Index (weka-dev 3.9.6 API)

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
All Classes and Interfaces|All Packages|Constant Field Values|Serialized Form

A

abortExperiment() - Method in class weka.experiment.RemoteExperiment: Set the abort flag
ABS_DIFF - Enum constant in enum class weka.core.pmml.jaxbbindings.COMPAREFUNCTION
ABSTRACT - Enum constant in enum class weka.core.TechnicalInformation.Field: An abstract of the work.
AbstractAssociator - Class in weka.associations: Abstract scheme for learning associations.
AbstractAssociator() - Constructor for class weka.associations.AbstractAssociator
AbstractClassifier - Class in weka.classifiers: Abstract classifier.
AbstractClassifier() - Constructor for class weka.classifiers.AbstractClassifier
AbstractClusterer - Class in weka.clusterers: Abstract clusterer.
AbstractClusterer() - Constructor for class weka.clusterers.AbstractClusterer
AbstractCommand - Class in weka.gui.simplecli: Ancestor for command.
AbstractCommand() - Constructor for class weka.gui.simplecli.AbstractCommand
AbstractDataSink - Class in weka.gui.beans: Abstract class for objects that store instances to some destination.
AbstractDataSink() - Constructor for class weka.gui.beans.AbstractDataSink
AbstractDataSinkBeanInfo - Class in weka.gui.beans: Bean info class for the AbstractDataSink
AbstractDataSinkBeanInfo() - Constructor for class weka.gui.beans.AbstractDataSinkBeanInfo
AbstractDataSource - Class in weka.gui.beans: Abstract class for objects that can provide instances from some source
AbstractDataSource() - Constructor for class weka.gui.beans.AbstractDataSource: Creates a new AbstractDataSource instance.
AbstractDataSourceBeanInfo - Class in weka.gui.beans: Bean info class for AbstractDataSource.
AbstractDataSourceBeanInfo() - Constructor for class weka.gui.beans.AbstractDataSourceBeanInfo
AbstractDensityBasedClusterer - Class in weka.clusterers: Abstract clustering model that produces (for each test instance) an estimate of the membership in each cluster (ie.
AbstractDensityBasedClusterer() - Constructor for class weka.clusterers.AbstractDensityBasedClusterer
AbstractEvaluationMetric - Class in weka.classifiers.evaluation: Abstract base class for pluggable classification/regression evaluation metrics.
AbstractEvaluationMetric() - Constructor for class weka.classifiers.evaluation.AbstractEvaluationMetric
AbstractEvaluationMetric.UnknownStatisticException - Exception in weka.classifiers.evaluation: Exception for subclasses to throw if asked for a statistic that is not part of their implementation
AbstractEvaluator - Class in weka.gui.beans: Abstract class for objects that can provide some kind of evaluation for classifier, clusterers etc.
AbstractEvaluator() - Constructor for class weka.gui.beans.AbstractEvaluator: Constructor
AbstractFileBasedStopwords - Class in weka.core.stopwords: Ancestor for file-based stopword schemes.
AbstractFileBasedStopwords() - Constructor for class weka.core.stopwords.AbstractFileBasedStopwords
AbstractFileLoader - Class in weka.core.converters: Abstract superclass for all file loaders.
AbstractFileLoader() - Constructor for class weka.core.converters.AbstractFileLoader
AbstractFileSaver - Class in weka.core.converters: Abstract class for Savers that save to a file Valid options are: -i input arff file
The input filw in arff format.
AbstractFileSaver() - Constructor for class weka.core.converters.AbstractFileSaver
AbstractGraphicalCommand - Class in weka.gui.knowledgeflow: Base class for a graphical command
AbstractGraphicalCommand() - Constructor for class weka.gui.knowledgeflow.AbstractGraphicalCommand
AbstractGUIApplication - Class in weka.gui: Base class for GUI applications in Weka
AbstractGUIApplication() - Constructor for class weka.gui.AbstractGUIApplication: Default constructor
AbstractGUIApplication(boolean, String...) - Constructor for class weka.gui.AbstractGUIApplication: Constructor
AbstractGUIApplication(boolean, String[], String[]) - Constructor for class weka.gui.AbstractGUIApplication: Constructor
AbstractInstance - Class in weka.core: Abstract class providing common functionality for the original instance implementations.
AbstractInstance() - Constructor for class weka.core.AbstractInstance
AbstractLoader - Class in weka.core.converters: Abstract class gives default implementation of setSource methods.
AbstractLoader() - Constructor for class weka.core.converters.AbstractLoader
AbstractOffscreenChartRenderer - Class in weka.gui.beans: Abstract base class for offscreen chart renderers.
AbstractOffscreenChartRenderer() - Constructor for class weka.gui.beans.AbstractOffscreenChartRenderer
AbstractOutput - Class in weka.classifiers.evaluation.output.prediction: A superclass for outputting the classifications of a classifier.
