu this item belongs to.
getGroup() - Method in class meka.gui.guichooser.ExplorerDefinition: The name of the menu this item belongs to.
getGroup() - Method in class meka.gui.guichooser.HomepageDefinition: The name of the menu this item belongs to.
getGroup() - Method in class meka.gui.guichooser.ModelViewerDefinition: The name of the menu this item belongs to.
getGroup() - Method in class meka.gui.guichooser.PrecisionRecallCurve: The name of the menu this item belongs to.
getGroup() - Method in class meka.gui.guichooser.ROC: The name of the menu this item belongs to.
getGroup() - Method in class meka.gui.guichooser.SystemInfo: The name of the menu this item belongs to.
getH() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
getH() - Method in class rbms.RBM
getHandler() - Method in class meka.gui.core.RecentFilesHandlerWithCommandline.Setup: Returns the handler.
getHandler() - Method in class meka.gui.events.RecentItemEvent: Returns the handler that triggered the event.
getHeader(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.AbstractClassifyResultHistoryPlugin: Returns the dataset header from the history list.
getHeaderMouseListener() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the mouse listener that got assigned to the header, if any.
getHistory() - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel: Returns the underlying history.
getHome() - Static method in class meka.core.Project: Returns the "home" directory of Meka, where to store the config files.
getI() - Method in class meka.classifiers.multilabel.CDN: GetI - Get the number of iterations.
getI() - Method in class meka.classifiers.multitarget.SCC
getIc() - Method in class meka.classifiers.multilabel.CDN: GetIc - Get the number of collection iterations.
getIcon(Class) - Static method in class meka.gui.core.GUIHelper: Returns an ImageIcon for the given class.
getIcon(String) - Static method in class meka.gui.core.GUIHelper: Returns an ImageIcon from the given name.
getIcon() - Method in class meka.gui.experimenter.menu.AbstractExperimenterMenuItem: Returns the icon for the menu item.
getIcon() - Method in class meka.gui.explorer.AbstractTabMenuItem: Returns the name of the icon to use.
getIcon() - Method in class meka.gui.explorer.classify.EditTestData: Returns the name of the icon to use.
getIcon() - Method in class meka.gui.explorer.classify.OpenModel: Returns the name of the icon to use.
getIcon() - Method in class meka.gui.explorer.classify.OpenTestData: Returns the name of the icon to use.
getIcon() - Method in class meka.gui.guichooser.AbstractMenuItemDefinition: Returns the icon to use.
getIconName() - Method in class meka.gui.experimenter.menu.AbstractExperimenterMenuItem: Returns the name of the icon to use.
getIconName() - Method in class meka.gui.experimenter.menu.CombineStatisticsFiles: Returns the name of the icon to use.
getIconName() - Method in class meka.gui.guichooser.AbstractMenuItemDefinition: The name of the menu icon.
getIconName() - Method in class meka.gui.guichooser.DataViewerDefinition: The name of the menu icon.
getIconName() - Method in class meka.gui.guichooser.ExperimenterDefinition: The name of the menu icon.
getIconName() - Method in class meka.gui.guichooser.ExplorerDefinition: The name of the menu icon.
getIconName() - Method in class meka.gui.guichooser.HomepageDefinition: The name of the menu icon.
getIconName() - Method in class meka.gui.guichooser.ModelViewerDefinition: The name of the menu icon.
getIconName() - Method in class meka.gui.guichooser.PrecisionRecallCurve: The name of the menu icon.
getIconName() - Method in class meka.gui.guichooser.ROC: The name of the menu icon.
getIconName() - Method in class meka.gui.guichooser.SystemInfo: The name of the menu icon.
getIgnoreStateChangeEvent() - Method in class meka.gui.core.MaximizationFixWindowListener: Returns whether change events are currently ignored.
getImageFilename(String) - Static method in class meka.gui.core.GUIHelper: Adds the path of the images directory to the name of the image.
getIndex() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel.SortContainer: Returns the original index of the item.
getInferenceIterations() - Method in class meka.classifiers.multilabel.MCC: Get the inference iterations
getInfo(String) - Method in class meka.core.Result: GetInfo.
getInformationDialog(Dialog) - Static method in class meka.gui.core.ApprovalDialog: Returns a basic (modal) info dialog (ok).
getInformationDialog(Dialog, Dialog.ModalityType) - Static method in class meka.gui.core.ApprovalDialog: Returns a basic info dialog (ok).
getInformationDialog(Frame) - Static method in class meka.gui.core.ApprovalDialog: Returns a basic (modal) info dialog (ok).
getInformationDialog(Frame, boolean) - Static method in class meka.gui.core.ApprovalDialog: Returns a basic info dialog (ok).
getInstances() - Method in class meka.gui.dataviewer.DataPanel: returns the instances of the panel, if none then NULL
getInstances() - Method in class meka.gui.dataviewer.DataSortedTableModel: returns the data
getInstances() - Method in class meka.gui.dataviewer.DataTableModel: returns the data
getInstances() - Method in class meka.gui.dataviewer.DataViewerDialog: returns the currently displayed instances
getInstancesAt(int, int) - Method in class meka.gui.dataviewer.DataTable.RelationalCellEditor: returns the underlying instances at the given position
getInstancesValueAt(int, int) - Method in class meka.gui.dataviewer.DataSortedTableModel: returns the double value of the underlying Instances object at the given position, -1 if out of bounds
getInstancesValueAt(int, int) - Method in class meka.gui.dataviewer.DataTableModel: returns the double value of the underlying Instances object at the given position, -1 if out of bounds
getIntegerOption(String, int) - Static method in class meka.core.MLUtils: GetIntegerOption - parse 'op' to an integer if we can, else used default 'def'.
getItem() - Method in class meka.gui.events.RecentItemEvent: Returns the affected file.
getItem() - Method in class meka.gui.experimenter.menu.AbstractExperimenterMenuItem: Returns the name of the menu item.
getItem() - Method in class meka.gui.experimenter.menu.CombineStatisticsFiles: Returns the name of the menu item.
getItemPrefix() - Method in class meka.gui.core.AbstractRecentItemsHandler: Returns the key prefix to use for the items in the props file.
getItemPrefix() - Method in class meka.gui.core.RecentFilesHandler: Returns the key prefix to use for the items in the props file.
getItemPrefix() - Method in class meka.gui.core.RecentFilesHandlerWithCommandline: Returns the key prefix to use for the items in the props file.
getIterations() - Method in class meka.classifiers.multilabel.meta.EM
getIv() - Method in class meka.classifiers.multitarget.SCC
getJTable() - Method in class meka.gui.core.JTableHelper: returns the JTable.
getK() - Method in class meka.classifiers.multilabel.RAkELd: GetK - Get the k parameter (size of partitions).
getK() - Method in class meka.classifiers.multitarget.RAkELd: GetK - Get the k parameter (size of partitions).
getK(Instances) - Method in class meka.core.MLUtils: Get K - get the number of values associated with each label L.
getKeys() - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray
getKeysString() - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray
getLabel(int) - Method in class meka.gui.core.ParameterPanel: Returns the label for the parameter at the specified location.
getLayoutType() - Method in class meka.gui.core.SearchPanel: Returns the type of layout.
getLearningRate() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
getLearningRate() - Method in class rbms.RBM
getLimit() - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
getLineWrap() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Returns whether line wrap is enabled.
getList() - Method in class meka.gui.core.ListWithButtons: Returns the list.
getLogListeners() - Method in class meka.events.LogObject: Returns the log listeners.
getLogoIcon() - Static method in class meka.gui.core.GUIHelper: Returns an ImageIcon of the logo (icon sized image).
getLogoImage() - Static method in class meka.gui.core.GUIHelper: Returns an ImageIcon of the logo (large image).
getLowerRuns() - Method in class meka.experiment.evaluators.RepeatedRuns: Returns the lower number of runs to perform (included).
getM() - Method in class meka.classifiers.multilabel.PMCC: Get the population size
getM() - Method in class meka.classifiers.multilabel.RAkEL: GetM - Get the M parameter (number of subsets).
getMainPanel() - Method in class meka.gui.dataviewer.DataViewer: returns the main panel
getMarkdown() - Method in class meka.gui.core.MarkdownDialog: Returns the markdown text.
getMaxCount() - Method in class meka.gui.core.AbstractRecentItemsHandler: Returns the maximum number of items to keep.
getMeasurement(String) - Method in class meka.core.Result: Retrieve the measurement for metric 'metric'.
getMeasurement() - Method in class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter: Returns the measurement in use.
getMeasurement() - Method in interface meka.experiment.statisticsexporters.FileBasedMeasurementEvaluationStatisticsExporter: Returns the measurement in use.
getMeasurement() - Method in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: Returns the measurement the model is for.
getMenu() - Method in class meka.gui.core.AbstractRecentItemsHandler: Returns the menu to add the recent items as subitems to.
getMenu() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the menu bar to be added in a frame
getMenu() - Method in class meka.gui.experimenter.AbstractExperimenterTab: Returns an optional menu to be added to the Experimenter menu.
getMenu() - Method in class meka.gui.experimenter.menu.AbstractExperimenterMenuItem: Returns the name of the menu this menu item will get added to.
getMenu() - Method in class meka.gui.experimenter.menu.CombineStatisticsFiles: Returns the name of the menu this menu item will get added to.
getMenu() - Method in class meka.gui.experimenter.Statistics: Returns an optional menu to be added to the Experimenter menu.
getMenu() - Method in class meka.gui.explorer.AbstractExplorerTab: Returns an optional menu to be added to the Explorer menu.
getMenu() - Method in class meka.gui.explorer.ClassifyTab: Returns an optional menu to be added to the Explorer menu.
getMenuBar() - Method in interface meka.gui.core.MenuBarProvider: Returns the menu bar to use.
getMenuBar() - Method in class meka.gui.experimenter.Experimenter: Returns the menu bar to use.
getMenuBar() - Method in class meka.gui.explorer.Explorer: Returns the menu bar to use.
getMenuBar() - Method in class meka.gui.guichooser.GUIChooser: Returns the menu bar to use.
getMenuBar() - Method in class meka.gui.modelviewer.ModelViewer: Returns the menu bar to use.
getMenuItem() - Method in class meka.gui.guichooser.AbstractMenuItemDefinition: Returns the menu item to insert
getMenuItems() - Static method in class meka.gui.experimenter.menu.AbstractExperimenterMenuItem: Returns the classnames of all additional experiment menu items.
getMessage() - Method in class meka.events.LogEvent: Returns the message.
getMethod() - Method in class meka.classifiers.multilabel.MULAN
getMinimumChars() - Method in class meka.gui.core.SearchPanel: Returns the minimum number of characters that the user needs to enter before triggering a search event.
getMLStats(double[][], int[][], String, String) - Static method in class meka.core.MLEvalUtils: GetMLStats - Given predictions and corresponding true values and a threshold string, retreive statistics.
getMLStats(double[][], int[][], double[], String) - Static method in class meka.core.MLEvalUtils: GetMLStats - Given predictions and corresponding true values and a threshold string, retreive statistics.
getMnemonic(String) - Static method in class meka.gui.core.GUIHelper: Returns the mnemonic for this caption, preceded by an underscore "_".
getModel() - Method in class meka.classifiers.multilabel.AbstractMultiLabelClassifier: Returns a string representation of the model.
getModel() - Method in class meka.classifiers.multilabel.CC: Returns a string representation of the model.
getModel() - Method in class meka.classifiers.multilabel.Maniac
getModel() - Method in class meka.classifiers.multilabel.meta.FilteredClassifier: Returns a string representation of the model.
getModel() - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod: Returns a string representation of the model.
getModel() - Method in class meka.classifiers.multilabel.MLCBMaD
getModel() - Method in interface meka.classifiers.multilabel.MultiLabelClassifier: Returns a string representation of the model.
getModel() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
getModel() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast
getModel() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse
getModel() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH
getModel() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT
getModel() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange
getModel() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV
getModel() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
getModel() - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM
getModel() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getModel() - Method in class meka.classifiers.multilabel.PLST: Returns a string representation of the model.
getModel() - Method in class meka.classifiers.multilabel.ProblemTransformationMethod: Returns a string representation of the model.
getModel() - Method in interface meka.classifiers.multitarget.MultiTargetClassifier: Returns a string representation of the model.
getModel(String) - Method in class meka.core.Result: Get the model value.
getModelValueAt(int, int) - Method in class meka.gui.dataviewer.DataSortedTableModel: returns the value at the given position
getMomentum() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
getMomentum() - Method in class rbms.RBM
getMonospacedFont() - Static method in class meka.gui.core.GUIHelper: Returns the system wide Monospaced font.
getMTStats(double[][], int[][], String) - Static method in class meka.core.MLEvalUtils: GetMTStats - Given multi-target predictions and corresponding true values, retreive evaluation statistics.
getN() - Method in class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
getN() - Method in class meka.classifiers.multilabel.PS: GetN - Get the subsampling value N.
getName() - Method in class meka.gui.explorer.AbstractResultHistoryPlugin: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.AbstractTabMenuItem: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.CopyModelSetup: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.EditTestData: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.IncrementalPerformance: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.OpenModel: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.OpenTestData: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.PredictionsOnTestset: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.ReevaluateModelOnTestset: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.SaveCSV: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.SaveGraphs: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.SaveModel: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.SavePredictions: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.ShowGraphs: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.ShowMacroCurve: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.ShowMicroCurve: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.ShowPrecisionRecall: Returns the name of the plugin.
getName() - Method in class meka.gui.explorer.classify.ShowROC: Returns the name of the plugin.
getName() - Method in class meka.gui.guichooser.AbstractMenuItemDefinition: The name of the menu item.
getName() - Method in class meka.gui.guichooser.DataViewerDefinition: The name of the menu item.
getName() - Method in class meka.gui.guichooser.ExperimenterDefinition: The name of the menu item.
getName() - Method in class meka.gui.guichooser.ExplorerDefinition: The name of the menu item.
getName() - Method in class meka.gui.guichooser.HomepageDefinition: The name of the menu item.
getName() - Method in class meka.gui.guichooser.ModelViewerDefinition: The name of the menu item.
getName() - Method in class meka.gui.guichooser.PrecisionRecallCurve: The name of the menu item.
getName() - Method in class meka.gui.guichooser.ROC: The name of the menu item.
getName() - Method in class meka.gui.guichooser.SystemInfo: The name of the menu item.
getNeighbours(int) - Method in class meka.classifiers.multilabel.cc.Trellis: Get the neighbouring variables of a given index.
getNeighbours(String, ArrayList<String>, int) - Static method in class meka.filters.multilabel.SuperNodeFilter: GetNeighbours - return from set S, label-vectors closest to y, having no more different than 'n' bits different.
getNeighbours(String, HashMap<String, Integer>, int) - Static method in class meka.filters.multilabel.SuperNodeFilter: GetNeighbours - return from set S (the keySet of HashMap C), label-vectors closest to y, having no more different than 'n' bits different.
getneuronsactivated() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
getneuronsactivity() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
getNeuronsActivity() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getNeuronsActivityFileName() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getNotes() - Method in class meka.experiment.DefaultExperiment: Returns the notes.
getNotes() - Method in interface meka.experiment.Experiment: Returns the notes.
getNumberAutoencoders() - Method in class meka.classifiers.multilabel.Maniac: Get the numberAutoencoders value.
getNumFolds() - Method in class meka.experiment.evaluators.CrossValidation: Gets the number of folds
getNumIterations() - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
getNumThreads() - Method in interface meka.core.ThreadLimiter: Returns the number of threads to use.
getNumThreads() - Method in class meka.experiment.evaluators.CrossValidation: Returns the number of threads to use.
getNumThreads() - Method in class meka.experiment.evaluators.RepeatedRuns: Returns the number of threads to use.
getO() - Method in class meka.classifiers.multilabel.PMCC: Get the temperature switch
getOpenFileFilters() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Returns the file filters for opening files.
getOpenFileFilters() - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Returns the file filters for opening files.
getOpenFileFilters() - Method in class meka.gui.choosers.EvaluationStatisticsExporterFileChooser: Returns the file filters for opening files.
getOpenFileFilters() - Method in class meka.gui.choosers.EvaluationStatisticsFileChooser: Returns the file filters for opening files.
getOpenFileFilters() - Method in class meka.gui.choosers.ExperimentFileChooser: Returns the file filters for opening files.
getOpenFileFilters() - Method in class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser: Returns the file filters for opening files.
getOption() - Method in class meka.gui.core.ApprovalDialog: Returns the selected option.
getOptions() - Method in class meka.classifiers.multilabel.BCC
getOptions() - Method in class meka.classifiers.multilabel.BRq
getOptions() - Method in class meka.classifiers.multilabel.CC
getOptions() - Method in class meka.classifiers.multilabel.CCq
getOptions() - Method in class meka.classifiers.multilabel.CDN
getOptions() - Method in class meka.classifiers.multilabel.CDT
getOptions() - Method in class meka.classifiers.multilabel.CT
getOptions() - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
getOptions() - Method in class meka.classifiers.multilabel.Maniac: Returns an array with the options of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.MCC
getOptions() - Method in class meka.classifiers.multilabel.meta.EM
getOptions() - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
getOptions() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
getOptions() - Method in class meka.classifiers.multilabel.MLCBMaD: Returns an array with the options of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.MULAN
getOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork: Gets the current settings of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast: Gets the current settings of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse: Gets the current settings of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH: Gets the current settings of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT: Gets the current settings of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange: Gets the current settings of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV: Gets the current settings of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork: Gets the current settings of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM: Gets the current settings of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM: Gets the current settings of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
getOptions() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
getOptions() - Method in class meka.classifiers.multilabel.PLST: Returns an array with the options of the classifier.
getOptions() - Method in class meka.classifiers.multilabel.PMCC
getOptions() - Method in class meka.classifiers.multilabel.PS
getOptions() - Method in class meka.classifiers.multilabel.RAkEL
getOptions() - Method in class meka.classifiers.multilabel.RAkELd
getOptions() - Method in class meka.classifiers.multitarget.RAkELd
getOptions() - Method in class meka.classifiers.multitarget.SCC
getOptions() - Method in class meka.experiment.datasetproviders.AbstractDatasetProvider: Returns the options.
getOptions() - Method in class meka.experiment.datasetproviders.LocalDatasetProvider: Returns the options.
getOptions() - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Returns the options.
getOptions() - Method in class meka.experiment.DefaultExperiment: Returns the options.
getOptions() - Method in class meka.experiment.evaluationstatistics.AbstractEvaluationStatisticsHandler: Returns the options.
getOptions() - Method in class meka.experiment.evaluationstatistics.AbstractFileBasedEvaluationStatisticsHandler: Returns the options.
getOptions() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Returns the options.
getOptions() - Method in class meka.experiment.evaluators.AbstractEvaluator: Returns the options.
getOptions() - Method in class meka.experiment.evaluators.AbstractMetaEvaluator: Returns the options.
getOptions() - Method in class meka.experiment.evaluators.CrossValidation: Returns the options.
getOptions() - Method in class meka.experiment.evaluators.PercentageSplit: Returns the options.
getOptions() - Method in class meka.experiment.evaluators.RepeatedRuns: Returns the options.
getOptions() - Method in class meka.experiment.filehandlers.AbstractExperimentFileHandler: Returns the options.
getOptions() - Method in class meka.experiment.statisticsexporters.AbstractEvaluationStatisticsExporter: Returns the options.
getOptions() - Method in class meka.experiment.statisticsexporters.AbstractFileBasedEvaluationStatisticsExporter: Returns the options.
getOptions() - Method in class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter: Returns the options.
getOptions() - Method in class meka.experiment.statisticsexporters.AbstractMetaEvaluationStatisticsExporter: Returns the options.
getOptions() - Method in class meka.experiment.statisticsexporters.MultiExporter: Returns the options.
getOptions() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns the options.
getOptions() - Method in class meka.experiment.statisticsexporters.WekaFilter: Returns the options.
getOptions() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes: Gets the current settings of the filter.
getOptions() - Method in class rbms.RBM: GetOptions - WEKA-style option processing.
getOwner() - Method in class meka.gui.core.MaximizationFixWindowListener: Returns the owner.
getOwner() - Method in class meka.gui.experimenter.AbstractExperimenterTab: Returns the Experimenter instance this tab belongs to.
getOwner() - Method in class meka.gui.experimenter.menu.AbstractExperimenterMenuItem: Returns the owner.
getOwner() - Method in class meka.gui.explorer.AbstractExplorerTab: Returns the Explorer instance this tab belongs to.
getOwner() - Method in class meka.gui.explorer.AbstractResultHistoryPlugin: Returns the tab the plugin belongs to.
getOwner() - Method in class meka.gui.explorer.AbstractThreadedExplorerTab.WorkerThread: Returns the tab this thread belongs to.
getP() - Method in class meka.classifiers.multilabel.PS: GetP - Get the pruning value P.
getP(Instances) - Static method in class meka.core.StatUtils: GetP - Get a pairwise empirical joint-probability matrix P[][] from dataset D.
getP(int[][], int) - Static method in class meka.core.StatUtils
getP() - Method in class meka.filters.multilabel.SuperNodeFilter
getPackFrame(Class) - Static method in class meka.gui.core.GUIHelper: Returns whether this application needs to be packed, rather than use a specific window size.
getPanel(int) - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the specified panel, null if index is out of bounds
getPanelCount() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the number of panels currently open
getParameter(int) - Method in class meka.gui.core.ParameterPanel: Returns the parameter component at the specified location.
getParameterCount() - Method in class meka.gui.core.ParameterPanel: Returns the number of parameters currently displayed.
getParameters() - Method in class meka.gui.events.SearchEvent: Returns the search parameters.
getParent(Container, Class) - Static method in class meka.gui.core.GUIHelper: Tries to determine the parent this panel is part of.
getParentDialog(Container) - Static method in class meka.gui.core.GUIHelper: Tries to determine the dialog this panel is part of.
getParentDialog() - Method in class meka.gui.core.MekaPanel: Tries to determine the dialog this panel is part of.
getParentFrame(Container) - Static method in class meka.gui.core.GUIHelper: Tries to determine the frame the container is part of.
getParentFrame() - Method in class meka.gui.core.MekaPanel: Tries to determine the frame this panel is part of.
getParentFrame() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the parent frame, if it's a JFrame, otherwise null
getParentInternalFrame() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the parent frame, if it's a JInternalFrame, otherwise null
getParentsY() - Method in class meka.classifiers.multilabel.cc.CNode: getParentsY - get the parents (indices) of this node
getPartitionFromDatasetHierarchy(Instances) - Static method in class meka.core.SuperLabelUtils: Get Partition From Dataset Hierarchy - assumes attributes are hierarchically arranged with '.'.
getPayload(int) - Method in class meka.gui.core.ResultHistory: Returns the payload of the specified history item.
getPayloadAt(int) - Method in class meka.gui.core.ResultHistoryList: Returns the payload at the specified location.
getPayloadAt(int) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel: Returns the payload at the specified location.
getPayoff() - Method in class meka.classifiers.multilabel.MCC: Get the payoff function
getPlainColumnName(int) - Method in class meka.gui.dataviewer.DataTable: returns the basically the attribute name of the column and not the HTML column name via getColumnName(int)
getPlugins() - Static method in class meka.gui.explorer.classify.AbstractClassifyResultHistoryPlugin: Returns all the available plugins.
getPopupMenuCustomizer() - Method in class meka.gui.core.ResultHistoryList: Returns the current customizer for the popup menu.
getPredictionsAsInstances(Result) - Static method in class meka.core.Result: Convert predictions into Instances (and true values).
getPreferredDimensionJSpinner() - Method in class meka.gui.core.ParameterPanel: Returns the preferred dimension for JSpinner and derived classes.
getPreferredScrollableViewportSize() - Method in class meka.gui.components.AttributeSelectionPanel
getPreserveOrder() - Method in class meka.experiment.evaluators.CrossValidation: Returns whether to preserve the order instead of randomizing the data.
getPreserveOrder() - Method in class meka.experiment.evaluators.PercentageSplit: Returns whether to preserve the order instead of randomizing the data.
getProperties() - Static method in class meka.gui.core.GUIHelper: Initializes the properties if necessary.
getPropertiesFile() - Method in class meka.gui.core.AbstractRecentItemsHandler: Returns the props file used to store the recent items in.
getPropertyPrefix() - Method in class meka.gui.core.AbstractRecentItemsHandler: Returns the prefix for the property names.
getProviders() - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Returns the dataset providers to use.
getRandomize() - Method in class meka.gui.explorer.ClassifyTabOptions: Returns the currently set Randomize value.
getRBMs() - Method in class rbms.DBM
getReader() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: returns the reader that was chosen by the user, can be null in case the user aborted the dialog or the save dialog was shown.
getReaderClass() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Returns the reader superclass for the GOE.
getReaderClass() - Method in class meka.gui.choosers.EvaluationStatisticsExporterFileChooser: Returns the reader superclass for the GOE.
getReaderClass() - Method in class meka.gui.choosers.EvaluationStatisticsFileChooser: Returns the reader superclass for the GOE.
getReaderClass() - Method in class meka.gui.choosers.ExperimentFileChooser: Returns the reader superclass for the GOE.
getReaderClass() - Method in class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser: Returns the reader superclass for the GOE.
getReaderForFile(File) - Method in class meka.gui.choosers.ExperimentFileChooser: Returns the reader for the specified file.
getReaderForFile(File) - Method in interface meka.gui.choosers.FileTypeDeterminingFileChooser: Returns the reader for the specified file.
getRecentItems() - Method in class meka.gui.core.AbstractRecentItemsHandler: Returns the currently stored recent items.
getRelation() - Method in class meka.experiment.evaluationstatistics.EvaluationStatistics: Returns the relation for these statistics.
getRelationName(String) - Static method in class meka.core.MLUtils: GetRelationName - get, e.g., 'Music' from 'Music: -C 6'
getRenderer(Object) - Static method in class meka.gui.modelviewer.renderers.AbstractObjectRenderer: Returns a renderer for the specified object.
getRenderer(Class) - Static method in class meka.gui.modelviewer.renderers.AbstractObjectRenderer: Returns a renderer for the specified class.
getRenderers() - Static method in class meka.gui.modelviewer.renderers.AbstractObjectRenderer: Returns a list with classnames of renderers.
getResult() - Method in class meka.experiment.evaluators.EvaluatorJob: Returns the results.
getResult() - Method in class meka.gui.goe.GenericObjectEditorDialog: Returns whether the dialog got cancelled or approved.
getResultAsString(Result) - Static method in class meka.core.Result: GetResultAsString - print out each prediction in a Result along with its true labelset.
getResultAsString(Result, int) - Static method in class meka.core.Result: GetResultAsString - print out each prediction in a Result (to a certain number of decimal points) along with its true labelset.
getResultAt(int) - Method in class meka.gui.core.ResultHistoryList: Returns the result at the specified location.
getResultAt(int) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel: Returns the element at the specified location.
getResultsAsInstances(ArrayList<HashMap<String, Object>>) - Static method in class meka.core.Result: Convert a list of Results into an Instances.
getResultType() - Method in class meka.gui.goe.GenericObjectEditorDialog: Returns whether the dialog got cancelled or approved.
getRevision() - Method in class meka.classifiers.multilabel.BR
getRevision() - Method in class meka.classifiers.multilabel.BRq
getRevision() - Method in class meka.classifiers.multilabel.CCq
getRevision() - Method in class meka.classifiers.multilabel.CDN
getRevision() - Method in class meka.classifiers.multilabel.CDT
getRevision() - Method in class meka.classifiers.multilabel.HASEL
getRevision() - Method in class meka.classifiers.multilabel.LabelTransformationClassifier
getRevision() - Method in class meka.classifiers.multilabel.LC
getRevision() - Method in class meka.classifiers.multilabel.meta.BaggingML
getRevision() - Method in class meka.classifiers.multilabel.meta.BaggingMLdup
getRevision() - Method in class meka.classifiers.multilabel.meta.CM
getRevision() - Method in class meka.classifiers.multilabel.meta.EM
getRevision() - Method in class meka.classifiers.multilabel.meta.EnsembleML
getRevision() - Method in class meka.classifiers.multilabel.meta.MBR
getRevision() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
getRevision() - Method in class meka.classifiers.multilabel.meta.SubsetMapper
getRevision() - Method in class meka.classifiers.multilabel.MULAN
getRevision() - Method in class meka.classifiers.multilabel.ProblemTransformationMethod
getRevision() - Method in class meka.classifiers.multilabel.PS
getRevision() - Method in class meka.classifiers.multilabel.PSt
getRevision() - Method in class meka.classifiers.multilabel.RAkEL
getRevision() - Method in class meka.classifiers.multilabel.RAkELd
getRevision() - Method in class meka.classifiers.multilabel.RT
getRevision() - Method in class meka.classifiers.multitarget.BCC
getRevision() - Method in class meka.classifiers.multitarget.CC
getRevision() - Method in class meka.classifiers.multitarget.CCp
getRevision() - Method in class meka.classifiers.multitarget.CR
getRevision() - Method in class meka.classifiers.multitarget.meta.BaggingMT
getRevision() - Method in class meka.classifiers.multitarget.meta.EnsembleMT
getRevision() - Method in class meka.classifiers.multitarget.NSR
getRevision() - Method in class meka.classifiers.multitarget.RAkELd
getRevision() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes
getRowCount() - Method in class meka.gui.core.EvaluationStatisticsTableModel: Returns the number of statistics in this model.
getRowCount() - Method in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: Returns the number of datasets in this model.
getRowCount() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the number of rows in the model.
getRowCount() - Method in class meka.gui.dataviewer.DataTableModel: returns the number of rows in the model
getRows() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Returns the rows.
getSamples() - Method in class meka.gui.explorer.ClassifyTabOptions: Returns the currently set samples value for prequential evaluation.
getSaveFileFilters() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Returns the file filters for writing files.
getSaveFileFilters() - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Returns the file filters for writing files.
getSaveFileFilters() - Method in class meka.gui.choosers.EvaluationStatisticsExporterFileChooser: Returns the file filters for writing files.
getSaveFileFilters() - Method in class meka.gui.choosers.EvaluationStatisticsFileChooser: Returns the file filters for writing files.
getSaveFileFilters() - Method in class meka.gui.choosers.ExperimentFileChooser: Returns the file filters for writing files.
getSaveFileFilters() - Method in class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser: Returns the file filters for writing files.
getSeachString() - Method in interface meka.gui.core.SearchableTable: Returns the current search string.
getSeachString() - Method in interface meka.gui.core.SearchableTableModel: Returns the current search string.
getSeachString() - Method in class meka.gui.core.SortableAndSearchableTable: Returns the current search string.
getSeachString() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the current search string.
getSearchPanel() - Method in class meka.gui.events.SearchEvent: Returns the search panel that sent the event.
getSearchString() - Method in class meka.gui.core.SearchParameters: Returns the current search string.
getSearchString() - Method in class meka.gui.dataviewer.DataTable: returns the search string, can be NULL if no search string is set
getSearchText() - Method in class meka.gui.core.SearchPanel: Returns the text in the search box.
getSeed() - Method in class meka.classifiers.multilabel.BRq
getSeed() - Method in class meka.classifiers.multilabel.CC
getSeed() - Method in class meka.classifiers.multilabel.CCq
getSeed() - Method in class meka.classifiers.multilabel.CDN
getSeed() - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
getSeed() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
getSeed() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getSeed() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
getSeed() - Method in class meka.classifiers.multilabel.PS
getSeed() - Method in class meka.experiment.evaluators.CrossValidation: Gets the seed for the random number generations
getSeed() - Method in class meka.experiment.evaluators.PercentageSplit: Gets the seed for the random number generations
getSeed() - Method in class meka.gui.explorer.ClassifyTabOptions: Returns the currently set seed value.
getSelectedAttributes() - Method in class meka.gui.components.AttributeSelectionPanel: Gets an array containing the indices of all selected attributes.
getSelectedText() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Returns the underlying text.
getSelectionModel() - Method in class meka.gui.components.AttributeSelectionPanel: Gets the selection model used by the table.
getSession() - Method in class meka.gui.explorer.AbstractExplorerTab: Returns the session object.
getSessionValue(String) - Method in class meka.gui.explorer.AbstractResultHistoryPlugin: Returns a session value, if present.
getSessionValue(T, String) - Method in class meka.gui.explorer.AbstractTabMenuItem: Returns a session value, if present.
getShortMethodName(String) - Static method in class meka.core.MLUtils: GetShortMethodName - get, e.g., 'BR' from 'meka.classifiers.multilabel.BR'.
getShowAttributeIndex() - Method in class meka.gui.dataviewer.DataPanel: Returns whether to display the attribute index in the header.
getShowAttributeIndex() - Method in class meka.gui.dataviewer.DataSortedTableModel: Returns whether to display the attribute index in the header.
getShowAttributeIndex() - Method in class meka.gui.dataviewer.DataTableModel: Returns whether to display the attribute index in the header.
getShowIndex() - Method in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: Returns whethert o show an index or the classifier in the header.
getSize() - Method in class meka.classifiers.multilabel.MLCBMaD: Returns the size of the compressed labels.
getSize() - Method in class meka.classifiers.multilabel.PLST: Returns the size of the compressed labels.
getSize() - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel: Returns the number of history entries.
getSkipCount() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns whether to skip the count.
getSkipMean() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns whether to skip the mean.
getSkipStdDev() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns whether to skip the stdDev.
getSortColumn() - Method in class meka.gui.core.SortableAndSearchableTable: Returns the sort column.
getSortColumn() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the sort column.
getSortColumn() - Method in interface meka.gui.core.SortableTable: Returns the sort column.
getSortColumn() - Method in interface meka.gui.core.SortableTableModel: Returns the sort column.
getSortedSubsets(LabelSet, Set<LabelSet>, Comparator) - Static method in class meka.core.PSUtils: Get Sorted Subsets - get all subsets of 'y' in the set 'set'; sorted according to 'cmp'.
getSortedSubsets(LabelSet, HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils: Get Sorted Subsets - get all subsets of 'y' in the set 'set'; sorted according to length, and counts in 'map'.
getSortNewTableModel() - Method in class meka.gui.core.SortableAndSearchableTable: Returns whether to sort new models.
getSparse() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getSparseH() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getSparseHT() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getSplitPercentage() - Method in class meka.gui.explorer.ClassifyTabOptions: Returns the currently set percentage value.
getStage() - Method in class meka.experiment.events.ExecutionStageEvent: Returns the stage.
getStatistics() - Method in class meka.experiment.DefaultExperiment: Returns the current statistics.
getStatistics() - Method in class meka.experiment.events.StatisticsNotificationEvent: Returns the statistics.
getStatistics() - Method in interface meka.experiment.Experiment: Returns the current statistics.
getStatistics() - Method in class meka.experiment.statisticsexporters.InMemory: Returns the statistics.
getStatistics() - Method in class meka.gui.core.EvaluationStatisticsTableModel: Returns the underlying statistics.
getStatistics() - Method in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: Returns the underlying statistics.
getStatisticsHandler() - Method in class meka.experiment.DefaultExperiment: Returns the statistics handler.
getStatisticsHandler() - Method in interface meka.experiment.Experiment: Returns the statistics handler.
getStats(Result, String) - Static method in class meka.core.Result: GetStats.
getStatusBar() - Method in class meka.gui.experimenter.Experimenter: Returns the status bar.
getStatusBar() - Method in class meka.gui.explorer.Explorer: Returns the status bar.
getStringSelection() - Method in class meka.gui.dataviewer.DataTable: returns the selected content in a StringSelection that can be copied to the clipboard and used in Excel, if nothing is selected the whole table is copied to the clipboard
getSubsets(LabelSet, Set<LabelSet>) - Static method in class meka.core.PSUtils: Get Subsets - get all subsets of 'y' in the set 'set'.
getSuffix(int) - Method in class meka.gui.core.ResultHistory: Returns the specified suffix.
getSuffixAt(int) - Method in class meka.gui.core.ResultHistoryList: Returns the suffix at the specified location.
getSuffixAt(int) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel: Returns the suffix at the specified location.
getSuffixCount() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns the suffix for the count.
getSuffixMean() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns the suffix for the mean.
getSuffixStdDev() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns the suffix for the stddev.
getSupport() - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
getSystemInfo() - Method in class meka.core.SystemInfo: returns a copy of the system info.
getTabbedPane() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns the tabbedpane instance
getTable() - Method in class meka.gui.dataviewer.DataPanel: returns the table component
getTableCellEditorComponent(JTable, Object, boolean, int, int) - Method in class meka.gui.dataviewer.DataTable.RelationalCellEditor: Sets an initial value for the editor.
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class meka.gui.components.AttributeSelectionPanel.CellRenderer
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class meka.gui.dataviewer.DataTableCellRenderer: Returns the default table cell renderer.
getTableHelper() - Method in class meka.gui.core.MekaTable: Returns the table helper instance.
getTableModel() - Method in class meka.gui.components.AttributeSelectionPanel: Get the table model in use (or null if no instances have been set yet).
getTableModelClass() - Method in class meka.gui.core.SortableAndSearchableTable: Returns the class of the table model that the models need to be derived from.
getTabs() - Static method in class meka.gui.experimenter.AbstractExperimenterTab: Returns all the available tabs.
getTabs() - Static method in class meka.gui.explorer.AbstractExplorerTab: Returns all the available tabs.
getTechnicalInformation() - Method in class meka.classifiers.multilabel.BCC
getTechnicalInformation() - Method in class meka.classifiers.multilabel.BRq
getTechnicalInformation() - Method in class meka.classifiers.multilabel.CC
getTechnicalInformation() - Method in class meka.classifiers.multilabel.CCq
getTechnicalInformation() - Method in class meka.classifiers.multilabel.CDN
getTechnicalInformation() - Method in class meka.classifiers.multilabel.CDT
getTechnicalInformation() - Method in class meka.classifiers.multilabel.CT
getTechnicalInformation() - Method in class meka.classifiers.multilabel.DBPNN
getTechnicalInformation() - Method in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable
getTechnicalInformation() - Method in class meka.classifiers.multilabel.Maniac
getTechnicalInformation() - Method in class meka.classifiers.multilabel.MCC
getTechnicalInformation() - Method in class meka.classifiers.multilabel.meta.DeepML
getTechnicalInformation() - Method in class meka.classifiers.multilabel.meta.EM
getTechnicalInformation() - Method in class meka.classifiers.multilabel.meta.MBR
getTechnicalInformation() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
getTechnicalInformation() - Method in class meka.classifiers.multilabel.meta.SubsetMapper
getTechnicalInformation() - Method in class meka.classifiers.multilabel.MLCBMaD
getTechnicalInformation() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
getTechnicalInformation() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getTechnicalInformation() - Method in class meka.classifiers.multilabel.PCC
getTechnicalInformation() - Method in class meka.classifiers.multilabel.PLST: 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 meka.classifiers.multilabel.PS
getTechnicalInformation() - Method in class meka.classifiers.multilabel.PSt
getTechnicalInformation() - Method in class meka.classifiers.multilabel.RAkEL
getTechnicalInformation() - Method in class meka.classifiers.multilabel.RAkELd
getTechnicalInformation() - Method in class meka.classifiers.multitarget.SCC
getTemplate() - Method in class meka.classifiers.multilabel.ProblemTransformationMethod
getTemplate() - Method in class meka.filters.multilabel.SuperNodeFilter
getTestData() - Method in class meka.gui.explorer.ClassifyTab: Returns the test instances, if any.
getText() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Returns the markdown code to display.
getText() - Method in class meka.gui.core.MarkdownTextPane: Returns the Markdown text.
getTextColumns() - Method in class meka.gui.core.SearchPanel: Returns the number of columns of the text field.
getTextFont() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Returns the text font in use.
getThreadedVoters() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getThreshold() - Method in class meka.classifiers.multilabel.MLCBMaD: Getter for the threshold for Boolean matrix decomposition.
getThreshold() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
getThreshold() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getThreshold(ArrayList<double[]>, Instances, String) - Static method in class meka.core.MLEvalUtils: GetThreshold - Get a threshold from a Threshold OPtion string 'top'.
getThreshold() - Method in class meka.experiment.evaluators.CrossValidation: Gets the threshold option.
getThreshold() - Method in class meka.experiment.evaluators.PercentageSplit: Gets the threshold option.
getTimestamp(int) - Method in class meka.gui.core.ResultHistory: Returns the specified timestamp.
getTimestampAt(int) - Method in class meka.gui.core.ResultHistoryList: Returns the timestamp at the specified location.
getTimestampAt(int) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel: Returns the element at the specified location.
getTitle() - Method in class meka.gui.dataviewer.DataPanel: returns the title for the Tab, i.e.
getTitle() - Method in class meka.gui.experimenter.AbstractExperimenterTab: Returns the title of the tab.
getTitle() - Method in class meka.gui.experimenter.AbstractSetupTab: Returns the title of the tab.
getTitle() - Method in class meka.gui.experimenter.BasicSetup: Returns the title of the tab.
getTitle() - Method in class meka.gui.experimenter.ExpertSetup: Returns the title of the tab.
getTitle() - Method in class meka.gui.experimenter.LogTab: Returns the title of the tab.
getTitle() - Method in class meka.gui.experimenter.Statistics: Returns the title of the tab.
getTitle() - Method in class meka.gui.explorer.AbstractExplorerTab: Returns the title of the tab.
getTitle() - Method in class meka.gui.explorer.ClassifyTab: Returns the title of the tab.
getTitle() - Method in class meka.gui.explorer.LogTab: Returns the title of the tab.
getTitle() - Method in class meka.gui.explorer.PreprocessTab: Returns the title of the tab.
getTitle() - Method in class meka.gui.explorer.VisualizeTab: Returns the title of the tab.
getTOP() - Method in class meka.gui.explorer.ClassifyTab: Returns the threshold option.
getTOP() - Method in class meka.gui.explorer.ClassifyTabOptions: Returns the currently set seed value.
getTopNSubsets(String, HashMap<String, Integer>, int) - Static method in class meka.classifiers.multitarget.NSR: GetTopNSubsets - return the top N subsets which differ from y by a single class value, ranked by the frequency storte in masterCombinations.
getTopNSubsets(LabelSet, HashMap<LabelSet, Integer>, int) - Static method in class meka.core.PSUtils: GetTopNSubsets - Don't cover all (like cover(y,map), rather only the top 'n')
getTopNSubsets(String, HashMap<String, Integer>, int) - Static method in class meka.core.SuperLabelUtils: GetTopNSubsets - return the top N subsets which differ from y by a single class value, ranked by the frequency storte in masterCombinations.
getTopNSubsetsAsSet(LabelSet, HashMap<LabelSet, Integer>, int) - Static method in class meka.core.PSUtils
getTopSubset(LabelSet, HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils
getTrainPercentage() - Method in class meka.experiment.evaluators.PercentageSplit: Gets the percentage to use for training.
getTransformTemplates(Instance) - Method in class meka.classifiers.multilabel.CC: GetTransformTemplates - pre-transform the instance x, to make things faster.
getTranspose(double[][]) - Static method in class meka.core.MatrixUtils
getType(int) - Method in class meka.gui.dataviewer.DataSortedTableModel: returns the TYPE of the attribute at the given position
getType(int, int) - Method in class meka.gui.dataviewer.DataSortedTableModel: returns the TYPE of the attribute at the given position
getType(int) - Method in class meka.gui.dataviewer.DataTableModel: returns the TYPE of the attribute at the given position
getType(int, int) - Method in class meka.gui.dataviewer.DataTableModel: returns the TYPE of the attribute at the given position
getUnsortedModel() - Method in class meka.gui.core.SortableAndSearchableTable: returns the underlying model, can be null.
getUnsortedModel() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: returns the underlying model, can be null.
getUnsortedModel() - Method in interface meka.gui.core.SortableTable: returns the underlying model, can be null.
getUnsortedModel() - Method in interface meka.gui.core.SortableTableModel: returns the underlying model, can be null.
getUpperRuns() - Method in class meka.experiment.evaluators.RepeatedRuns: Returns the upper number of runs to perform (included).
getUseOptimalColumnWidths() - Method in class meka.gui.core.SortableAndSearchableTable: Returns whether to automatically set optimal column widths.
getValue(String) - Method in class meka.core.Result: AddValue.
getValue() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel.SortContainer: Returns the value to sort on.
getValueAt(int, int) - Method in class meka.gui.core.EvaluationStatisticsTableModel: Returns the cell value at the specified location.
getValueAt(int, int) - Method in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: Returns the cell value at the specified location.
getValueAt(int, int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the value for the cell at columnIndex and rowIndex.
getValueAt(int, int) - Method in class meka.gui.dataviewer.DataTableModel: returns the value for the cell at columnindex and rowIndex
getValueForComparison(int, int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns the value used in the comparison.
getValues(Instances, int[], int) - Static method in class meka.filters.multilabel.SuperNodeFilter: Return a set of all the combinations of attributes at 'indices' in 'D', pruned by 'p'; e.g., {00,01,11}.
getVerbosity() - Method in class meka.experiment.evaluators.CrossValidation: Gets the verbosity option.
getVerbosity() - Method in class meka.experiment.evaluators.PercentageSplit: Gets the verbosity option.
getVersion() - Static method in class meka.core.Version: Returns the version of MEKA.
getVigilancy() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
getVigilancy() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getVOP() - Method in class meka.gui.explorer.ClassifyTab: Returns the verbosity option.
getVOP() - Method in class meka.gui.explorer.ClassifyTabOptions: Returns the currently set seed value.
getVoters() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
getW() - Method in class rbms.RBM
getWait() - Method in class meka.gui.core.MaximizationFixWindowListener: Returns the wait period in msec.
getWidth() - Method in class meka.classifiers.multilabel.CDT: GetH - Get the trellis width.
getWidth() - Method in class meka.classifiers.multilabel.CT: GetH - Get the trellis width.
getWrapStyleWord() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Returns whether word wrap is enabled.
getWriter() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: returns the writer that was chosen by the user, can be null in case the user aborted the dialog or the open dialog was shown.
getWriterClass() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Returns the writer superclass for the GOE.
getWriterClass() - Method in class meka.gui.choosers.EvaluationStatisticsExporterFileChooser: Returns the writer superclass for the GOE.
getWriterClass() - Method in class meka.gui.choosers.EvaluationStatisticsFileChooser: Returns the writer superclass for the GOE.
getWriterClass() - Method in class meka.gui.choosers.ExperimentFileChooser: Returns the writer superclass for the GOE.
getWriterClass() - Method in class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser: Returns the writer superclass for the GOE.
getWriterForFile(File) - Method in class meka.gui.choosers.ExperimentFileChooser: Returns the writer for the specified file.
getWriterForFile(File) - Method in interface meka.gui.choosers.FileTypeDeterminingFileChooser: Returns the writer for the specified file.
getWs() - Method in class rbms.DBM
getWs() - Method in class rbms.RBM
getXfromD(Instances) - Static method in class meka.core.MLUtils: GetXfromD - Extract attributes as a double X[][] from Instances D.
getxfromInstance(Instance) - Static method in class meka.core.MLUtils: GetxfromInstances - Extract attributes as a double x[] from an Instance.
getYfromD(Instances) - Static method in class meka.core.MLUtils: GetXfromD - Extract labels as a double Y[][] from Instances D.
globalInfo() - Method in class meka.classifiers.multilabel.AbstractMultiLabelClassifier: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.BCC: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.BR: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.BRq: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.CC: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.CCq: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.CDN: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.CDT: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.CT
globalInfo() - Method in class meka.classifiers.multilabel.DBPNN: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.FW
globalInfo() - Method in class meka.classifiers.multilabel.HASEL: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.incremental.BRUpdateable
globalInfo() - Method in class meka.classifiers.multilabel.incremental.CCUpdateable
globalInfo() - Method in class meka.classifiers.multilabel.incremental.MajorityLabelsetUpdateable
globalInfo() - Method in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
globalInfo() - Method in class meka.classifiers.multilabel.incremental.RTUpdateable
globalInfo() - Method in class meka.classifiers.multilabel.LC: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.MajorityLabelset: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.Maniac: Returns the global information of the classifier.
globalInfo() - Method in class meka.classifiers.multilabel.MCC
globalInfo() - Method in class meka.classifiers.multilabel.meta.BaggingML: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.meta.BaggingMLdup: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.meta.CM
globalInfo() - Method in class meka.classifiers.multilabel.meta.DeepML
globalInfo() - Method in class meka.classifiers.multilabel.meta.EM
globalInfo() - Method in class meka.classifiers.multilabel.meta.EnsembleML: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.meta.MBR: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.meta.SubsetMapper: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.MLCBMaD: Returns the global information of the classifier.
globalInfo() - Method in class meka.classifiers.multilabel.MULAN: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork: Returns a string describing this classifier
globalInfo() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast: Returns a string describing this classifier
globalInfo() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse: Returns a string describing this classifier
globalInfo() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH: Returns a string describing this classifier
globalInfo() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT: Returns a string describing this classifier
globalInfo() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange: Returns a string describing this classifier
globalInfo() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV: Returns a string describing this classifier
globalInfo() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM: Returns a string describing this classifier
globalInfo() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.PCC
globalInfo() - Method in class meka.classifiers.multilabel.PLST: Returns the global information of the classifier.
globalInfo() - Method in class meka.classifiers.multilabel.PMCC
globalInfo() - Method in class meka.classifiers.multilabel.ProblemTransformationMethod: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.PS: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.PSt: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.RAkEL: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.RAkELd: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multilabel.RT: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multitarget.BCC: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multitarget.CC: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multitarget.CCp: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multitarget.CR: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multitarget.meta.BaggingMT: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multitarget.meta.EnsembleMT: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multitarget.NSR: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multitarget.RAkELd: Description to display in the GUI.
globalInfo() - Method in class meka.classifiers.multitarget.SCC: Description to display in the GUI.
globalInfo() - Method in class meka.experiment.datasetproviders.AbstractDatasetProvider: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.datasetproviders.LocalDatasetProvider: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.evaluationstatistics.AbstractEvaluationStatisticsHandler: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.evaluationstatistics.InMemory: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.evaluationstatistics.Serialized: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.evaluators.AbstractEvaluator: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.evaluators.CrossValidation: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.evaluators.PercentageSplit: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.evaluators.RepeatedRuns: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.filehandlers.AbstractExperimentFileHandler: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.filehandlers.CommandLineSetup: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.filehandlers.SerializedExperiment: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.statisticsexporters.AbstractEvaluationStatisticsExporter: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.statisticsexporters.InMemory: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.statisticsexporters.LatexMeasurement: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.statisticsexporters.MultiExporter: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.statisticsexporters.TabSeparated: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.statisticsexporters.TabSeparatedMeasurement: Description to be displayed in the GUI.
globalInfo() - Method in class meka.experiment.statisticsexporters.WekaFilter: Description to be displayed in the GUI.
globalInfo() - Method in class meka.filters.multilabel.SuperNodeFilter
globalInfo() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes: Returns a string describing this filter.
grabFocus() - Method in class meka.gui.core.SearchPanel: The text field for the search tries to grab the focus.
graph() - Method in class meka.classifiers.multilabel.BR: Returns a string that describes a graph representing the object.
graph() - Method in class meka.classifiers.multilabel.CC: Returns a string that describes a graph representing the object.
graph() - Method in class meka.classifiers.multilabel.LC: Returns a string that describes a graph representing the object.
graph() - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM
graph() - Method in interface meka.core.MultiLabelDrawable: Returns a string that describes a graph representing the object.
graphType() - Method in class meka.classifiers.multilabel.BR: Returns the type of graph representing the object.
graphType() - Method in class meka.classifiers.multilabel.CC: Returns the type of graph representing the object.
graphType() - Method in class meka.classifiers.multilabel.LC: Returns the type of graph representing the object.
graphType() - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM
graphType() - Method in interface meka.core.MultiLabelDrawable: Returns the type of graph representing the object.
GUIChooser - Class in meka.gui.guichooser: The main application launcher.
GUIChooser() - Constructor for class meka.gui.guichooser.GUIChooser
GUIHelper - Class in meka.gui.core: A little helper class for GUI related stuff.
GUIHelper() - Constructor for class meka.gui.core.GUIHelper
GUILauncher - Class in meka.gui.core: Helper class for launching applications and frames.
GUILauncher() - Constructor for class meka.gui.core.GUILauncher