AbstractOutput() - Constructor for class weka.classifiers.evaluation.output.prediction.AbstractOutput: Initializes the output class.
AbstractPerspective - Class in weka.gui: Base classes for GUI perspectives to extend.
AbstractPerspective() - Constructor for class weka.gui.AbstractPerspective: Constructor
AbstractPerspective(String, String) - Constructor for class weka.gui.AbstractPerspective: Constructor
AbstractPlotInstances - Class in weka.gui.explorer: Abstract superclass for generating plottable instances.
AbstractPlotInstances() - Constructor for class weka.gui.explorer.AbstractPlotInstances: Initializes the container.
AbstractPMMLProducerHelper - Class in weka.classifiers.pmml.producer: Abstract base class for PMMLProducer helper classes to extend.
AbstractPMMLProducerHelper() - Constructor for class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper
AbstractSaver - Class in weka.core.converters: Abstract class for Saver
AbstractSaver() - Constructor for class weka.core.converters.AbstractSaver
AbstractSetupPanel - Class in weka.gui.experiment: Ancestor for setup panels for experiments.
AbstractSetupPanel() - Constructor for class weka.gui.experiment.AbstractSetupPanel
AbstractStopwords - Class in weka.core.stopwords: Ancestor for stopwords classes.
AbstractStopwords() - Constructor for class weka.core.stopwords.AbstractStopwords
AbstractTestSetProducer - Class in weka.gui.beans: Abstract class for TestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
AbstractTestSetProducer() - Constructor for class weka.gui.beans.AbstractTestSetProducer: Creates a new AbstractTestSetProducer instance.
AbstractTestSetProducerBeanInfo - Class in weka.gui.beans: BeanInfo class for AbstractTestSetProducer
AbstractTestSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTestSetProducerBeanInfo
AbstractTimeSeries - Class in weka.filters.unsupervised.attribute: An abstract instance filter that assumes instances form time-series data and performs some merging of attribute values in the current instance with attribute attribute values of some previous (or future) instance.
AbstractTimeSeries() - Constructor for class weka.filters.unsupervised.attribute.AbstractTimeSeries
AbstractTrainAndTestSetProducer - Class in weka.gui.beans: Abstract base class for TrainAndTestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
AbstractTrainAndTestSetProducer() - Constructor for class weka.gui.beans.AbstractTrainAndTestSetProducer: Creates a new AbstractTrainAndTestSetProducer instance.
AbstractTrainAndTestSetProducerBeanInfo - Class in weka.gui.beans: Bean info class for AbstractTrainAndTestSetProducers
AbstractTrainAndTestSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo
AbstractTrainingSetProducer - Class in weka.gui.beans: Abstract class for TrainingSetProducers that contains default implementations of add/remove listener methods and default visual representation
AbstractTrainingSetProducer() - Constructor for class weka.gui.beans.AbstractTrainingSetProducer: Creates a new AbstractTrainingSetProducer instance.
AbstractTrainingSetProducerBeanInfo - Class in weka.gui.beans: BeanInfo class for AbstractTrainingSetProducer
AbstractTrainingSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTrainingSetProducerBeanInfo
accept(File) - Method in class weka.core.ClassCache.ClassFileFilter: Checks whether the file is a class.
accept(File) - Method in class weka.core.ClassCache.DirectoryFilter: Checks whether the file is a directory.
accept(File) - Method in class weka.gui.ExtensionFileFilter: Returns true if the supplied file should be accepted (i.e.: if it has the required extension or is a directory).
accept(File, String) - Method in class weka.gui.ExtensionFileFilter: Returns true if the file in the given directory with the given name should be accepted.
ACCEPT - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent: States that the user has accepted the tree.
acceptAssociationRules(BatchAssociationRulesEvent) - Method in interface weka.gui.beans.BatchAssociationRulesListener: Accept a BatchAssociationRulesEvent
acceptClassifier(BatchClassifierEvent) - Method in interface weka.gui.beans.BatchClassifierListener: Accept a BatchClassifierEvent
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Accept a classifier to be evaluated.
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.PredictionAppender: Accept and process a batch classifier event
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.SerializedModelSaver: Accept and save a batch trained classifier.
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Accepts and processes a classifier encapsulated in an incremental classifier event
acceptClassifier(IncrementalClassifierEvent) - Method in interface weka.gui.beans.IncrementalClassifierListener: Accept the event
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.PredictionAppender: Accept and process an incremental classifier event
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.SerializedModelSaver: Accept and save an incrementally trained classifier.
acceptClusterer(BatchClustererEvent) - Method in interface weka.gui.beans.BatchClustererListener: Accept a BatchClustererEvent
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Accept a clusterer to be evaluated
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.PredictionAppender: Accept and process a batch clusterer event
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.SerializedModelSaver: Accept and save a batch trained clusterer.
acceptConfiguration(ConfigurationEvent) - Method in interface weka.gui.beans.ConfigurationListener: Implementers do not have to do anything in this method (see the above documentation).
acceptDataPoint(double[]) - Method in class weka.gui.beans.StripChart: Accept a data point to plot
acceptDataPoint(double[]) - Method in class weka.gui.knowledgeflow.steps.StripChartInteractiveView: Accept and process a data point
acceptDataPoint(double[]) - Method in interface weka.knowledgeflow.steps.StripChart.PlotNotificationListener
acceptDataPoint(ChartEvent) - Method in interface weka.gui.beans.ChartListener
acceptDataPoint(ChartEvent) - Method in class weka.gui.beans.StripChart: Accept a data point (encapsulated in a chart event) to plot
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Subclass must implement
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Appender: Accept and process a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Associator
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.ClassValuePicker
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker: Accept a data set
acceptDataSet(DataSetEvent) - Method in interface weka.gui.beans.DataSourceListener
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.DataVisualizer: Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Filter: Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.FlowByExpression
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Join: Accept and process a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Saver: Method reacts to a dataset event and starts the writing process in batch mode
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Sorter: Accept and process a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TestSetMaker: Accepts and processes a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TextViewer: Accept a data set for displaying as text
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TrainingSetMaker: Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker: Accept a data set
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a threshold data set
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.CostBenefitAnalysis: Accept a threshold data event and set up the visualization.
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.ModelPerformanceChart: Display a threshold curve.
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.Saver: Method reacts to a threshold data event ans starts the writing process in batch mode.
acceptDataSet(ThresholdDataEvent) - Method in interface weka.gui.beans.ThresholdDataListener
acceptDataSet(VisualizableErrorEvent) - Method in class weka.gui.beans.ModelPerformanceChart: Display a scheme error plot.
acceptDataSet(VisualizableErrorEvent) - Method in interface weka.gui.beans.VisualizableErrorListener
acceptGraph(GraphEvent) - Method in interface weka.gui.beans.GraphListener: Describe acceptGraph method here.
acceptGraph(GraphEvent) - Method in class weka.gui.beans.GraphViewer: Accept a graph
acceptImage(ImageEvent) - Method in interface weka.gui.beans.ImageListener: Accept and process an ImageEvent
acceptImage(ImageEvent) - Method in class weka.gui.beans.ImageSaver: Accept and process an ImageEvent
acceptImage(ImageEvent) - Method in class weka.gui.beans.ImageViewer
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept an instance
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Appender: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.ClassAssigner
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Classifier: Accepts an instance for incremental processing.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Filter: Accept an instance for processing by StreamableFilters only
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.FlowByExpression
acceptInstance(InstanceEvent) - Method in interface weka.gui.beans.InstanceListener: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Accept an instance to add to the batch.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Join
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Saver: Methods reacts to instance events and saves instances incrementally.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Sorter: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.StripChart
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.SubstringReplacer: Accept and process an instance event
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.AveragingResultProducer: Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.CSVResultListener: Just prints out each result as it is received.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseResultListener: Submit the result to the appropriate table of the database
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseResultProducer: Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.InstancesResultListener: Collects each instance and adjusts the header information.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.LearningRateResultProducer: Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in interface weka.experiment.ResultListener: Accepts results from a ResultProducer.
acceptsInstances() - Method in class weka.gui.AbstractPerspective: Returns true if this perspective can do something meaningful with a set of instances
acceptsInstances() - Method in class weka.gui.beans.AttributeSummarizer: Returns true if this perspective accepts instances
acceptsInstances() - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective: Returns true if this perspective accepts instances
acceptsInstances() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
acceptsInstances() - Method in class weka.gui.beans.ScatterPlotMatrix: Returns true if this perspective accepts instances
acceptsInstances() - Method in class weka.gui.beans.SQLViewerPerspective: Returns true if this perspective accepts instances
acceptsInstances() - Method in class weka.gui.explorer.AssociationsPanel
acceptsInstances() - Method in class weka.gui.explorer.AttributeSelectionPanel
acceptsInstances() - Method in class weka.gui.explorer.ClassifierPanel
acceptsInstances() - Method in class weka.gui.explorer.ClustererPanel
acceptsInstances() - Method in class weka.gui.explorer.PreprocessPanel: We can accept instances
acceptsInstances() - Method in class weka.gui.explorer.VisualizePanel: This perspective processes instances
acceptsInstances() - Method in class weka.gui.knowledgeflow.AttributeSummaryPerspective: Returns true, as this perspective does accept instances
acceptsInstances() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Returns true if this perspective can do something meaningful with a set of instances
acceptsInstances() - Method in class weka.gui.knowledgeflow.ScatterPlotMatrixPerspective: Returns true - we accept instances.