H

h - Variable in class meka.classifiers.multilabel.CDN
h - Variable in class meka.classifiers.multilabel.PMCC
H(int[][], int, int, int) - Static method in class meka.core.StatUtils: H - Conditional Entropy H(y_j|y_k).
H(int[][], int) - Static method in class meka.core.StatUtils: H - Get a Conditional Entropy Matrix.
H(Instances) - Static method in class meka.core.StatUtils: H - Get a Conditional Entropy Matrix.
h - Variable in class rbms.DBM
handleError(Object, String) - Method in class meka.experiment.DefaultExperiment: Adds the source's class name to the message if not null.
handleException(Object, String, Throwable) - Static method in class meka.core.ExceptionUtils: Outputs the stacktrace along with the message on stderr and returns a combination of both of them as string.
handleException(Object, String, Throwable, boolean) - Static method in class meka.core.ExceptionUtils: Generates a string from the stacktrace along with the message and returns that.
handleException(String, Throwable) - Method in class meka.events.LogObject: Logs the stacktrace along with the message on stderr and returns a combination of both of them as string.
handleException(String, Throwable) - Static method in class meka.gui.choosers.MekaFileChooser: Outputs the error in the console window.
handleException(String, Throwable) - Method in class meka.gui.experimenter.AbstractExperimenterTab: Logs the stacktrace along with the message on the log tab and returns a combination of both of them as string.
handleException(AbstractExperimenterTab, String, Throwable) - Method in class meka.gui.experimenter.Experimenter: Logs the stacktrace along with the message on the log tab and returns a combination of both of them as string.
handleException(String, Throwable) - Method in class meka.gui.explorer.AbstractExplorerTab: Logs the stacktrace along with the message on the log tab and returns a combination of both of them as string.
handleException(AbstractExplorerTab, String, Throwable) - Method in class meka.gui.explorer.Explorer: Logs the stacktrace along with the message on the log tab and returns a combination of both of them as string.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.AbstractResultHistoryPlugin: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.AbstractShowThresholdCurve: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.CopyModelSetup: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.IncrementalPerformance: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.PredictionsOnTestset: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.ReevaluateModelOnTestset: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.SaveCSV: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.SaveGraphs: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.SaveModel: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.SavePredictions: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.ShowGraphs: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.ShowMacroCurve: Checks whether the current item can be handled.
handles(ResultHistoryList, int) - Method in class meka.gui.explorer.classify.ShowMicroCurve: Checks whether the current item can be handled.
handles(Class) - Method in class meka.gui.modelviewer.renderers.AbstractObjectRenderer: Checks whether the renderer can handle the specified class.
handles(Class) - Method in class meka.gui.modelviewer.renderers.InstancesRenderer: Checks whether the renderer can handle the specified class.
handles(Class) - Method in class meka.gui.modelviewer.renderers.MultiLabelClassifierRenderer: Checks whether the renderer can handle the specified class.
handles(Class) - Method in class meka.gui.modelviewer.renderers.PlainTextRenderer: Checks whether the renderer can handle the specified class.
handlesExperiment(Experiment) - Method in class meka.gui.experimenter.AbstractSetupTab: Checks whether this type of experiment is handled by this tab.
handlesExperiment(Experiment) - Method in class meka.gui.experimenter.BasicSetup: Checks whether this type of experiment is handled by this tab.
handlesExperiment(Experiment) - Method in class meka.gui.experimenter.ExpertSetup: Checks whether this type of experiment is handled by this tab.
HARAMNetwork - Class in meka.classifiers.multilabel.neurofuzzy: ****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION.
HARAMNetwork(int, int, double, double, double) - Constructor for class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
HARAMNetwork() - Constructor for class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
hasData() - Method in class meka.gui.explorer.AbstractExplorerTab: Returns whether data is currently present.
HASEL - Class in meka.classifiers.multilabel: HASEL - Partitions labels into subsets based on the dataset defined hierarchy.
HASEL() - Constructor for class meka.classifiers.multilabel.HASEL
hasExperiment() - Method in class meka.gui.experimenter.AbstractExperimenterTab: Returns whether experiment is currently present.
hashCode() - Method in class meka.core.LabelSet
hashCode() - Method in class meka.gui.core.RecentFilesHandlerWithCommandline.Setup: Returns the hashCode of the file's absolute path.
hashMapToString(HashMap<?, ?>, int) - Static method in class meka.core.MLUtils: Print out a HashMap nicely.
hashMapToString(HashMap<?, ?>) - Static method in class meka.core.MLUtils
hasImageFile(String) - Static method in class meka.gui.core.GUIHelper: Checks whether the image is available.
hasMnemonic(String) - Static method in class meka.gui.core.GUIHelper: Checks the caption whether an underscore "_" is present to indicate that the following character is to act as mnemonic.
hasNext() - Method in interface meka.experiment.datasetproviders.DatasetProvider: Returns whether another dataset is available.
hasNext() - Method in class meka.experiment.datasetproviders.LocalDatasetProvider: Returns whether another dataset is available.
hasNext() - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Returns whether another dataset is available.
hasNoModifierKey(MouseEvent) - Static method in class meka.gui.core.MouseUtils: Checks whether no modified key is pressed.
hasPrefix() - Method in class meka.gui.core.SearchPanel: Checks whether a prefix string was provided.
hasSessionValue(String) - Method in class meka.gui.explorer.AbstractResultHistoryPlugin: Checks whether a session value is present.
hasSessionValue(T, String) - Method in class meka.gui.explorer.AbstractTabMenuItem: Checks whether a session value is present.
headers(List<EvaluationStatistics>, boolean, boolean) - Static method in class meka.experiment.evaluationstatistics.EvaluationStatisticsUtils: Creates a list of headers (= stats keys) from the provided statistics.
HEIGHT - Static variable in class meka.gui.dataviewer.DataViewerMainPanel: default height
HistoryCustomizer() - Constructor for class meka.gui.explorer.ClassifyTab.HistoryCustomizer
HomepageDefinition - Class in meka.gui.guichooser: Launches the Homepage.
HomepageDefinition() - Constructor for class meka.gui.guichooser.HomepageDefinition
hTipText() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet

I

I - Variable in class meka.classifiers.multilabel.CDN
I(int[][], int, int, int) - Static method in class meka.core.StatUtils: I - Mutual Information I(y_j;y_k).
I(double[][]) - Static method in class meka.core.StatUtils: I - Mutual Information -- fast version, must calcualte P[][] = getP(D) first.
I(double[][], int, int) - Static method in class meka.core.StatUtils: I - Mutual Information.
I(Instances, int, int) - Static method in class meka.core.StatUtils: I - Mutual Information.
I(Instances, int) - Static method in class meka.core.StatUtils: I - Get an Unconditional Depndency Matrix.
I(int[][], int) - Static method in class meka.core.StatUtils: I - Get a Mutual Information Matrix.
I_c - Variable in class meka.classifiers.multilabel.CDN
icTipText() - Method in class meka.classifiers.multilabel.CDN
idealIntArraySize(int) - Static method in class meka.classifiers.multilabel.neurofuzzy.SparseArray
IMAGE_DIR - Static variable in class meka.gui.core.GUIHelper: the directory with the images.
incrementalDisabledTipText() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Describes this property.
incrementalDisabledTipText() - Method in interface meka.experiment.evaluationstatistics.OptionalIncrementalEvaluationStatisticsHandler: Describes this property.
IncrementalEvaluation - Class in meka.classifiers.multilabel.incremental: IncrementalEvaluation.java - For Evaluating Incremental (Updateable) Classifiers.
IncrementalEvaluation() - Constructor for class meka.classifiers.multilabel.incremental.IncrementalEvaluation
IncrementalEvaluationStatisticsHandler - Interface in meka.experiment.evaluationstatistics: For handlers that support incremental writes.
IncrementalMultiLabelClassifier - Interface in meka.classifiers.multilabel: Interface for incremental multi-label classifiers.
IncrementalPerformance - Class in meka.gui.explorer.classify: Allows the user to displays graphs of the performance of an incremental classifier if available.
IncrementalPerformance() - Constructor for class meka.gui.explorer.classify.IncrementalPerformance
indexOfKey(int) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Returns the index for which SparseArray.keyAt(int) would return the specified key, or a negative number if the specified key is not mapped.
indexOfValue(Double) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Returns an index for which SparseArray.valueAt(int) would return the specified key, or a negative number if no keys map to the specified value.
indices - Variable in class meka.classifiers.multilabel.cc.Trellis
indices - Variable in class meka.core.LabelSet
indices - Variable in class meka.core.SuperLabel
indices - Variable in class meka.filters.multilabel.SuperNodeFilter
inferenceIterationsTipText() - Method in class meka.classifiers.multilabel.MCC
info - Variable in class meka.core.Result
initGUI(int) - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: initializes the GUI.
initGUI(int) - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: initializes the GUI.
initGUI() - Method in class meka.gui.core.ApprovalDialog: Initializes the widgets.
initGUI() - Method in class meka.gui.core.ListWithButtons: Initializes the widgets.
initGUI() - Method in class meka.gui.core.MarkdownDialog: Initializes the widgets.
initGUI() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Initializes the widgets.
initGUI() - Method in class meka.gui.core.MarkdownTextPane: Initializes the widgets.
initGUI() - Method in class meka.gui.core.MekaDialog: For initializing the GUI.
initGUI() - Method in class meka.gui.core.MekaFrame: For initializing the GUI.
initGUI() - Method in class meka.gui.core.MekaPanel: Initializes the widgets.
initGUI() - Method in class meka.gui.core.MekaPanelWithButtons: Initializes the widgets.
initGUI() - Method in class meka.gui.core.MekaTable: Initializes some GUI-related things.
initGUI() - Method in class meka.gui.core.ParameterPanel: Initializes the members.
initGUI() - Method in class meka.gui.core.SearchPanel: Initializes the widgets.
initGUI() - Method in class meka.gui.core.SortableAndSearchableTable: Initializes some GUI-related things.
initGUI() - Method in class meka.gui.core.StatusBar: Initializes the widgets.
initGUI() - Method in class meka.gui.experimenter.AbstractSetupTab: Initializes the widgets.
initGUI() - Method in class meka.gui.experimenter.BasicSetup: Initializes the widgets.
initGUI() - Method in class meka.gui.experimenter.Experimenter: Initializes the widgets.
initGUI() - Method in class meka.gui.experimenter.ExpertSetup: Initializes the widgets.
initGUI() - Method in class meka.gui.experimenter.LogTab: Initializes the widgets.
initGUI() - Method in class meka.gui.experimenter.Statistics: Initializes the widgets.
initGUI() - Method in class meka.gui.explorer.ClassifyTab: Initializes the widgets.
initGUI() - Method in class meka.gui.explorer.ClassifyTabOptions: Initializes the widgets.
initGUI() - Method in class meka.gui.explorer.Explorer: Initializes the widgets.
initGUI() - Method in class meka.gui.explorer.LogTab: Initializes the widgets.
initGUI() - Method in class meka.gui.explorer.PreprocessTab: Initializes the widgets.
initGUI() - Method in class meka.gui.explorer.VisualizeTab: Initializes the widgets.
initGUI() - Method in class meka.gui.goe.GenericObjectEditorDialog: For initializing the GUI.
initGUI() - Method in class meka.gui.guichooser.GUIChooser: Initializes the widgets.
initGUI() - Method in class meka.gui.modelviewer.ModelViewer: Initializes the widgets.
initialize() - Static method in class meka.core.Project: Makes sure that the project's home directory is present.
initialize() - Method in class meka.experiment.datasetproviders.AbstractDatasetProvider: Initializes the provider to start providing datasets from scratch.
initialize() - Method in interface meka.experiment.datasetproviders.DatasetProvider: Initializes the provider to start providing datasets from scratch.
initialize() - Method in class meka.experiment.datasetproviders.LocalDatasetProvider: Initializes the provider to start providing datasets from scratch.
initialize() - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Initializes the provider to start providing datasets from scratch.
initialize() - Method in class meka.experiment.DefaultExperiment: Initializes the experiment.
initialize() - Method in class meka.experiment.evaluationstatistics.AbstractFileBasedEvaluationStatisticsHandler: Initializes the handler.
initialize() - Method in interface meka.experiment.evaluationstatistics.EvaluationStatisticsHandler: Initializes the handler.
initialize() - Method in class meka.experiment.evaluationstatistics.InMemory: Initializes the handler.
initialize() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Initializes the handler.
initialize() - Method in class meka.experiment.evaluators.AbstractEvaluator: Initializes the evaluator.
initialize() - Method in class meka.experiment.evaluators.AbstractMetaEvaluator: Initializes the evaluator.
initialize() - Method in interface meka.experiment.evaluators.Evaluator: Initializes the evaluator.
initialize() - Method in interface meka.experiment.Experiment: Initializes the experiment.
initialize() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Further initializations.
initialize() - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Further initializations.
initialize() - Method in class meka.gui.choosers.MekaFileChooser: For initializing some stuff.
initialize() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Initializes the members.
initialize() - Method in class meka.gui.core.MarkdownTextPane: Initializes the members.
initialize() - Method in class meka.gui.core.MekaDialog: For initializing members.
initialize() - Method in class meka.gui.core.MekaFrame: For initializing members.
initialize() - Method in class meka.gui.core.MekaPanel: Initializes the members.
initialize() - Method in class meka.gui.core.ParameterPanel: Initializes the members.
initialize() - Method in class meka.gui.core.SearchPanel: Initializes the members.
initialize() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Initializes indices etc.
initialize() - Method in class meka.gui.dataviewer.DataPanel: any member variables are initialized here
initialize() - Method in class meka.gui.experimenter.AbstractExperimenterTab: Initializes the members.
initialize() - Method in class meka.gui.experimenter.AbstractSetupTab: Initializes the members.
initialize() - Method in class meka.gui.experimenter.BasicSetup: Initializes the member variables.
initialize() - Method in class meka.gui.experimenter.Experimenter: Initializes the members.
initialize() - Method in class meka.gui.experimenter.LogTab: Initializes the members.
initialize() - Method in class meka.gui.experimenter.Statistics: Initializes the members.
initialize() - Method in class meka.gui.explorer.AbstractExplorerTab: Initializes the members.
initialize() - Method in class meka.gui.explorer.AbstractThreadedExplorerTab: Initializes the members.
initialize() - Method in class meka.gui.explorer.ClassifyTab: Initializes the members.
initialize() - Method in class meka.gui.explorer.Explorer: Initializes the members.
initialize() - Method in class meka.gui.explorer.LogTab: Initializes the members.
initialize() - Method in class meka.gui.explorer.PreprocessTab: Initializes the members.
initialize() - Method in class meka.gui.goe.GenericObjectEditorDialog: For initializing members.
initialize() - Method in class meka.gui.modelviewer.ModelViewer: Initializes the members.
initializeColumnTypes() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Determines which column is a numeric one (skipped in search).
initializeFilters(AbstractExtensionFileFilterFileChooser) - Static method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Performs the initialization of the file filters, if necessary.
initializeSortIndices() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: (re-)initializes the indices.
initialSortNewTableModel() - Method in class meka.gui.core.SortableAndSearchableTable: Returns the initial setting of whether to sort new models.
initialUseOptimalColumnWidths() - Method in class meka.gui.core.SortableAndSearchableTable: Returns the initial setting of whether to set optimal column widths.
initRenderers() - Static method in class meka.gui.modelviewer.renderers.AbstractObjectRenderer: Initializes the renderers.
initWeights(int, int, int[]) - Method in class meka.classifiers.multilabel.BPNN: InitWeights - Initialize a BPNN of H.length hidden layers with H[0], H[1], etc hidden units in each layer (W will be random, and of the corresponding dimensions).
initWeights(int) - Method in class rbms.RBM: Initialize W, and make _dW (for momentum) of the same dimensions.
InMemory - Class in meka.experiment.evaluationstatistics: Simple in-memory handler.
InMemory() - Constructor for class meka.experiment.evaluationstatistics.InMemory
InMemory - Class in meka.experiment.statisticsexporters: Just stores the statistics in mmemory.
InMemory() - Constructor for class meka.experiment.statisticsexporters.InMemory
insertInstance(int) - Method in class meka.gui.dataviewer.DataSortedTableModel: Insert a new instance (all values 0) at the given index.
insertInstance(int) - Method in class meka.gui.dataviewer.DataTableModel
insertInstance(int, boolean) - Method in class meka.gui.dataviewer.DataTableModel
InstancesRenderer - Class in meka.gui.modelviewer.renderers: Renders Instances objects.
InstancesRenderer() - Constructor for class meka.gui.modelviewer.renderers.InstancesRenderer
instancesToMatrix(Instances) - Static method in class meka.core.MatrixUtils: Helper method that transforma an Instances object to a Matrix object.
instantiate(List<Class>) - Static method in class meka.gui.modelviewer.renderers.AbstractObjectRenderer: Instantiates the renderers.
introduceUnlabelledData(Instances) - Method in class meka.classifiers.multilabel.meta.EM
introduceUnlabelledData(Instances) - Method in interface meka.classifiers.multilabel.SemisupervisedClassifier: Set Unlabelled Data - provide unlabelled data prior to calling buildClassifier(Instances).
invert(int[], int) - Static method in class meka.core.A: Invert - take the compliment of indices up to length L, e.g., if indices = [3,5,6], then invert(indices,7) = [1,2,4,7].
isAllFilter(ExtensionFileFilter) - Static method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Checks whether the filter uses "*.*".
isAndroid() - Static method in class meka.core.OS: Checks whether the operating system is Android.
isApproveVisible() - Method in class meka.gui.core.ApprovalDialog: Returns the visibility of the approve button.
isAscending() - Method in class meka.gui.core.SortableAndSearchableTable: Returns whether sorting is ascending or not.
isAscending() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns whether sorting is ascending or not.
isAscending() - Method in interface meka.gui.core.SortableTable: Returns whether sorting is ascending or not.
isAscending() - Method in interface meka.gui.core.SortableTableModel: Returns whether sorting is ascending or not.
isCancelVisible() - Method in class meka.gui.core.ApprovalDialog: Returns the visibility of the cancel button.
isCellEditable(int, int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns true if the cell at rowIndex and columnIndex is editable.
isCellEditable(int, int) - Method in class meka.gui.dataviewer.DataTableModel: returns true if the cell at rowindex and columnindexis editable
isChanged() - Method in class meka.gui.dataviewer.DataPanel: returns whether the content of the panel was changed
isChanged() - Method in class meka.gui.dataviewer.DataViewerDialog: returns whether the data has been changed
isClassIndex(int) - Method in class meka.gui.dataviewer.DataTableModel: checks whether the column represents the class or not
isColumnNumeric(int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns whether the specified column is numeric.
isDiscardVisible() - Method in class meka.gui.core.ApprovalDialog: Returns the visibility of the discard button.
isDouble() - Method in class meka.gui.core.SearchParameters: Returns whether the search string represents a double.
isDoubleClick(MouseEvent) - Static method in class meka.gui.core.MouseUtils: Checks whether the mouse event is a double-click event (with the left mouse button).
isEditable() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Returns whether the text area is editable or not.
isEditable() - Method in class meka.gui.core.MarkdownTextPane: Returns whether the text pane is editable or not.
isEmpty() - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Is this symbol table empty?
isEnabled() - Method in class meka.gui.core.MaximizationFixWindowListener: Returns whether the listener is enabled.
isEnabled() - Method in class meka.gui.core.SearchPanel: Returns whether the panel is enabled or not.
isGlobFilter(FileFilter) - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Returns whether the filter is a "glob" filter, e.g., when the user enters "*.txt" manually.
isGOEEditor() - Method in class meka.gui.goe.GenericObjectEditorDialog: Returns whether the underlying editor is GenericObjectEditor.
isIncremental() - Method in class meka.gui.core.SearchPanel: Returns whether incremental search is enabled.
isIncrementalDisabled() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Returns whether incremental mode is turned off.
isIncrementalDisabled() - Method in interface meka.experiment.evaluationstatistics.OptionalIncrementalEvaluationStatisticsHandler: Returns whether incremental mode is turned on.
isInitialized() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: whether the model is initialized.
isInitializing() - Method in class meka.experiment.DefaultExperiment: Returns whether the experiment is initializing.
isInitializing() - Method in interface meka.experiment.Experiment: Returns whether the experiment is initializing.
isInteger() - Method in class meka.gui.core.SearchParameters: Returns whether the search string represents an integer.
isLeftClick(MouseEvent) - Static method in class meka.gui.core.MouseUtils: Checks whether the mouse event is a left-click event.
isLinux() - Static method in class meka.core.OS: Checks whether the operating system is Linux (but not Android).
isLoggingEnabled() - Method in class meka.gui.core.MaximizationFixWindowListener: Returns whether logging is enabled.
isMac() - Static method in class meka.core.OS: Checks whether the operating system is Mac.
isMiddleClick(MouseEvent) - Static method in class meka.gui.core.MouseUtils: Checks whether the mouse event is a middle/wheel-click event.
isMissingAt(int, int) - Method in class meka.gui.dataviewer.DataSortedTableModel: checks whether the value at the given position is missing
isMissingAt(int, int) - Method in class meka.gui.dataviewer.DataTableModel: checks whether the value at the given position is missing
isModified() - Method in class meka.gui.experimenter.AbstractSetupTab: Returns the modified state.
isMT(Instances) - Static method in class meka.classifiers.multilabel.Evaluation: IsMT - see if dataset D is multi-target (else only multi-label)
isMultiThreaded(int) - Static method in class meka.core.ThreadUtils: Returns whether the number of threads represent a multi-threaded setup.
isMultiThreaded(Experiment, Evaluator) - Static method in class meka.experiment.ExperimentUtils: Checks whether an Evaluator implements ThreadLimiter and uses multi-threading.
isNotificationEnabled() - Method in class meka.gui.dataviewer.DataSortedTableModel: returns whether the notification of changes is enabled
isNotificationEnabled() - Method in class meka.gui.dataviewer.DataTableModel: returns whether the notification of changes is enabled
isOptimizeAE() - Method in class meka.classifiers.multilabel.Maniac: Get the OptimizeAE value.
isPanelSelected() - Method in class meka.gui.dataviewer.DataViewerMainPanel: checks whether a panel is currently selected
isReadOnly() - Method in class meka.gui.dataviewer.DataPanel: returns whether the model is read-only
isReadOnly() - Method in class meka.gui.dataviewer.DataSortedTableModel: returns whether the model is read-only
isReadOnly() - Method in class meka.gui.dataviewer.DataTable: returns whether the model is read-only
isReadOnly() - Method in class meka.gui.dataviewer.DataTableModel: returns whether the model is read-only
isRegExp() - Method in class meka.gui.core.SearchParameters: Returns whether the search uses regular expression matching or simple substring matching.
isRegExpSearch() - Method in interface meka.gui.core.SearchableTable: Returns whether the last search was a regular expression based one.
isRegExpSearch() - Method in interface meka.gui.core.SearchableTableModel: Returns whether the last search was a regular expression based one.
isRegExpSearch() - Method in class meka.gui.core.SortableAndSearchableTable: Returns whether the last search was a regular expression based one.
isRegExpSearch() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Returns whether the last search was a regular expression based one.
isRegularExpression() - Method in class meka.gui.core.SearchPanel: Returns whether the search text is a regular expression one or not.
isRegularExpressionEnabled() - Method in class meka.gui.core.SearchPanel: Returns whether regular expressions are turned on.
isRightClick(MouseEvent) - Static method in class meka.gui.core.MouseUtils: Checks whether the mouse event is a right-click event.
isRunning() - Method in class meka.experiment.DefaultExperiment: Returns whether the experiment is running.
isRunning() - Method in interface meka.experiment.Experiment: Returns whether the experiment is running.
isRunning() - Method in class meka.gui.explorer.AbstractThreadedExplorerTab: Checks whether a task is currently running.
isSearchMatch(SearchParameters, int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Tests whether the search matches the specified row.
isShortcutButton() - Method in class meka.gui.guichooser.AbstractMenuItemDefinition: Returns whether this menu item should also be listed as a shortcut button.
isShortcutButton() - Method in class meka.gui.guichooser.ExperimenterDefinition: Returns whether this menu item should also be listed as a shortcut button.
isShortcutButton() - Method in class meka.gui.guichooser.ExplorerDefinition: Returns whether this menu item should also be listed as a shortcut button.
isSorted() - Method in class meka.gui.core.SortableAndSearchableTable: returns whether the table was sorted.
isSorted() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: returns whether the table was sorted.
isSorted() - Method in interface meka.gui.core.SortableTable: returns whether the table was sorted.
isSorted() - Method in interface meka.gui.core.SortableTableModel: returns whether the table was sorted.
isStopping() - Method in class meka.experiment.DefaultExperiment: Returns whether the experiment is stopping.
isStopping() - Method in interface meka.experiment.Experiment: Returns whether the experiment is stopping.
isThreaded() - Method in interface meka.classifiers.multilabel.MultiLabelClassifierThreaded
isThreaded() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
isThreaded() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast
isThreaded() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse
isThreaded() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH
isThreaded() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT
isThreaded() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange
isThreaded() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV
isThreaded() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
isThreaded() - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM
isThreaded() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
isThreadSafe() - Method in class meka.experiment.evaluationstatistics.AbstractEvaluationStatisticsHandler: Returns whether the handler is threadsafe.
isThreadSafe() - Method in interface meka.experiment.evaluationstatistics.EvaluationStatisticsHandler: Returns whether the handler is threadsafe.
isThreadSafe() - Method in class meka.experiment.evaluationstatistics.InMemory: Returns whether the handler is threadsafe.
isThreadSafe() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Returns whether the handler is threadsafe.
isUndoEnabled() - Method in class meka.gui.dataviewer.DataPanel: returns whether undo support is enabled
isUndoEnabled() - Method in class meka.gui.dataviewer.DataSortedTableModel: returns whether undo support is enabled
isUndoEnabled() - Method in class meka.gui.dataviewer.DataTableModel: returns whether undo support is enabled
isValidSearch() - Method in class meka.gui.core.SearchPanel: Checks whether the search is valid.
isWindows() - Static method in class meka.core.OS: Checks whether the operating system is Windows.
IterationNotificationEvent - Class in meka.experiment.events: Event that gets sent by an experiment when a new classifier/dataset combination is being evaluated.
IterationNotificationEvent(Experiment, MultiLabelClassifier, Instances) - Constructor for class meka.experiment.events.IterationNotificationEvent: Gets called when the experiment starts on a new evaluation.
IterationNotificationListener - Interface in meka.experiment.events: Interface for classes that listen to iteration events of an experiment.
iterationsTipText() - Method in class meka.classifiers.multilabel.meta.EM
iterator() - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Returns all of the keys in the symbol table as an iterator.
iTipText() - Method in class meka.classifiers.multilabel.CDN

J

join(int[], int[]) - Static method in class meka.core.A
jPMF(Instances, int, int) - Static method in class meka.core.StatUtils: jPMF - Joint PMF.
jPMF(Instances, int, int, int) - Static method in class meka.core.StatUtils: Joint Distribution.
JTableHelper - Class in meka.gui.core: A helper class for JTable, e.g.
JTableHelper(JTable) - Constructor for class meka.gui.core.JTableHelper: initializes the object.