acceptsInstances() - Method in interface weka.gui.Perspective: Returns true if this perspective can do something meaningful with a set of instances
acceptsInstances() - Method in class weka.gui.SimpleCLIPanel
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Appender: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Classifier: Accepts a test set for a batch trained classifier
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Clusterer: Accepts a test set for a batch trained clusterer
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.DataVisualizer: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Filter: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.FlowByExpression
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Join: Accept and process a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Saver: Method reacts to a test set event and starts the writing process in batch mode
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Sorter: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in interface weka.gui.beans.TestSetListener: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TextViewer: Accept a test set for displaying as text
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TrainingSetMaker
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker: Accept a test set
acceptText(TextEvent) - Method in interface weka.gui.beans.TextListener: Accept and process a text event
acceptText(TextEvent) - Method in class weka.gui.beans.TextSaver: Accept and process an TextEvent
acceptText(TextEvent) - Method in class weka.gui.beans.TextViewer: Accept some text
acceptTextResult(String, String) - Method in class weka.gui.knowledgeflow.steps.TextViewerInteractiveView: Accept a new text result and add it to the result list
acceptTextResult(String, String) - Method in interface weka.knowledgeflow.steps.TextViewer.TextNotificationListener: Accept a new textual result
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Appender: Accept and process a training set event
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Associator: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Classifier: Accepts a training set and builds batch classifier
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Clusterer: Accepts a training set and builds batch clusterer
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.DataVisualizer: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Filter: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.FlowByExpression
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Join: Accept and process a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Saver: Method reacts to a training set event and starts the writing process in batch mode
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Sorter: Accept and process a training set event
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process a training set event
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TestSetMaker
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TextViewer: Accept a training set for displaying as text
acceptTrainingSet(TrainingSetEvent) - Method in interface weka.gui.beans.TrainingSetListener: Accept and process a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker: Accept a training set
ACROSS_TIME_WINDOWS - Enum constant in enum class weka.core.pmml.jaxbbindings.DELIMITER2
actEntropy - Variable in class weka.classifiers.lazy.kstar.KStarWrapper: used/reused to hold the actual entropy
action_table() - Method in class weka.core.expressionlanguage.parser.Parser: Access to parse-action table.
action_table() - Method in class weka.core.json.Parser: Access to parse-action table.
actionPerformed(ActionEvent) - Method in class weka.gui.arffviewer.ArffPanel: invoked when an action occurs
actionPerformed(ActionEvent) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: invoked when an action occurs
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.AlgorithmListPanel: Handle actions when buttons get pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.DatasetListPanel: Handle actions when buttons get pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel: Handles the various button clicking type activities.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.HostListPanel: Handle actions when text is entered into the host field or the delete button is pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.RunPanel: Controls starting and stopping the experiment.
actionPerformed(ActionEvent) - Method in class weka.gui.SimpleCLIPanel: Only gets called when return is pressed in the input area, which starts the command running.
actionPerformed(ActionEvent) - Method in class weka.gui.streams.InstanceLoader
actionPerformed(ActionEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer: Performs the action associated with the ActionEvent.
activateFilter(boolean) - Method in class weka.gui.knowledgeflow.InvisibleTreeModel: Activate/deactivate the visibility filter
ACTIVATIONFUNCTION - Enum Class in weka.core.pmml.jaxbbindings: Java class for ACTIVATION-FUNCTION.
ACTIVE - Enum constant in enum class weka.core.pmml.jaxbbindings.FIELDUSAGETYPE
ActiveHNode - Class in weka.classifiers.trees.ht: Node that is "active" (i.e.
ActiveHNode() - Constructor for class weka.classifiers.trees.ht.ActiveHNode
actual() - Method in class weka.classifiers.evaluation.NominalPrediction: Gets the actual class value.
actual() - Method in class weka.classifiers.evaluation.NumericPrediction: Gets the actual class value.
actual() - Method in interface weka.classifiers.evaluation.Prediction: Gets the actual class value.
actualNumBags() - Method in class weka.classifiers.trees.j48.Distribution: Returns number of non-empty bags of distribution.
actualNumClasses() - Method in class weka.classifiers.trees.j48.Distribution: Returns number of classes actually occuring in distribution.
actualNumClasses(int) - Method in class weka.classifiers.trees.j48.Distribution: Returns number of classes actually occuring in given bag.
acuityTipText() - Method in class weka.clusterers.Cobweb: Returns the tip text for this property
AdaBoostM1 - Class in weka.classifiers.meta: Class for boosting a nominal class classifier using the Adaboost M1 method.
AdaBoostM1() - Constructor for class weka.classifiers.meta.AdaBoostM1: Constructor.
add(double) - Method in class weka.experiment.Stats: Adds a value to the observed values
add(double[], double[]) - Method in class weka.experiment.PairedStats: Adds an array of observed pair of values.
add(double, double) - Method in class weka.experiment.PairedStats: Add an observed pair of values.
add(double, double) - Method in class weka.experiment.Stats: Adds a weighted value to the observed values
add(int, double[]) - Method in class weka.classifiers.trees.j48.Distribution: Adds counts to given bag.
add(int, Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Inserts the specified element at the specified position in this list.
add(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution: Adds given instance to given bag.
add(int, Instance) - Method in class weka.core.Instances: Adds one instance at the given position in the list.
add(PrintStream) - Method in class weka.core.Tee: adds the given PrintStream to the list of streams, with NO timestamp and NO prefix.
add(PrintStream, boolean) - Method in class weka.core.Tee: adds the given PrintStream to the list of streams, with NO prefix.
add(PrintStream, boolean, String) - Method in class weka.core.Tee: adds the given PrintStream to the list of streams.
add(Class<?>, Method) - Method in class weka.core.xml.MethodHandler: adds the specified method for the given class to its internal list.
add(Object) - Method in class weka.gui.GenericObjectEditorHistory: Adds the object to the history.
add(String) - Method in class weka.core.ClassCache: Adds the classname to the cache.
add(String) - Method in class weka.core.Stopwords: adds the given word to the stopword list (is automatically converted to lower case and trimmed)
add(String) - Method in class weka.core.Trie: Ensures that this collection contains the specified element.
add(String) - Method in class weka.core.Trie.TrieNode: adds the given string to its children (creates children if necessary)
add(String) - Method in class weka.gui.HierarchyPropertyParser: Add the given item of property to the tree
add(String, Method) - Method in class weka.core.xml.MethodHandler: adds the specified method for the property with the given displayname to its internal list.
add(AlgVector) - Method in class weka.core.AlgVector: Returns the sum of this vector with another.
add(Defaults) - Method in class weka.core.Defaults: Add the supplied defaults to this one.
add(Instance) - Method in class weka.core.Instances: Adds one instance to the end of the set.
add(Matrix) - Method in class weka.core.Matrix: Deprecated.

Returns the sum of this matrix with another.
add(TechnicalInformation) - Method in class weka.core.TechnicalInformation: adds the given information to the list of additional technical informations
add(TechnicalInformation.Type) - Method in class weka.core.TechnicalInformation: Adds an empty technical information with the given type to the list of additional informations and returns the instance.
Add - Class in weka.filters.unsupervised.attribute: An instance filter that adds a new attribute to the dataset.
Add() - Constructor for class weka.filters.unsupervised.attribute.Add
ADD_CHILDREN - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
addActionListener(ActionListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Register a listener to be notified when plotting completes
addActionListener(ActionListener) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel: Add a listener interested in kowing about editor status changes
addActionListener(ActionListener) - Method in class weka.gui.visualize.ClassPanel: Add an action listener that will be notified if the user changes the colour of a label
addActionListener(ActionListener) - Method in class weka.gui.visualize.VisualizePanel: Add a listener for this visualize panel
addAll(Collection<? extends String>) - Method in class weka.core.Trie: Adds all of the elements in the specified collection to this collection
addAll(Collection<? extends T>) - Method in class weka.core.neighboursearch.covertrees.Stack: Adds all the given elements in the stack.
addAll(List<StepManagerImpl>) - Method in class weka.knowledgeflow.Flow: All all steps in the supplied list to this Flow
addAllBeansToContainer(JComponent, Integer...) - Static method in class weka.gui.beans.BeanInstance: Adds all beans to the supplied component
addAllowed(Class<?>, String) - Method in class weka.core.xml.PropertyHandler: adds the given property (display name) to the list of allowed properties for the specified class.
addAllResults(Map<String, LinkedHashSet<Data>>) - Method in class weka.knowledgeflow.JobEnvironment: Add all the results from the supplied map to this environment's results
addAndUpdate(Rule) - Method in class weka.classifiers.rules.RuleStats: Add a rule to the ruleset and update the stats
addArc(int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
addArc(String, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
addArc(String, ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add arc between parent node and each of the nodes in a given list.
addArray(String) - Method in class weka.core.json.JSONNode: Adds an array child to the object.
addArrayElement(Object) - Method in class weka.core.json.JSONNode: Adds an array element child to the array.