K

keepAttributesAt(Instance, int[], int) - Static method in class meka.core.MLUtils: Delete all attributes from an instance 'x' except those indexed by 'indicesToRemove[]', up to the 'lim'-th attribute.
keepAttributesAt(Instances, int[], int) - Static method in class meka.core.MLUtils: Delete all attributes from a dataset 'D' except those indexed by 'indicesToRemove[]', up to the 'lim'-th attribute.
keepLabels(Instances, int, int[]) - Static method in class meka.core.F: Remove Indices - Remove some labels (assume they are the first L attributes) from D.
KEY_CLASSIFIER - Static variable in class meka.experiment.evaluationstatistics.EvaluationStatistics: the key for the classifier.
KEY_CLASSIFIER - Static variable in class meka.experiment.evaluationstatistics.KeyValuePairs: the key for the classifier.
KEY_FILECHOOSER - Static variable in class meka.gui.explorer.classify.SaveCSV: the key in the session for the filechooser.
KEY_FILECHOOSER - Static variable in class meka.gui.explorer.classify.SaveGraphs: the key in the session for the filechooser.
KEY_FILECHOOSER - Static variable in class meka.gui.explorer.classify.SaveModel: the key in the session for the filechooser.
KEY_FILECHOOSER - Static variable in class meka.gui.explorer.classify.SavePredictions: the key in the session for the filechooser.
KEY_FOLD - Static variable in class meka.experiment.evaluators.CrossValidation: the key for the fold.
KEY_RELATION - Static variable in class meka.experiment.evaluationstatistics.EvaluationStatistics: the key for the relation.
KEY_RELATION - Static variable in class meka.experiment.evaluationstatistics.KeyValuePairs: the key for the relation.
KEY_RUN - Static variable in class meka.experiment.evaluators.RepeatedRuns: the key for the run number.
KEY_SEARCHREGEXP - Static variable in class meka.gui.core.SortableAndSearchableTable: the key for the regular expression search flag.
KEY_SEARCHSTRING - Static variable in class meka.gui.core.SortableAndSearchableTable: the key for the search string.
KEY_SORTCOL - Static variable in class meka.gui.core.SortableAndSearchableTable: the key for the sort column setting.
KEY_SORTORDER - Static variable in class meka.gui.core.SortableAndSearchableTable: the key for the sort oder.
keyAt(int) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Given an index in the range 0...size()-1, returns the key from the indexth key-value mapping that this SparseArray stores.
keys() - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Returns all keys in the symbol table as an Iterable.
keys(List<EvaluationStatistics>, boolean) - Static method in class meka.experiment.evaluationstatistics.EvaluationStatisticsUtils: Returns all the keys of all the statistics.
KeyValuePairs - Class in meka.experiment.evaluationstatistics: Simple plain text format.
KeyValuePairs() - Constructor for class meka.experiment.evaluationstatistics.KeyValuePairs
kMap - Variable in class meka.classifiers.multilabel.RAkELd
kMap - Variable in class meka.classifiers.multitarget.RAkELd
kTipText() - Method in class meka.classifiers.multilabel.RAkEL
kTipText() - Method in class meka.classifiers.multilabel.RAkELd
kTipText() - Method in class meka.classifiers.multitarget.RAkELd

L

L - Variable in class meka.classifiers.multilabel.cc.Trellis
L - Variable in class meka.classifiers.multilabel.incremental.PSUpdateable
L - Variable in class meka.core.Result: The number of label (target) variables in the problem
L_Hamming(int[], int[]) - Static method in class meka.core.Metrics: Hamming loss.
L_Hamming(int[][], int[][]) - Static method in class meka.core.Metrics: Hamming loss.
L_JaccardDist(int[][], int[][]) - Static method in class meka.core.Metrics: Jaccard Distance -- the loss version of Jaccard Index
L_LevenshteinDistance(int[][], int[][]) - Static method in class meka.core.Metrics: Levenshtein Distance.
L_LevenshteinDistance(int[], int[]) - Static method in class meka.core.Metrics: Levenshtein Distance divided by the number of labels.
L_LogLoss(double, double, double) - Static method in class meka.core.Metrics: L_LogLoss - the log loss between real-valued confidence rpred and true prediction y.
L_LogLoss(int[][], double[][], double) - Static method in class meka.core.Metrics: L_LogLoss - the log loss between real-valued confidences Rpred and true predictions Y with a maximum penalty C [Important Note: Earlier versions of Meka only normalised by N, and not N*L as here].
L_LogLossD(int[][], double[][]) - Static method in class meka.core.Metrics: L_LogLoss - the log loss between real-valued confidences Rpred and true predictions Y with a maximum penalty based on the number of examples D [Important Note: Earlier versions of Meka only normalised by N, and not N*L as here].
L_LogLossL(int[][], double[][]) - Static method in class meka.core.Metrics: L_LogLoss - the log loss between real-valued confidences Rpred and true predictions Y with a maximum penalty based on the number of labels L [Important Note: Earlier versions of Meka only normalised by N, and not N*L as here].
L_MAE(int[], double[]) - Method in class meka.core.Metrics: MAE
L_MSE(int[], double[]) - Method in class meka.core.Metrics: MSE
L_OneError(int[][], double[][]) - Static method in class meka.core.Metrics: OneError -
L_RankLoss(int[][], double[][]) - Static method in class meka.core.Metrics
L_RankLoss(int[], double[]) - Static method in class meka.core.Metrics
L_RankLoss(int[], int[]) - Static method in class meka.core.Metrics: Rank Loss - the average fraction of labels which are not correctly ordered.
L_ZeroOne(int[], int[]) - Static method in class meka.core.Metrics: 0/1 Loss.
L_ZeroOne(int[][], int[][]) - Static method in class meka.core.Metrics: 0/1 Loss.
labelCardinalities(Instances) - Static method in class meka.core.MLUtils: LabelCardinalities - return the frequency of each label of dataset D.
labelCardinalities(ArrayList<int[]>) - Static method in class meka.core.MLUtils: LabelCardinalities - return the frequency of each label of dataset D.
labelCardinality(Instances) - Static method in class meka.core.MLUtils: LabelCardinality - return the label cardinality of dataset D.
labelCardinality(Instances, int) - Static method in class meka.core.MLUtils: LabelCardinality - return the label cardinality of dataset D of L labels.
labelCardinality(int[][], int) - Static method in class meka.core.MLUtils: LabelCardinality - return the average number of times the j-th label is relevant in label data Y.
labelCardinality(int[][]) - Static method in class meka.core.MLUtils: LabelCardinality - return the label cardinality of label data Y.
LabelSet - Class in meka.core: Comparator - A fast sparse labelset representation.
LabelSet() - Constructor for class meka.core.LabelSet
LabelSet(int[]) - Constructor for class meka.core.LabelSet: A new LabelSet, given a list of SORTED indices.
LabelSet(int[], boolean) - Constructor for class meka.core.LabelSet: A new LabelSet, indicating sort=true if indices they need to be sorted (i.e., are NOT sorted).
LabelSet(List<Integer>) - Constructor for class meka.core.LabelSet
LabelSet(Set<Integer>) - Constructor for class meka.core.LabelSet
LabelSetComparator - Class in meka.core
LabelSetComparator(HashMap<LabelSet, Integer>) - Constructor for class meka.core.LabelSetComparator
LabelTransformationClassifier - Class in meka.classifiers.multilabel: Abstract label transformation classifiers, all classes that transform the labels should inherit from this classifier.
LabelTransformationClassifier() - Constructor for class meka.classifiers.multilabel.LabelTransformationClassifier: Default constructor using BR.
LabelVector - Class in meka.core: LabelVector - Multi-target compatible vector.
LabelVector(int[]) - Constructor for class meka.core.LabelVector
LatexMeasurement - Class in meka.experiment.statisticsexporters: Exports a single statistic to a tab-separated file.
LatexMeasurement() - Constructor for class meka.experiment.statisticsexporters.LatexMeasurement
LatexUtils - Class in meka.core: Helper functions around LaTeX.
LatexUtils() - Constructor for class meka.core.LatexUtils
LatexUtils.Characters - Enum in meka.core: The characters to escape.
launch() - Method in class meka.gui.experimenter.menu.AbstractExperimenterMenuItem: Launches the menu item action.
launch() - Method in class meka.gui.experimenter.menu.CombineStatisticsFiles: Launches the menu item action.
launch() - Method in class meka.gui.guichooser.AbstractMenuItemDefinition: Called by the menu items action listener.
launch() - Method in class meka.gui.guichooser.DataViewerDefinition: Called by the menu items action listener.
launch() - Method in class meka.gui.guichooser.ExperimenterDefinition: Called by the menu items action listener.
launch() - Method in class meka.gui.guichooser.ExplorerDefinition: Called by the menu items action listener.
launch() - Method in class meka.gui.guichooser.HomepageDefinition: Called by the menu items action listener.
launch() - Method in class meka.gui.guichooser.ModelViewerDefinition: Called by the menu items action listener.
launch() - Method in class meka.gui.guichooser.PrecisionRecallCurve: Called by the menu items action listener.
launch() - Method in class meka.gui.guichooser.ROC: Called by the menu items action listener.
launch() - Method in class meka.gui.guichooser.SystemInfo: Called by the menu items action listener.
launchApplication(Class, String, boolean, String[]) - Static method in class meka.gui.core.GUILauncher: Embeds the panel in a frame and displays.
launchFrame(Class, String, boolean) - Static method in class meka.gui.core.GUILauncher: Embeds the panel in a frame and displays.
launchFrame(JPanel, String, boolean) - Static method in class meka.gui.core.GUILauncher: Embeds the panel in a frame and displays.
LC - Class in meka.classifiers.multilabel: LC.java - The LC (Label Combination) aka LP (Laber Powerset) Method.
LC() - Constructor for class meka.classifiers.multilabel.LC
LCTransformation(Instances) - Static method in class meka.core.PSUtils
LCTransformation(Instances, int) - Static method in class meka.core.PSUtils
LEAD(Instances, Result, String) - Static method in class meka.core.StatUtils: LEAD - Performs LEAD on dataset 'D', with corresponding gresult 'R', and dependency measurement type 'MDType'.
LEAD(Instances, Result) - Static method in class meka.core.StatUtils
LEAD(Instances, Classifier, Random) - Static method in class meka.core.StatUtils: LEAD - Performs LEAD on dataset 'D', using BR with base classifier 'h', under random seed 'r'.
LEAD(Instances, Classifier, Random, String) - Static method in class meka.core.StatUtils
LEAD2(Instances, Result) - Static method in class meka.core.StatUtils: LEAD.
learn(double[][], int[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARTCluster
LEARNING_RATE - Variable in class rbms.RBM
learningRateTipText() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
limitTipText() - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
Link(int[], int, Instances) - Constructor for class meka.classifiers.multitarget.CCp.Link
linkTransform(Instances, int, int[]) - Static method in class meka.core.CCUtils: LinkTransform - prepare 'D' for training at a node 'j' of the chain, by excluding 'exl'.
linkTransformation(Instance, int[], Instances) - Static method in class meka.core.CCUtils: LinkTransform - prepare 'x' for testing at a node 'j' of the chain, by excluding 'exl'.
listOptions() - Method in class meka.classifiers.multilabel.BCC
listOptions() - Method in class meka.classifiers.multilabel.BRq
listOptions() - Method in class meka.classifiers.multilabel.CC
listOptions() - Method in class meka.classifiers.multilabel.CCq
listOptions() - Method in class meka.classifiers.multilabel.CDN
listOptions() - Method in class meka.classifiers.multilabel.CDT
listOptions() - Method in class meka.classifiers.multilabel.CT
listOptions() - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
listOptions() - Method in class meka.classifiers.multilabel.Maniac: Returns an enumeration of the options.
listOptions() - Method in class meka.classifiers.multilabel.MCC
listOptions() - Method in class meka.classifiers.multilabel.meta.EM
listOptions() - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
listOptions() - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
listOptions() - Method in class meka.classifiers.multilabel.MLCBMaD: Returns an enumeration of the options.
listOptions() - Method in class meka.classifiers.multilabel.MULAN
listOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork: Returns an enumeration describing the available options.
listOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast: Returns an enumeration describing the available options.
listOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse: Returns an enumeration describing the available options.
listOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH: Returns an enumeration describing the available options.
listOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT: Returns an enumeration describing the available options.
listOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange: Returns an enumeration describing the available options.
listOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV: Returns an enumeration describing the available options.
listOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork: Returns an enumeration describing the available options.
listOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM: Returns an enumeration describing the available options.
listOptions() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM: Returns an enumeration describing the available options.
listOptions() - Method in class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
listOptions() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
listOptions() - Method in class meka.classifiers.multilabel.PLST: Returns an enumeration of the options.
listOptions() - Method in class meka.classifiers.multilabel.PMCC
listOptions() - Method in class meka.classifiers.multilabel.PS
listOptions() - Method in class meka.classifiers.multilabel.RAkEL
listOptions() - Method in class meka.classifiers.multilabel.RAkELd
listOptions() - Method in class meka.classifiers.multitarget.RAkELd
listOptions() - Method in class meka.classifiers.multitarget.SCC
listOptions() - Method in class meka.experiment.datasetproviders.AbstractDatasetProvider: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.datasetproviders.LocalDatasetProvider: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.DefaultExperiment: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.evaluationstatistics.AbstractEvaluationStatisticsHandler: Returns an enumeration of all the available options.
listOptions() - Method in class meka.experiment.evaluationstatistics.AbstractFileBasedEvaluationStatisticsHandler: Returns an enumeration of all the available options.
listOptions() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Returns an enumeration of all the available options.
listOptions() - Method in class meka.experiment.evaluators.AbstractEvaluator: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.evaluators.AbstractMetaEvaluator: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.evaluators.CrossValidation: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.evaluators.PercentageSplit: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.evaluators.RepeatedRuns: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.filehandlers.AbstractExperimentFileHandler: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.statisticsexporters.AbstractEvaluationStatisticsExporter: Returns an enumeration of all the available options.
listOptions() - Method in class meka.experiment.statisticsexporters.AbstractFileBasedEvaluationStatisticsExporter: Returns an enumeration of all the available options.
listOptions() - Method in class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.statisticsexporters.AbstractMetaEvaluationStatisticsExporter: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.statisticsexporters.MultiExporter: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Returns an enumeration of all the available options..
listOptions() - Method in class meka.experiment.statisticsexporters.WekaFilter: Returns an enumeration of all the available options..
listOptions() - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes: Returns an enumeration describing the available options.
ListWithButtons - Class in meka.gui.core: A JList with buttons.
ListWithButtons() - Constructor for class meka.gui.core.ListWithButtons
load() - Method in class meka.gui.experimenter.Statistics: Loads statistics from disk.
loadDataset(String[]) - Static method in class meka.classifiers.multilabel.Evaluation: loadDataset - load a dataset, given command line option '-t' specifying an arff file.
loadDataset(String[], char) - Static method in class meka.classifiers.multilabel.Evaluation: loadDataset - load a dataset, given command line options specifying an arff file.
loadDefinitions() - Method in class meka.gui.guichooser.GUIChooser: Loads the menu item definitions.
loadFile(String, AbstractFileLoader...) - Method in class meka.gui.dataviewer.DataTableModel: loads the specified ARFF file
loadFile(String, AbstractFileLoader...) - Method in class meka.gui.dataviewer.DataViewerMainPanel: loads the specified file
loadFile() - Method in class meka.gui.dataviewer.DataViewerMainPanel: loads the specified file into the table
loadMap(String) - Static method in class meka.core.PSUtils: LoadMap - Load the HashMap stored in 'filename'.
loadObject(String) - Static method in class meka.core.MLUtils: Load Object - load the Object stored in 'filename'.
loadProps() - Method in class meka.gui.core.AbstractRecentItemsHandler: Loads the properties file from disk, if possible.
LocalDatasetProvider - Class in meka.experiment.datasetproviders: Loads local files from disk.
LocalDatasetProvider() - Constructor for class meka.experiment.datasetproviders.LocalDatasetProvider
log(String) - Method in class meka.events.LogObject: For logging messages.
log(String) - Method in interface meka.events.LogSupporter: For logging messages.
log(String) - Method in class meka.gui.core.MaximizationFixWindowListener: Logs the message to stdout.
log(String) - Method in class meka.gui.experimenter.AbstractExperimenterTab: For logging messages.
log(AbstractExperimenterTab, String) - Method in class meka.gui.experimenter.Experimenter: For logging messages.
log(AbstractExperimenterTab, String) - Method in class meka.gui.experimenter.LogTab: For logging messages.
log(String) - Method in class meka.gui.explorer.AbstractExplorerTab: For logging messages.
log(AbstractExplorerTab, String) - Method in class meka.gui.explorer.Explorer: For logging messages.
log(AbstractExplorerTab, String) - Method in class meka.gui.explorer.LogTab: For logging messages.
LogEvent - Class in meka.events: Event that contains a log message.
LogEvent(Object, String) - Constructor for class meka.events.LogEvent: Gets called when the experiment starts on a new evaluation.
LogListener - Interface in meka.events: Interface for classes that listen to log events of an experiment.
logMessage(LogEvent) - Method in interface meka.events.LogListener: Gets called if there is a new log message.
logMessage(LogEvent) - Method in class meka.gui.experimenter.Experimenter: Gets called if there is a new log message.
LogObject - Class in meka.events: Ancestor for objects that support logging.
LogObject() - Constructor for class meka.events.LogObject
LogSupporter - Interface in meka.events: Interface for classes that support logging.
LogTab - Class in meka.gui.experimenter: For logging output.
LogTab() - Constructor for class meka.gui.experimenter.LogTab
LogTab - Class in meka.gui.explorer: For logging output.
LogTab() - Constructor for class meka.gui.explorer.LogTab
lowerRunsTipText() - Method in class meka.experiment.evaluators.RepeatedRuns: Describes this property.