addAssociationModelOrBaselineModelOrClusteringModes(Object) - Method in class weka.core.pmml.jaxbbindings.PMML
addAttributePanelListener(AttributePanelListener) - Method in class weka.gui.visualize.AttributePanel: Add a listener to the list of things listening to this panel
addAttributeSpec(String) - Method in class weka.filters.unsupervised.attribute.AddUserFields: Add an attribute spec to the list
addBatchAssociationRulesListener(BatchAssociationRulesListener) - Method in class weka.gui.beans.Associator: Add a batch association rules listener
addBatchClassifierListener(BatchClassifierListener) - Method in class weka.gui.beans.Classifier: Add a batch classifier listener
addBatchClustererListener(BatchClustererListener) - Method in class weka.gui.beans.Clusterer: Add a batch clusterer listener
addBean(JComponent, Integer...) - Method in class weka.gui.beans.BeanInstance: Adds this bean to the global list of beans and to the supplied container.
addBeanInstances(Vector<Object>, JComponent) - Static method in class weka.gui.beans.BeanInstance: Adds the supplied collection of beans to the end of the list of collections and to the JComponent container (if not null)
addBoolean(String) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations: Adds a variable declaration for a boolean variable
addButton(JButton) - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Adds a button to the bottom of the window.
addCancelListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel: This is used to hook an action listener to the cancel button.
addCapabilities(String) - Method in class weka.core.Capabilities: generates a string from the capabilities, suitable to add to the help text.
addCapabilities(String, Capabilities) - Static method in class weka.core.CapabilitiesUtils: generates a string from the capabilities, suitable to add to the help text.
addCapabilitiesFilterListener(Explorer.CapabilitiesFilterChangeListener) - Method in class weka.gui.explorer.Explorer: adds the listener to the list of objects that listen for changes of the CapabilitiesFilter
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffPanel: Adds a ChangeListener to the panel
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffTable: Adds a ChangeListener to the panel
addChartListener(ChartListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Add a chart listener
addCheckBoxActionListener(ActionListener) - Method in class weka.gui.experiment.DistributeExperimentPanel: Enable objects to listen for changes to the check box
addChild(Edge) - Method in class weka.gui.treevisualizer.Node: Set the value of children.
addChild(FlowByExpression.ExpressionNode) - Method in class weka.knowledgeflow.steps.FlowByExpression.BracketNode: Add a child to this bracket node
addChildClique(MarginCalculator.JunctionTreeNode) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
addChildFrame(Container) - Method in class weka.gui.GUIChooserApp: adds the given child frame to the list of frames.
addChildFrame(Container) - Method in class weka.gui.Main: adds the given child frame to the list of frames.
AddClassification - Class in weka.filters.supervised.attribute: A filter for adding the classification, the class distribution and an error flag to a dataset with a classifier.
AddClassification() - Constructor for class weka.filters.supervised.attribute.AddClassification
AddCluster - Class in weka.filters.unsupervised.attribute: A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm.
Either the clustering algorithm gets built with the first batch of data or one specifies are serialized clusterer model file to use instead.
AddCluster() - Constructor for class weka.filters.unsupervised.attribute.AddCluster
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Associator: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Classifier: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Clusterer: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in interface weka.gui.beans.ConfigurationProducer: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Filter: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConnectionListener(ConnectionListener) - Method in class weka.gui.sql.ConnectionPanel: adds the given listener to the list of listeners.
addConnectionListener(ConnectionListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
addConnections(Vector<BeanConnection>) - Static method in class weka.gui.beans.BeanConnection: Add the supplied collection of connections to the end of the list.
addContent(Object) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel
addContent(Object) - Method in class weka.core.pmml.jaxbbindings.RegressionModel
addCVParameter(String) - Method in class weka.classifiers.meta.CVParameterSelection: Adds a scheme parameter to the list of parameters to be set by cross-validation
addDataDictionary(Instances, PMML) - Static method in class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper: Adds a data dictionary to the supplied PMML object.
addDataField(DataField) - Method in class weka.core.pmml.jaxbbindings.DataDictionary
addDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassAssigner
addDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassValuePicker
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.AbstractDataSource: Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Appender: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassAssigner
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassValuePicker
addDataSourceListener(DataSourceListener) - Method in interface weka.gui.beans.DataSource: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.DataVisualizer: Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Filter: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.FlowByExpression
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Join: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Loader: Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.PredictionAppender: Add a datasource listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Sorter: Add a datasource listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.SubstringLabeler: Add a datasource listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.SubstringReplacer: Add a data source listener
addDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.LocalTransformations
addDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.TransformationDictionary
addDouble(String) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations: Adds a variable declaration for a double variable
addElement(double) - Method in class weka.core.matrix.DoubleVector: Adds an element into the vector
addElement(int, int, double) - Method in class weka.core.Matrix: Deprecated.

Add a value to an element.
addElement(E) - Method in class weka.core.FastVector: Deprecated.