M

m_ActualNumThreads - Variable in class meka.experiment.evaluators.CrossValidation: the actual number of threads to use.
m_ActualNumThreads - Variable in class meka.experiment.evaluators.RepeatedRuns: the actual number of threads to use.
m_addInstanceButton - Variable in class meka.gui.dataviewer.DataViewerDialog: Click to add a new instance to the end of the dataset
m_AdditionalMenuItems - Variable in class meka.gui.experimenter.Experimenter: additional menu items.
m_AdditionalMenuItems - Variable in class meka.gui.explorer.ClassifyTab: the additional menu items.
m_AggregationKeys - Variable in class meka.experiment.statisticsexporters.SimpleAggregate: the aggregation keys.
m_Animation - Variable in class meka.gui.core.StatusBar: the runnable for animating the icon.
m_AttributeIndices - Variable in class meka.filters.unsupervised.attribute.MekaClassAttributes: the range of attributes to use as class attributes.
m_AttSizePercent - Variable in class meka.classifiers.multilabel.meta.RandomSubspaceML
m_BagSizePercent - Variable in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
m_BASE - Variable in class meka.classifiers.multilabel.meta.MBR
m_Beta - Variable in class meka.classifiers.multilabel.PMCC
m_Button - Variable in class meka.gui.dataviewer.DataTable.RelationalCellEditor: the button for opening the dialog
m_ButtonAddClassifier - Variable in class meka.gui.experimenter.BasicSetup: the button for adding a classifier.
m_ButtonAddClassifier - Variable in class meka.gui.experimenter.ExpertSetup: the button for adding a classifier.
m_ButtonAddDataset - Variable in class meka.gui.experimenter.BasicSetup: the button for adding a dataset.
m_ButtonApply - Variable in class meka.gui.experimenter.AbstractSetupTab: the button for applying the setup.
m_ButtonApplyFilter - Variable in class meka.gui.explorer.PreprocessTab: the button for applying a filter.
m_ButtonApprove - Variable in class meka.gui.core.ApprovalDialog: the approve button.
m_ButtonCancel - Variable in class meka.gui.core.ApprovalDialog: the cancel button.
m_ButtonCaption - Variable in class meka.gui.core.SearchPanel: the caption (+ optional mnemonic indicator) for the search button.
m_ButtonClear - Variable in class meka.gui.experimenter.LogTab: the button for clearing the log.
m_ButtonClear - Variable in class meka.gui.explorer.LogTab: the button for clearing the log.
m_ButtonDiscard - Variable in class meka.gui.core.ApprovalDialog: the discard button.
m_ButtonEditClassifier - Variable in class meka.gui.experimenter.BasicSetup: the button for editing a classifier.
m_ButtonEditClassifier - Variable in class meka.gui.experimenter.ExpertSetup: the button for editing a classifier.
m_ButtonMoveDownClassifier - Variable in class meka.gui.experimenter.BasicSetup: the button for moving a classifier down.
m_ButtonMoveDownClassifier - Variable in class meka.gui.experimenter.ExpertSetup: the button for moving a classifier down.
m_ButtonMoveDownDataset - Variable in class meka.gui.experimenter.BasicSetup: the button for moving a dataset down.
m_ButtonMoveUpClassifier - Variable in class meka.gui.experimenter.BasicSetup: the button for moving a classifier up.
m_ButtonMoveUpClassifier - Variable in class meka.gui.experimenter.ExpertSetup: the button for moving a classifier up.
m_ButtonMoveUpDataset - Variable in class meka.gui.experimenter.BasicSetup: the button for moving a dataset up.
m_ButtonNotes - Variable in class meka.gui.experimenter.BasicSetup: the button for the notes.
m_ButtonNotes - Variable in class meka.gui.experimenter.ExpertSetup: the button for the notes.
m_ButtonOptions - Variable in class meka.gui.explorer.ClassifyTab: the button for the options dialog.
m_ButtonRemoveAllClassifiers - Variable in class meka.gui.experimenter.BasicSetup: the button for removing all classifiers.
m_ButtonRemoveAllClassifiers - Variable in class meka.gui.experimenter.ExpertSetup: the button for removing all classifiers.
m_ButtonRemoveAllDatasets - Variable in class meka.gui.experimenter.BasicSetup: the button for removing all datasets.
m_ButtonRemoveAttributes - Variable in class meka.gui.explorer.PreprocessTab: Button for removing attributes
m_ButtonRemoveClassifier - Variable in class meka.gui.experimenter.BasicSetup: the button for removing a classifier.
m_ButtonRemoveClassifier - Variable in class meka.gui.experimenter.ExpertSetup: the button for removing a classifier.
m_ButtonRemoveDataset - Variable in class meka.gui.experimenter.BasicSetup: the button for removing a dataset.
m_ButtonRevert - Variable in class meka.gui.experimenter.AbstractSetupTab: the button for reverting the setup.
m_ButtonSave - Variable in class meka.gui.experimenter.LogTab: the button for saving the log.
m_ButtonSave - Variable in class meka.gui.explorer.LogTab: the button for saving the log.
m_ButtonSearch - Variable in class meka.gui.core.SearchPanel: the button for searching the table.
m_ButtonSetClassAttributes - Variable in class meka.gui.explorer.PreprocessTab: the button for setting the class attributes.
m_ButtonStart - Variable in class meka.gui.explorer.ClassifyTab: the button for running an experiment.
m_ButtonStop - Variable in class meka.gui.explorer.ClassifyTab: the button for stopping an experiment.
m_Cache - Variable in class meka.gui.dataviewer.DataTableModel: for caching long relational and string values that get processed for display.
m_Cache - Static variable in class meka.gui.modelviewer.renderers.AbstractObjectRenderer: the cache for object class / renderer relation.
m_CancelButton - Variable in class meka.gui.dataviewer.DataViewerDialog: Click to cancel the dialog
m_Chain - Variable in class meka.classifiers.multilabel.CC
m_CheckBoxClear - Variable in class meka.gui.experimenter.LogTab: whether to clear before each run.
m_CheckBoxOptions - Variable in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: the checkbox for bringing up the GenericObjectEditor.
m_CheckBoxPreserveOrder - Variable in class meka.gui.experimenter.BasicSetup: whether to preserve the order.
m_CheckboxRegExp - Variable in class meka.gui.core.SearchPanel: whether to use regular expressions for searching or plain string comparison.
m_Classifier - Variable in class meka.experiment.evaluationstatistics.EvaluationStatistics: the classifier.
m_Classifier - Variable in class meka.experiment.events.IterationNotificationEvent: the classifier.
m_Classifiers - Variable in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
m_Classifiers - Variable in class meka.classifiers.multilabel.RAkELd
m_Classifiers - Variable in class meka.classifiers.multitarget.RAkELd
m_Classifiers - Variable in class meka.experiment.DefaultExperiment: the classifiers to evaluate.
m_Classifiers - Variable in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: the classifiers.
m_ClassifyTabOptions - Variable in class meka.gui.explorer.ClassifyTab: the panel with the options.
m_Classname - Variable in class meka.gui.choosers.ExtensionFileFilterWithClass: the classname.
m_ColumnIndex - Variable in class meka.gui.dataviewer.DataTable.RelationalCellEditor: the column index this editor is for
m_ColumnIsNumeric - Variable in class meka.gui.core.SortableAndSearchableWrapperTableModel: whether a column is numeric.
m_ComboBoxEvaluation - Variable in class meka.gui.experimenter.BasicSetup: the type of evaluation.
m_ComboBoxExperiment - Variable in class meka.gui.explorer.ClassifyTab: the type of experiment to perform.
m_ComboBoxMeasurements - Variable in class meka.gui.experimenter.Statistics: the combobox with the measurements.
m_CommandLine - Variable in class meka.experiment.evaluationstatistics.EvaluationStatistics: the classifier commandline.
m_Comparator - Variable in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: for comparing the filters.
m_ConfirmExit - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_Count - Variable in class meka.classifiers.multilabel.meta.SubsetMapper
m_Current - Variable in class meka.experiment.datasetproviders.LocalDatasetProvider: the iterator index.
m_Current - Variable in class meka.experiment.datasetproviders.MultiDatasetProvider: the iterator index.
m_Current - Variable in class meka.gui.goe.GenericObjectEditorDialog: the current object.
m_CurrentBounds - Variable in class meka.gui.core.MaximizationFixWindowListener: the current size/location.
m_CurrentFile - Variable in class meka.gui.experimenter.Experimenter: the current file.
m_CurrentFile - Variable in class meka.gui.explorer.Explorer: the current file.
m_CurrentHandler - Variable in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: the converter that was chosen by the user.
m_CurrentInst - Variable in class meka.gui.dataviewer.DataTable.RelationalCellEditor: the current instances
m_Data - Variable in class meka.gui.dataviewer.DataTableModel: the data
m_Data - Variable in class meka.gui.explorer.AbstractExplorerTab: the current dataset.
m_Data - Variable in class meka.gui.explorer.Explorer: data currently loaded.
m_DataPanel - Variable in class meka.gui.dataviewer.DataViewerDialog: the panel to display the Instances-object
m_Dataset - Variable in class meka.experiment.events.IterationNotificationEvent: the dataset.
m_DatasetProvider - Variable in class meka.experiment.DefaultExperiment: the dataset provider.
m_Datasets - Variable in class meka.experiment.datasetproviders.LocalDatasetProvider: the files to load.
m_Datasets - Variable in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: the datasets.
m_Debug - Variable in class meka.events.LogObject: whether to run code in DEBUG mode
m_Delay - Variable in class meka.gui.core.StatusBar.Animation: the delay between changing the icon in msec.
m_Density - Variable in class meka.classifiers.multilabel.CDT
m_Density - Variable in class meka.classifiers.multilabel.CT
m_DependencyMetric - Variable in class meka.classifiers.multilabel.CDT
m_DependencyMetric - Variable in class meka.classifiers.multilabel.CT
m_DialogType - Variable in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: the type of dialog to display.
m_DisplayIndices - Variable in class meka.gui.core.SortableAndSearchableWrapperTableModel: the indices of the rows to display that match a search string.
m_Double - Variable in class meka.gui.core.SearchParameters: not null if the search string is a double.
m_DownSampleRatio - Variable in class meka.classifiers.multilabel.BRq: The downsample ratio
m_DownSampleRatio - Variable in class meka.classifiers.multilabel.CCq: The downsample ratio
m_E - Variable in class meka.classifiers.multilabel.NN.AbstractNeuralNet: number of epochs
m_E - Variable in class rbms.RBM
m_Editor - Variable in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: the GOE for displaying the options of a reader/writer.
m_Editor - Variable in class meka.gui.goe.GenericObjectEditorDialog: the underlying editor.
m_Enabled - Variable in class meka.gui.core.MaximizationFixWindowListener: whether enabled or not.
m_Evaluator - Variable in class meka.experiment.DefaultExperiment: the evaluator.
m_Evaluator - Variable in class meka.experiment.evaluators.AbstractMetaEvaluator: the base evaluator.
m_ExecutionStageListeners - Variable in class meka.experiment.DefaultExperiment: the listeners for execution stages.
m_Executor - Variable in class meka.experiment.evaluators.CrossValidation: the executor service to use for parallel execution.
m_Executor - Variable in class meka.experiment.evaluators.RepeatedRuns: the executor service to use for parallel execution.
m_ExitOnClose - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_Experiment - Variable in class meka.gui.experimenter.AbstractExperimenterTab: the current experiment.
m_Experiment - Variable in class meka.gui.experimenter.Experimenter: the current experiment.
m_ExportButton - Variable in class meka.gui.dataviewer.DataViewerDialog: Click to export the data
m_Exporter - Variable in class meka.experiment.statisticsexporters.AbstractMetaEvaluationStatisticsExporter: the base exporter.
m_Exporters - Variable in class meka.experiment.statisticsexporters.MultiExporter: the base exporter.
m_File - Variable in class meka.experiment.evaluationstatistics.AbstractFileBasedEvaluationStatisticsHandler: the file to read from/write to.
m_File - Variable in class meka.experiment.statisticsexporters.AbstractFileBasedEvaluationStatisticsExporter: the file to read from/write to.
m_File - Variable in class meka.gui.core.RecentFilesHandlerWithCommandline.Setup: the file.
m_FileChooser - Variable in class meka.gui.core.ResultHistoryList: the file chooser for saving the output.
m_FileChooser - Variable in class meka.gui.dataviewer.DataViewerDialog: the file chooser for loading/saving files.
m_FileChooser - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_FileChooser - Variable in class meka.gui.experimenter.Experimenter: the file chooser for the experiments.
m_FileChooser - Variable in class meka.gui.experimenter.LogTab: the filechooser for saving the log.
m_FileChooser - Variable in class meka.gui.experimenter.Statistics: the filechooser for saving the statistics.
m_FileChooser - Variable in class meka.gui.explorer.Explorer: the file chooser for loading/saving files.
m_FileChooser - Variable in class meka.gui.explorer.LogTab: the filechooser for saving the log.
m_FileChooser - Variable in class meka.gui.guichooser.PrecisionRecallCurve: filechooser for ROCs.
m_FileChooser - Variable in class meka.gui.guichooser.ROC: filechooser for ROCs.
m_FileChooser - Variable in class meka.gui.modelviewer.ModelViewer: the filechooser for loading the model files.
m_FileChooserDatasets - Variable in class meka.gui.experimenter.BasicSetup: the file chooser for datasets.
m_FileChooserMeasurement - Variable in class meka.gui.experimenter.Statistics: the filechooser for saving the measurement statistics.
m_FileChooserStatistics - Variable in class meka.gui.experimenter.Statistics: the filechooser for loading the statistics.
m_FileFilters - Static variable in class meka.gui.choosers.EvaluationStatisticsExporterFileChooser: the file filters for the readers.
m_FileFilters - Static variable in class meka.gui.choosers.EvaluationStatisticsFileChooser: the file filters for the readers.
m_FileFilters - Static variable in class meka.gui.choosers.ExperimentFileChooser: the file filters for the readers.
m_FileFilters - Static variable in class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser: the file filters for the readers.
m_FileMustExist - Variable in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: whether the file to be opened must exist (only open dialog).
m_Filter - Variable in class meka.experiment.statisticsexporters.WekaFilter: the filter to apply to the data before passing it on to the base exporter.
m_Folds - Variable in class meka.gui.explorer.ClassifyTab: the number of folds.
m_Formatter - Variable in class meka.gui.experimenter.LogTab: the formatter for the timestamp.
m_Formatter - Variable in class meka.gui.explorer.LogTab: the formatter for the timestamp.
m_FrameTitle - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_GapHorizontal - Variable in class meka.gui.core.ParameterPanel: the horizontal gap.
m_GapVertical - Variable in class meka.gui.core.ParameterPanel: the vertical gap.
m_GenericObjectEditor - Variable in class meka.gui.explorer.ClassifyTab: the GOE for the classifier.
m_GenericObjectEditor - Variable in class meka.gui.explorer.PreprocessTab: for filtering the data.
m_GOEDatasets - Variable in class meka.gui.experimenter.ExpertSetup: the GOE for the datasets.
m_GOEEvaluator - Variable in class meka.gui.experimenter.ExpertSetup: the GOE for the evaluator.
m_GOEStatisticsHandler - Variable in class meka.gui.experimenter.BasicSetup: the GOE for the statistics handler.
m_GOEStatisticsHandler - Variable in class meka.gui.experimenter.ExpertSetup: the GOE for the statistics handler.
m_H - Variable in class meka.classifiers.multilabel.NN.AbstractNeuralNet: number of hidden units
m_H - Variable in class rbms.RBM
m_Handler - Variable in class meka.gui.core.RecentFilesHandlerWithCommandline.Setup: the object.
m_Headers - Variable in class meka.gui.core.EvaluationStatisticsTableModel: the headers.
m_History - Variable in class meka.gui.core.ResultHistoryList.ResultHistoryModel: the underlying history list.
m_I - Variable in class meka.classifiers.multilabel.meta.EM
m_IgnoreChanges - Variable in class meka.gui.core.AbstractRecentItemsHandler: whether to ignore changes temporarily.
m_IgnoreChanges - Variable in class meka.gui.dataviewer.DataTableModel: whether to ignore changes, i.e.
m_IgnoreChanges - Variable in class meka.gui.experimenter.AbstractSetupTab: whether to ignore changes (= don't set modified flag).
m_IgnoreChanges - Variable in class meka.gui.experimenter.Statistics: whether to ignore changes in the UI.
m_IgnoreStateChangeEvent - Variable in class meka.gui.core.MaximizationFixWindowListener: whether to ignored the state change event.
m_IncludeAll - Variable in class meka.gui.components.AttributeSelectionPanel: Press to select all attributes
m_Incremental - Variable in class meka.gui.core.SearchPanel: whether incremental search is enabled.
m_IncrementalDisabled - Variable in class meka.experiment.evaluationstatistics.KeyValuePairs: whether the incremental mode is off.
m_Index - Variable in class meka.gui.core.SortableAndSearchableWrapperTableModel.SortContainer: the index of the value.
m_IndicesCut - Variable in class meka.classifiers.multilabel.meta.RandomSubspaceML
m_Initializing - Variable in class meka.experiment.DefaultExperiment: whether the experiment is initializing.
m_InstancesTemplate - Variable in class meka.classifiers.multilabel.ProblemTransformationMethod: A Template for Problem Transformations
m_InstancesTemplates - Variable in class meka.classifiers.multilabel.BR
m_InstancesTemplates - Variable in class meka.classifiers.multilabel.meta.RandomSubspaceML
m_InstancesTemplates - Variable in class meka.classifiers.multilabel.RAkELd
m_InstancesTemplates - Variable in class meka.classifiers.multitarget.RAkELd
m_InstanceTemplates - Variable in class meka.classifiers.multilabel.meta.RandomSubspaceML
m_Integer - Variable in class meka.gui.core.SearchParameters: not null if the search string is an integer.
m_Invert - Variable in class meka.gui.components.AttributeSelectionPanel: Press to invert the current selection
m_Is - Variable in class meka.classifiers.multilabel.MCC
m_IsAndroid - Static variable in class meka.core.OS: whether the OS is Android.
m_IsLinux - Static variable in class meka.core.OS: whether the OS is Linux.
m_IsMac - Static variable in class meka.core.OS: whether the OS is Mac.
m_IsWindows - Static variable in class meka.core.OS: whether the OS is Windows.
m_Item - Variable in class meka.gui.events.RecentItemEvent: the affected item.
m_IterationNotficationListeners - Variable in class meka.experiment.DefaultExperiment: the listeners for iterations.
m_Iy - Variable in class meka.classifiers.multilabel.MCC
m_Keys - Variable in class meka.experiment.evaluationstatistics.EvaluationStatisticsComparator: the keys to use for comparison.
m_LabelFile - Variable in class meka.gui.modelviewer.ModelViewer: the label for the filename.
m_LabelIcon - Variable in class meka.gui.core.StatusBar.Animation: the JLabel used for displaying the icon.
m_LabelIcon - Variable in class meka.gui.core.StatusBar: for displaying the icon.
m_LabelPrefix - Variable in class meka.gui.core.SearchPanel: the label for the text field.
m_Labels - Variable in class meka.gui.core.ParameterPanel: the labels.
m_LabelText - Variable in class meka.gui.core.StatusBar: for displaying the status text.
m_LastFilter - Variable in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: the last filter that was used for opening/saving.
m_LastIncrementalClassifier - Variable in class meka.gui.explorer.ClassifyTab: the last incremental classifier in use.
m_LastNonIncrementalClassifier - Variable in class meka.gui.explorer.ClassifyTab: the last non-incremental classifier in use.
m_LastOpenHandler - Variable in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: the last "open" handler.
m_LastSaveHandler - Variable in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: the last "save" handler.
m_LastSearch - Variable in class meka.gui.core.SearchPanel: the last search term.
m_LayoutButtons - Variable in class meka.gui.core.MekaPanelWithButtons: the layout for the buttons.
m_LayoutType - Variable in class meka.gui.core.SearchPanel: the layout.
m_LayoutWidgets - Variable in class meka.gui.core.SearchPanel: the layout for the Widgets.
m_Limit - Variable in class meka.classifiers.multilabel.incremental.PSUpdateable
m_List - Variable in class meka.gui.core.ListWithButtons: the list.
m_ListClassifiers - Variable in class meka.gui.experimenter.BasicSetup: the classifiers.
m_ListClassifiers - Variable in class meka.gui.experimenter.ExpertSetup: the classifiers.
m_ListDatasets - Variable in class meka.gui.experimenter.BasicSetup: the datasets.
m_Listener - Variable in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: the propertychangelistener.
m_Listeners - Variable in class meka.gui.core.AbstractRecentItemsHandler: the event listeners.
m_Listeners - Variable in class meka.gui.dataviewer.DataTableModel: the listeners
m_Logging - Variable in class meka.gui.core.MaximizationFixWindowListener: whether to output some logging information.
m_LogListeners - Variable in class meka.events.LogObject: the listeners.
m_LogTab - Variable in class meka.gui.experimenter.Experimenter: the log tab.
m_LogTab - Variable in class meka.gui.explorer.Explorer: the log tab.
m_LowerRuns - Variable in class meka.experiment.evaluators.RepeatedRuns: the lower number of runs (included).
m_M - Variable in class meka.classifiers.multilabel.NN.AbstractNeuralNet: momentum
m_M - Variable in class meka.classifiers.multilabel.PMCC
m_Markdown - Variable in class meka.gui.core.MarkdownTextPane: the markdown text.
m_MaxCount - Variable in class meka.gui.core.AbstractRecentItemsHandler: the maximum number of items to keep.
m_MaximizationFixWindowListener - Variable in class meka.gui.core.MekaFrame: the maximization fix listener.
m_Measurement - Variable in class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter: the measurement to output.
m_Measurement - Variable in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: the measurement.
m_MekaEditorsRegistered - Static variable in class meka.gui.goe.GenericObjectEditor: whether the MEAK Editors were already registered.
m_Menu - Variable in class meka.gui.core.AbstractRecentItemsHandler: the menu to add the items as sub-items to.
m_Menu - Variable in class meka.gui.explorer.ClassifyTab: the custom menu.
m_MenuBar - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuBar - Variable in class meka.gui.experimenter.Experimenter: the menu bar.
m_MenuBar - Variable in class meka.gui.explorer.Explorer: the menu bar.
m_MenuBar - Variable in class meka.gui.guichooser.GUIChooser: the menu bar.
m_MenuBar - Variable in class meka.gui.modelviewer.ModelViewer: the menu bar.
m_MenuEdit - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuEditAttributeAsClass - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuEditClearSearch - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuEditCopy - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuEditDeleteAttribute - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuEditDeleteAttributes - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuEditDeleteInstance - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuEditDeleteInstances - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuEditRenameAttribute - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuEditSearch - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuEditSortInstances - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuEditUndo - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuFile - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuFileClose - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuFileCloseAll - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuFileExit - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuFileOpen - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuFileOpenRecent - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuFileOpenRecent - Variable in class meka.gui.experimenter.Experimenter: the "load recent" submenu.
m_MenuFileOpenRecent - Variable in class meka.gui.explorer.Explorer: the "load recent" submenu.
m_MenuFileOpenRecent - Variable in class meka.gui.modelviewer.ModelViewer: the "load recent" submenu.
m_MenuFileProperties - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuFileSave - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuFileSaveAs - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuItemEditData - Variable in class meka.gui.explorer.Explorer: the "redo" menu item.
m_MenuItemEditUndo - Variable in class meka.gui.explorer.Explorer: the "undo" menu item.
m_MenuItemExecutionStart - Variable in class meka.gui.experimenter.Experimenter: the "start" menu item.
m_MenuItemExecutionStop - Variable in class meka.gui.experimenter.Experimenter: the "stop" menu item.
m_MenuItemFileClose - Variable in class meka.gui.experimenter.Experimenter: the "close" menu item.
m_MenuItemFileClose - Variable in class meka.gui.explorer.Explorer: the "close" menu item.
m_MenuItemFileClose - Variable in class meka.gui.modelviewer.ModelViewer: the "close" menu item.
m_MenuItemFileNew - Variable in class meka.gui.experimenter.Experimenter: the "new" menu.
m_MenuItemFileOpen - Variable in class meka.gui.experimenter.Experimenter: the "open" menu item.
m_MenuItemFileOpen - Variable in class meka.gui.explorer.Explorer: the "open" menu item.
m_MenuItemFileOpen - Variable in class meka.gui.modelviewer.ModelViewer: the "open" menu item.
m_MenuItemFileSave - Variable in class meka.gui.experimenter.Experimenter: the "save" menu item.
m_MenuItemFileSave - Variable in class meka.gui.explorer.Explorer: the "save" menu item.
m_MenuItemFileSaveAs - Variable in class meka.gui.experimenter.Experimenter: the "save as" menu item.
m_MenuItemFileSaveAs - Variable in class meka.gui.explorer.Explorer: the "save as" menu item.
m_MenuItemOpen - Variable in class meka.gui.experimenter.Statistics: the menu item for loading stats.
m_MenuItemProgramClose - Variable in class meka.gui.guichooser.GUIChooser: the "close" menu item.
m_MenuItemSaveAsAggregated - Variable in class meka.gui.experimenter.Statistics: the menu item for saving aggregated stats.
m_MenuItemSaveAsMeasurement - Variable in class meka.gui.experimenter.Statistics: the menu item for saving measurement stats.
m_MenuItemSaveAsRaw - Variable in class meka.gui.experimenter.Statistics: the menu item for saving raw stats.
m_Menus - Variable in class meka.gui.guichooser.GUIChooser: the menus.
m_MenuView - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuViewAttributes - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuViewOptimalColWidths - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_MenuViewValues - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_Message - Variable in class meka.events.LogEvent: the log message.
m_META - Variable in class meka.classifiers.multilabel.meta.MBR
m_MethodString - Variable in class meka.classifiers.multilabel.MULAN
m_MinimumChars - Variable in class meka.gui.core.SearchPanel: the minimum number of characters before triggering search events.
m_MinNumParentDirs - Variable in class meka.gui.core.RecentFilesHandler: the minimum number of parent directories to use.
m_MinNumParentDirs - Variable in class meka.gui.core.RecentFilesHandlerWithCommandline: the minimum number of parent directories to use.
m_Model - Variable in class meka.gui.components.AttributeSelectionPanel: The table model containing attribute names and selection status
m_Model - Variable in class meka.gui.core.SortableAndSearchableTable: the sortable/searchable model.
m_Model - Variable in class meka.gui.core.SortableAndSearchableWrapperTableModel: the actual table model.
m_ModelAggregated - Variable in class meka.gui.experimenter.Statistics: the model for the aggregated statistics.
m_ModelClassifiers - Variable in class meka.gui.experimenter.BasicSetup: the model with the classifiers.
m_ModelClassifiers - Variable in class meka.gui.experimenter.ExpertSetup: the model with the classifiers.
m_ModelDatasets - Variable in class meka.gui.experimenter.BasicSetup: the model with the datasets.
m_ModelMeasurement - Variable in class meka.gui.experimenter.Statistics: the model for the measurement statistics.
m_ModelMeasurementKey - Variable in class meka.gui.experimenter.Statistics: the model for the keys of the measurement statistics.
m_ModelRaw - Variable in class meka.gui.experimenter.Statistics: the model for the raw statistics.
m_Modified - Variable in class meka.gui.experimenter.AbstractSetupTab: whether the setup has been modified.
m_MouseListener - Variable in class meka.gui.core.SortableAndSearchableWrapperTableModel: the mouse listener in use.
m_MULAN - Variable in class meka.classifiers.multilabel.MULAN
m_MultiClassifiers - Variable in class meka.classifiers.multilabel.BR
m_MultiClassifiers - Variable in class meka.classifiers.multilabel.BRq
m_N - Variable in class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
m_N - Variable in class meka.classifiers.multilabel.PS
m_N - Variable in class meka.filters.multilabel.SuperNodeFilter
m_Notes - Variable in class meka.experiment.DefaultExperiment: the notes.
m_Notes - Variable in class meka.gui.experimenter.BasicSetup: the notes.
m_Notes - Variable in class meka.gui.experimenter.ExpertSetup: the notes.
m_NotificationEnabled - Variable in class meka.gui.dataviewer.DataTableModel: whether notfication is enabled
m_NumClasses - Variable in class meka.classifiers.multilabel.CCq: The number of classes
m_NumFolds - Variable in class meka.experiment.evaluators.CrossValidation: the number of folds.
m_NumIterations - Variable in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
m_NumThreads - Variable in class meka.experiment.evaluators.CrossValidation: the number of threads to use for parallel execution.
m_NumThreads - Variable in class meka.experiment.evaluators.RepeatedRuns: the number of threads to use for parallel execution.
m_O - Variable in class meka.classifiers.multilabel.PMCC
m_OkButton - Variable in class meka.gui.dataviewer.DataViewerDialog: Click to activate the current set parameters
m_Option - Variable in class meka.gui.core.ApprovalDialog: the option selected by the user (CANCEL_OPTION, APPROVE_OPTION).
m_Ordered - Variable in class meka.gui.core.ResultHistory: the ordered list of results.
m_Owner - Variable in class meka.gui.core.MaximizationFixWindowListener: the owning window.
m_Owner - Variable in class meka.gui.experimenter.AbstractExperimenterTab: the owning experimenter.
m_Owner - Variable in class meka.gui.experimenter.menu.AbstractExperimenterMenuItem: the experimenter the menu item belongs to.
m_Owner - Variable in class meka.gui.explorer.AbstractExplorerTab: the Explorer instance this tab belongs to.
m_Owner - Variable in class meka.gui.explorer.AbstractResultHistoryPlugin: the tab this plugin belongs to (for accessing the session).
m_Owner - Variable in class meka.gui.explorer.AbstractThreadedExplorerTab.WorkerThread: the tab that this thread belongs to.
m_P - Variable in class meka.classifiers.multilabel.PS
m_P - Variable in class meka.filters.multilabel.SuperNodeFilter
m_PanelAttributes - Variable in class meka.gui.explorer.PreprocessTab: Panel to let the user toggle attributes.
m_PanelAttributeSummary - Variable in class meka.gui.explorer.PreprocessTab: Displays summary stats on the selected attribute
m_PanelBookmarks - Variable in class meka.gui.choosers.MekaFileChooser: the bookmarks.
m_PanelButtons - Variable in class meka.gui.core.ApprovalDialog: the buttons panel.
m_PanelButtons - Variable in class meka.gui.core.MekaPanelWithButtons: the panel containing the buttons.
m_PanelClassAttributes - Variable in class meka.gui.explorer.PreprocessTab: Panel to let the user select the class attributes.
m_PanelContent - Variable in class meka.gui.core.ApprovalDialog: the content panel.
m_PanelDataSummary - Variable in class meka.gui.explorer.PreprocessTab: Displays simple stats on the working instances
m_PanelFile - Variable in class meka.gui.modelviewer.ModelViewer: the panel for the file.
m_PanelGOE - Variable in class meka.gui.explorer.ClassifyTab: the panel for the GOE.
m_PanelIcon - Variable in class meka.gui.core.StatusBar: the panel for the icon.
m_PanelMatrix - Variable in class meka.gui.explorer.VisualizeTab: the panel for visualizing the data.
m_PanelSetup - Variable in class meka.gui.experimenter.AbstractSetupTab: the panel for the setup.
m_PanelSplit - Variable in class meka.gui.explorer.PreprocessTab: the panel for the split view of attributes and selected attribute.
m_PanelText - Variable in class meka.gui.core.StatusBar: the panel for the text.
m_PanelUnsupported - Variable in class meka.gui.experimenter.AbstractSetupTab: the message that experiment cannot be handled.
m_PanelWidgets - Variable in class meka.gui.core.SearchPanel: the panel with the buttons and search box.
m_PanePreview - Variable in class meka.gui.core.MarkdownTextAreaWithPreview: the preview.
m_PaneView - Variable in class meka.gui.core.MarkdownTextPane: for rendering the markdown.
m_ParameterPanel - Variable in class meka.gui.experimenter.BasicSetup: for the parameters.
m_ParameterPanel - Variable in class meka.gui.experimenter.ExpertSetup: the parameters of the experiment.
m_Parameters - Variable in class meka.gui.core.ParameterPanel: the parameters.
m_Parameters - Variable in class meka.gui.events.SearchEvent: the search parameters.
m_Parent - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_Pattern - Variable in class meka.gui.components.AttributeSelectionPanel: Press to enter a perl regular expression for selection
m_Pattern - Variable in class meka.gui.core.SearchParameters: for speeding up the matching of regular expressions.
m_PatternInstances - Variable in class meka.classifiers.multilabel.PLST
m_PatternRegEx - Variable in class meka.gui.components.AttributeSelectionPanel: The current regular expression.
m_Payloads - Variable in class meka.gui.core.ResultHistory: for storing an associated payload (timestamp / object).
m_Payoff - Variable in class meka.classifiers.multilabel.MCC
m_PopupMenuCustomizer - Variable in class meka.gui.core.ResultHistoryList: the popup menu customizer.
m_PreferredDimensionJSpinner - Variable in class meka.gui.core.ParameterPanel: the preferred dimensions for JSpinner components.
m_Prefix - Variable in class meka.gui.core.SearchPanel: the prefix (caption + optional mnemonic indicator).
m_PreserveOrder - Variable in class meka.experiment.evaluators.CrossValidation: whether to preserve the order.
m_PreserveOrder - Variable in class meka.experiment.evaluators.PercentageSplit: whether to preserve the order.
m_Processor - Variable in class meka.gui.core.MarkdownTextAreaWithPreview: the markdown processor.
m_Processor - Variable in class meka.gui.core.MarkdownTextPane: the markdown processor.
m_Properties - Static variable in class meka.gui.core.GUIHelper: the properties.
m_PropertiesFile - Variable in class meka.gui.core.AbstractRecentItemsHandler: the props file to use.
m_PropertyPrefix - Variable in class meka.gui.core.AbstractRecentItemsHandler: the prefix for the properties.
m_Providers - Variable in class meka.experiment.datasetproviders.MultiDatasetProvider: the datasset providers to use.
m_R - Variable in class meka.classifiers.multilabel.CC
m_R - Variable in class meka.classifiers.multilabel.CDN
m_R - Variable in class meka.classifiers.multilabel.NN.AbstractNeuralNet: learning rate
m_R - Variable in class rbms.RBM
m_Random - Variable in class meka.classifiers.multilabel.BRq
m_Random - Variable in class meka.classifiers.multilabel.CCq
m_Randomize - Variable in class meka.gui.explorer.ClassifyTab: the randomize option.
m_ReadOnly - Variable in class meka.gui.dataviewer.DataTableModel: whether the table is read-only
m_RecentFilesHandler - Variable in class meka.gui.dataviewer.DataViewerMainPanel: the recent files handler.
m_RecentFilesHandler - Variable in class meka.gui.experimenter.Experimenter: the recent files handler.
m_RecentFilesHandler - Variable in class meka.gui.explorer.Explorer: the recent files handler.
m_RecentFilesHandler - Variable in class meka.gui.modelviewer.ModelViewer: the recent files handler.
m_RecentItems - Variable in class meka.gui.core.AbstractRecentItemsHandler: the items.
m_RegExp - Variable in class meka.gui.core.SearchParameters: whether to perform regular expression matching.
m_RegExpEnabled - Variable in class meka.gui.core.SearchPanel: whether regular expressions are enabled.
m_RegExpSearch - Variable in class meka.gui.core.SortableAndSearchableWrapperTableModel: whether the search was a regular expression based one.
m_Relation - Variable in class meka.experiment.evaluationstatistics.EvaluationStatistics: the relation name.
m_RemoveAll - Variable in class meka.gui.components.AttributeSelectionPanel: Press to deselect all attributes
m_RendererClasses - Static variable in class meka.gui.modelviewer.renderers.AbstractObjectRenderer: the renderers (classes) currently available.
m_Renderers - Static variable in class meka.gui.modelviewer.renderers.AbstractObjectRenderer: the renderers (classnames) currently available.
m_Reorder - Variable in class meka.filters.unsupervised.attribute.MekaClassAttributes: for reordering the attributes.
m_Result - Variable in class meka.experiment.evaluators.EvaluatorJob: the results.
m_Result - Variable in class meka.gui.dataviewer.DataViewerDialog: the result of the user's action, either OK or CANCEL
m_Result - Variable in class meka.gui.goe.GenericObjectEditorDialog: whether the dialog was cancelled or ok'ed.
m_ResultHistoryList - Variable in class meka.gui.explorer.ClassifyTab: the result history.
m_Results - Variable in class meka.gui.core.ResultHistory: for storing the results (timestamp / result).
m_RowIndex - Variable in class meka.gui.dataviewer.DataTable.RelationalCellEditor: the row index this editor is for
m_Rows - Variable in class meka.gui.core.ParameterPanel: the panels that make up the rows.
m_Running - Variable in class meka.experiment.DefaultExperiment: whether the experiment is running.
m_Running - Variable in class meka.gui.core.StatusBar.Animation: whether the animation is still running.
m_S - Variable in class meka.classifiers.multilabel.BRq: The random generator
m_S - Variable in class meka.classifiers.multilabel.CC
m_S - Variable in class meka.classifiers.multilabel.CCq: The random generator
m_S - Variable in class meka.classifiers.multilabel.CDN
m_S - Variable in class meka.classifiers.multilabel.PS
m_Samples - Variable in class meka.gui.explorer.ClassifyTab: the number of samples for prequential evaluation.
m_SearchListeners - Variable in class meka.gui.core.SearchPanel: the listeners for a search being initiated.
m_SearchPanel - Variable in class meka.gui.experimenter.Statistics: the search panel.
m_SearchString - Variable in class meka.gui.core.SearchParameters: the search string.
m_SearchString - Variable in class meka.gui.core.SortableAndSearchableWrapperTableModel: the string that was searched for.
m_Seed - Variable in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
m_Seed - Variable in class meka.classifiers.multilabel.NN.AbstractNeuralNet: random seed
m_Seed - Variable in class meka.experiment.evaluators.CrossValidation: the seed value.
m_Seed - Variable in class meka.experiment.evaluators.PercentageSplit: the seed value.
m_Seed - Variable in class meka.filters.multilabel.SuperNodeFilter
m_Seed - Variable in class meka.gui.explorer.ClassifyTab: the seed value.
m_Session - Variable in class meka.gui.explorer.AbstractExplorerTab: the session object.
m_Shift - Variable in class meka.classifiers.multilabel.PLST
m_ShowAttributeIndex - Variable in class meka.gui.dataviewer.DataTableModel: whether to display the attribute index in the table header.
m_ShowIndex - Variable in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: whether to show the classifier or an index in the column header.
m_Size - Variable in class meka.classifiers.multilabel.PLST
m_SkipCount - Variable in class meka.experiment.statisticsexporters.SimpleAggregate: whether to skip the count.
m_SkipMean - Variable in class meka.experiment.statisticsexporters.SimpleAggregate: whether to skip the mean.
m_SkipStdDev - Variable in class meka.experiment.statisticsexporters.SimpleAggregate: whether to skip the stdev.
m_SortAscending - Variable in class meka.gui.core.SortableAndSearchableWrapperTableModel: whether sorting is ascending or descending.
m_SortColumn - Variable in class meka.gui.core.SortableAndSearchableWrapperTableModel: the sort column.
m_SortedIndices - Variable in class meka.gui.core.SortableAndSearchableWrapperTableModel: the mapping between displayed and actual index.
m_SortNewTableModel - Variable in class meka.gui.core.SortableAndSearchableTable: whether to automatically sort table models that get set via setModel.
m_SpinnerNumFolds - Variable in class meka.gui.experimenter.BasicSetup: the number of folds.
m_SpinnerNumRuns - Variable in class meka.gui.experimenter.BasicSetup: the number of runs.
m_SplitPercentage - Variable in class meka.gui.explorer.ClassifyTab: the percentage split.
m_Stage - Variable in class meka.experiment.events.ExecutionStageEvent: the stage.
m_Statistics - Variable in class meka.experiment.DefaultExperiment: the collected statistics.
m_Statistics - Variable in class meka.experiment.evaluationstatistics.InMemory: the collected statistics.
m_Statistics - Variable in class meka.experiment.evaluationstatistics.KeyValuePairs: the statistics so far.
m_Statistics - Variable in class meka.experiment.events.StatisticsNotificationEvent: the statistics.
m_Statistics - Variable in class meka.experiment.statisticsexporters.InMemory: the statistics.
m_Statistics - Variable in class meka.gui.core.EvaluationStatisticsTableModel: the underlying statistics.
m_Statistics - Variable in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: the underlying statistics.
m_Statistics - Variable in class meka.gui.experimenter.Statistics: the collected statistics.
m_StatisticsHandler - Variable in class meka.experiment.DefaultExperiment: the statistics handler.
m_StatisticsNotificationListeners - Variable in class meka.experiment.DefaultExperiment: the listeners for statistics.
m_StatusBar - Variable in class meka.gui.experimenter.Experimenter: the statusbar to use.
m_StatusBar - Variable in class meka.gui.explorer.Explorer: the statusbar to use.
m_Stopped - Variable in class meka.experiment.evaluators.AbstractEvaluator: whether the evaluation got stopped.
m_Stopping - Variable in class meka.experiment.DefaultExperiment: whether the experiment is stopping.
m_SuffixCount - Variable in class meka.experiment.statisticsexporters.SimpleAggregate: the count suffix.
m_Suffixes - Variable in class meka.gui.core.ResultHistory: for storing the suffixes for the index (timestamp / suffix).
m_SuffixMean - Variable in class meka.experiment.statisticsexporters.SimpleAggregate: the mean suffix.
m_SuffixStdDev - Variable in class meka.experiment.statisticsexporters.SimpleAggregate: the stdev suffix.
m_Support - Variable in class meka.classifiers.multilabel.incremental.PSUpdateable
m_TabbedPane - Variable in class meka.gui.core.MarkdownTextAreaWithPreview: the tabbed pane.
m_TabbedPane - Variable in class meka.gui.dataviewer.DataViewerMainPanel
m_TabbedPane - Variable in class meka.gui.experimenter.Experimenter: the tabbed pane for the various panels.
m_TabbedPane - Variable in class meka.gui.experimenter.Statistics: the tabbed pane for the statistics.
m_TabbedPane - Variable in class meka.gui.explorer.Explorer: the tabbed pane for the various panels.
m_TabbedPane - Variable in class meka.gui.modelviewer.ModelViewer: the tabbed pane for displaying the content of the files.
m_Table - Variable in class meka.gui.components.AttributeSelectionPanel: The table displaying attribute names and selection status
m_Table - Variable in class meka.gui.core.JTableHelper: the table to work with.
m_TableAggregated - Variable in class meka.gui.experimenter.Statistics: the table for the aggregated statistics.
m_TableHelper - Variable in class meka.gui.core.MekaTable: for setting the optimal column width.
m_TableMeasurement - Variable in class meka.gui.experimenter.Statistics: the table for the measurement statistics.
m_TableMeasurementKey - Variable in class meka.gui.experimenter.Statistics: the table for the keys of the measurement statistics.
m_TableRaw - Variable in class meka.gui.experimenter.Statistics: the table for the raw statistics.
m_Tabs - Variable in class meka.gui.experimenter.Experimenter: the tabs.
m_Tabs - Variable in class meka.gui.explorer.Explorer: the tabs.
m_Task - Variable in class meka.gui.explorer.AbstractThreadedExplorerTab: the thread for running tasks.
m_Templates - Variable in class meka.classifiers.multitarget.CR
m_TestInstances - Variable in class meka.gui.explorer.ClassifyTab: the test Instances.
m_TextArea - Variable in class meka.gui.experimenter.LogTab: the panel for visualizing the data.
m_TextArea - Variable in class meka.gui.explorer.LogTab: the panel for visualizing the data.
m_TextAreaResults - Variable in class meka.gui.explorer.ClassifyTab: the text area for displaying the results.
m_TextCode - Variable in class meka.gui.core.MarkdownTextAreaWithPreview: the text area for writing markdown code.
m_TextFolds - Variable in class meka.gui.explorer.ClassifyTabOptions: the number of folds for CV.
m_TextMarkdown - Variable in class meka.gui.core.MarkdownDialog: the markdown widget.
m_TextPercentage - Variable in class meka.gui.experimenter.BasicSetup: the percentage for the percentage split.
m_TextSamples - Variable in class meka.gui.explorer.ClassifyTabOptions: the number of samples for incremental evaluation.
m_TextSearch - Variable in class meka.gui.core.SearchPanel: the text field for entering the search text.
m_TextSeed - Variable in class meka.gui.explorer.ClassifyTabOptions: the text field for the seed value.
m_TextSplitPercentage - Variable in class meka.gui.explorer.ClassifyTabOptions: the text field for split percentage.
m_TextTOP - Variable in class meka.gui.explorer.ClassifyTabOptions: the threshold option.
m_TextVOP - Variable in class meka.gui.explorer.ClassifyTabOptions: the verbosity option.
m_Threshold - Variable in class meka.experiment.evaluators.CrossValidation: the threshold option.
m_Threshold - Variable in class meka.experiment.evaluators.PercentageSplit: the threshold option.
m_ToggleRandomize - Variable in class meka.gui.explorer.ClassifyTabOptions: for randomizing.
m_TOP - Variable in class meka.gui.explorer.ClassifyTab: the threshold option.
m_TrainPercentage - Variable in class meka.experiment.evaluators.PercentageSplit: percentage to use for training.
m_Undo - Variable in class meka.gui.explorer.Explorer: the undo list.
m_UndoButton - Variable in class meka.gui.dataviewer.DataViewerDialog: Click to undo the last action
m_UndoEnabled - Variable in class meka.gui.dataviewer.DataTableModel: whether undo is active
m_UndoList - Variable in class meka.gui.dataviewer.DataTableModel: the undo list (contains temp.
m_UnMaximizedBounds - Variable in class meka.gui.core.MaximizationFixWindowListener: the unmaximized size/location.
m_UpperRuns - Variable in class meka.experiment.evaluators.RepeatedRuns: the upper number of runs (included).
m_UseOptimalColumnWidths - Variable in class meka.gui.core.SortableAndSearchableTable: whether to automatically set optimal column widths.
m_v - Variable in class meka.classifiers.multilabel.PLST
m_Value - Variable in class meka.gui.core.SortableAndSearchableWrapperTableModel.SortContainer: the value to sort.
m_Verbosity - Variable in class meka.experiment.evaluators.CrossValidation: the verbosity option.
m_Verbosity - Variable in class meka.experiment.evaluators.PercentageSplit: the verbosity option.
m_VOP - Variable in class meka.gui.explorer.ClassifyTab: the verbosity option.
m_Wait - Variable in class meka.gui.core.MaximizationFixWindowListener: the wait period in msec.
m_Width - Variable in class meka.classifiers.multilabel.CDT
m_Width - Variable in class meka.classifiers.multilabel.CT
main(String[]) - Static method in class meka.classifiers.multilabel.BCC
main(String[]) - Static method in class meka.classifiers.multilabel.BPNN
main(String[]) - Static method in class meka.classifiers.multilabel.BR
main(String[]) - Static method in class meka.classifiers.multilabel.BRq
main(String[]) - Static method in class meka.classifiers.multilabel.cc.CNode: Main - run some tests.
main(String[]) - Static method in class meka.classifiers.multilabel.CC
main(String[]) - Static method in class meka.classifiers.multilabel.CCq
main(String[]) - Static method in class meka.classifiers.multilabel.CDN
main(String[]) - Static method in class meka.classifiers.multilabel.CDT
main(String[]) - Static method in class meka.classifiers.multilabel.CT
main(String[]) - Static method in class meka.classifiers.multilabel.DBPNN
main(String[]) - Static method in class meka.classifiers.multilabel.FW
main(String[]) - Static method in class meka.classifiers.multilabel.HASEL
main(String[]) - Static method in class meka.classifiers.multilabel.incremental.BRUpdateable
main(String[]) - Static method in class meka.classifiers.multilabel.incremental.CCUpdateable
main(String[]) - Static method in class meka.classifiers.multilabel.incremental.MajorityLabelsetUpdateable
main(String[]) - Static method in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable
main(String[]) - Static method in class meka.classifiers.multilabel.incremental.PSUpdateable
main(String[]) - Static method in class meka.classifiers.multilabel.incremental.RTUpdateable
main(String[]) - Static method in class meka.classifiers.multilabel.LC
main(String[]) - Static method in class meka.classifiers.multilabel.MajorityLabelset
main(String[]) - Static method in class meka.classifiers.multilabel.Maniac: Main method for testing.
main(String[]) - Static method in class meka.classifiers.multilabel.MCC
main(String[]) - Static method in class meka.classifiers.multilabel.meta.BaggingML
main(String[]) - Static method in class meka.classifiers.multilabel.meta.BaggingMLdup
main(String[]) - Static method in class meka.classifiers.multilabel.meta.CM
main(String[]) - Static method in class meka.classifiers.multilabel.meta.DeepML
main(String[]) - Static method in class meka.classifiers.multilabel.meta.EM
main(String[]) - Static method in class meka.classifiers.multilabel.meta.EnsembleML
main(String[]) - Static method in class meka.classifiers.multilabel.meta.FilteredClassifier
main(String[]) - Static method in class meka.classifiers.multilabel.meta.MBR
main(String[]) - Static method in class meka.classifiers.multilabel.meta.RandomSubspaceML
main(String[]) - Static method in class meka.classifiers.multilabel.meta.SubsetMapper
main(String[]) - Static method in class meka.classifiers.multilabel.MLCBMaD: Main method for testing.
main(String[]) - Static method in class meka.classifiers.multilabel.MULAN
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast: Main method for testing this class.
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.SparseVector
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.ST: Unit tests the ST data type.
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.WARAM
main(String[]) - Static method in class meka.classifiers.multilabel.neurofuzzy.WvARAM: Main method for testing this class.
main(String[]) - Static method in class meka.classifiers.multilabel.PCC
main(String[]) - Static method in class meka.classifiers.multilabel.PLST: Main method for testing.
main(String[]) - Static method in class meka.classifiers.multilabel.PMCC
main(String[]) - Static method in class meka.classifiers.multilabel.PS
main(String[]) - Static method in class meka.classifiers.multilabel.PSt
main(String[]) - Static method in class meka.classifiers.multilabel.RAkEL
main(String[]) - Static method in class meka.classifiers.multilabel.RAkELd
main(String[]) - Static method in class meka.classifiers.multilabel.RT
main(String[]) - Static method in class meka.classifiers.multitarget.BCC
main(String[]) - Static method in class meka.classifiers.multitarget.CC
main(String[]) - Static method in class meka.classifiers.multitarget.CCp
main(String[]) - Static method in class meka.classifiers.multitarget.CR
main(String[]) - Static method in class meka.classifiers.multitarget.meta.BaggingMT
main(String[]) - Static method in class meka.classifiers.multitarget.meta.EnsembleMT
main(String[]) - Static method in class meka.classifiers.multitarget.meta.FilteredClassifier
main(String[]) - Static method in class meka.classifiers.multitarget.NSR
main(String[]) - Static method in class meka.classifiers.multitarget.RAkELd
main(String[]) - Static method in class meka.classifiers.multitarget.SCC
main(String[]) - Static method in class meka.core.A: Do some tests.
main(String[]) - Static method in class meka.core.Metrics: Do some tests.
main(String[]) - Static method in class meka.core.MLEvalUtils: Main - can use this function for writing tests during development.
main(String[]) - Static method in class meka.core.MLUtils: For retrieving some dataset statistics on the command line.
main(String[]) - Static method in class meka.core.PropsUtils: Allows some basic operations on properties files: read <props>- reads the specified props file and outputs it, e.g., "read meka/gui/goe/MekaEditors.props" find <props>- finds all occurrences of the specified props file and outputs them, e.g., "find meka/gui/goe/MekaEditors.props"
main(String[]) - Static method in class meka.core.StatUtils: Main - do some tests.
main(String[]) - Static method in class meka.core.Version: Outputs the version on stdout.
main(String[]) - Static method in class meka.filters.multilabel.SuperNodeFilter
main(String[]) - Static method in class meka.filters.unsupervised.attribute.MekaClassAttributes: runs the filter with the given arguments.
main(String[]) - Static method in class meka.gui.choosers.EvaluationStatisticsExporterFileChooser: Only for testing.
main(String[]) - Static method in class meka.gui.choosers.EvaluationStatisticsFileChooser: Only for testing.
main(String[]) - Static method in class meka.gui.choosers.ExperimentFileChooser: Only for testing.
main(String[]) - Static method in class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser: Only for testing.
main(String[]) - Static method in class meka.gui.components.AttributeSelectionPanel: Tests the attribute selection panel from the command line.
main(String[]) - Static method in class meka.gui.core.MarkdownTextAreaWithPreview: For testing only.
main(String[]) - Static method in class meka.gui.core.MarkdownTextPane: For testing only.
main(String[]) - Static method in class meka.gui.dataviewer.DataViewer: shows the frame and it tries to load all the arff files that were provided as arguments.
main(String[]) - Static method in class meka.gui.experimenter.Experimenter: Starts the GUI.
main(String[]) - Static method in class meka.gui.explorer.Explorer: Starts the GUI.
main(String[]) - Static method in class meka.gui.goe.GenericObjectEditor: For testing only.
main(String[]) - Static method in class meka.gui.goe.GenericObjectEditorDialog: For testing only.
main(String[]) - Static method in class meka.gui.goe.GenericPropertiesCreator: For testing only.
main(String[]) - Static method in class meka.gui.guichooser.GUIChooser: Starts the GUI.
main(String[]) - Static method in class meka.gui.modelviewer.ModelViewer: Starts the GUI.
main(String[]) - Static method in class rbms.RBM: Main - do some test routines.
MajorityLabelset - Class in meka.classifiers.multilabel: MajorityLabelset.java - The most simplest multi-label classifier.
MajorityLabelset() - Constructor for class meka.classifiers.multilabel.MajorityLabelset
MajorityLabelsetUpdateable - Class in meka.classifiers.multilabel.incremental: MajorityLabelsetUpdateable.java - Updateable version of MajorityLabelset.
MajorityLabelsetUpdateable() - Constructor for class meka.classifiers.multilabel.incremental.MajorityLabelsetUpdateable
make() - Method in class meka.classifiers.multilabel.cc.Trellis
make_sequence(int) - Static method in class meka.core.A: Make Sequence - Given L, generate and return new int[]{0,1,2,3,...,L-1}.
make_sequence(int, int) - Static method in class meka.core.A: Make Sequence - Generate and return new int[]{start,start+1,...,end-2,end-1}.
makeCopies(MultiLabelClassifier, int) - Static method in class meka.classifiers.multilabel.AbstractMultiLabelClassifier: Creates a given number of deep copies of the given multi-label classifier using serialization.
makeCopies(MultiLabelClassifier, int) - Static method in class meka.classifiers.multilabel.ProblemTransformationMethod: Creates a given number of deep copies of the given multi-label classifier using serialization.
makeLabelSetMap(Instances) - Static method in class meka.core.PSUtils
makePartitionDataset(Instances, int[]) - Static method in class meka.core.SuperLabelUtils: Make Partition Dataset - out of dataset D, on indices part[].
makePartitionDataset(Instances, int[], int, int) - Static method in class meka.core.SuperLabelUtils: Make Partition Dataset - out of dataset D, on indices part[].
makeW(int, int, Random) - Static method in class rbms.RBM: Make W matrix of dimensions d+1 and h+1 (+1 for biases).
makeW(int, int) - Method in class rbms.RBM
Maniac - Class in meka.classifiers.multilabel: Maniac - Multi-lAbel classificatioN using AutoenCoders.
Maniac() - Constructor for class meka.classifiers.multilabel.Maniac
margDepMatrix(Instances, String) - Static method in class meka.core.StatUtils: MargDepMatrix - Get an Unconditional Depndency Matrix.
MarkdownDialog - Class in meka.gui.core: Dialog for editing/previewing Markdown.
MarkdownDialog() - Constructor for class meka.gui.core.MarkdownDialog: Creates a modeless dialog without a title and without a specified Frame owner.
MarkdownDialog(Dialog) - Constructor for class meka.gui.core.MarkdownDialog: Creates a modeless dialog without a title with the specified Dialog as its owner.
MarkdownDialog(Dialog, Dialog.ModalityType) - Constructor for class meka.gui.core.MarkdownDialog: Creates a dialog with the specified owner Dialog and modality.
MarkdownDialog(Dialog, String) - Constructor for class meka.gui.core.MarkdownDialog: Creates a modeless dialog with the specified title and with the specified owner dialog.
MarkdownDialog(Dialog, String, Dialog.ModalityType) - Constructor for class meka.gui.core.MarkdownDialog: Creates a dialog with the specified title, modality and the specified owner Dialog.
MarkdownDialog(Frame) - Constructor for class meka.gui.core.MarkdownDialog: Creates a modeless dialog without a title with the specified Frame as its owner.
MarkdownDialog(Frame, boolean) - Constructor for class meka.gui.core.MarkdownDialog: Creates a dialog with the specified owner Frame, modality and an empty title.
MarkdownDialog(Frame, String) - Constructor for class meka.gui.core.MarkdownDialog: Creates a modeless dialog with the specified title and with the specified owner frame.
MarkdownDialog(Frame, String, boolean) - Constructor for class meka.gui.core.MarkdownDialog: Creates a dialog with the specified owner Frame, modality and title.
MarkdownTextAreaWithPreview - Class in meka.gui.core: Text area for handling Markdown with code and preview tabs.
MarkdownTextAreaWithPreview() - Constructor for class meka.gui.core.MarkdownTextAreaWithPreview
MarkdownTextPane - Class in meka.gui.core: Renders Markdown text.
MarkdownTextPane() - Constructor for class meka.gui.core.MarkdownTextPane
matches(String) - Method in class meka.gui.core.SearchParameters: Matches the search string against the provided string.
matches(Integer) - Method in class meka.gui.core.SearchParameters: Matches the integer against the search string if it represents an integer.
matches(Double) - Method in class meka.gui.core.SearchParameters: Matches the double against the search string if it represents an double.
matrixToInstances(Matrix, Instances) - Static method in class meka.core.MatrixUtils: Helper method that transforms a Matrix object to an Instances object.
MatrixUtils - Class in meka.core: Utility functions relating to matrices.
MatrixUtils() - Constructor for class meka.core.MatrixUtils
max() - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Returns the largest key in the symbol table.
max(double[]) - Static method in class meka.core.A: Max
max(int[]) - Static method in class meka.core.A: Max
MAX_ROWS - Static variable in class meka.gui.core.JTableHelper: the maximum number of rows to use for calculation.
MaximizationFixWindowListener - Class in meka.gui.core: Provides a work-around for platforms where the maximization of frames (eg JFrame) results in strange behaviors.
MaximizationFixWindowListener(Frame, boolean, int) - Constructor for class meka.gui.core.MaximizationFixWindowListener: Initializes the listener.
MaximizationFixWindowListener(Frame, boolean, int, boolean) - Constructor for class meka.gui.core.MaximizationFixWindowListener: Initializes the listener.
maxIndices(double[][]) - Static method in class meka.core.MatrixUtils: returns argmax_{j,k} M[j][k]
maxItem(HashMap<?, Double>) - Static method in class meka.core.MLUtils: maxItem - argmax function for a HashMap
maxValue - Variable in class meka.classifiers.multilabel.MajorityLabelset
MBR - Class in meka.classifiers.multilabel.meta: MBR.java - Meta BR: BR stacked with feature outputs into another BR.
MBR() - Constructor for class meka.classifiers.multilabel.meta.MBR
MCC - Class in meka.classifiers.multilabel: MCC.java - CC with Monte Carlo optimisation.
MCC() - Constructor for class meka.classifiers.multilabel.MCC
meanSquaredError(double[][], double[][]) - Static method in class meka.core.MatrixUtils
MeasurementEvaluationStatisticsExporterFileChooser - Class in meka.gui.choosers: File chooser for evaluation statistics exporters for a single measurement (only writers, no readers!).
MeasurementEvaluationStatisticsExporterFileChooser() - Constructor for class meka.gui.choosers.MeasurementEvaluationStatisticsExporterFileChooser
MeasurementEvaluationStatisticsTableModel - Class in meka.gui.core: Table model for displaying a Dataset X Classifier table for a specific measurement.
MeasurementEvaluationStatisticsTableModel() - Constructor for class meka.gui.core.MeasurementEvaluationStatisticsTableModel: Initializes the model with no statistics.
MeasurementEvaluationStatisticsTableModel(List<EvaluationStatistics>, String, boolean) - Constructor for class meka.gui.core.MeasurementEvaluationStatisticsTableModel: Initializes the model with the statistics.
measurements(List<EvaluationStatistics>, MultiLabelClassifier, Instances, String) - Static method in class meka.experiment.evaluationstatistics.EvaluationStatisticsUtils: Returns all the values of a specific measurement for the specified classifier/dataset combination.
measurements(List<EvaluationStatistics>, String, String, String) - Static method in class meka.experiment.evaluationstatistics.EvaluationStatisticsUtils: Returns all the values of a specific measurement for the specified classifier/dataset combination.
measurements(List<EvaluationStatistics>) - Static method in class meka.experiment.evaluationstatistics.EvaluationStatisticsUtils: Returns all available measurements.
measurementTipText() - Method in class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter: Describes this property.
measurementTipText() - Method in interface meka.experiment.statisticsexporters.FileBasedMeasurementEvaluationStatisticsExporter: Describes this property.
meka.classifiers.multilabel - package meka.classifiers.multilabel
meka.classifiers.multilabel.cc - package meka.classifiers.multilabel.cc
meka.classifiers.multilabel.incremental - package meka.classifiers.multilabel.incremental
meka.classifiers.multilabel.incremental.meta - package meka.classifiers.multilabel.incremental.meta
meka.classifiers.multilabel.meta - package meka.classifiers.multilabel.meta
meka.classifiers.multilabel.neurofuzzy - package meka.classifiers.multilabel.neurofuzzy
meka.classifiers.multilabel.NN - package meka.classifiers.multilabel.NN
meka.classifiers.multitarget - package meka.classifiers.multitarget
meka.classifiers.multitarget.meta - package meka.classifiers.multitarget.meta
meka.core - package meka.core
meka.events - package meka.events
meka.experiment - package meka.experiment
meka.experiment.datasetproviders - package meka.experiment.datasetproviders
meka.experiment.evaluationstatistics - package meka.experiment.evaluationstatistics
meka.experiment.evaluators - package meka.experiment.evaluators
meka.experiment.events - package meka.experiment.events
meka.experiment.filehandlers - package meka.experiment.filehandlers
meka.experiment.statisticsexporters - package meka.experiment.statisticsexporters
meka.filters.multilabel - package meka.filters.multilabel
meka.filters.unsupervised.attribute - package meka.filters.unsupervised.attribute
meka.gui.choosers - package meka.gui.choosers
meka.gui.components - package meka.gui.components
meka.gui.core - package meka.gui.core
meka.gui.dataviewer - package meka.gui.dataviewer
meka.gui.events - package meka.gui.events
meka.gui.experimenter - package meka.gui.experimenter
meka.gui.experimenter.menu - package meka.gui.experimenter.menu
meka.gui.explorer - package meka.gui.explorer
meka.gui.explorer.classify - package meka.gui.explorer.classify
meka.gui.goe - package meka.gui.goe
meka.gui.guichooser - package meka.gui.guichooser
meka.gui.modelviewer - package meka.gui.modelviewer
meka.gui.modelviewer.renderers - package meka.gui.modelviewer.renderers
meka2mulan(Instances, int) - Static method in class meka.core.F: meka2mulan - Move L label attributes from the beginning to end of attribute space of an Instances.
meka2mulan(Instance, int) - Static method in class meka.core.F: meka2mulan - Move L label attributes from the beginning to end of attribute space of an Instance.
MEKA_CREATOR_FILE - Static variable in class meka.gui.goe.GenericPropertiesCreator: The name of the properties file to use as a template.
MEKA_EDITOR_PROPERTIES - Static variable in class meka.gui.goe.GenericObjectEditor: Contains the editor properties.
MEKA_GUIEDITORS_PROPERTY_FILE - Static variable in class meka.gui.goe.GenericObjectEditor: the properties files containing the class/editor mappings.
MekaClassAttributes - Class in meka.filters.unsupervised.attribute: Reorders attributes for MEKA to use as class attributes.
MekaClassAttributes() - Constructor for class meka.filters.unsupervised.attribute.MekaClassAttributes
MekaDialog - Class in meka.gui.core: A dialog that loads the size and location from the props file automatically.
MekaDialog() - Constructor for class meka.gui.core.MekaDialog: Creates a modeless dialog without a title and without a specified Frame owner.
MekaDialog(Dialog) - Constructor for class meka.gui.core.MekaDialog: Creates a modeless dialog without a title with the specified Dialog as its owner.
MekaDialog(Dialog, Dialog.ModalityType) - Constructor for class meka.gui.core.MekaDialog: Creates a dialog with the specified owner Dialog and modality.
MekaDialog(Dialog, String) - Constructor for class meka.gui.core.MekaDialog: Creates a modeless dialog with the specified title and with the specified owner dialog.
MekaDialog(Dialog, String, Dialog.ModalityType) - Constructor for class meka.gui.core.MekaDialog: Creates a dialog with the specified title, modality and the specified owner Dialog.
MekaDialog(Frame) - Constructor for class meka.gui.core.MekaDialog: Creates a modeless dialog without a title with the specified Frame as its owner.
MekaDialog(Frame, boolean) - Constructor for class meka.gui.core.MekaDialog: Creates a dialog with the specified owner Frame, modality and an empty title.
MekaDialog(Frame, String) - Constructor for class meka.gui.core.MekaDialog: Creates a modeless dialog with the specified title and with the specified owner frame.
MekaDialog(Frame, String, boolean) - Constructor for class meka.gui.core.MekaDialog: Creates a dialog with the specified owner Frame, modality and title.
MekaFileChooser - Class in meka.gui.choosers: A file chooser dialog with directory bookmarks.
MekaFileChooser() - Constructor for class meka.gui.choosers.MekaFileChooser: Constructs a MekaFileChooser pointing to the user's default directory.
MekaFileChooser(String) - Constructor for class meka.gui.choosers.MekaFileChooser: Constructs a MekaFileChooser using the given path.
MekaFileChooser(File) - Constructor for class meka.gui.choosers.MekaFileChooser: Constructs a MekaFileChooser using the given File as the path.
MekaFrame - Class in meka.gui.core: A frame that loads the size and location from the props file automatically.
MekaFrame() - Constructor for class meka.gui.core.MekaFrame: Initializes the frame with no title.
MekaFrame(String) - Constructor for class meka.gui.core.MekaFrame: Initializes the frame with the given title.
MekaFrame(GraphicsConfiguration) - Constructor for class meka.gui.core.MekaFrame: Initializes the frame with no title.
MekaFrame(String, GraphicsConfiguration) - Constructor for class meka.gui.core.MekaFrame: Initializes the frame with the specified title.
MekaPanel - Class in meka.gui.core: Extended JPanel.
MekaPanel() - Constructor for class meka.gui.core.MekaPanel: Initializes the GUI.
MekaPanelWithButtons - Class in meka.gui.core: Panel that offers associated buttons on the right-hand side.
MekaPanelWithButtons() - Constructor for class meka.gui.core.MekaPanelWithButtons
MekaTable - Class in meka.gui.core: A specialized JTable that allows double-clicking on header for resizing to optimal width.
MekaTable() - Constructor for class meka.gui.core.MekaTable: Constructs a default BaseTable that is initialized with a default data model, a default column model, and a default selection model.
MekaTable(int, int) - Constructor for class meka.gui.core.MekaTable: Constructs a BaseTable with numRows and numColumns of empty cells using DefaultTableModel.
MekaTable(Object[][], Object[]) - Constructor for class meka.gui.core.MekaTable: Constructs a BaseTable to display the values in the two dimensional array, rowData, with column names, columnNames.
MekaTable(Vector, Vector) - Constructor for class meka.gui.core.MekaTable: Constructs a BaseTable to display the values in the Vector of Vectors, rowData, with column names, columnNames.
MekaTable(TableModel) - Constructor for class meka.gui.core.MekaTable: Constructs a BaseTable that is initialized with dm as the data model, a default column model, and a default selection model.
MekaTable(TableModel, TableColumnModel) - Constructor for class meka.gui.core.MekaTable: Constructs a BaseTable that is initialized with dm as the data model, cm as the column model, and a default selection model.
MekaTable(TableModel, TableColumnModel, ListSelectionModel) - Constructor for class meka.gui.core.MekaTable: Constructs a BaseTable that is initialized with dm as the data model, cm as the column model, and sm as the selection model.
MENU_HELP - Static variable in class meka.gui.guichooser.AbstractMenuItemDefinition: "Help", the last menu.
MENU_PROGRAM - Static variable in class meka.gui.guichooser.AbstractMenuItemDefinition: "Program", the first menu.
MENU_TOOLS - Static variable in class meka.gui.guichooser.AbstractMenuItemDefinition: "Tools" menu.
MENU_VISUALIZATION - Static variable in class meka.gui.guichooser.AbstractMenuItemDefinition: "Visualization" menu.
MenuBarProvider - Interface in meka.gui.core: Interface for panels that generate a menu bar.
mergeLabels(Instances, int[][], int, int) - Static method in class meka.filters.multilabel.SuperNodeFilter: Merge Labels - Make a new 'D', with labels made into superlabels, according to partition 'indices', and pruning values 'p' and 'n'.
mergeLabels(Instances, int, int, int) - Static method in class meka.filters.multilabel.SuperNodeFilter: Merge Labels.
MetaProblemTransformationMethod - Class in meka.classifiers.multilabel.meta: MultilabelMetaClassifier.java - For ensembles of multi-label methods.
MetaProblemTransformationMethod() - Constructor for class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
methodTipText() - Method in class meka.classifiers.multilabel.MULAN
Metrics - Class in meka.core: Metrics.java - Evaluation Metrics.
Metrics() - Constructor for class meka.core.Metrics
min() - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Returns the smallest key in the symbol table.
min(int[]) - Static method in class meka.core.A: Minimum
minus(LabelSet) - Method in class meka.core.LabelSet
minus(int[], int[]) - Static method in class meka.core.LabelSet: Minus aka Set Difference, e.g., [3,4,7,9] \ [3,7] = [4,9].
MLCBMaD - Class in meka.classifiers.multilabel: MLC-BMaD - Multi-Label Classification using Boolean Matrix Decomposition.
MLCBMaD() - Constructor for class meka.classifiers.multilabel.MLCBMaD
MLEvalUtils - Class in meka.core: MLEvalUtils - Utility functions for Evaluation.
MLEvalUtils() - Constructor for class meka.core.MLEvalUtils
mlu - Variable in class meka.classifiers.multilabel.incremental.PSUpdateable
MLUtils - Class in meka.core: MLUtils - Helpful functions for dealing with multi-labelled data.
MLUtils() - Constructor for class meka.core.MLUtils
MNEMONIC_INDICATOR - Static variable in class meka.gui.core.GUIHelper: the mnemonic character indicator.
mode(int[]) - Static method in class meka.core.A: Mode
model - Variable in class meka.core.Result
ModelViewer - Class in meka.gui.modelviewer: Simple viewer for serialized model files.
ModelViewer() - Constructor for class meka.gui.modelviewer.ModelViewer
ModelViewerDefinition - Class in meka.gui.guichooser: Launches the Model Viewer.
ModelViewerDefinition() - Constructor for class meka.gui.guichooser.ModelViewerDefinition
MOMENTUM - Variable in class rbms.RBM
momentumTipText() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
mostCommonCombination(Instances) - Static method in class meka.core.MLUtils: MostCommonCombination - Most common label combination in D.
mostCommonCombination(Instances, int) - Static method in class meka.core.MLUtils: MostCommonCombination - Most common label combination in D (of L labels).
mouseClicked(MouseEvent) - Method in class meka.gui.dataviewer.DataPanel: Invoked when a mouse button has been pressed and released on a component
mouseEntered(MouseEvent) - Method in class meka.gui.dataviewer.DataPanel: Invoked when the mouse enters a component.
mouseExited(MouseEvent) - Method in class meka.gui.dataviewer.DataPanel: Invoked when the mouse exits a component
mousePressed(MouseEvent) - Method in class meka.gui.dataviewer.DataPanel: Invoked when a mouse button has been pressed on a component
mouseReleased(MouseEvent) - Method in class meka.gui.dataviewer.DataPanel: Invoked when a mouse button has been released on a component.
MouseUtils - Class in meka.gui.core: Helper class for mouse events.
MouseUtils() - Constructor for class meka.gui.core.MouseUtils
mTipText() - Method in class meka.classifiers.multilabel.PMCC
mTipText() - Method in class meka.classifiers.multilabel.RAkEL
MULAN - Class in meka.classifiers.multilabel: MULAN.java - A wrapper for MULAN classifiers MULAN.
MULAN() - Constructor for class meka.classifiers.multilabel.MULAN
mulan2meka(Instances, int) - Static method in class meka.core.F: mulan2meka - Move label attributes from the End to the Beginning of attribute space (MULAN format to MEKA format).
MultiDatasetProvider - Class in meka.experiment.datasetproviders: Combines multiple dataset providers.
MultiDatasetProvider() - Constructor for class meka.experiment.datasetproviders.MultiDatasetProvider
MultiExporter - Class in meka.experiment.statisticsexporters: Exports the statistics using multiple exporters.
MultiExporter() - Constructor for class meka.experiment.statisticsexporters.MultiExporter
MultiLabelClassifier - Interface in meka.classifiers.multilabel: Interface for multi-label classifiers.
MultiLabelClassifierRenderer - Class in meka.gui.modelviewer.renderers: Renders MultiLabelClassifier objects.
MultiLabelClassifierRenderer() - Constructor for class meka.gui.modelviewer.renderers.MultiLabelClassifierRenderer
MultiLabelClassifierThreaded - Interface in meka.classifiers.multilabel: Interface for multi-label classifiers.
MultiLabelDrawable - Interface in meka.core: Interface for classes that generate graphs per label.
multiply(double[], double) - Static method in class meka.core.A: Multiply a vector with a constant.
multiply(double[], double[]) - Static method in class meka.core.A: Multiply two vectors (element-wise) together.
multiply(double[][], double) - Static method in class meka.core.MatrixUtils: Multiply - multiply each value in A[][] by constant K.
multiply(double[][], double[][]) - Static method in class meka.core.MatrixUtils: Multiply - multiply matrices A and B together.
multiply(double[], double[]) - Static method in class meka.core.MatrixUtils: Multiply - multiply vectors a and b together.
multiplyTranspose(double[][], double[][]) - Static method in class meka.core.MatrixUtils
MultiTargetCapable - Interface in meka.classifiers.multilabel: MultiTargetCapable.java - A multi-label Classifier that can also handle generic multi-target data.
MultiTargetClassifier - Interface in meka.classifiers.multitarget: MultiTargetClassifier.java - A Multi-Target (i.e., Multi-Output / Multi-Dimensional) Classifier.