Adds an element to this vector.
addElement(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Adds the specified component to the end of this list.
addEmptyRow() - Method in class weka.gui.InteractiveTableModel: Adds an empty row to the model
addErrs(double, double, float) - Static method in class weka.classifiers.trees.j48.Stats: Computes estimated extra error for given total number of instances and error using normal approximation to binomial distribution (and continuity correction).
addExecutionFinishedCallback(ExecutionFinishedCallback) - Method in interface weka.knowledgeflow.FlowExecutor: Add a callback to notify when execution finishes
addExecutionFinishedCallback(ExecutionFinishedCallback) - Method in class weka.knowledgeflow.FlowRunner: Set a callback to notify when flow execution finishes
AddExpression - Class in weka.filters.unsupervised.attribute: An instance filter that creates a new attribute by applying a mathematical expression to existing attributes.
AddExpression() - Constructor for class weka.filters.unsupervised.attribute.AddExpression
addFile(File) - Static method in class weka.core.ClassloaderUtil: Add file to CLASSPATH
addFile(String) - Static method in class weka.core.ClassloaderUtil: Add file to CLASSPATH
addFileFilter(FileFilter) - Method in class weka.gui.beans.FileEnvironmentField: Deprecated.

Add a file filter to use
addFileFilter(FileFilter) - Method in class weka.gui.FileEnvironmentField: Add a file filter to use
addFromProperties(File) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied property file
addFromProperties(File) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied property file
addFromProperties(File, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied property file
addFromProperties(File, boolean) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied property file
addFromProperties(InputStream) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties stream
addFromProperties(InputStream) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied properties stream
addFromProperties(InputStream, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties stream
addFromProperties(InputStream, boolean) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied properties stream
addFromProperties(String, File) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied property file
addFromProperties(String, File, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied property file
addFromProperties(String, InputStream) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties stream
addFromProperties(String, InputStream, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties stream
addFromProperties(String, Properties) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties object
addFromProperties(String, Properties, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties object
addFromProperties(Properties) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties object
addFromProperties(Properties) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied properties object
addFromProperties(Properties, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties object
addFromProperties(Properties, boolean) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied properties object
addGraphListener(GraphListener) - Method in class weka.gui.beans.Associator: Add a graph listener
addGraphListener(GraphListener) - Method in class weka.gui.beans.Classifier: Add a graph listener
addGraphListener(GraphListener) - Method in class weka.gui.beans.Clusterer: Add a graph listener
addHeader(String, String) - Method in class weka.experiment.ResultMatrix: adds the key-value pair to the header.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.ConnectionPanel: adds the given listener to the list of listeners.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.QueryPanel: adds the given listener to the list of listeners.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
AddID - Class in weka.filters.unsupervised.attribute: An instance filter that adds an ID attribute to the dataset.
AddID() - Constructor for class weka.filters.unsupervised.attribute.AddID
addIgnored(Class<?>, String) - Method in class weka.core.xml.PropertyHandler: adds the given class with the display name of a property to the ignore list.
addIgnored(String) - Method in class weka.core.xml.PropertyHandler: adds the given display name of a property to the ignore list.
addImageListener(ImageListener) - Method in class weka.gui.beans.DataVisualizer: Add an image listener
addImageListener(ImageListener) - Method in class weka.gui.beans.ModelPerformanceChart: Add an image listener
addIncomingConnection(String, StepManagerImpl) - Method in class weka.knowledgeflow.StepManagerImpl: Add an incoming connection (comprising of the type of connection and associated step component) to this step of the specified type
addIncrementalClassifierListener(IncrementalClassifierListener) - Method in class weka.gui.beans.Classifier: Add an incremental classifier listener
addIndexedValueToNamedStore(String, Integer, Object) - Method in class weka.knowledgeflow.steps.PairedDataHelper: Adds a value to a named store with the given index.
addInstance() - Method in class weka.gui.arffviewer.ArffPanel: Add an instance at the currently selected index.
addInstance(Instance) - Method in class weka.clusterers.Cobweb: Deprecated.
updateClusterer(Instance) should be used instead
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Adds an instance to the ball tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Adds an instance to the ball tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Adds an instance to the tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Adds an instance to the ball tree.
addInstanceAtEnd() - Method in class weka.gui.arffviewer.ArffPanel: Add an instance at the end of the dataset
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.BallTree: Adds the given instance's info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.CoverTree: Adds the given instance info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Updates the instance info in the underlying search method, once the instance has been filtered.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.KDTree: Adds one instance to KDTree loosly.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.LinearNNSearch: Adds the given instance info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Adds information from the given instance without modifying the datastructure a lot.