N

nearestSubset(double[]) - Method in class meka.classifiers.multilabel.meta.SubsetMapper
neuronsactivated - Variable in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkClass
neuronsactivity - Variable in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkClass
neuronsActivityFileNameTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
neuronsActivityTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
newConverterFileChooser() - Static method in class meka.gui.core.GUIHelper: Returns a new instance of a filechooser for datasets including the bookmarks panel.
newFactory() - Method in class meka.gui.core.FileChooserBookmarksPanel: Creates a new instance of the factory.
newFileChooser() - Static method in class meka.gui.core.GUIHelper: Returns a new instance of a filechooser including the bookmarks panel.
Newick - Static variable in interface meka.core.MultiLabelDrawable
newPropertiesHandler() - Method in class meka.gui.core.FileChooserBookmarksPanel.FileChooserBookmarksFactory: Returns a new instance of the properties handler to be used.
newSetup(Class) - Method in class meka.gui.experimenter.Experimenter: Instantiates an experiment from the provided class.
next() - Method in interface meka.experiment.datasetproviders.DatasetProvider: Returns the next dataset.
next() - Method in class meka.experiment.datasetproviders.LocalDatasetProvider: Returns the next dataset.
next() - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Returns the next dataset.
nextIteration(IterationNotificationEvent) - Method in interface meka.experiment.events.IterationNotificationListener: Gets called if there is a new iteration (classifier/dataset combination) occurring in the experiment.
nextIteration(IterationNotificationEvent) - Method in class meka.gui.experimenter.Experimenter: Gets called if there is a new iteration (classifier/dataset combination) occurring in the experiment.
nnz() - Method in class meka.classifiers.multilabel.neurofuzzy.SparseVector
NO_FILE_LOADED - Static variable in class meka.gui.modelviewer.ModelViewer
nodes - Variable in class meka.classifiers.multilabel.CC
nodes - Variable in class meka.classifiers.multilabel.CDT
norm() - Method in class meka.classifiers.multilabel.neurofuzzy.SparseVector
norm(double[]) - Static method in class meka.core.A: Normalize (to sum to 1)
NOT_DRAWABLE - Static variable in interface meka.core.MultiLabelDrawable
notesTipText() - Method in class meka.experiment.DefaultExperiment: Describes this property.
notifyExecutionStageListeners(ExecutionStageEvent.Stage) - Method in class meka.experiment.DefaultExperiment: Notifies all listeners of a new execution stage.
notifyIterationNotificationListeners(MultiLabelClassifier, Instances) - Method in class meka.experiment.DefaultExperiment: Notifies all listeners of a new classifier/dataset combination.
notifyListener() - Method in class meka.gui.dataviewer.DataPanel: notfies all listener of the change
notifyListener(TableModelEvent) - Method in class meka.gui.dataviewer.DataSortedTableModel: notfies all listener of the change of the model
notifyListener(TableModelEvent) - Method in class meka.gui.dataviewer.DataTableModel: notfies all listener of the change of the model
notifyRecentItemListenersOfAdd(T) - Method in class meka.gui.core.AbstractRecentItemsHandler: Notifies the listeners of a item that got added.
notifyRecentItemListenersOfSelect(T) - Method in class meka.gui.core.AbstractRecentItemsHandler: Notifies the listeners of a item that got selected.
notifySearchListeners(SearchEvent) - Method in class meka.gui.core.SearchPanel: Sends out the event to all listeners.
notifyStatisticsNotificationListeners(List<EvaluationStatistics>) - Method in class meka.experiment.DefaultExperiment: Notifies all listeners of a new classifier/dataset combination.
notifyTabsDataChanged(AbstractExplorerTab, Instances) - Method in class meka.gui.explorer.Explorer: Notifies all the tabs that the data has changed.
notifyTabsExperimentChanged(AbstractExperimenterTab, Experiment) - Method in class meka.gui.experimenter.Experimenter: Notifies all the tabs that the experiment has changed.
NSR - Class in meka.classifiers.multitarget: NSR.java - The Nearest Set Relpacement (NSR) method.
NSR() - Constructor for class meka.classifiers.multitarget.NSR
nTipText() - Method in class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
nTipText() - Method in class meka.classifiers.multilabel.PS
numberAutoencoders - Variable in class meka.classifiers.multilabel.Maniac: Number of autoencoders to train, i.e.
numberAutoencodersTipText() - Method in class meka.classifiers.multilabel.Maniac: Gives the tiptext for numberAutoencoders.
numberAutoencodersToolTip() - Method in class meka.classifiers.multilabel.Maniac: Gives the tooltip for numberAutoencoders.
numberOfMissingLabels(int[]) - Static method in class meka.core.Metrics: Helper function for missing values in the labels.
numberOfUniqueCombinations(Instances) - Static method in class meka.core.MLUtils: Get the number of unique label combinations in a dataset
numClasses - Variable in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
numClasses - Variable in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkClass
numFeatures - Variable in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
numFeatures - Variable in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkClass
numFoldsTipText() - Method in class meka.experiment.evaluators.CrossValidation: Describes this property.
numIterationsTipText() - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
numThreadsTipText() - Method in class meka.experiment.evaluators.CrossValidation: Returns the tip text for this property.
numThreadsTipText() - Method in class meka.experiment.evaluators.RepeatedRuns: Returns the tip text for this property.

O

ObjectUtils - Class in meka.core: Helper class for object-related operations.
ObjectUtils() - Constructor for class meka.core.ObjectUtils
ones(int) - Static method in class meka.core.MatrixUtils: Ones - return a vector full of 1s.
open() - Method in class meka.gui.experimenter.Experimenter: Opens an experiment.
open(File, ExperimentFileHandler) - Method in class meka.gui.experimenter.Experimenter: Opens the specified experiment file.
open(File, AbstractFileLoader) - Method in class meka.gui.explorer.Explorer: Opens the specified file.
open() - Method in class meka.gui.explorer.Explorer: Opens a dataset.
open() - Method in class meka.gui.modelviewer.ModelViewer: Prompts the user to select a model file.
open(File) - Method in class meka.gui.modelviewer.ModelViewer: Opens the specified model file.
OpenModel - Class in meka.gui.explorer.classify: Menu item for loading a model from disk.
OpenModel() - Constructor for class meka.gui.explorer.classify.OpenModel
OpenTestData - Class in meka.gui.explorer.classify: Menu item for loading a model from disk.
OpenTestData() - Constructor for class meka.gui.explorer.classify.OpenTestData
optimizeAE - Variable in class meka.classifiers.multilabel.Maniac: Flag to tell if the number of autoencoders should be optimized.
optimizeAETipText() - Method in class meka.classifiers.multilabel.Maniac: Gives the tiptext for optimizeAE.
optimizeAEToolTip() - Method in class meka.classifiers.multilabel.Maniac: Gives the tooltip for OptimizeAE.
OptionalIncrementalEvaluationStatisticsHandler - Interface in meka.experiment.evaluationstatistics: For handlers that support incremental writes but use it as optional feature that can be turned off.
OptionUtils - Class in meka.core: Helper class for option parsing.
OptionUtils() - Constructor for class meka.core.OptionUtils
orderTrellis(Trellis, double[][], Random) - Static method in class meka.classifiers.multilabel.CT: OrderTrellis - order the trellis according to marginal label dependencies.
OS - Class in meka.core: Helper class for operating system related stuff.
OS() - Constructor for class meka.core.OS
oTipText() - Method in class meka.classifiers.multilabel.PMCC
output - Variable in class meka.core.Result

P

P(double[][], int[]) - Static method in class meka.core.StatUtils: P - Empirical prior.
P(double[][], int[], int[]) - Static method in class meka.core.StatUtils: P - Empirical prior.
p(double[][], int, int) - Static method in class meka.core.StatUtils: p - Empirical prior.
p(Instances, int, int) - Static method in class meka.core.StatUtils: p - Empirical prior.
P(double[][], int, int, int, int) - Static method in class meka.core.StatUtils: P - Empirical joint.
P(Instances, int, int, int, int) - Static method in class meka.core.StatUtils: p - Empirical joint.
P(Instances, int[], int[]) - Static method in class meka.core.StatUtils: P - Empirical joint.
P_Accuracy(int[], int[]) - Static method in class meka.core.Metrics: Jaccard Index -- often simply called multi-label 'accuracy'.
P_Accuracy(int[][], int[][]) - Static method in class meka.core.Metrics: Jaccard Index -- often simply called multi-label 'accuracy'.
P_AveragePrecision(int[][], double[][]) - Static method in class meka.core.Metrics
P_AveragePrecision(int[], double[]) - Static method in class meka.core.Metrics: Converts confidences in prediction array to ranking array, and continues with P_AveragePrecision(using ranking array).
P_AveragePrecision(int[], int[]) - Static method in class meka.core.Metrics: Average Precision - computes for each relevant label the percentage of relevant labels among all labels that are ranked before it.
P_ExactMatch(int[][], int[][]) - Static method in class meka.core.Metrics: Exact Match, i.e., 1 - [0/1 Loss].
P_FalseNegatives(int[], int[]) - Static method in class meka.core.Metrics: P_FalseNegatives - 0 but supposed to be 1 (the length of ypred \ y).
P_FalsePositives(int[], int[]) - Static method in class meka.core.Metrics: P_FalsePositives - 1 but supposed to be 0 (the length of y \ ypred).
P_FmacroAvgD(int[][], int[][]) - Static method in class meka.core.Metrics: F-Measure Averaged by D - The F-measure macro averaged by example.
P_FmacroAvgL(int[][], int[][]) - Static method in class meka.core.Metrics: F-Measure Macro Averaged by L - The 'standard' macro average.
P_FmicroAvg(int[][], int[][]) - Static method in class meka.core.Metrics: P_FmicroAvg - Micro Averaged F-measure (F1, as if all labels in the dataset formed a single vector)
P_Hamming(int[][], int[][]) - Static method in class meka.core.Metrics: Hamming score aka label accuracy.
P_Hamming(int[][], int[][], int) - Static method in class meka.core.Metrics: Hamming score aka label accuracy.
P_Harmonic(int[], int[]) - Static method in class meka.core.Metrics: Harmonic Accuracy.
P_Harmonic(int[][], int[][], int) - Static method in class meka.core.Metrics: Harmonic Accuracy -- for the j-th label.
P_Harmonic(int[][], int[][]) - Static method in class meka.core.Metrics: Harmonic Accuracy -- average over all labels.
P_JaccardIndex(int[][], int[][]) - Static method in class meka.core.Metrics: Jaccard Index -- often simply called multi-label 'accuracy'.
P_LogLikelihood(int[], double[]) - Method in class meka.core.Metrics: Log Likelihood
P_macroAUPRC(int[][], double[][]) - Static method in class meka.core.Metrics: Calculate AUPRC: Area Under the Precision-Recall curve.
P_macroAUROC(int[][], double[][]) - Static method in class meka.core.Metrics: Calculate AUROC: Area Under the ROC curve.
P_Precision(int[], int[]) - Static method in class meka.core.Metrics: P_Precision - (retrieved AND relevant) / retrieved
P_Precision(int[][], int[][], int) - Static method in class meka.core.Metrics: P_Precision - (retrieved AND relevant) / retrieved
P_PrecisionMacro(int[][], int[][]) - Static method in class meka.core.Metrics: P_Precision - (retrieved AND relevant) / retrieved
P_PrecisionMicro(int[][], int[][]) - Static method in class meka.core.Metrics: P_Precision - (retrieved AND relevant) / retrieved
P_Recall(int[], int[]) - Static method in class meka.core.Metrics: P_Recall - (retrieved AND relevant) / relevant
P_Recall(int[][], int[][], int) - Static method in class meka.core.Metrics: P_Recall - (retrieved AND relevant) / relevant
P_RecallMacro(int[][], int[][]) - Static method in class meka.core.Metrics: P_Recall - (retrieved AND relevant) / relevant
P_RecallMicro(int[][], int[][]) - Static method in class meka.core.Metrics: P_Recall - (retrieved AND relevant) / relevant
P_TrueNegatives(int[], int[]) - Static method in class meka.core.Metrics: P_TrueNegatives - 0 and supposed to be 0.
P_TruePositives(int[], int[]) - Static method in class meka.core.Metrics: P_TruePositives - 1 and supposed to be 1 (the intersection, i.e., logical AND).
ParameterPanel - Class in meka.gui.core: A panel that lists one parameter (label and component or just AbstractChooserPanel) per row.
ParameterPanel() - Constructor for class meka.gui.core.ParameterPanel: Initializes the panel.
ParameterPanel(int, int) - Constructor for class meka.gui.core.ParameterPanel: Initializes the panel.
parse(String[], char, int) - Static method in class meka.core.OptionUtils: Parses an int option, uses default if option is missing.
parse(String[], String, int) - Static method in class meka.core.OptionUtils: Parses an int option, uses default if option is missing.
parse(String[], char, long) - Static method in class meka.core.OptionUtils: Parses an long option, uses default if option is missing.
parse(String[], String, long) - Static method in class meka.core.OptionUtils: Parses a long option, uses default if option is missing.
parse(String[], char, float) - Static method in class meka.core.OptionUtils: Parses a float option, uses default if option is missing.
parse(String[], String, float) - Static method in class meka.core.OptionUtils: Parses a float option, uses default if option is missing.
parse(String[], char, double) - Static method in class meka.core.OptionUtils: Parses a double option, uses default if option is missing.
parse(String[], String, double) - Static method in class meka.core.OptionUtils: Parses a double option, uses default if option is missing.
parse(String[], char, String) - Static method in class meka.core.OptionUtils: Parses a String option, uses default if option is missing.
parse(String[], String, String) - Static method in class meka.core.OptionUtils: Parses a String option, uses default if option is missing.
parse(String[], char, File) - Static method in class meka.core.OptionUtils: Parses a File option, uses default if option is missing.
parse(String[], String, File) - Static method in class meka.core.OptionUtils: Parses a File option, uses default if option is missing.
parse(String[], char, OptionHandler) - Static method in class meka.core.OptionUtils: Parses an OptionHandler option, uses default if option is missing.
parse(String[], String, OptionHandler) - Static method in class meka.core.OptionUtils: Parses an OptionHandler option, uses default if option is missing.
parse(String[], char) - Static method in class meka.core.OptionUtils: Parses an array option, returns all the occurrences of the option as a string array.
parse(String[], String) - Static method in class meka.core.OptionUtils: Parses an array option, returns all the occurrences of the option as a string array.
parse(String[], char, Class<T>) - Static method in class meka.core.OptionUtils: Parses an array option, returns all the occurrences of the option as a string array.
parse(String[], char, boolean) - Static method in class meka.core.OptionUtils: Parses a double option, uses default if option is missing.
parse(String[], String, boolean) - Static method in class meka.core.OptionUtils: Parses a double option, uses default if option is missing.
parse(String[], String, Class<T>) - Static method in class meka.core.OptionUtils: Parses an array option, returns all the occurrences of the option as a string array.
pasteFromClipboard(DataFlavor) - Static method in class meka.gui.core.GUIHelper: Obtains an object from the clipboard.
pasteStringFromClipboard() - Static method in class meka.gui.core.GUIHelper: Obtains a string from the clipboard.
payoff(CC, Instances) - Method in class meka.classifiers.multilabel.MCC: Payoff - Return a default score of h evaluated on D.
payoffTipText() - Method in class meka.classifiers.multilabel.MCC
PCC - Class in meka.classifiers.multilabel: PCC.java - (Bayes Optimal) Probabalistic Classifier Chains.
PCC() - Constructor for class meka.classifiers.multilabel.PCC
peekClassIndex(File) - Static method in class meka.core.MLUtils: Attempts to determine the number of classes/class index from the specified file.
PercentageSplit - Class in meka.experiment.evaluators: Evaluates the classifier on a percentage split.
PercentageSplit() - Constructor for class meka.experiment.evaluators.PercentageSplit
performInitialization() - Method in class meka.gui.core.MekaFrame: Contains all the initialization steps to perform.
performSearch() - Method in class meka.gui.core.SearchPanel: Initiates a search.
permute(String) - Static method in class meka.core.MLUtils: Permute -- e.g., permute("AB") returns ["AB","BA"]
pi(int[], Random, int, double) - Static method in class meka.classifiers.multilabel.PMCC: pi - proposal distribution; swap elements in s, depending on iteration t (temperature).
PlainTextRenderer - Class in meka.gui.modelviewer.renderers: Renders objects as plain text.
PlainTextRenderer() - Constructor for class meka.gui.modelviewer.renderers.PlainTextRenderer
PLST - Class in meka.classifiers.multilabel: PLST - Principal Label Space Transformation.
PLST() - Constructor for class meka.classifiers.multilabel.PLST
plus(SparseVector) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseVector
PMCC - Class in meka.classifiers.multilabel: PMCC.java - Like MCC but creates a population of M chains at training time (from Is candidate chains, using Monte Carlo sampling), and uses this population for inference at test time; If you are looking for a 'more typical' majority-vote ensemble method, use something like EnsembleML or BaggingML with MCC.
PMCC() - Constructor for class meka.classifiers.multilabel.PMCC
poisson(double, Random) - Static method in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable
populateMenu(AbstractExplorerTab, List<String>, ResultHistoryList, int, JPopupMenu) - Static method in class meka.gui.explorer.AbstractResultHistoryPlugin: Allows to customize the popup menu for the result history.
populateMenu(AbstractExplorerTab, ResultHistoryList, int, JPopupMenu) - Static method in class meka.gui.explorer.classify.AbstractClassifyResultHistoryPlugin: Allows to customize the popup menu for the classify result history.
popy(double[]) - Method in class meka.classifiers.multilabel.BPNN: Forward Pass - Given input x_, get output y_.
popY(double[][]) - Method in class meka.classifiers.multilabel.BPNN: Forward Pass - Given input X_, get output Y_.
postUpdateMenu() - Method in class meka.gui.core.AbstractRecentItemsHandler: Hook method which gets executed just after the menu was updated.
PrecisionRecallCurve - Class in meka.gui.guichooser: Displays an ROC curve from a dataset.
PrecisionRecallCurve() - Constructor for class meka.gui.guichooser.PrecisionRecallCurve
prediction - Variable in class meka.classifiers.multilabel.MajorityLabelset
predictions - Variable in class meka.core.Result
PredictionsOnTestset - Class in meka.gui.explorer.classify: Makes predictions on the current test set (if any loaded).
PredictionsOnTestset() - Constructor for class meka.gui.explorer.classify.PredictionsOnTestset
predictionsToRanking(double[]) - Static method in class meka.core.MLUtils: Transforms the predictions into a ranking array.
prepareChain(int) - Method in class meka.classifiers.multilabel.CC: Prepare a Chain.
prepareChain(int[]) - Method in class meka.classifiers.multilabel.CC: Prepare a Chain.
prepareData(Instances) - Static method in class meka.core.MLUtils: Prepares the class index of the data.
PrepareHClusters() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
PreprocessTab - Class in meka.gui.explorer: For preprocessing data.
PreprocessTab() - Constructor for class meka.gui.explorer.PreprocessTab
preserveOrderTipText() - Method in class meka.experiment.evaluators.CrossValidation: Describes this property.
preserveOrderTipText() - Method in class meka.experiment.evaluators.PercentageSplit: Describes this property.
presetWeights(Matrix[], int) - Method in class meka.classifiers.multilabel.BPNN: Preset Weights - Initialize a BPNN with (pre-trained) weight matrices W (which also determines X dimensions).
preUpdateMenu() - Method in class meka.gui.core.AbstractRecentItemsHandler: Hook method which gets executed just before the menu gets updated.
preUpdateMenu() - Method in class meka.gui.core.RecentFilesHandler: Hook method which gets executed just before updating the menu.
preUpdateMenu() - Method in class meka.gui.core.RecentFilesHandlerWithCommandline: Hook method which gets executed just before updating the menu.
printAsTextMatrix(double[][]) - Static method in class meka.core.MLUtils
printDim(Matrix) - Static method in class meka.core.MatrixUtils
printDim(double[][]) - Static method in class meka.core.MatrixUtils
printMatrix(double[][]) - Static method in class meka.core.MatrixUtils
printOptions(Enumeration) - Static method in class meka.classifiers.multilabel.Evaluation
printOptions(Enumeration) - Static method in class meka.classifiers.multilabel.incremental.IncrementalEvaluation
printUsage() - Static method in class meka.core.PropsUtils: Prints the usage of this class from the commandline to stdout.
prob_x(double[]) - Method in class rbms.RBM: Visible Activation Probability - returns P(x|z) where p(x[j]==1|z) for each j-th element.
prob_X(Matrix) - Method in class rbms.RBM: Visible Activation Probability - returns P(X|Z).
prob_z(double[]) - Method in class rbms.DBM
prob_Z(double[][]) - Method in class rbms.DBM
prob_z(double[]) - Method in class rbms.RBM: Hidden Activation Probability - returns P(z|x) where p(z[i]==1|x) for each element.
prob_Z(double[][]) - Method in class rbms.RBM: Hidden Activation Probability - returns P(Z|X).
prob_Z(Matrix) - Method in class rbms.RBM: Hidden Activation Probability - returns P(Z|X).
probabilityForInstance(Instance, double[]) - Method in class meka.classifiers.multilabel.CC: ProbabilityForInstance - Force our way down the imposed 'path'.
ProblemTransformationMethod - Class in meka.classifiers.multilabel: MultilabelClassifier.java - A Multilabel Classifier.
ProblemTransformationMethod() - Constructor for class meka.classifiers.multilabel.ProblemTransformationMethod
process(Instances) - Method in class meka.filters.multilabel.SuperNodeFilter
process(Instance) - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes: processes the given instance (may change the provided instance) and returns the modified version.
processCommandLineArgs(String[]) - Method in interface meka.gui.core.CommandLineArgsHandler: Processes the commandline arguments.
processCommandLineArgs(String[]) - Method in class meka.gui.experimenter.Experimenter: Processes the commandline arguments.
processCommandLineArgs(String[]) - Method in class meka.gui.explorer.Explorer: Processes the commandline arguments.
processCommandLineArgs(String[]) - Method in class meka.gui.modelviewer.ModelViewer: Processes the commandline arguments.
product(double[]) - Static method in class meka.core.A
Project - Class in meka.core: Helper class related to the project and it's "home" directory.
Project() - Constructor for class meka.core.Project
PropertyText - Class in meka.gui.goe: Support for a PropertyEditor that uses text.
PropertyValueSelector - Class in meka.gui.goe: Support for any PropertyEditor that uses tags.
PropertyValueSelector(PropertyEditor) - Constructor for class meka.gui.goe.PropertyValueSelector: Sets up the editing component with the supplied editor.
PropsUtils - Class in meka.core: Utility class for props files.
PropsUtils() - Constructor for class meka.core.PropsUtils
propUp(double[][]) - Method in class rbms.RBM: Hidden Activation Value.
providersTipText() - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Describes this property.
pruneCountHashMap(HashMap<?, Integer>, int) - Static method in class meka.core.MLUtils: PruneCountHashMap - remove entries in hm = {(label,count)} where 'count' is no more than 'p'.
pruneCountHashMapBasedAsAFractionOf(HashMap<?, Integer>, double, int) - Static method in class meka.core.MLUtils
PS - Class in meka.classifiers.multilabel: PS.java - The Pruned Sets Method.
PS() - Constructor for class meka.classifiers.multilabel.PS
PSt - Class in meka.classifiers.multilabel: PSt.java - Pruned Sets with a a threshold so as to be able to predict sets not seen in the training set.
PSt() - Constructor for class meka.classifiers.multilabel.PSt
PSTransformation(Instances, int, int) - Static method in class meka.core.PSUtils
PSTransformation(Instances, int, int, int) - Static method in class meka.core.PSUtils
PSTransformation(Instances, int, String, int, int) - Static method in class meka.core.PSUtils: Transform instances into a multi-class representation.
PSTransformation(Instance, int, HashMap<LabelSet, Integer>, int, Instances) - Static method in class meka.core.PSUtils: Transform one instance into multi-class representations (an array of possibly multiple single-label instances).
PSUpdateable - Class in meka.classifiers.multilabel.incremental: PSUpdateable.java - Pruned Sets Updateable.
PSUpdateable() - Constructor for class meka.classifiers.multilabel.incremental.PSUpdateable
PSUtils - Class in meka.core: PSUtils.java - Handy Utils for working with Pruned Sets.
PSUtils() - Constructor for class meka.core.PSUtils
pTipText() - Method in class meka.classifiers.multilabel.PS
put(int, Double) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Adds a mapping from the specified key to the specified value, replacing the previous mapping from the specified key if there was one.
put(int, double) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseVector
put(Key, Value) - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Inserts the key-value pair into the symbol table, overwriting the old value with the new value if the key is already in the symbol table.
putTogether(int, int) - Method in class meka.classifiers.multilabel.cc.Trellis

Q

QLink(int[], int, Instances) - Constructor for class meka.classifiers.multilabel.CCq.QLink

R

r - Variable in class meka.classifiers.multilabel.BPNN
RAkEL - Class in meka.classifiers.multilabel: RAkEL.java - Draws M subsets of size k from the set of labels, and trains PS upon each one, then combines label votes from these PS classifiers to get a label-vector prediction.
RAkEL() - Constructor for class meka.classifiers.multilabel.RAkEL
RAkELd - Class in meka.classifiers.multilabel: RAkELd - Takes RAndom partition of labELs; like RAkEL but labelsets are disjoint / non-overlapping subsets.
RAkELd() - Constructor for class meka.classifiers.multilabel.RAkELd
RAkELd - Class in meka.classifiers.multitarget: RAkELd - Multi-target Version of RAkELd.
RAkELd() - Constructor for class meka.classifiers.multitarget.RAkELd
randn(int, int, Random) - Static method in class meka.core.MatrixUtils: A 2D array of Gaussian random numbers
random - Variable in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable
randomize(int[], Random) - Static method in class meka.core.MLUtils: Deprecated.
randomn(int, int, Random) - Static method in class meka.core.MatrixUtils: A matrix of Gaussian random numbers
RandomSubspaceML - Class in meka.classifiers.multilabel.meta: RandomSubspaceML.java - Subsample the attribute space and instance space randomly for each ensemble member.
RandomSubspaceML() - Constructor for class meka.classifiers.multilabel.meta.RandomSubspaceML
rankMatrix(List<EvaluationStatistics>, String) - Static method in class meka.experiment.evaluationstatistics.EvaluationStatisticsUtils: Rank Matrix
rbm - Variable in class rbms.DBM
RBM - Class in rbms: RBM.java - Restricted Boltzmann Machine.
RBM() - Constructor for class rbms.RBM: RBM - Create an RBM with default options.
RBM(String[]) - Constructor for class rbms.RBM: RBM - Create an RBM with 'options' (using WEKA-style option processing).
rbm_time - Variable in class meka.classifiers.multilabel.DBPNN
rbm_time - Variable in class meka.classifiers.multilabel.meta.DeepML
rbms - package rbms
read(String) - Static method in class meka.core.PropsUtils: Reads properties that inherit from three locations.
read() - Method in interface meka.experiment.evaluationstatistics.EvaluationStatisticsHandler: Reads the statistics.
read() - Method in class meka.experiment.evaluationstatistics.InMemory: Reads the statistics.
read() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Reads the statistics.
read() - Method in class meka.experiment.evaluationstatistics.Serialized: Reads the statistics.
read(File) - Method in class meka.experiment.filehandlers.AbstractExperimentFileHandler: Reads an experiment from disk.
read(File) - Method in class meka.experiment.filehandlers.CommandLineSetup: Reads an experiment from disk.
read(File) - Method in interface meka.experiment.filehandlers.ExperimentFileHandler: Reads an experiment from disk.
read(File) - Method in class meka.experiment.filehandlers.SerializedExperiment: Reads an experiment from disk.
readProps() - Method in class meka.gui.core.AbstractRecentItemsHandler: Reads the recent items from the props file.
rebuildCC(CC, int[], Instances) - Method in class meka.classifiers.multilabel.PMCC: RebuildCC - rebuild a classifier chain 'h_old' to have a new sequence 's_new'.
rebuildClassifier(int[], Instances) - Method in class meka.classifiers.multilabel.CC: Rebuild - NOT YET IMPLEMENTED.
RECENTFILES_COUNT - Static variable in class meka.gui.core.RecentFilesHandler: the property for storing the number of recent files.
RECENTFILES_COUNT - Static variable in class meka.gui.core.RecentFilesHandlerWithCommandline: the property for storing the number of recent files.
RECENTFILES_PREFIX - Static variable in class meka.gui.core.RecentFilesHandler: the property prefix for a recent file.
RECENTFILES_PREFIX - Static variable in class meka.gui.core.RecentFilesHandlerWithCommandline: the property prefix for a recent file.
RecentFilesHandler<M> - Class in meka.gui.core: A class that handles a list of recent files.
RecentFilesHandler(String, M) - Constructor for class meka.gui.core.RecentFilesHandler: Initializes the handler with a maximum of 5 items.
RecentFilesHandler(String, int, M) - Constructor for class meka.gui.core.RecentFilesHandler: Initializes the handler.
RecentFilesHandler(String, String, int, M) - Constructor for class meka.gui.core.RecentFilesHandler: Initializes the handler.
RecentFilesHandlerWithCommandline<M> - Class in meka.gui.core: Recent files handler that stores a commandline alongside the file.
RecentFilesHandlerWithCommandline(String, M) - Constructor for class meka.gui.core.RecentFilesHandlerWithCommandline: Initializes the handler with a maximum of 5 items.
RecentFilesHandlerWithCommandline(String, int, M) - Constructor for class meka.gui.core.RecentFilesHandlerWithCommandline: Initializes the handler.
RecentFilesHandlerWithCommandline(String, String, int, M) - Constructor for class meka.gui.core.RecentFilesHandlerWithCommandline: Initializes the handler.
RecentFilesHandlerWithCommandline.Setup - Class in meka.gui.core: Container class for storing file and optionhandler alongside.
recentItemAdded(RecentItemEvent<M, T>) - Method in interface meka.gui.events.RecentItemListener: Gets called in case a recent item got added.
RecentItemEvent<M,T> - Class in meka.gui.events: Event that gets sent when recent items change or get selected.
RecentItemEvent(AbstractRecentItemsHandler<M, T>, T) - Constructor for class meka.gui.events.RecentItemEvent: Initializes the event.
RecentItemListener<M,T> - Interface in meka.gui.events: Interface for classes that listen to events of AbstractRecentItemsHandler.
recentItemSelected(RecentItemEvent<M, T>) - Method in interface meka.gui.events.RecentItemListener: Gets called in case a recent item got selected.
recombination(double[], int, LabelSet[]) - Static method in class meka.core.PSUtils: Convert Distribution - Given the posterior across combinations, return the distribution across labels.
recombination_t(double[], int, Instances) - Static method in class meka.core.PSUtils: Convert Distribution - Given the posterior across combinations, return the distribution across labels.
recombination_t(double[], int, LabelSet[]) - Static method in class meka.core.PSUtils
ReevaluateModelOnTestset - Class in meka.gui.explorer.classify: Reevaluates the model on the current test set (if any loaded).
ReevaluateModelOnTestset() - Constructor for class meka.gui.explorer.classify.ReevaluateModelOnTestset
refresh() - Method in class meka.gui.dataviewer.DataViewer: validates and repaints the frame
refresh() - Method in class meka.gui.dataviewer.DataViewerMainPanel: validates and repaints the frame
registerAllEditors() - Static method in class meka.gui.goe.GenericObjectEditor: registers all the editors in WEKA and MEKA.
RelationalCellEditor(int, int) - Constructor for class meka.gui.dataviewer.DataTable.RelationalCellEditor: initializes the editor
relations(List<EvaluationStatistics>, boolean) - Static method in class meka.experiment.evaluationstatistics.EvaluationStatisticsUtils: Returns all the unique relations of all the statistics.
remove(int) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Alias for SparseArray.delete(int).
remove(Instances, int[], boolean) - Static method in class meka.core.F: Remove Indices - Remove attribute indices 'indices' from 'D'.
remove() - Method in class meka.experiment.datasetproviders.AbstractDatasetProvider: Does nothing.
remove(int) - Method in class meka.gui.core.ResultHistory: Removes the specified entry.
removeAll() - Method in class meka.gui.core.AbstractRecentItemsHandler: Removes all items from the internal list.
removeAttributes() - Method in class meka.gui.explorer.PreprocessTab: Removes the currently selected attributes.
removeBias(double[]) - Static method in class meka.core.MatrixUtils
removeBias(Matrix) - Static method in class meka.core.MatrixUtils
removeBias(double[][]) - Static method in class meka.core.MatrixUtils
removeChangeListener(ChangeListener) - Method in class meka.gui.dataviewer.DataPanel: Removes a ChangeListener from the panel
removeChangeListener(ChangeListener) - Method in class meka.gui.dataviewer.DataTable: Removes a ChangeListener from the panel
removeClassifiers(int[]) - Method in class meka.gui.experimenter.BasicSetup: Removes the specified classifiers.
removeClassifiers(int[]) - Method in class meka.gui.experimenter.ExpertSetup: Removes the specified classifiers.
removeDatasets(int[]) - Method in class meka.gui.experimenter.BasicSetup: Removes the specified datasets.
removeElementAt(int) - Method in class meka.gui.core.ResultHistoryList.ResultHistoryModel: Removes the element at the specified location.
removeExecutionStageListener(ExecutionStageListener) - Method in class meka.experiment.DefaultExperiment: Removes the execution stage listener.
removeExecutionStageListener(ExecutionStageListener) - Method in interface meka.experiment.Experiment: Removes the execution stage listener.
removeFromButtonsPanel(Component) - Method in class meka.gui.core.MekaPanelWithButtons: Removes the component from the panel with the buttons.
removeFromWidgetsPanel(Component) - Method in class meka.gui.core.SearchPanel: Removes the component from the panel with the Widgets.
removeItem(int) - Method in class meka.gui.core.ResultHistoryList: Removes the item at the specified location.
removeIterationNotificationListener(IterationNotificationListener) - Method in class meka.experiment.DefaultExperiment: Removes the iteration listener.
removeIterationNotificationListener(IterationNotificationListener) - Method in interface meka.experiment.Experiment: Removes the iteration listener.
removeLabels(Instances, int) - Static method in class meka.core.F: Remove Indices - Remove ALL labels (assume they are the first L attributes) from D.
removeLogListener(LogListener) - Method in class meka.events.LogObject: Remove the log listener to use.
removeLogListener(LogListener) - Method in interface meka.events.LogSupporter: Remove the log listener to use.
removeLogListener(LogListener) - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Remove the log listener to use.
removeLogListener(LogListener) - Method in class meka.experiment.evaluators.AbstractMetaEvaluator: Remove the log listener to use.
removeLogListener(LogListener) - Method in class meka.experiment.statisticsexporters.AbstractMetaEvaluationStatisticsExporter: Remove the log listener to use.
removeLogListener(LogListener) - Method in class meka.experiment.statisticsexporters.MultiExporter: Remove the log listener to use.
removeParameter(int) - Method in class meka.gui.core.ParameterPanel: Removes the parameter at the specified location.
removeRecentItem(T) - Method in class meka.gui.core.AbstractRecentItemsHandler: Removes the item from the internal list, e.g., if it no longer exists on disk.
removeRecentItemListener(RecentItemListener) - Method in class meka.gui.core.AbstractRecentItemsHandler: Removes the listener from the internal list.
removeSearchListener(SearchListener) - Method in class meka.gui.core.SearchPanel: Removes the specified listener from the internal list of listeners.
removeStatisticsNotificationListener(StatisticsNotificationListener) - Method in class meka.experiment.DefaultExperiment: Removes the statistics listener.
removeStatisticsNotificationListener(StatisticsNotificationListener) - Method in interface meka.experiment.Experiment: Removes the statistics listener.
removeTableModelListener(TableModelListener) - Method in class meka.gui.dataviewer.DataSortedTableModel: removes a listener from the list that is notified each time a change to the data model occurs
removeTableModelListener(TableModelListener) - Method in class meka.gui.dataviewer.DataTableModel: removes a listener from the list that is notified each time a change to the data model occurs
renameAttribute() - Method in class meka.gui.dataviewer.DataPanel: renames the current attribute
renameAttribute() - Method in class meka.gui.dataviewer.DataViewerMainPanel: renames the current selected Attribute
renameAttributeAt(int, String) - Method in class meka.gui.dataviewer.DataSortedTableModel: renames the attribute at the given col index
renameAttributeAt(int, String) - Method in class meka.gui.dataviewer.DataTableModel: renames the attribute at the given col index
render(Object, JPanel) - Method in class meka.gui.modelviewer.renderers.AbstractObjectRenderer: Exports the object.
reorderLabels(Instances, int[]) - Static method in class meka.core.F: ReorderLabels - swap values of y[1] to y[L] according to s[].
RepeatedRuns - Class in meka.experiment.evaluators: Repeatedly executes the base evaluator.
RepeatedRuns() - Constructor for class meka.experiment.evaluators.RepeatedRuns
replaceZasAttributes(Instances, double[][], int) - Static method in class meka.core.MLUtils: ReplaceZasAttributes - data Z[][] will be the new attributes in D.
replaceZasClasses(Instances, double[][], int) - Static method in class meka.core.MLUtils: ReplaceZasClasses - data Z[][] will be the new class labels in D.
requires(MultiLabelClassifier, Instances) - Method in interface meka.experiment.evaluationstatistics.IncrementalEvaluationStatisticsHandler: Checks whether the specified combination of classifier and dataset is required for evaluation or already present from previous evaluation.
requires(MultiLabelClassifier, Instances) - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Checks whether the specified combination of classifier and dataset is required for evaluation or already present from previous evaluation.
restoreLastFilter(int) - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Attempts to restore the last filter in use.
restoreModelSettings(TableModel, Hashtable<String, Object>) - Method in class meka.gui.core.SortableAndSearchableTable: Restores the settings previously backed up.
Result - Class in meka.core: Result - Stores predictions alongside true labels, for evaluation.
Result() - Constructor for class meka.core.Result
Result(int) - Constructor for class meka.core.Result
Result(int, int) - Constructor for class meka.core.Result
ResultHistory - Class in meka.gui.core: For maintaining a history of results.
ResultHistory() - Constructor for class meka.gui.core.ResultHistory: Initializes the history.
ResultHistoryList - Class in meka.gui.core: A specialized JList to display results.
ResultHistoryList() - Constructor for class meka.gui.core.ResultHistoryList: Initializes the list.
ResultHistoryList.ResultHistoryModel - Class in meka.gui.core: Model for results histories.
ResultHistoryList.ResultHistoryPopupMenuCustomizer - Interface in meka.gui.core: The interface for classes that can customize the popup menu of the result history.
ResultHistoryModel() - Constructor for class meka.gui.core.ResultHistoryList.ResultHistoryModel: Initializes the model with an empty history.
ResultHistoryModel(ResultHistory) - Constructor for class meka.gui.core.ResultHistoryList.ResultHistoryModel: Initializes the model with the history.
RESULTS_SAMPLED_OVER_TIME - Static variable in class meka.gui.explorer.classify.IncrementalPerformance
retrieve(MultiLabelClassifier, Instances) - Method in interface meka.experiment.evaluationstatistics.IncrementalEvaluationStatisticsHandler: Retrieves the statis for the specified combination of classifier and dataset.
retrieve(MultiLabelClassifier, Instances) - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Retrieves the statis for the specified combination of classifier and dataset.
retrieveChain() - Method in class meka.classifiers.multilabel.CC
reverse(int[]) - Static method in class meka.core.A
revert() - Method in class meka.gui.experimenter.AbstractSetupTab: Reverts the settings to the experiment ones.
ROC - Class in meka.gui.guichooser: Displays an ROC curve from a dataset.
ROC() - Constructor for class meka.gui.guichooser.ROC
root - Variable in class meka.classifiers.multilabel.CCq
root - Variable in class meka.classifiers.multilabel.incremental.CCUpdateable
root - Variable in class meka.classifiers.multitarget.CCp
round(double[][]) - Static method in class meka.core.ThresholdUtils: Round - simply round numbers (e.g., 2.0 to 2) -- for multi-target data (where we don't *yet* use a threshold).
rowConfidence(int) - Method in class meka.core.Result: RowConfidence - Retrieve the prediction confidences for the i-th instance.
rowPrediction(int, double) - Method in class meka.core.Result: RowPrediction - Retrieve the predicted values for the i-th instance according to threshold t.
rowPrediction(int) - Method in class meka.core.Result: RowPrediction - Retrieve the predicted values for the i-th instance according to pre-calibrated/chosen threshold.
rowTrue(int) - Method in class meka.core.Result: RowActual - Retrieve the true values for the i-th instance.
RT - Class in meka.classifiers.multilabel: RT.java - The 'Ranking + Threshold' classifier.
RT() - Constructor for class meka.classifiers.multilabel.RT
RTUpdateable - Class in meka.classifiers.multilabel.incremental: RTUpdateable.java - Updateable RT.
RTUpdateable() - Constructor for class meka.classifiers.multilabel.incremental.RTUpdateable
run() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM.BuildClassifier
run() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM.DistributionCalc
run() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM.DistributionCalcM
run() - Method in class meka.experiment.DefaultExperiment: Runs the experiment.
run() - Method in interface meka.experiment.Experiment: Runs the experiment.
run() - Method in class meka.gui.core.StatusBar.Animation: Performs the animation.
run() - Method in class meka.gui.explorer.AbstractThreadedExplorerTab.WorkerThread
runClassifier(MultiLabelClassifier, String[]) - Static method in class meka.classifiers.multilabel.AbstractMultiLabelClassifier: Called by classifier's main() method upon initialisation from the command line.
runClassifier(MultiLabelClassifier, String[]) - Static method in class meka.classifiers.multilabel.ProblemTransformationMethod: Called by classifier's main() method upon initialisation from the command line.
runExperiment(MultiLabelClassifier, String[]) - Static method in class meka.classifiers.multilabel.Evaluation: RunExperiment - Build and evaluate a model with command-line options.
runExperiment(MultiLabelClassifier, String[]) - Static method in class meka.classifiers.multilabel.incremental.IncrementalEvaluation: RunExperiment - Build and evaluate a model with command-line options.

S

sample(Instance, double[], Random) - Method in class meka.classifiers.multilabel.cc.CNode: Sample the distribution given by #distribution(Instance, double[]).
sample(double[][], Random) - Static method in class meka.core.MatrixUtils: Sample - Returns Matrix C where each value C[j][k] is 1 with probability M[j][k] and 0 otherwise.
sample(double[], Random) - Static method in class meka.core.MatrixUtils: Sample - Returns vector c where each value c[j][k] is 1 with probability v[j][k] and 0 otherwise.
sample(Matrix, Random) - Static method in class meka.core.MatrixUtils: Sample - Returns Matrix C where each value C[j][k] is 1 with probability M[j][k] and 0 otherwise.
sample_epoch(Matrix) - Method in class rbms.RBM
sample_x(double[]) - Method in class rbms.RBM: Sample Visible - returns x[j] ~ p(x[j]==1|z) for each j-th element.
sample_X(Matrix) - Method in class rbms.RBM: Sample Visible - returns X ~ P(X|Z).
sample_Z(Matrix) - Method in class rbms.RBM: Sample Hidden Value - returns Z ~ P(Z|X).
sample_z(double[]) - Method in class rbms.RBM: Sample Hidden Value - returns z[i] ~ p(z[i]==1|x) for each i-th element.
sampleForInstance(Instance, Random) - Method in class meka.classifiers.multilabel.CC: SampleForInstance.
sampleForInstanceFast(Instance[], Random) - Method in class meka.classifiers.multilabel.CC: SampleForInstance - given an Instance template for each label, and a Random.
samplePMF(double[], Random) - Static method in class meka.core.A: Sample a PMF - select i with probabilitiy w[i] (w must be normalised)
SAMPLES - Static variable in class meka.gui.explorer.classify.IncrementalPerformance
SAMPLES - Static variable in class meka.gui.explorer.classify.ShowMacroCurve
SAMPLES - Static variable in class meka.gui.explorer.classify.ShowMicroCurve
save(int) - Method in class meka.gui.core.ResultHistoryList: Brings up a dialog to save the specified item to a file.
save(File, ExperimentFileHandler) - Method in class meka.gui.experimenter.Experimenter: Saves the experiment to the specified file.
save() - Method in class meka.gui.experimenter.Experimenter: Saves the current experiment.
save() - Method in class meka.gui.experimenter.LogTab: Saves the logging content.
save() - Method in class meka.gui.experimenter.Statistics: Prompts the user with a filechooser for saving the statistics to a file.
save(File, AbstractFileSaver) - Method in class meka.gui.explorer.Explorer: Saves the data to the specified file.
save() - Method in class meka.gui.explorer.Explorer: Saves the current dataset.
save() - Method in class meka.gui.explorer.LogTab: Saves the logging content.
saveAs() - Method in class meka.gui.experimenter.Experimenter: Saves the current experiment under a new name.
saveAs() - Method in class meka.gui.explorer.Explorer: Saves the current dataset under a new name.
saveChanges() - Method in class meka.gui.dataviewer.DataViewerMainPanel: if the file is changed it pops up a dialog whether to change the settings.
saveChanges(boolean) - Method in class meka.gui.dataviewer.DataViewerMainPanel: if the file is changed it pops up a dialog whether to change the settings.
SaveCSV - Class in meka.gui.explorer.classify: Allows the user to displays graphs of the performance of an incremental classifier if available.
SaveCSV() - Constructor for class meka.gui.explorer.classify.SaveCSV
saveFile() - Method in class meka.gui.dataviewer.DataViewerMainPanel: saves the current data into a file
saveFileAs() - Method in class meka.gui.dataviewer.DataViewerMainPanel: saves the current data into a new file
SaveGraphs - Class in meka.gui.explorer.classify: Allows the user to save the graphs.
SaveGraphs() - Constructor for class meka.gui.explorer.classify.SaveGraphs
saveMap(String, HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils: SaveMap - Save the HashMap 'map' to the file 'filename'.
SaveModel - Class in meka.gui.explorer.classify: Allows the user to save the model.
SaveModel() - Constructor for class meka.gui.explorer.classify.SaveModel
saveObject(Object, String) - Static method in class meka.core.MLUtils: Save Object - save 'object' into file 'filename'.
SavePredictions - Class in meka.gui.explorer.classify: Allows the user to save the predictions to CSV.
SavePredictions() - Constructor for class meka.gui.explorer.classify.SavePredictions
scale(double) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseVector
SCC - Class in meka.classifiers.multitarget: SCC.java - Super Class Classifier (aka Super Node Classifier).
SCC() - Constructor for class meka.classifiers.multitarget.SCC
scrollColumnToVisible(int) - Method in class meka.gui.core.MekaTable: Scrolls the column into view.
scrollRowToVisible(int) - Method in class meka.gui.core.MekaTable: Scrolls the row into view.
scrollToVisible(int, int) - Method in class meka.gui.core.JTableHelper: Assumes table is contained in a JScrollPane.
scrollToVisible(JTable, int, int) - Static method in class meka.gui.core.JTableHelper: Assumes table is contained in a JScrollPane.
search(String, boolean) - Method in interface meka.gui.core.SearchableTable: Performs a search for the given string.
search(String, boolean) - Method in interface meka.gui.core.SearchableTableModel: Performs a search for the given string.
search() - Method in class meka.gui.core.SearchPanel: Imitates a click on the search button to initiate a search.
search(String, boolean) - Method in class meka.gui.core.SortableAndSearchableTable: Performs a search for the given string.
search(String, boolean) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Performs a search for the given string.
search() - Method in class meka.gui.dataviewer.DataPanel: searches for a string in the cells
search() - Method in class meka.gui.dataviewer.DataViewerMainPanel: searches for a string in the cells
SearchableTable - Interface in meka.gui.core: Interface for Tables that can be searched.
SearchableTableModel - Interface in meka.gui.core: Interface for TableModels that can be searched.
SearchEvent - Class in meka.gui.events: Event gets sent when a search is to be initiated.
SearchEvent(SearchPanel, String, boolean) - Constructor for class meka.gui.events.SearchEvent: Initializes the event.
searchInitiated(SearchEvent) - Method in interface meka.gui.events.SearchListener: Gets called whenever a search should be performed.
SearchListener - Interface in meka.gui.events: For classes that wait for search events sent by a SearchPanel.
SearchPanel - Class in meka.gui.core: A panel that displays a search box.
SearchPanel(SearchPanel.LayoutType, boolean) - Constructor for class meka.gui.core.SearchPanel: Initializes the panel.
SearchPanel(SearchPanel.LayoutType, boolean, String, String) - Constructor for class meka.gui.core.SearchPanel: Initializes the panel.
SearchPanel(SearchPanel.LayoutType, boolean, String, boolean, String) - Constructor for class meka.gui.core.SearchPanel: Initializes the panel with optional incremental search (and no search button if incremental search turned on).
SearchPanel.LayoutType - Enum in meka.gui.core: The layout of the panel.
SearchParameters - Class in meka.gui.core: A container for search parameters.
SearchParameters(String) - Constructor for class meka.gui.core.SearchParameters: Initializes the search with simple substring matching.
SearchParameters(String, boolean) - Constructor for class meka.gui.core.SearchParameters: Initializes the search.
seedTipText() - Method in class meka.classifiers.multilabel.BRq
seedTipText() - Method in class meka.classifiers.multilabel.CC
seedTipText() - Method in class meka.classifiers.multilabel.CCq
seedTipText() - Method in class meka.classifiers.multilabel.CDN
seedTipText() - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
seedTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
seedTipText() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
seedTipText() - Method in class meka.classifiers.multilabel.PS
seedTipText() - Method in class meka.experiment.evaluators.CrossValidation: Describes this property.
seedTipText() - Method in class meka.experiment.evaluators.PercentageSplit: Describes this property.
select(int[], int[]) - Static method in class meka.core.A
SemisupervisedClassifier - Interface in meka.classifiers.multilabel: SemisupervisedClassifier.java - An Interface for Multilabel Semisupervised Classifiers.
SEQUENTIAL - Static variable in class meka.core.ThreadUtils: the number of threads used to be considered sequential.
Serialized - Class in meka.experiment.evaluationstatistics: Uses Java serialization for readin/writing the statistics.
Serialized() - Constructor for class meka.experiment.evaluationstatistics.Serialized
SerializedExperiment - Class in meka.experiment.filehandlers: Stores the experiment as a Java serialized object.
SerializedExperiment() - Constructor for class meka.experiment.filehandlers.SerializedExperiment
serialVersionUID - Static variable in class meka.classifiers.multilabel.Maniac
serialVersionUID - Static variable in class meka.classifiers.multilabel.MLCBMaD
SESSION_FILE - Static variable in class meka.gui.dataviewer.DataViewerMainPanel: the file to store the recent files in.
SESSION_FILE - Static variable in class meka.gui.experimenter.Experimenter: the file to store the recent files in.
SESSION_FILE - Static variable in class meka.gui.explorer.Explorer: the file to store the recent files in.
SESSION_FILE - Static variable in class meka.gui.modelviewer.ModelViewer: the file to store the recent files in.
SESSION_KEY_FILECHOOSER - Static variable in class meka.gui.explorer.classify.OpenTestData: the session key for the file filechooser.
SESSION_KEY_MODELCHOOSER - Static variable in class meka.gui.explorer.classify.EditTestData: the session key for the model filechooser.
SESSION_KEY_MODELCHOOSER - Static variable in class meka.gui.explorer.classify.OpenModel: the session key for the model filechooser.
set(double[], int, double) - Static method in class meka.core.A: Set
setAcceptAllFileFilterUsed(boolean) - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Is always using false, since we can't determine the reader/writer based on the extension.
setAE(Autoencoder) - Method in class meka.classifiers.multilabel.Maniac: Sets the autoencoder (for using a trained one, e.g.
setAggregationKeys(String) - Method in interface meka.experiment.statisticsexporters.AggregatedEvaluationStatisticsExporter: Sets the blank-separated list of keys to use for aggregating.
setAggregationKeys(String) - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Sets the blank-separated list of keys to use for aggregating.
setApproveCaption(String) - Method in class meka.gui.core.ApprovalDialog: Sets the caption/text of the approve button.
setApproveMnemonic(int) - Method in class meka.gui.core.ApprovalDialog: Sets the mnemonic of the approve button.
setApproveVisible(boolean) - Method in class meka.gui.core.ApprovalDialog: Sets the visbility of the approve button.
setAttributeIndices(String) - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes: Set which attributes are to be used as MEKA class attributes.
setAttSizePercent(int) - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML: Sets the percentage of attributes to sample from the original set.
setBagSizePercent(int) - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
setBeta(double) - Method in class meka.classifiers.multilabel.PMCC: Set the temperature factor
setBounds(int, int, int, int) - Method in class meka.gui.core.MekaFrame: Updates the bounds of the window.
setButtonCaption(String) - Method in class meka.gui.core.SearchPanel: The caption for the search button (incl.
setButtons() - Method in class meka.gui.dataviewer.DataViewerDialog: sets the state of the buttons
setCancelCaption(String) - Method in class meka.gui.core.ApprovalDialog: Sets the caption/text of the Cancel button.
setCancelMnemonic(int) - Method in class meka.gui.core.ApprovalDialog: Sets the mnemonic of the Cancel button.
setCancelVisible(boolean) - Method in class meka.gui.core.ApprovalDialog: Sets the visbility of the cancel button.
setCaretPosition(int) - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Sets the caret position.
setCaretPosition(int) - Method in class meka.gui.core.MarkdownTextPane: Sets the position of the cursor.
setCaretPositionLast() - Method in class meka.gui.core.MarkdownTextPane: Sets the position of the cursor at the end.
setCenteredLocation() - Method in class meka.gui.dataviewer.DataViewer: positions the window at the center of the screen
setChainIterations(int) - Method in class meka.classifiers.multilabel.MCC: Set the iterations of s (chain order)
setChanged(boolean) - Method in class meka.gui.dataviewer.DataPanel: can only reset the changed state to FALSE
setClassifier(Classifier) - Method in class meka.classifiers.multilabel.LabelTransformationClassifier
setClassifier(Classifier) - Method in class meka.classifiers.multilabel.meta.FilteredClassifier: Set the base learner.
setClassifier(Classifier) - Method in class meka.classifiers.multitarget.meta.FilteredClassifier: Set the base learner.
setClassifiers(MultiLabelClassifier[]) - Method in class meka.experiment.DefaultExperiment: Sets the classifiers to be evaluated.
setClassifiers(MultiLabelClassifier[]) - Method in interface meka.experiment.Experiment: Sets the classifiers to be evaluated.
setClusterVigilance(double) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
setColumns(int) - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Sets the columns.
setComboBoxIndices(Instances, ThresholdVisualizePanel) - Method in class meka.gui.explorer.classify.AbstractShowThresholdCurve: Sets the combobox indices.
setCompression(double) - Method in class meka.classifiers.multilabel.Maniac: Set the Compression value.
setConfirmExit(boolean) - Method in class meka.gui.dataviewer.DataViewer: whether to present a MessageBox on Exit or not
setConfirmExit(boolean) - Method in class meka.gui.dataviewer.DataViewerMainPanel: whether to present a MessageBox on Exit or not
setCorrectOpenFileFilter(File) - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Attempts to set the correct file filter for the specified file, using its extension to determine the file filter.
setCorrectOpenFileFilter(File) - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Attempts to set the correct file filter for the specified file, using its extension to determine the file filter.
setCorrectSaveFileFilter(File) - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Attempts to set the correct file filter for the specified file, using its extension to determine the file filter.
setCorrectSaveFileFilter(File) - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Attempts to set the correct file filter for the specified file, using its extension to determine the file filter.
setCurrent(Object) - Method in class meka.gui.goe.GenericObjectEditorDialog: Sets the current object.
setCurrentFilename(String) - Method in class meka.gui.dataviewer.DataViewerMainPanel: sets the filename of the current tab
setData(Instances) - Method in class meka.gui.explorer.AbstractExplorerTab: Sets the data to use.
setDatasetProvider(DatasetProvider) - Method in class meka.experiment.DefaultExperiment: Sets the dataset provider to use.
setDatasetProvider(DatasetProvider) - Method in interface meka.experiment.Experiment: Sets the dataset provider to use.
setDatasets(File[]) - Method in class meka.experiment.datasetproviders.LocalDatasetProvider: Sets the datasets to use in the experiment.
setDebug(boolean) - Method in interface meka.classifiers.multilabel.MultiLabelClassifier: Set debugging mode.
setDebug(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
setDebug(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM
setDebug(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setDebug(boolean) - Method in interface meka.classifiers.multitarget.MultiTargetClassifier: Set debugging mode.
setDensity(int) - Method in class meka.classifiers.multilabel.CDT: SetDensity - Sets the neighbourhood density (number of neighbours for each node).
setDensity(int) - Method in class meka.classifiers.multilabel.CT: SetDensity - Sets the neighbourhood density (number of neighbours for each node).
setDependencyMetric(String) - Method in class meka.classifiers.multilabel.CDT: SetDependency - Sets the type of depependency to use in rearranging the trellis (None by default)
setDependencyMetric(String) - Method in class meka.classifiers.multilabel.CT: SetDependency - Sets the type of depependency to use in rearranging the trellis
setDependencyType(String) - Method in class meka.classifiers.multilabel.BCC
setDiscardCaption(String) - Method in class meka.gui.core.ApprovalDialog: Sets the caption/text of the discard button.
setDiscardMnemonic(int) - Method in class meka.gui.core.ApprovalDialog: Sets the mnemonic of the discard button.
setDiscardVisible(boolean) - Method in class meka.gui.core.ApprovalDialog: Sets the visbility of the discard button.
setDownSampleRatio(double) - Method in class meka.classifiers.multilabel.BRq
setDownSampleRatio(double) - Method in class meka.classifiers.multilabel.CCq: Set the downsample ratio
setE(int) - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
setE(int) - Method in class rbms.RBM: SetE - set the number of epochs (if n is negative, it means max epochs).
setEditable(boolean) - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Sets whether the text area is editable or not.
setEditable(boolean) - Method in class meka.gui.core.MarkdownTextPane: Sets whether the text pane is editable or not.
setEditor(PropertyEditor) - Method in class meka.gui.goe.GenericObjectEditorDialog: Sets the editor to use.
setEnabled(boolean) - Method in class meka.gui.core.ParameterPanel: Sets the enabled state of the panel.
setEnabled(boolean) - Method in class meka.gui.core.SearchPanel: Sets the enabled state of the components.
setEvaluator(Evaluator) - Method in class meka.experiment.DefaultExperiment: Sets the evaluator to use.
setEvaluator(Evaluator) - Method in class meka.experiment.evaluators.AbstractMetaEvaluator: Sets the evaluator to use.
setEvaluator(Evaluator) - Method in interface meka.experiment.Experiment: Sets the evaluator to use.
setExitOnClose(boolean) - Method in class meka.gui.dataviewer.DataViewer: whether to do a System.exit(0) on close
setExitOnClose(boolean) - Method in class meka.gui.dataviewer.DataViewerMainPanel: whether to do a System.exit(0) on close
setExperiment(Experiment) - Method in class meka.gui.experimenter.AbstractExperimenterTab: Sets the experiment to use.
setExperiment(Experiment) - Method in class meka.gui.experimenter.AbstractSetupTab: Sets the experiment to use.
setExporter(EvaluationStatisticsExporter) - Method in class meka.experiment.statisticsexporters.AbstractMetaEvaluationStatisticsExporter: Sets the exporter to use.
setExporters(EvaluationStatisticsExporter[]) - Method in class meka.experiment.statisticsexporters.MultiExporter: Sets the exporters to use.
setFastLearn(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setFile(File) - Method in class meka.experiment.evaluationstatistics.AbstractFileBasedEvaluationStatisticsHandler: Sets the file to read from/write to.
setFile(File) - Method in interface meka.experiment.evaluationstatistics.FileBasedEvaluationStatisticsHandler: Sets the file to read from/write to.
setFile(File) - Method in class meka.experiment.statisticsexporters.AbstractFileBasedEvaluationStatisticsExporter: Sets the file to read from/write to.
setFile(File) - Method in interface meka.experiment.statisticsexporters.FileBasedEvaluationStatisticsExporter: Sets the file to read from/write to.
setFileMustExist(boolean) - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Whether the selected file must exst (only open dialog).
setFilename(String) - Method in class meka.gui.dataviewer.DataPanel: sets the filename
setFilename(int, String) - Method in class meka.gui.dataviewer.DataViewerMainPanel: sets the filename of the specified panel
setFilter(Filter) - Method in class meka.experiment.statisticsexporters.WekaFilter: Sets the filter to use.
setFolds(int) - Method in class meka.gui.explorer.ClassifyTabOptions: Sets the folds value.
setH(int) - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
setH(int[]) - Method in class rbms.DBM: Set hidden layers specification
setH(int, int, int) - Method in class rbms.DBM: SetH - for a discriminative DBM (where the last h == L)
setH(int, int) - Method in class rbms.DBM: SetH -
setH(int) - Method in class rbms.DBM
setH(int) - Method in class rbms.RBM
setI(int) - Method in class meka.classifiers.multilabel.CDN: SetI - Sets the number of iterations.
setI(int) - Method in class meka.classifiers.multitarget.SCC
setIc(int) - Method in class meka.classifiers.multilabel.CDN: SetIc - Sets the number of collection iterations.
setIncrementalDisabled(boolean) - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Sets whether incremental model is turned off.
setIncrementalDisabled(boolean) - Method in interface meka.experiment.evaluationstatistics.OptionalIncrementalEvaluationStatisticsHandler: Sets whether incremental model is turned on.
setIndices(int[][]) - Method in class meka.filters.multilabel.SuperNodeFilter
setInferenceIterations(int) - Method in class meka.classifiers.multilabel.MCC: Set the inference iterations
setInfo(String, String) - Method in class meka.core.Result: SetInfo.
setinstance(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM.DistributionCalc
setinstances(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM.BuildClassifier
setinstances(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM.DistributionCalcM
setInstances(Instances) - Method in class meka.gui.components.AttributeSelectionPanel: Sets the instances who's attribute names will be displayed.
setInstances(Instances) - Method in class meka.gui.dataviewer.DataPanel: displays the given instances, i.e.
setInstances(Instances) - Method in class meka.gui.dataviewer.DataSortedTableModel: sets the data
setInstances(Instances) - Method in class meka.gui.dataviewer.DataTableModel: sets the data
setInstances(Instances) - Method in class meka.gui.dataviewer.DataViewerDialog: sets the instances to display
setIterations(int) - Method in class meka.classifiers.multilabel.meta.EM
setIv(int) - Method in class meka.classifiers.multitarget.SCC
setK(int) - Method in class meka.classifiers.multilabel.RAkELd: SetP - Sets the k parameter (size of partitions)
setK(int) - Method in class meka.classifiers.multitarget.RAkELd: SetP - Sets the k parameter (size of partitions)
setLabelsMissing(Instances) - Static method in class meka.core.MLUtils: SetLabelsMissing - Set all labels in D to missing.
setLabelsMissing(Instance) - Static method in class meka.core.MLUtils: SetLabelsMissing - Set all labels in x to missing.
setLabelsMissing(Instance, int) - Static method in class meka.core.MLUtils: SetLabelsMissing - Set all (L) labels in x to missing.
setLearningRate(double) - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
setLearningRate(double) - Method in class rbms.RBM
setLimit(int) - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
setLineWrap(boolean) - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Sets whether to line wrap or not.
setLowerRuns(int) - Method in class meka.experiment.evaluators.RepeatedRuns: Sets the lower number of runs to perform (included).
setM(int) - Method in class meka.classifiers.multilabel.PMCC: Set the population size
setM(int) - Method in class meka.classifiers.multilabel.RAkEL: SetM - Sets the M parameter (number of subsets)
setMarkdown(String) - Method in class meka.gui.core.MarkdownDialog: Sets the markdown text.
setMeasurement(String, Object) - Method in class meka.core.Result: Set the measurement for metric 'metric'.
setMeasurement(String) - Method in class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter: Sets the measurement to use.
setMeasurement(String) - Method in interface meka.experiment.statisticsexporters.FileBasedMeasurementEvaluationStatisticsExporter: Sets the measurement to use.
setMeasurement(String) - Method in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: Sets the measurement the model is for.
setMethod(String) - Method in class meka.classifiers.multilabel.MULAN: Set a prescribed MULAN classifier configuration.
setMinimumChars(int) - Method in class meka.gui.core.SearchPanel: Sets the minimum number of characters that the user needs to enter before triggering a search event.
setModel(String, String) - Method in class meka.core.Result: Set a model string.
setModel(ListModel) - Method in class meka.gui.core.ResultHistoryList: Sets the model to use, must derived from ResultHistoryList.ResultHistoryModel.
setModel(TableModel) - Method in class meka.gui.core.SortableAndSearchableTable: Sets the model to display - only SortableAndSearchableTable.getTableModelClass().
setModel(TableModel) - Method in class meka.gui.dataviewer.DataTable: sets the new model
setModified(boolean) - Method in class meka.gui.experimenter.AbstractSetupTab: Sets the modified state, updates the buttons.
setMomentum(double) - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
setMomentum(double) - Method in class rbms.RBM
setN(int) - Method in class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
setN(int) - Method in class meka.classifiers.multilabel.PS: SetN - Sets the subsampling value N, the (maximum) number of frequent labelsets to subsample from the infrequent labelsets.
setN(int) - Method in class meka.filters.multilabel.SuperNodeFilter
setNeuronsActivity(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setNeuronsActivityFileName(String) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setNotes(String) - Method in class meka.experiment.DefaultExperiment: Sets the notes.
setNotes(String) - Method in interface meka.experiment.Experiment: Sets the notes.
setNotificationEnabled(boolean) - Method in class meka.gui.dataviewer.DataSortedTableModel: sets whether the notification of changes is enabled
setNotificationEnabled(boolean) - Method in class meka.gui.dataviewer.DataTableModel: sets whether the notification of changes is enabled
setNumberAutoencoders(int) - Method in class meka.classifiers.multilabel.Maniac: Set the numberAutoencoders value.
setNumFolds(int) - Method in class meka.experiment.evaluators.CrossValidation: Set the number of folds.
setNumIterations(int) - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
setNumThreads(int) - Method in interface meka.core.ThreadLimiter: Sets the number of threads to use.
setNumThreads(int) - Method in class meka.experiment.evaluators.CrossValidation: Sets the number of threads to use.
setNumThreads(int) - Method in class meka.experiment.evaluators.RepeatedRuns: Sets the number of threads to use.
setO(int) - Method in class meka.classifiers.multilabel.PMCC: Set the temperature switch
setOptimalColumnWidth(int) - Method in class meka.gui.core.JTableHelper: sets the optimal column width for the given column.
setOptimalColumnWidth(JTable, int) - Static method in class meka.gui.core.JTableHelper: sets the optimal column width for the given column.
setOptimalColumnWidth() - Method in class meka.gui.core.JTableHelper: sets the optimal column width for all columns.
setOptimalColumnWidth(JTable) - Static method in class meka.gui.core.JTableHelper: sets the optimal column width for alls column if the given table.
setOptimalColumnWidth() - Method in class meka.gui.core.MekaTable: Sets the optimal column width for all columns.
setOptimalColumnWidth(int) - Method in class meka.gui.core.MekaTable: Sets the optimal column width for the specified column.
setOptimalColWidth() - Method in class meka.gui.dataviewer.DataPanel: calculates the optimal column width for the current column
setOptimalColWidths() - Method in class meka.gui.dataviewer.DataPanel: calculates the optimal column widths for all columns
setOptimalColWidths() - Method in class meka.gui.dataviewer.DataViewerMainPanel: sets the optimal column width for all columns
setOptimalHeaderWidth(int) - Method in class meka.gui.core.JTableHelper: sets the optimal header width for the given column.
setOptimalHeaderWidth(JTable, int) - Static method in class meka.gui.core.JTableHelper: sets the optimal header width for the given column.
setOptimalHeaderWidth() - Method in class meka.gui.core.JTableHelper: sets the optimal header width for all columns.
setOptimalHeaderWidth(JTable) - Static method in class meka.gui.core.JTableHelper: sets the optimal header width for alls column if the given table.
setOptimizeAE(boolean) - Method in class meka.classifiers.multilabel.Maniac: Set the OptimizeAE value.
setOptions(String[]) - Method in class meka.classifiers.multilabel.BCC
setOptions(String[]) - Method in class meka.classifiers.multilabel.BRq
setOptions(String[]) - Method in class meka.classifiers.multilabel.CC
setOptions(String[]) - Method in class meka.classifiers.multilabel.CCq
setOptions(String[]) - Method in class meka.classifiers.multilabel.CDN
setOptions(String[]) - Method in class meka.classifiers.multilabel.CDT
setOptions(String[]) - Method in class meka.classifiers.multilabel.CT
setOptions(String[]) - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
setOptions(String[]) - Method in class meka.classifiers.multilabel.Maniac: Sets the options to the given values in the array.
setOptions(String[]) - Method in class meka.classifiers.multilabel.MCC
setOptions(String[]) - Method in class meka.classifiers.multilabel.meta.EM
setOptions(String[]) - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
setOptions(String[]) - Method in class meka.classifiers.multilabel.meta.RandomSubspaceML
setOptions(String[]) - Method in class meka.classifiers.multilabel.MLCBMaD: Sets the options to the given values in the array.
setOptions(String[]) - Method in class meka.classifiers.multilabel.MULAN
setOptions(String[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork: Parses a given list of options.
setOptions(String[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast: Parses a given list of options.
setOptions(String[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse: Parses a given list of options.
setOptions(String[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH: Parses a given list of options.
setOptions(String[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT: Parses a given list of options.
setOptions(String[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange: Parses a given list of options.
setOptions(String[]) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV: Parses a given list of options.
setOptions(String[]) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork: Parses a given list of options.
setOptions(String[]) - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM: Parses a given list of options.
setOptions(String[]) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM: Parses a given list of options.
setOptions(String[]) - Method in class meka.classifiers.multilabel.NN.AbstractDeepNeuralNet
setOptions(String[]) - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
setOptions(String[]) - Method in class meka.classifiers.multilabel.PLST: Sets the options to the given values in the array.
setOptions(String[]) - Method in class meka.classifiers.multilabel.PMCC
setOptions(String[]) - Method in class meka.classifiers.multilabel.PS
setOptions(String[]) - Method in class meka.classifiers.multilabel.RAkEL
setOptions(String[]) - Method in class meka.classifiers.multilabel.RAkELd
setOptions(String[]) - Method in class meka.classifiers.multitarget.RAkELd
setOptions(String[]) - Method in class meka.classifiers.multitarget.SCC
setOptions(String[]) - Method in class meka.experiment.datasetproviders.AbstractDatasetProvider: Sets the options.
setOptions(String[]) - Method in class meka.experiment.datasetproviders.LocalDatasetProvider: Sets the options.
setOptions(String[]) - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Sets the options.
setOptions(String[]) - Method in class meka.experiment.DefaultExperiment: Sets the options.
setOptions(String[]) - Method in class meka.experiment.evaluationstatistics.AbstractEvaluationStatisticsHandler: Sets the options.
setOptions(String[]) - Method in class meka.experiment.evaluationstatistics.AbstractFileBasedEvaluationStatisticsHandler: Sets the options.
setOptions(String[]) - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Sets the options.
setOptions(String[]) - Method in class meka.experiment.evaluators.AbstractEvaluator: Sets the options.
setOptions(String[]) - Method in class meka.experiment.evaluators.AbstractMetaEvaluator: Sets the options.
setOptions(String[]) - Method in class meka.experiment.evaluators.CrossValidation: Sets the options.
setOptions(String[]) - Method in class meka.experiment.evaluators.PercentageSplit: Sets the options.
setOptions(String[]) - Method in class meka.experiment.evaluators.RepeatedRuns: Sets the options.
setOptions(String[]) - Method in class meka.experiment.filehandlers.AbstractExperimentFileHandler: Sets the options.
setOptions(String[]) - Method in class meka.experiment.statisticsexporters.AbstractEvaluationStatisticsExporter: Sets the options.
setOptions(String[]) - Method in class meka.experiment.statisticsexporters.AbstractFileBasedEvaluationStatisticsExporter: Sets the options.
setOptions(String[]) - Method in class meka.experiment.statisticsexporters.AbstractMeasurementEvaluationStatisticsExporter: Sets the options.
setOptions(String[]) - Method in class meka.experiment.statisticsexporters.AbstractMetaEvaluationStatisticsExporter: Sets the options.
setOptions(String[]) - Method in class meka.experiment.statisticsexporters.MultiExporter: Sets the options.
setOptions(String[]) - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Sets the options.
setOptions(String[]) - Method in class meka.experiment.statisticsexporters.WekaFilter: Sets the options.
setOptions(String[]) - Method in class meka.filters.unsupervised.attribute.MekaClassAttributes: Parses a given list of options.
setOptions(String[]) - Method in class rbms.RBM: Set Options - WEKA-style option processing.
setOwner(Experimenter) - Method in class meka.gui.experimenter.AbstractExperimenterTab: Sets the Experimenter instance this tab belongs to.
setOwner(Experimenter) - Method in class meka.gui.experimenter.menu.AbstractExperimenterMenuItem: Sets the owner.
setOwner(Explorer) - Method in class meka.gui.explorer.AbstractExplorerTab: Sets the Explorer instance this tab belongs to.
setOwner(AbstractExplorerTab) - Method in class meka.gui.explorer.AbstractResultHistoryPlugin
setP(int) - Method in class meka.classifiers.multilabel.PS: SetP - Sets the pruning value P, defining an infrequent labelset as one which occurs less than P times in the data (P = 0 defaults to LC).
setP(int) - Method in class meka.filters.multilabel.SuperNodeFilter
setParent(Container) - Method in class meka.gui.dataviewer.DataViewerMainPanel: sets the new parent frame
setPath(Instance, double[]) - Static method in class meka.core.CCUtils: SetPath - set 'path[]' into the first L attributes of Instance 'xy'.
setPayoff(String) - Method in class meka.classifiers.multilabel.MCC: Set the payoff function
setPopupMenuCustomizer(ResultHistoryList.ResultHistoryPopupMenuCustomizer) - Method in class meka.gui.core.ResultHistoryList: Sets the customizer to use for the popup menu.
setPreferredDimensionJSpinner(Dimension) - Method in class meka.gui.core.ParameterPanel: Sets the preferred dimension for JSpinner and derived classes.
setPreferredScrollableViewportSize(Dimension) - Method in class meka.gui.components.AttributeSelectionPanel
setPreferredSize(JPanel) - Method in class meka.gui.experimenter.AbstractSetupTab: Sets the preferred size of the panel.
setPreserveOrder(boolean) - Method in class meka.experiment.evaluators.CrossValidation: Sets whether to preserve the order instead of randomizing the data.
setPreserveOrder(boolean) - Method in class meka.experiment.evaluators.PercentageSplit: Sets whether to preserve the order instead of randomizing the data.
setProviders(DatasetProvider[]) - Method in class meka.experiment.datasetproviders.MultiDatasetProvider: Sets the dataset providers to use.
setRandomize(boolean) - Method in class meka.gui.explorer.ClassifyTabOptions: Sets the Randomize option
setReadOnly(boolean) - Method in class meka.gui.dataviewer.DataPanel: sets whether the model is read-only
setReadOnly(boolean) - Method in class meka.gui.dataviewer.DataSortedTableModel: sets whether the model is read-only
setReadOnly(boolean) - Method in class meka.gui.dataviewer.DataTable: sets whether the model is read-only
setReadOnly(boolean) - Method in class meka.gui.dataviewer.DataTableModel: sets whether the model is read-only
setRegularExpression(boolean) - Method in class meka.gui.core.SearchPanel: Sets whether the search text is a regular expression one or not.
setRows(int) - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Sets the rows.
setSamples(int) - Method in class meka.gui.explorer.ClassifyTabOptions: Sets the samples value for prequential evaluation.
setSearchString(String) - Method in class meka.gui.dataviewer.DataTable: sets the search string to look for in the table, NULL or "" disables the search
setSearchText(String) - Method in class meka.gui.core.SearchPanel: Sets the search text.
setSeed(int) - Method in class meka.classifiers.multilabel.BRq
setSeed(int) - Method in class meka.classifiers.multilabel.CC
setSeed(int) - Method in class meka.classifiers.multilabel.CCq
setSeed(int) - Method in class meka.classifiers.multilabel.CDN
setSeed(int) - Method in class meka.classifiers.multilabel.meta.MetaProblemTransformationMethod
setSeed(int) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
setSeed(int) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setSeed(int) - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
setSeed(int) - Method in class meka.classifiers.multilabel.PS: SetSeed - Use random P and N values (in this case P and N arguments determine a range of values to select from randomly, e.g., -P 1-5 selects P randomly in {1,2,3,4,5}.
setSeed(int) - Method in class meka.experiment.evaluators.CrossValidation: Set the seed for random number generation.
setSeed(int) - Method in class meka.experiment.evaluators.PercentageSplit: Set the seed for random number generation.
setSeed(int) - Method in class meka.gui.explorer.ClassifyTabOptions: Sets the seed value.
setSeed(int) - Method in class rbms.RBM
setSelectedAttributes(boolean[]) - Method in class meka.gui.components.AttributeSelectionPanel: Set the selected attributes in the widget.
setSelectedColumn(int) - Method in class meka.gui.dataviewer.DataTable: sets the selected column
setSessionValue(String, Object) - Method in class meka.gui.explorer.AbstractResultHistoryPlugin: Sets a session value.
setSessionValue(T, String, Object) - Method in class meka.gui.explorer.AbstractTabMenuItem: Sets a session value.
setShowAttributeIndex(boolean) - Method in class meka.gui.dataviewer.DataPanel: Sets whether to display the attribute index in the header.
setShowAttributeIndex(boolean) - Method in class meka.gui.dataviewer.DataSortedTableModel: Sets whether to display the attribute index in the header.
setShowAttributeIndex(boolean) - Method in class meka.gui.dataviewer.DataTableModel: Sets whether to display the attribute index in the header.
setShowIndex(boolean) - Method in class meka.gui.core.MeasurementEvaluationStatisticsTableModel: Sets whether to show an index or the classifier in the header.
setSize(int) - Method in class meka.classifiers.multilabel.MLCBMaD: Sets the size of the compressed labels.
setSize(int) - Method in class meka.classifiers.multilabel.PLST: Sets the size of the compressed labels.
setSkipCount(boolean) - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Sets whether to skip the count.
setSkipMean(boolean) - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Sets whether to skip the mean.
setSkipStdDev(boolean) - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Sets whether to skip the stdDev.
setSortNewTableModel(boolean) - Method in class meka.gui.core.SortableAndSearchableTable: Sets whether to sort new models.
setSparse(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setSparseH(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setSparseHT(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setSplitPercentage(double) - Method in class meka.gui.explorer.ClassifyTabOptions: Sets the percentage value.
setStatisticsHandler(EvaluationStatisticsHandler) - Method in class meka.experiment.DefaultExperiment: Sets the statistics handler.
setStatisticsHandler(EvaluationStatisticsHandler) - Method in interface meka.experiment.Experiment: Sets the statistics handler.
setSuffixCount(String) - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Sets the suffix for the count.
setSuffixMean(String) - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Sets the suffix for the mean.
setSuffixStdDev(String) - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Sets the suffix for the stddev.
setSupport(int) - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
setTabTitle(JComponent) - Method in class meka.gui.dataviewer.DataViewerMainPanel: sets the title of the tab that contains the given component
setTemplate(Instance, Instances) - Static method in class meka.core.MLUtils
setTemplate(Instance, Instance, Instances) - Static method in class meka.core.MLUtils: SetTemplate - returns a copy of x_template, set with x's attributes, and set to dataset D_template (of which x_template) is a template of this.
setTestData(Instances) - Method in class meka.gui.explorer.ClassifyTab: Sets the test instances.
setText(String) - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Sets the markdown code to display.
setText(String) - Method in class meka.gui.core.MarkdownTextPane: Sets the Markdown text and renders it.
setTextColumns(int) - Method in class meka.gui.core.SearchPanel: Sets the number of columns for the text field.
setTextFont(Font) - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Sets the text font.
setThreaded(boolean) - Method in interface meka.classifiers.multilabel.MultiLabelClassifierThreaded
setThreaded(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
setThreaded(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast
setThreaded(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse
setThreaded(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH
setThreaded(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT
setThreaded(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange
setThreaded(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV
setThreaded(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
setThreaded(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM
setThreaded(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setThreadedVoters(boolean) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setThreshold(double) - Method in class meka.classifiers.multilabel.MLCBMaD: Sets the threshold for the Boolean matrix decomposition.
setThreshold(double) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
setThreshold(double) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setThreshold(String) - Method in class meka.experiment.evaluators.CrossValidation: Set the threshold option.
setThreshold(String) - Method in class meka.experiment.evaluators.PercentageSplit: Set the threshold option.
setTOP(String) - Method in class meka.gui.explorer.ClassifyTabOptions: Sets the threshold option
setTrainPercentage(double) - Method in class meka.experiment.evaluators.PercentageSplit: Set the percentage to use for training.
setUndoEnabled(boolean) - Method in class meka.gui.dataviewer.DataPanel: sets whether undo support is enabled
setUndoEnabled(boolean) - Method in class meka.gui.dataviewer.DataSortedTableModel: sets whether undo support is enabled
setUndoEnabled(boolean) - Method in class meka.gui.dataviewer.DataTableModel: sets whether undo support is enabled
setUnsortedModel(TableModel) - Method in class meka.gui.core.SortableAndSearchableTable: Sets the base model to use.
setUnsortedModel(TableModel, boolean) - Method in class meka.gui.core.SortableAndSearchableTable: Sets the base model to use.
setUnsortedModel(TableModel) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Sets the model to use.
setUnsortedModel(TableModel, boolean) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Sets the model to use.
setUnsortedModel(TableModel) - Method in interface meka.gui.core.SortableTable: Sets the base model to use.
setUnsortedModel(TableModel) - Method in interface meka.gui.core.SortableTableModel: Sets the base model to use.
setUp(Instances) - Method in class meka.classifiers.multilabel.meta.FilteredClassifier: Sets up the filter and runs checks.
Setup(File, Object) - Constructor for class meka.gui.core.RecentFilesHandlerWithCommandline.Setup: Initializes the setup container.
Setup(String) - Constructor for class meka.gui.core.RecentFilesHandlerWithCommandline.Setup: Initializes the setup container using the string.
setUpperRuns(int) - Method in class meka.experiment.evaluators.RepeatedRuns: Sets the upper number of runs to perform (included).
setUseOptimalColumnWidhts(boolean) - Method in class meka.gui.core.SortableAndSearchableTable: Sets whether to automatically set optimal column widths.
setValue(String, double) - Method in class meka.core.Result: SetValue.
setValueAt(int, Double) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Given an index in the range 0...size()-1, sets a new value for the indexth key-value mapping that this SparseArray stores.
setValueAt(Object, int, int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: Sets the value in the cell at columnIndex and rowIndex to aValue.
setValueAt(Object, int, int) - Method in class meka.gui.dataviewer.DataTableModel: sets the value in the cell at columnIndex and rowIndex to aValue.
setValueAt(Object, int, int, boolean) - Method in class meka.gui.dataviewer.DataTableModel: sets the value in the cell at columnIndex and rowIndex to aValue.
setValues(Instance, double[], int) - Static method in class meka.core.MLUtils: SetValues - set the attribute values in Instsance x (having L labels) to z[].
setVerbosity(String) - Method in class meka.experiment.evaluators.CrossValidation: Set the verbosity option.
setVerbosity(String) - Method in class meka.experiment.evaluators.PercentageSplit: Set the verbosity option.
setVigilancy(double) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork
setVigilancy(double) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setVisible(boolean) - Method in class meka.gui.core.MekaDialog: closes/shows the dialog.
setVisible(boolean) - Method in class meka.gui.core.MekaFrame: closes/shows the dialog.
setVOP(String) - Method in class meka.gui.explorer.ClassifyTabOptions: Sets the verbosity option
setVoters(int) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
setWidth(int) - Method in class meka.classifiers.multilabel.CDT: SetH - Sets the trellis width.
setWidth(int) - Method in class meka.classifiers.multilabel.CT: SetH - Sets the trellis width.
setWrapStyleWord(boolean) - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Sets whether to word wrap or not.
shallowCopy(OptionHandler) - Static method in class meka.core.OptionUtils: Creates a shallow copy of the option handler, just using its options.
show(int) - Method in class meka.gui.core.StatusBar.Animation: Shows the specified
showAttributes() - Method in class meka.gui.dataviewer.DataViewerMainPanel: displays all the attributes, returns the selected item or NULL if canceled
showCell(int, int) - Method in class meka.gui.core.MekaTable: Displays the specified cell.
showDialog(Component, String) - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Pops a custom file chooser dialog with a custom approve button.
showDialog() - Method in class meka.gui.dataviewer.DataViewerDialog: Pops up the modal dialog and waits for Cancel or OK.
showDialog(Instances) - Method in class meka.gui.dataviewer.DataViewerDialog: Pops up the modal dialog and waits for Cancel or OK.
ShowGraphs - Class in meka.gui.explorer.classify: Allows the user to displays graphs if available.
ShowGraphs() - Constructor for class meka.gui.explorer.classify.ShowGraphs
ShowMacroCurve - Class in meka.gui.explorer.classify: Allows the user to display the precision recall curves per label.
ShowMacroCurve() - Constructor for class meka.gui.explorer.classify.ShowMacroCurve
ShowMicroCurve - Class in meka.gui.explorer.classify: Allows the user to displays graphs of the performance of an incremental classifier if available.
ShowMicroCurve() - Constructor for class meka.gui.explorer.classify.ShowMicroCurve
showOpenDialog(Component) - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Pops up an "Open File" file chooser dialog.
showOpenDialog(Component) - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Pops up an "Open File" file chooser dialog.
showOptions() - Method in class meka.gui.explorer.ClassifyTab: Brings up the dialog with the classification options.
ShowPrecisionRecall - Class in meka.gui.explorer.classify: Allows the user to display the precision recall curves per label.
ShowPrecisionRecall() - Constructor for class meka.gui.explorer.classify.ShowPrecisionRecall
showProperties() - Method in class meka.gui.dataviewer.DataViewerMainPanel: displays some properties of the instances
ShowROC - Class in meka.gui.explorer.classify: Allows the user to display the ROC curves per label.
ShowROC() - Constructor for class meka.gui.explorer.classify.ShowROC
showSaveDialog(Component) - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: Pops up an "Save File" file chooser dialog.
showSaveDialog(Component) - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Pops up an "Save File" file chooser dialog.
showStatus(String) - Method in class meka.gui.core.StatusBar: Displays the specified status message.
showStatus(String) - Method in class meka.gui.experimenter.AbstractExperimenterTab: Displays the specified status message.
showStatus(String) - Method in class meka.gui.explorer.AbstractExplorerTab: Displays the specified status message.
showValues() - Method in class meka.gui.dataviewer.DataViewerMainPanel: displays all the distinct values for an attribute
shuffle(int[], Random) - Static method in class meka.core.A: Shuffle 'array' given Random 'r'
sigma(double) - Static method in class meka.classifiers.multitarget.SCC: Sigmoid / Logistic function
sigma(double) - Static method in class meka.core.MatrixUtils: Sigmoid / Logistic function
sigma(double[]) - Static method in class meka.core.MatrixUtils: Sigmoid function applied to vector
sigma(double[][]) - Static method in class meka.core.MatrixUtils: Sigmoid function applied to matrix (2D array)
sigma(Matrix) - Static method in class meka.core.MatrixUtils: Sigmoid function applied to Matrix
SimpleAggregate - Class in meka.experiment.statisticsexporters: Simple aggregator of statistics.
SimpleAggregate() - Constructor for class meka.experiment.statisticsexporters.SimpleAggregate
size - Variable in class meka.classifiers.multilabel.MLCBMaD: The size of the compressed matrix, i.e., the number of columns of Y'.
size() - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Returns the number of key-value mappings that this SparseArray currently stores.
size() - Method in class meka.classifiers.multilabel.neurofuzzy.SparseVector
size() - Method in class meka.classifiers.multilabel.neurofuzzy.ST: Returns the number of key-value pairs in this symbol table.
size() - Method in class meka.core.Result: The number of value-prediction pairs stared in this Result
size() - Method in class meka.gui.core.AbstractRecentItemsHandler: Returns the number of recent items currently stored.
size() - Method in class meka.gui.core.ResultHistory: Returns the number of history items stored.
sizeTipText() - Method in class meka.classifiers.multilabel.MLCBMaD: The tooltip for the size.
sizeTipText() - Method in class meka.classifiers.multilabel.PLST: The tooltip for the size.
skipCountTipText() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Describes this property.
skipMeanTipText() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Describes this property.
skipStdDevTipText() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Describes this property.
SLTransformation(Instances, int, String, int, int) - Static method in class meka.core.PSUtils: Transform instances into a multi-class representation.
SLTransformation(Instances, int[][], int, int) - Static method in class meka.core.SuperLabelUtils: Super Label Transformation - transform dataset D into a dataset with k multi-class target attributes.
sort(int[]) - Static method in class meka.core.A
sort(int) - Method in class meka.gui.core.SortableAndSearchableTable: sorts the table over the given column (ascending).
sort(int, boolean) - Method in class meka.gui.core.SortableAndSearchableTable: sorts the table over the given column, either ascending or descending.
sort(int) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: sorts the table over the given column (ascending).
sort(int, boolean) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: sorts the table over the given column, either ascending or descending.
sort(int) - Method in interface meka.gui.core.SortableTable: sorts the table over the given column (ascending).
sort(int, boolean) - Method in interface meka.gui.core.SortableTable: sorts the table over the given column, either ascending or descending.
sort(int) - Method in interface meka.gui.core.SortableTableModel: sorts the table over the given column (ascending).
sort(int, boolean) - Method in interface meka.gui.core.SortableTableModel: sorts the table over the given column, either ascending or descending.
sort(int, boolean) - Method in class meka.gui.dataviewer.DataSortedTableModel: sorts the table over the given column, either ascending or descending
SortableAndSearchableTable - Class in meka.gui.core: A specialized JTable that allows double-clicking on header for resizing to optimal width, as well as being searchable and sortable.
SortableAndSearchableTable() - Constructor for class meka.gui.core.SortableAndSearchableTable: Constructs a default SortedBaseTable that is initialized with a default data model, a default column model, and a default selection model.
SortableAndSearchableTable(int, int) - Constructor for class meka.gui.core.SortableAndSearchableTable: Constructs a SortedBaseTable with numRows and numColumns of empty cells using DefaultTableModel.
SortableAndSearchableTable(Object[][], Object[]) - Constructor for class meka.gui.core.SortableAndSearchableTable: Constructs a SortedBaseTable to display the values in the two dimensional array, rowData, with column names, columnNames.
SortableAndSearchableTable(Vector, Vector) - Constructor for class meka.gui.core.SortableAndSearchableTable: Constructs a SortedBaseTable to display the values in the Vector of Vectors, rowData, with column names, columnNames.
SortableAndSearchableTable(TableModel) - Constructor for class meka.gui.core.SortableAndSearchableTable: Constructs a SortedBaseTable that is initialized with dm as the data model, a default column model, and a default selection model.
SortableAndSearchableTable(TableModel, TableColumnModel) - Constructor for class meka.gui.core.SortableAndSearchableTable: Constructs a SortedBaseTable that is initialized with dm as the data model, cm as the column model, and a default selection model.
SortableAndSearchableTable(TableModel, TableColumnModel, ListSelectionModel) - Constructor for class meka.gui.core.SortableAndSearchableTable: Constructs a SortedBaseTable that is initialized with dm as the data model, cm as the column model, and sm as the selection model.
SortableAndSearchableWrapperTableModel - Class in meka.gui.core: Wraps around any table model and makes them automatically sortable and searchable.
SortableAndSearchableWrapperTableModel() - Constructor for class meka.gui.core.SortableAndSearchableWrapperTableModel: initializes with no model.
SortableAndSearchableWrapperTableModel(TableModel) - Constructor for class meka.gui.core.SortableAndSearchableWrapperTableModel: initializes with the given model.
SortableAndSearchableWrapperTableModel.SortContainer - Class in meka.gui.core: Helper class for sorting the columns.
SortableTable - Interface in meka.gui.core: Interface for tables that are sortable.
SortableTableModel - Interface in meka.gui.core: Interface for table models that are sortable.
SortContainer(Comparable, int) - Constructor for class meka.gui.core.SortableAndSearchableWrapperTableModel.SortContainer: Initializes the container.
sortInstances() - Method in class meka.gui.dataviewer.DataPanel: sorts the instances via the currently selected column
sortInstances(int) - Method in class meka.gui.dataviewer.DataSortedTableModel: sorts the instances via the given attribute
sortInstances(int, boolean) - Method in class meka.gui.dataviewer.DataSortedTableModel: sorts the instances via the given attribute
sortInstances(int) - Method in class meka.gui.dataviewer.DataTableModel: sorts the instances via the given attribute
sortInstances(int, boolean) - Method in class meka.gui.dataviewer.DataTableModel: sorts the instances via the given attribute
sortInstances() - Method in class meka.gui.dataviewer.DataViewerMainPanel: sorts the current selected attribute
SparseArray - Class in meka.classifiers.multilabel.neurofuzzy: SparseArrays map integers to Objects.
SparseArray() - Constructor for class meka.classifiers.multilabel.neurofuzzy.SparseArray: Creates a new SparseArray containing no mappings.
SparseArray(int) - Constructor for class meka.classifiers.multilabel.neurofuzzy.SparseArray: Creates a new SparseArray containing no mappings that will not require any additional memory allocation to store the specified number of mappings.
sparseHTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
sparseHTTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
sparseTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
SparseVector - Class in meka.classifiers.multilabel.neurofuzzy
SparseVector(int) - Constructor for class meka.classifiers.multilabel.neurofuzzy.SparseVector
squaredError(double[], double[]) - Static method in class meka.core.MatrixUtils
SS(double[][]) - Static method in class meka.core.MatrixUtils: squared sum
ST<Key extends Comparable<Key>,Value> - Class in meka.classifiers.multilabel.neurofuzzy: The ST class represents an ordered symbol table of generic key-value pairs.
ST() - Constructor for class meka.classifiers.multilabel.neurofuzzy.ST: Initializes an empty symbol table.
start() - Method in class meka.gui.experimenter.Experimenter: Starts the experiment.
start(Runnable) - Method in class meka.gui.explorer.AbstractThreadedExplorerTab: Starts the task.
startBusy() - Method in class meka.gui.core.StatusBar: Starts the animated icon, without setting status message.
startBusy(String) - Method in class meka.gui.core.StatusBar: Starts the animated icon, setting the specified status message.
startBusy() - Method in class meka.gui.experimenter.AbstractExperimenterTab: Starts the animated icon, without setting status message.
startBusy(String) - Method in class meka.gui.experimenter.AbstractExperimenterTab: Starts the animated icon, setting the specified status message.
startBusy() - Method in class meka.gui.explorer.AbstractExplorerTab: Starts the animated icon, without setting status message.
startBusy(String) - Method in class meka.gui.explorer.AbstractExplorerTab: Starts the animated icon, setting the specified status message.
startClassification() - Method in class meka.gui.explorer.ClassifyTab: Starts the classification.
stateChanged(ChangeEvent) - Method in class meka.gui.dataviewer.DataPanel: Invoked when the target of the listener has changed its state.
stateChanged(ChangeEvent) - Method in class meka.gui.dataviewer.DataViewerDialog: Invoked when the target of the listener has changed its state.
stateChanged(ChangeEvent) - Method in class meka.gui.dataviewer.DataViewerMainPanel: Invoked when the target of the listener has changed its state.
Statistics - Class in meka.gui.experimenter: Tab for evaluating an experiment.
Statistics() - Constructor for class meka.gui.experimenter.Statistics
statisticsAvailable(StatisticsNotificationEvent) - Method in interface meka.experiment.events.StatisticsNotificationListener: Gets called if new statistics have become available.
statisticsAvailable(StatisticsNotificationEvent) - Method in class meka.gui.experimenter.Experimenter: Gets called if new statistics have become available.
statisticsAvailable(StatisticsNotificationEvent) - Method in class meka.gui.experimenter.Statistics: Gets called if new statistics have become available.
statisticsHandlerTipText() - Method in class meka.experiment.DefaultExperiment: Describes this property.
statisticsHandlerTipText() - Method in interface meka.experiment.Experiment: Describes this property.
StatisticsNotificationEvent - Class in meka.experiment.events: Event that gets sent by an experiment when new statistics become available.
StatisticsNotificationEvent(Experiment, List<EvaluationStatistics>) - Constructor for class meka.experiment.events.StatisticsNotificationEvent: Gets called when the experiment makes new statistics available.
StatisticsNotificationListener - Interface in meka.experiment.events: Interface for classes that want to be notified whenever new statistics are available.
StatusBar - Class in meka.gui.core: Statusbar for displaying short notifications and an animated icon, e.g., when busy doing calculations.
StatusBar() - Constructor for class meka.gui.core.StatusBar
StatusBar.Animation - Class in meka.gui.core: the runnable for the animation.
StatUtils - Class in meka.core: StatUtils - Helpful statistical functions.
StatUtils() - Constructor for class meka.core.StatUtils
stop() - Method in class meka.experiment.DefaultExperiment: Stops the experiment if running.
stop() - Method in class meka.experiment.evaluators.AbstractEvaluator: Stops the evaluation, if possible.
stop() - Method in class meka.experiment.evaluators.AbstractMetaEvaluator: Stops the evaluation, if possible.
stop() - Method in class meka.experiment.evaluators.CrossValidation: Stops the evaluation, if possible.
stop() - Method in interface meka.experiment.evaluators.Evaluator: Stops the evaluation, if possible.
stop() - Method in class meka.experiment.evaluators.RepeatedRuns: Stops the evaluation, if possible.
stop() - Method in interface meka.experiment.Experiment: Stops the experiment if still running.
stop() - Method in class meka.gui.experimenter.Experimenter: Stops the current experiment.
stop() - Method in class meka.gui.explorer.AbstractThreadedExplorerTab: Stops the execution.
stopAnimation() - Method in class meka.gui.core.StatusBar.Animation: Stops the animation.
stopClassification() - Method in class meka.gui.explorer.ClassifyTab: Stops the classification, if running.
stripMnemonic(String) - Static method in class meka.gui.core.GUIHelper: Removes the mnemonic indicator in this caption.
subset(int[], int[]) - Static method in class meka.core.LabelSet: Subset - returns > 0 if y1 \subsetof y2
SubsetMapper - Class in meka.classifiers.multilabel.meta: Maps the output of a multi-label classifier to a known label combination using the hamming distance.
SubsetMapper() - Constructor for class meka.classifiers.multilabel.meta.SubsetMapper
subsetof(LabelSet) - Method in class meka.core.LabelSet
subtract(double[][], double[][]) - Static method in class meka.core.MatrixUtils
SUFFIX_COUNT - Static variable in class meka.experiment.statisticsexporters.SimpleAggregate: the suffix for the count.
SUFFIX_MEAN - Static variable in class meka.experiment.statisticsexporters.SimpleAggregate: the suffix for the mean.
SUFFIX_STDEV - Static variable in class meka.experiment.statisticsexporters.SimpleAggregate: the suffix for the stdev.
suffixCountTipText() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Describes this property.
suffixMeanTipText() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Describes this property.
suffixStdDevTipText() - Method in class meka.experiment.statisticsexporters.SimpleAggregate: Describes this property.
sum() - Method in class meka.classifiers.multilabel.neurofuzzy.SparseVector
sum(double[]) - Static method in class meka.core.A
sum(int[]) - Static method in class meka.core.A
sum(int[][]) - Static method in class meka.core.MatrixUtils: Sum - sum this matrix.
sum(double[][]) - Static method in class meka.core.MatrixUtils: Sum - sum this matrix.
sumCounts(HashMap<LabelSet, Integer>) - Static method in class meka.core.PSUtils: Sum Counts - sum all the values in 'map'.
SuperLabel - Class in meka.core: SuperLabel - A meta label is a label composed of multiple labels, e.g., [3,7], which can take multiple values, e.g., [[0,0],[0,1],[1,1]].
SuperLabel(int[], int[][]) - Constructor for class meka.core.SuperLabel: SuperLabel
SuperLabel(int[], Enumeration<String>) - Constructor for class meka.core.SuperLabel
SuperLabel(int[], ArrayList<String>) - Constructor for class meka.core.SuperLabel
SuperLabelUtils - Class in meka.core: SuperLabelUtils.java - Handy Utils for working with Meta Labels.
SuperLabelUtils() - Constructor for class meka.core.SuperLabelUtils
SuperNodeFilter - Class in meka.filters.multilabel: SuperNodeFilter.java - Super Class Filter.
SuperNodeFilter() - Constructor for class meka.filters.multilabel.SuperNodeFilter
supportsIncrementalUpdate() - Method in interface meka.experiment.evaluationstatistics.IncrementalEvaluationStatisticsHandler: Returns whether the handler supports incremental write.
supportsIncrementalUpdate() - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Returns whether the handler supports incremental write.
supportTipText() - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
swap(int, int) - Method in class meka.classifiers.multilabel.cc.Trellis
swap(int[], int, int) - Static method in class meka.core.A
swap(int[], Random) - Static method in class meka.core.A
SystemInfo - Class in meka.core: Gathers information about the system environment.
SystemInfo() - Constructor for class meka.core.SystemInfo
SystemInfo - Class in meka.gui.guichooser: Displays the system info data.
SystemInfo() - Constructor for class meka.gui.guichooser.SystemInfo

T

TAB_AGGREGATED - Static variable in class meka.gui.experimenter.Statistics
TAB_INSTANCES - Static variable in class meka.gui.dataviewer.DataPanel: the name of the tab for instances that were set directly
TAB_MEASUREMENT - Static variable in class meka.gui.experimenter.Statistics
TAB_RAW - Static variable in class meka.gui.experimenter.Statistics
tableChanged(TableModelEvent) - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel: This fine grain notification tells listeners the exact range of cells, rows, or columns that changed.
tableChanged(TableModelEvent) - Method in class meka.gui.dataviewer.DataTable: This fine grain notification tells listeners the exact range of cells, rows, or columns that changed.
TabSeparated - Class in meka.experiment.statisticsexporters: Exports the statistics to a tab-separated file.
TabSeparated() - Constructor for class meka.experiment.statisticsexporters.TabSeparated
TabSeparatedMeasurement - Class in meka.experiment.statisticsexporters: Exports a single statistic to a tab-separated file.
TabSeparatedMeasurement() - Constructor for class meka.experiment.statisticsexporters.TabSeparatedMeasurement
testCapabilities(Instances) - Method in class meka.classifiers.multilabel.AbstractMultiLabelClassifier: TestCapabilities.
testCapabilities(Instances) - Method in class meka.classifiers.multilabel.LabelTransformationClassifier: TestCapabilities.
testCapabilities(Instances) - Method in class meka.classifiers.multilabel.meta.FilteredClassifier: TestCapabilities.
testCapabilities(Instances) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkClass: Generates the classifier.
testCapabilities(Instances) - Method in class meka.classifiers.multilabel.ProblemTransformationMethod: TestCapabilities.
testClassifier(MultiLabelClassifier, Instances) - Static method in class meka.classifiers.multilabel.Evaluation: TestClassifier - test classifier h on D_test
testClassifier(Classifier, Instances, Instances, int[][]) - Method in class meka.classifiers.multitarget.SCC: Test classifier h, on dataset D, under super-class partition 'partition'.
testClassifierM(MultiLabelClassifier, Instances) - Static method in class meka.classifiers.multilabel.Evaluation: Test Classifier but threaded (Multiple)
threadedTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
threadedVotersTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
ThreadLimiter - Interface in meka.core: Interface for classes that allow limiting the number of threads in use.
ThreadUtils - Class in meka.core: Thread and multi-process related methods.
ThreadUtils() - Constructor for class meka.core.ThreadUtils
threshold - Variable in class meka.classifiers.multilabel.MLCBMaD: The threshold t of the decomposition process, see the paper for details.
threshold - Variable in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork
threshold - Variable in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkClass
threshold(double[][], double) - Static method in class meka.core.MatrixUtils: Threshold - apply threshold t to matrix P[][].
threshold(double[][], Random) - Static method in class meka.core.MatrixUtils: sample from matrix
threshold(double[], double) - Static method in class meka.core.MatrixUtils: threshold function applied to vector
threshold(Matrix, double) - Static method in class meka.core.MatrixUtils: sigmoid function applied to vector
threshold(double[][], double[]) - Static method in class meka.core.ThresholdUtils: Threshold - returns the labels after the prediction-confidence vector is passed through a vector of thresholds.
threshold(double[][], double) - Static method in class meka.core.ThresholdUtils: Threshold - returns the labels after the prediction-confidence vector is passed through threshold.
threshold(double[], String) - Static method in class meka.core.ThresholdUtils: Threshold - returns the labels after the prediction-confidence vector is passed through threshold(s).
thresholdStringToArray(String, int) - Static method in class meka.core.ThresholdUtils: ThresholdStringToArray - parse a threshold option string to an array of L thresholds (one for each label variable).
thresholdTipText() - Method in class meka.classifiers.multilabel.MLCBMaD: Tooltip for the threshold.
thresholdTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
thresholdTipText() - Method in class meka.experiment.evaluators.CrossValidation: Describes this property.
thresholdTipText() - Method in class meka.experiment.evaluators.PercentageSplit: Describes this property.
ThresholdUtils - Class in meka.core: ThresholdUtils - Helpful functions for calibrating thresholds.
ThresholdUtils() - Constructor for class meka.core.ThresholdUtils
throwableToString(Throwable) - Static method in class meka.core.ExceptionUtils: Returns the stacktrace of the throwable as string.
throwableToString(Throwable, int) - Static method in class meka.core.ExceptionUtils: Returns the stacktrace of the throwable as string.
toArray(List<String>) - Static method in class meka.core.OptionUtils: Turns the list of options into an array.
toBinaryString(int, int) - Static method in class meka.core.MLUtils: ToBinaryString - use to go through all 'L' binary combinations.
toBitString(Instance, int) - Static method in class meka.core.MLUtils: ToBitString - returns a String representation of x = [0,0,1,0,1,0,0,0], e.g., "000101000".
toBitString(int[]) - Static method in class meka.core.MLUtils: ToBitString - returns a String representation of i[].
toBitString(double[]) - Static method in class meka.core.MLUtils: ToBitString - returns a String representation of d[].
toCommandLine(Object) - Static method in class meka.core.OptionUtils: Returns the commandline string for the object.
toDebugString(Instances) - Static method in class meka.core.MLUtils
toDebugString(Instance) - Static method in class meka.core.MLUtils
toDoubleArray(int[]) - Static method in class meka.core.A: ToDoubleArray - cast int[] to double[].
toDoubleArray(int, int) - Static method in class meka.core.A: Convert integer to binary string (double representation) of L digits.
toDoubleArray(Instance, int) - Static method in class meka.core.MLUtils: Instance with L labels to double[] of length L.
toDoubleArray(Instance) - Static method in class meka.core.MLUtils: Instance with L labels to double[] of length L, where L = x.classIndex().
toDoubleArray(String) - Static method in class meka.core.MLUtils: To Double Arary - Convert something like "[1.0,2.0]" to [1.0,2.0]
toDoubleArray(String[]) - Static method in class meka.core.MLUtils: To Double Arary - Convert something like ["1.0","2.0"] to [1.0,2.0]
toEnumeration(Vector) - Static method in class meka.core.OptionUtils: Returns the option descriptions as an enumeration.
toExperiment() - Method in class meka.gui.experimenter.AbstractSetupTab: Stores the parameters in an experiment.
toExperiment() - Method in class meka.gui.experimenter.BasicSetup: Stores the parameters in an experiment.
toExperiment() - Method in class meka.gui.experimenter.ExpertSetup: Stores the parameters in an experiment.
toIndicesSet(double[], double) - Static method in class meka.core.MLUtils: To Indices Set - return the indices in x[], whose values are greater than t, e.g., [0.3,0.0,0.5,0.8],0.4 to {2,3}.
toIndicesSet(int[]) - Static method in class meka.core.MLUtils: To Indices Set - return the indices in x[], whose values are greater than 0, e.g., [0,0,1,1] to {2,3}.
toIndicesSet(Instance, int) - Static method in class meka.core.MLUtils: To Indices Set - return the indices in x, whose values are greater than 1.
toInstances(List<EvaluationStatistics>) - Method in class meka.experiment.statisticsexporters.WekaFilter: Turns the statistics into Instances.
toIntArray(String) - Static method in class meka.core.A: Convert eg "12" to [1,2].
toIntArray(String[]) - Static method in class meka.core.A: Convert eg ["1","2"] to [1,2]
toIntArray(double[]) - Static method in class meka.core.A: Convert an array of doubles to ints through a threshold.
toIntArray(double[], double) - Static method in class meka.core.A: Convert an array of doubles to ints through a threshold.
toIntArray(double[]) - Static method in class meka.core.Metrics: Helper function for missing values in the labels.
toIntArray(String) - Static method in class meka.core.MLUtils: ToIntArray - Return an int[] from a String, e.g., "[0,1,2,0]" to [0,1,2,3].
toIntArray(String[]) - Static method in class meka.core.MLUtils: ToIntArray - Return an int[] from a String[], e.g., ["0","1","2","3"] to [0,1,2,3].
toIntArray(Instance, int) - Static method in class meka.core.MLUtils: ToIntArray - raw instance to int[] representation
toIntArray(double[], double) - Static method in class meka.core.MLUtils: Deprecated.
toPrimitive(Integer[]) - Static method in class meka.core.A: ToPrimitive - cast Integer[] to int[].
toPrimitive(Double[]) - Static method in class meka.core.A: ToPrimitive - cast Double[] to double[].
toPrimitive(List<Integer>) - Static method in class meka.core.A: ToPrimitive - cast List<Integer> to int[].
toPrimitive(Integer[]) - Static method in class meka.core.MLUtils
toSparseIntArray(Instance, int) - Static method in class meka.core.MLUtils: To Sparse Int Array - A sparse String representation, e.g., [1,34,73].
toString() - Method in class meka.classifiers.multilabel.AbstractMultiLabelClassifier
toString() - Method in class meka.classifiers.multilabel.CC
toString() - Method in class meka.classifiers.multilabel.cc.Trellis
toString() - Method in class meka.classifiers.multilabel.CCq.QLink
toString() - Method in class meka.classifiers.multilabel.CT
toString() - Method in class meka.classifiers.multilabel.incremental.CCUpdateable.ULink
toString() - Method in class meka.classifiers.multilabel.LC
toString() - Method in class meka.classifiers.multilabel.Maniac
toString() - Method in class meka.classifiers.multilabel.meta.DeepML
toString() - Method in class meka.classifiers.multilabel.MLCBMaD
toString() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork: Returns a description of the classifier.
toString() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast: Returns a description of the classifier.
toString() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse: Returns a description of the classifier.
toString() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH: Returns a description of the classifier.
toString() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT: Returns a description of the classifier.
toString() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange: Returns a description of the classifier.
toString() - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV: Returns a description of the classifier.
toString() - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork: Returns a description of the classifier.
toString() - Method in class meka.classifiers.multilabel.neurofuzzy.SparseVector
toString() - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM: Returns a description of the classifier.
toString() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM: Returns a description of the classifier.
toString() - Method in class meka.classifiers.multilabel.NN.AbstractNeuralNet
toString() - Method in class meka.classifiers.multilabel.PLST
toString() - Method in class meka.classifiers.multilabel.ProblemTransformationMethod
toString() - Method in class meka.classifiers.multilabel.RAkELd
toString() - Method in class meka.classifiers.multitarget.CCp.Link
toString() - Method in class meka.classifiers.multitarget.RAkELd
toString(double[]) - Static method in class meka.core.A: ToString - Return a double[] as a nice String.
toString(double[], int) - Static method in class meka.core.A: ToString - Return a double[] as a nice String (formated to a 'adp' digits after the decimal point).
toString(int[]) - Static method in class meka.core.A: ToString - Return an int[] as a nice String.
toString(int[], int) - Static method in class meka.core.A: ToString - Return an int[] as a nice String.
toString() - Method in class meka.core.LabelSet
toString() - Method in class meka.core.LabelVector
toString(Matrix) - Static method in class meka.core.MatrixUtils
toString(double[][], int) - Static method in class meka.core.MatrixUtils: ToString - return a String representation (to adp decimal places).
toString(double[][]) - Static method in class meka.core.MatrixUtils: ToString - return a String representation.
toString(int[][]) - Static method in class meka.core.MatrixUtils: ToString - return a String representation.
toString(double[][], String) - Static method in class meka.core.MatrixUtils: ToString - return a String representation of 'M', in Matlab format, called 'name'.
toString(Properties, String) - Static method in class meka.core.PropsUtils: Outputs the properties as they would be written to a file.
toString() - Method in class meka.core.Result: Provides a nice textual output of all evaluation information.
toString() - Method in class meka.core.SuperLabel
toString(int[][]) - Static method in class meka.core.SuperLabelUtils: ToString - A string representation for the super-class partition 'partition'.
toString() - Method in class meka.experiment.evaluationstatistics.EvaluationStatistics: Returns the statistics as string.
toString() - Method in class meka.experiment.evaluationstatistics.EvaluationStatisticsComparator: Returns the keys as string.
toString(T) - Method in class meka.gui.core.AbstractRecentItemsHandler: Turns an object into a string for storing in the props.
toString(File) - Method in class meka.gui.core.RecentFilesHandler: Turns an object into a string for storing in the props.
toString() - Method in class meka.gui.core.RecentFilesHandlerWithCommandline.Setup: Returns the container setup as string.
toString(RecentFilesHandlerWithCommandline.Setup) - Method in class meka.gui.core.RecentFilesHandlerWithCommandline: Turns an object into a string for storing in the props.
toString() - Method in class meka.gui.core.ResultHistory: Returns the history.
toString() - Method in class meka.gui.core.SearchParameters: Returns a short string representation of the search container.
toString() - Method in class meka.gui.core.SortableAndSearchableWrapperTableModel.SortContainer: Returns a string representation of the sort container.
toString() - Method in class meka.gui.dataviewer.DataViewer: returns only the classname
toString() - Method in class meka.gui.dataviewer.DataViewerMainPanel: returns only the classname
toString() - Method in class meka.gui.events.SearchEvent: Returns a string representation of the event.
toString() - Method in class rbms.RBM: ToString - return a String representation of the weight Matrix defining this RBM.
toSubIndicesSet(Instance, int[]) - Static method in class meka.core.MLUtils: To Sub Indices Set - return the indices out of 'sub_indices', in x, whose values are greater than 1.
toWekaPredictions(int[], double[]) - Static method in class meka.core.MLUtils: Convert to Weka (multi-target) Predictions.
train(double[][], double[][]) - Method in class meka.classifiers.multilabel.BPNN
train(double[][], double[][], int) - Method in class meka.classifiers.multilabel.BPNN: Train - Train for I iterations.
train(double[][]) - Method in class rbms.DBM
train(double[][], int) - Method in class rbms.DBM
train(double[][]) - Method in class rbms.RBM: Train - Setup and train the RBM on X, over m_E epochs.
train(double[][], int) - Method in class rbms.RBM: Train - Setup and batch-train the RBM on X.
train(double[][], int, Random) - Method in class rbms.RBM: Train - Setup and batch-train the RBM on X, with some random sampling involved.
trainClassifier(Classifier, Instances, int[][]) - Method in class meka.classifiers.multitarget.SCC: Train classifier h, on dataset D, under super-class partition partition.
trainPercentageTipText() - Method in class meka.experiment.evaluators.PercentageSplit: Describes this property.
transform(Instances) - Method in class meka.classifiers.multilabel.cc.CNode: Transform - transform dataset D for this node.
transform(Instance, double[]) - Method in class meka.classifiers.multilabel.cc.CNode: Transform - turn [y1,y2,y3,x1,x2] into [y1,y2,x1,x2].
transform(Instances, int, int[]) - Static method in class meka.classifiers.multilabel.cc.CNode: Transform.
transformInstance(Instance) - Method in class meka.classifiers.multilabel.CC: TransformInstances - this function is DEPRECATED.
transformInstance(Instance) - Method in class meka.classifiers.multilabel.LabelTransformationClassifier: Transforms the instance in the prediction process before given to the internal multi-label or multi-target classifier.
transformInstance(Instance) - Method in class meka.classifiers.multilabel.Maniac
transformInstance(Instance) - Method in class meka.classifiers.multilabel.MLCBMaD
transformInstance(Instance) - Method in class meka.classifiers.multilabel.PLST: Transforms the instance in the prediction process before given to the internal multi-label or multi-target classifier.
transformLabels(Instances) - Method in class meka.classifiers.multilabel.LabelTransformationClassifier: The method to transform the labels into another set of latent labels, typically a compression method is used, e.g., Boolean matrix decomposition in the case of MLC-BMaD, or matrix multiplication based on SVD for PLST.
transformLabels(Instances) - Method in class meka.classifiers.multilabel.Maniac
transformLabels(Instances) - Method in class meka.classifiers.multilabel.MLCBMaD
transformLabels(Instances) - Method in class meka.classifiers.multilabel.PLST: The method to transform the labels into another set of latent labels, typically a compression method is used, e.g., Boolean matrix decomposition in the case of MLC-BMaD, or matrix multiplication based on SVD for PLST.
transformPredictionsBack(double[]) - Method in class meka.classifiers.multilabel.LabelTransformationClassifier: Transforms the predictions of the internal classifier back to the original labels.
transformPredictionsBack(double[]) - Method in class meka.classifiers.multilabel.Maniac
transformPredictionsBack(double[]) - Method in class meka.classifiers.multilabel.MLCBMaD
transformPredictionsBack(double[]) - Method in class meka.classifiers.multilabel.PLST: Transforms the predictions of the internal classifier back to the original labels.
transposeMultiply(double[][], double[][]) - Static method in class meka.core.MatrixUtils
TREE - Static variable in interface meka.core.MultiLabelDrawable
Trellis - Class in meka.classifiers.multilabel.cc: CTrellis.
Trellis(int[], int, int) - Constructor for class meka.classifiers.multilabel.cc.Trellis
Trellis(int[], int[][], int, int) - Constructor for class meka.classifiers.multilabel.cc.Trellis
trellis - Variable in class meka.classifiers.multilabel.cc.Trellis
trimBiases(Matrix) - Static method in class meka.classifiers.multilabel.DBPNN
trimBiases(Matrix[]) - Static method in class meka.classifiers.multilabel.DBPNN
TYPE - Variable in class meka.classifiers.multilabel.cc.Trellis
TYPE_BINCREMENTAL - Static variable in class meka.gui.explorer.ClassifyTab: incremental batch train/test split.
TYPE_CROSSVALIDATION - Static variable in class meka.gui.explorer.ClassifyTab: cross-validation.
TYPE_PREQUENTIAL - Static variable in class meka.gui.explorer.ClassifyTab: incremental pequential.
TYPE_SUPPLIEDTESTSET - Static variable in class meka.gui.explorer.ClassifyTab: supplied test set.
TYPE_TRAINTESTSPLIT - Static variable in class meka.gui.explorer.ClassifyTab: train/test split.

U

ULink(int[], int, Instances) - Constructor for class meka.classifiers.multilabel.incremental.CCUpdateable.ULink
unbackQuoteChars(String, String[], char[]) - Static method in class meka.core.OptionUtils: The inverse operation of backQuoteChars().
unbackQuoteChars(String) - Static method in class meka.core.OptionUtils: The inverse operation of backQuoteChars().
undo() - Method in class meka.gui.dataviewer.DataPanel: performs an undo action
undo() - Method in class meka.gui.dataviewer.DataSortedTableModel: undoes the last action
undo() - Method in class meka.gui.dataviewer.DataTableModel: undoes the last action
undo() - Method in class meka.gui.dataviewer.DataViewerDialog: undoes the last action
undo() - Method in class meka.gui.dataviewer.DataViewerMainPanel: undoes the last action
undo() - Method in class meka.gui.explorer.Explorer: Undos the last operation.
UNHANDLED_DIALOG - Static variable in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: unhandled type of dialog.
update(double[][], double[][]) - Method in class meka.classifiers.multilabel.BPNN: Update - A single training epoch.
update(Instance) - Method in class meka.classifiers.multilabel.incremental.CCUpdateable.ULink
update() - Method in class meka.gui.core.MarkdownTextAreaWithPreview: Updates the markdown display.
update() - Method in class meka.gui.core.ParameterPanel: Updates the layout.
update() - Method in class meka.gui.experimenter.AbstractExperimenterTab: Gets called when the experiment changed.
update() - Method in class meka.gui.experimenter.AbstractSetupTab: Gets called when the experiment changed.
update(Experimenter, AbstractAction) - Method in class meka.gui.experimenter.menu.AbstractExperimenterMenuItem: Updates the action using the experimenter.
update() - Method in class meka.gui.experimenter.Statistics: Gets called when the experiment changed.
update() - Method in class meka.gui.explorer.AbstractExplorerTab: Gets called when the data changed.
update(T, JMenuItem) - Method in class meka.gui.explorer.AbstractTabMenuItem: Updates the menu item using the current state of the tab.
update(ClassifyTab, JMenuItem) - Method in class meka.gui.explorer.classify.EditTestData: Updates the menu item using the current state of the tab.
update(ClassifyTab, JMenuItem) - Method in class meka.gui.explorer.classify.OpenModel: Updates the menu item using the current state of the tab.
update(ClassifyTab, JMenuItem) - Method in class meka.gui.explorer.classify.OpenTestData: Updates the menu item using the current state of the tab.
update() - Method in class meka.gui.explorer.ClassifyTab: Gets called when the data changed.
update() - Method in class meka.gui.explorer.PreprocessTab: Gets called when the data changed.
update() - Method in class meka.gui.explorer.VisualizeTab: Gets called when the data changed.
update(Matrix) - Method in class rbms.DBM
update(Matrix, double) - Method in class rbms.DBM
update(double[][]) - Method in class rbms.DBM
update(Matrix) - Method in class rbms.RBM: Update - Carry out one epoch of CD, update W.
update(Matrix, double) - Method in class rbms.RBM: Update - Carry out one epoch of CD, update W.
update(double[][]) - Method in class rbms.RBM: Update - On raw data (with no bias column)
update(double[]) - Method in class rbms.RBM: Update - On raw data (with no bias column)
update(double[], double) - Method in class rbms.RBM: Update - On raw data (with no bias column)
update_Weights(double[], int, int) - Method in class meka.classifiers.multilabel.neurofuzzy.ARTCluster
updateBounds(int, int, int, int) - Method in class meka.gui.core.MaximizationFixWindowListener: Updates the current bounds.
updateBounds(Rectangle) - Method in class meka.gui.core.MaximizationFixWindowListener: Updates the current bounds.
updateButtons() - Method in class meka.gui.experimenter.AbstractSetupTab: Updates the enabled state of the buttons.
updateButtons() - Method in class meka.gui.experimenter.BasicSetup: Updates the enabled state of the buttons.
updateButtons() - Method in class meka.gui.experimenter.ExpertSetup: Updates the enabled state of the buttons.
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.incremental.BRUpdateable
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.incremental.CCUpdateable
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.incremental.MajorityLabelsetUpdateable
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.incremental.meta.BaggingMLUpdateable
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.incremental.PSUpdateable
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.incremental.RTUpdateable
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetwork: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkfast: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparse: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseH: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseHT_Strange: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.ARAMNetworkSparseV: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.HARAMNetwork: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.WARAM: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
updateCount(Instance, int) - Method in class meka.classifiers.multilabel.MajorityLabelset
updateCurrentHandlerHook() - Method in class meka.gui.choosers.AbstractConfigurableExtensionFileFilterFileChooser: sets the current converter according to the current filefilter.
updateCurrentHandlerHook() - Method in class meka.gui.choosers.AbstractExtensionFileFilterFileChooser: Sets the current handler according to the current filefilter.
updateEditor() - Method in class meka.gui.goe.PropertyText: Attempts to update the editor value from the textfield.
updateFrameTitle() - Method in class meka.gui.dataviewer.DataViewerMainPanel: sets the title of the parent frame, if one was provided
updateGOE() - Method in class meka.gui.explorer.ClassifyTab: Updates the GOE for the classifier.
updateMenu() - Method in class meka.gui.core.AbstractRecentItemsHandler: Updates the menu with the currently stored recent files.
updateMenu() - Method in class meka.gui.dataviewer.DataViewerMainPanel: sets the enabled/disabled state of the menu
updateMenu() - Method in class meka.gui.experimenter.Experimenter: Updates the enabled/disabled state of the menu items.
updateMenu() - Method in class meka.gui.experimenter.Statistics: Updates the menu items in the custom menu.
updateMenu() - Method in class meka.gui.explorer.ClassifyTab: Updates the enabled/disabled state of the menu items.
updateMenu() - Method in class meka.gui.explorer.Explorer: Updates the enabled/disabled state of the menu items.
updateMenu() - Method in class meka.gui.modelviewer.ModelViewer: Updates the enabled/disabled state of the menu items.
updateTransform(Instance, double[]) - Method in class meka.classifiers.multilabel.cc.CNode
updateUs() - Method in class meka.gui.goe.PropertyText: Attempts to update the textfield value from the editor.
updateView() - Method in class meka.gui.experimenter.Statistics: Updates the view on the current statistics.
updateWeights(ProblemTransformationMethod, Instances) - Method in class meka.classifiers.multilabel.meta.CM
updateWeights(ProblemTransformationMethod, Instances) - Method in class meka.classifiers.multilabel.meta.EM
updateWidth(int) - Method in class meka.gui.core.SearchPanel: In case of vertical display, the size of the panel can be adjusted to the specified width.
uppermatrix - Variable in class meka.classifiers.multilabel.MLCBMaD: The upper matrix.
upperRunsTipText() - Method in class meka.experiment.evaluators.RepeatedRuns: Describes this property.
useClassAttributes() - Method in class meka.gui.explorer.PreprocessTab: Sets the selected attributes as class attributes.

V

vals - Variable in class meka.core.Result
valueAt(int) - Method in class meka.classifiers.multilabel.neurofuzzy.SparseArray: Given an index in the range 0...size()-1, returns the value from the indexth key-value mapping that this SparseArray stores.
valueMatrix(List<EvaluationStatistics>, String) - Static method in class meka.experiment.evaluationstatistics.EvaluationStatisticsUtils: Value Matrix
valueOf(String) - Static method in enum meka.core.LatexUtils.Characters: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum meka.experiment.events.ExecutionStageEvent.Stage: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum meka.gui.core.SearchPanel.LayoutType: Returns the enum constant of this type with the specified name.
values - Variable in class meka.core.LabelVector
values() - Static method in enum meka.core.LatexUtils.Characters: Returns an array containing the constants of this enum type, in the order they are declared.
values - Variable in class meka.core.SuperLabel
values() - Static method in enum meka.experiment.events.ExecutionStageEvent.Stage: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum meka.gui.core.SearchPanel.LayoutType: Returns an array containing the constants of this enum type, in the order they are declared.
verbosityTipText() - Method in class meka.experiment.evaluators.CrossValidation: Describes this property.
verbosityTipText() - Method in class meka.experiment.evaluators.PercentageSplit: Describes this property.
Version - Class in meka.core: For handling the MEKA version.
Version() - Constructor for class meka.core.Version
vigilance - Variable in class meka.classifiers.multilabel.neurofuzzy.ARTCluster
vigilancyTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM
VisualizeTab - Class in meka.gui.explorer: For visualizing the data.
VisualizeTab() - Constructor for class meka.gui.explorer.VisualizeTab
vMap - Variable in class meka.classifiers.multitarget.RAkELd
votersTipText() - Method in class meka.classifiers.multilabel.neurofuzzy.WvARAM

W

W - Variable in class meka.classifiers.multilabel.BPNN: Weight Matrix
w - Variable in class meka.classifiers.multilabel.PMCC
W - Variable in class rbms.RBM
WARAM - Class in meka.classifiers.multilabel.neurofuzzy: ****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION.
WARAM(int, int, double, double) - Constructor for class meka.classifiers.multilabel.neurofuzzy.WARAM
WARAM() - Constructor for class meka.classifiers.multilabel.neurofuzzy.WARAM
weight(Instances) - Method in class meka.classifiers.multilabel.cc.Trellis
weight(int[], int, int, double[][]) - Method in class meka.classifiers.multilabel.cc.Trellis: What would the 'score' be, putting j_ at position j, in indices, with I matrix.
weightNeighbourhood(int) - Method in class meka.classifiers.multilabel.cc.Trellis
WekaFilter - Class in meka.experiment.statisticsexporters: Applies a Weka filter to the data.
WekaFilter() - Constructor for class meka.experiment.statisticsexporters.WekaFilter
WIDTH - Variable in class meka.classifiers.multilabel.cc.Trellis
WIDTH - Static variable in class meka.gui.dataviewer.DataViewerMainPanel: default width
widthTipText() - Method in class meka.classifiers.multilabel.CDT
widthTipText() - Method in class meka.classifiers.multilabel.CT
windowActivated(WindowEvent) - Method in class meka.gui.dataviewer.DataViewer: invoked when a window is activated
windowClosed(WindowEvent) - Method in class meka.gui.dataviewer.DataViewer: invoked when a window is closed
windowClosing(WindowEvent) - Method in class meka.gui.dataviewer.DataViewer: invoked when a window is in the process of closing
windowDeactivated(WindowEvent) - Method in class meka.gui.dataviewer.DataViewer: invoked when a window is deactivated
windowDeiconified(WindowEvent) - Method in class meka.gui.dataviewer.DataViewer: invoked when a window is deiconified
windowIconified(WindowEvent) - Method in class meka.gui.dataviewer.DataViewer: invoked when a window is iconified
windowOpened(WindowEvent) - Method in class meka.gui.dataviewer.DataViewer: invoked when a window is has been opened
windowStateChanged(WindowEvent) - Method in class meka.gui.core.MaximizationFixWindowListener
WorkerThread(AbstractThreadedExplorerTab, Runnable) - Constructor for class meka.gui.explorer.AbstractThreadedExplorerTab.WorkerThread: Initializes the thread.
write(List<EvaluationStatistics>) - Method in interface meka.experiment.evaluationstatistics.EvaluationStatisticsHandler: Stores the given statistics.
write(List<EvaluationStatistics>) - Method in class meka.experiment.evaluationstatistics.InMemory: Stores the given statistics.
write(List<EvaluationStatistics>) - Method in class meka.experiment.evaluationstatistics.KeyValuePairs: Stores the given statistics.
write(List<EvaluationStatistics>) - Method in class meka.experiment.evaluationstatistics.Serialized: Stores the given statistics.
write(Experiment, File) - Method in class meka.experiment.filehandlers.AbstractExperimentFileHandler: Writes and experiment to disk.
write(Experiment, File) - Method in class meka.experiment.filehandlers.CommandLineSetup: Writes and experiment to disk.
write(Experiment, File) - Method in interface meka.experiment.filehandlers.ExperimentFileHandler: Writes and experiment to disk.
write(Experiment, File) - Method in class meka.experiment.filehandlers.SerializedExperiment: Writes and experiment to disk.
writeProps() - Method in class meka.gui.core.AbstractRecentItemsHandler: Writes the current recent items back to the props file.
writeResultToFile(Result, String) - Static method in class meka.core.Result: WriteResultToFile -- write a Result 'result' out in plain text format to file 'fname'.
WvARAM - Class in meka.classifiers.multilabel.neurofuzzy: ****REPLACE THE FOLLOWING WITH SIMILAR INFORMATION.
WvARAM(int) - Constructor for class meka.classifiers.multilabel.neurofuzzy.WvARAM
WvARAM() - Constructor for class meka.classifiers.multilabel.neurofuzzy.WvARAM
WvARAM.BuildClassifier - Class in meka.classifiers.multilabel.neurofuzzy
WvARAM.DistributionCalc - Class in meka.classifiers.multilabel.neurofuzzy
WvARAM.DistributionCalcM - Class in meka.classifiers.multilabel.neurofuzzy

X

x_template - Variable in class meka.filters.multilabel.SuperNodeFilter

_

_template - Variable in class meka.classifiers.multilabel.CCq.QLink
_template - Variable in class meka.classifiers.multilabel.incremental.CCUpdateable.ULink
_template - Variable in class meka.classifiers.multitarget.CCp.Link

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