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.AbstractDataSource: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Appender: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.ClassAssigner
addInstanceListener(InstanceListener) - Method in interface weka.gui.beans.DataSource: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Filter: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.FlowByExpression
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Join: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Loader: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.PredictionAppender: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Sorter: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.SubstringLabeler: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.SubstringReplacer: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceJoiner
addInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceLoader
addInstanceListener(InstanceListener) - Method in interface weka.gui.streams.InstanceProducer
addInstanceNumberAttribute() - Method in class weka.gui.visualize.PlotData2D: Adds an instance number attribute to the plottable instances,
addInstWithUnknown(Instances, int) - Method in class weka.classifiers.trees.j48.Distribution: Adds all instances with unknown values for given attribute, weighted according to frequency of instances in each bag.
additional() - Method in class weka.core.TechnicalInformation: returns an enumeration of all the additional technical informations (if there are any)
AdditionalMeasureProducer - Interface in weka.core: Interface to something that can produce measures other than those calculated by evaluation modules.
AdditiveRegression - Class in weka.classifiers.meta: Meta classifier that enhances the performance of a regression base classifier.
AdditiveRegression() - Constructor for class weka.classifiers.meta.AdditiveRegression: Default constructor specifying DecisionStump as the classifier
AdditiveRegression(Classifier) - Constructor for class weka.classifiers.meta.AdditiveRegression: Constructor which takes base classifier as argument.
addKeyword(String, MutableAttributeSet) - Method in class weka.gui.scripting.SyntaxDocument: Associates a keyword with a particular formatting style.
addKeywords(String[], MutableAttributeSet) - Method in class weka.gui.scripting.SyntaxDocument: Associates the keywords with a particular formatting style.
addLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: Method to add a LayoutCompleteEventListener
addLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in interface weka.gui.graphvisualizer.LayoutEngine: This method adds a LayoutCompleteEventListener to the LayoutEngine.
addMiningFields(MiningField) - Method in class weka.core.pmml.jaxbbindings.MiningSchema
addModel(SimpleLinearRegression) - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Takes the given simple linear regression model and adds it to this one.
addMouseListener(MouseListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Adds a mouse listener.
addMouseListenerToHeader(JTable) - Method in class weka.gui.SortedTableModel: Adds a mouselistener to the header: left-click on the header sorts in ascending manner, using shift-left-click in descending manner.
addNode(String, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add new node to the network, initializing instances, parentsets, distributions.
addNode(String, int, int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add node to network at a given position, initializing instances, parentsets, distributions.
addNodeValue(int, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add node value to a node.
addNoise(Instances, int, int, int, boolean) - Method in class weka.filters.unsupervised.attribute.AddNoise: add noise to the dataset a given percentage of the instances are changed in the way that a set of instances are randomly selected using seed.
AddNoise - Class in weka.filters.unsupervised.attribute: An instance filter that changes a percentage of a given attribute's values.
AddNoise() - Constructor for class weka.filters.unsupervised.attribute.AddNoise
addNull(String) - Method in class weka.core.json.JSONNode: Adds a "null" child to the object.
addNullArrayElement() - Method in class weka.core.json.JSONNode: Adds a null array element child to the array.
addNumericPredictor(NumericPredictor) - Method in class weka.core.pmml.jaxbbindings.RegressionTable
addObject(String) - Method in class weka.core.json.JSONNode: Adds an object child to the object.
addObject(String, Object) - Method in class weka.gui.ResultHistoryPanel: Adds an object to the results list.
addObjectArrayElement() - Method in class weka.core.json.JSONNode: Add a key-value object child into the array
addOkListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel: This is used to hook an action listener to the ok button.
addOrOverwriteObject(String, Object) - Method in class weka.gui.ResultHistoryPanel: Adds an object to the result list.
addOutgoingConnection(String, StepManagerImpl) - Method in class weka.knowledgeflow.StepManagerImpl: Add an outgoing connection (comprising of the type of connection and associated target step) to this step of the specified type.
addOutgoingConnection(String, StepManagerImpl, boolean) - Method in class weka.knowledgeflow.StepManagerImpl: Add an outgoing connection (comprising of the type of connection and associated target step) to this step of the specified type.
addOutputField(OutputField) - Method in class weka.core.pmml.jaxbbindings.Output
addPackageToClassLoader(File) - Method in class weka.core.WekaPackageClassLoaderManager: Create a class loader for the given package directory
addParent(int, int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet: Add parent to parent set at specific location and update internals (specifically the cardinality of the parent set)
addParent(int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet: Add parent to parent set and update internals (specifically the cardinality of the parent set)
addPCell(PCell) - Method in class weka.core.pmml.jaxbbindings.ParamMatrix
addPlot(PlotData2D) - Method in class weka.gui.visualize.Plot2D: Add a plot to the list of plots to display
addPlot(PlotData2D) - Method in class weka.gui.visualize.VisualizePanel: Set a new plot to the visualize panel
addPlotNotificationListener(StripChart.PlotNotificationListener) - Method in class weka.knowledgeflow.steps.StripChart: Add a plot notification listener
addPlugin(String, String, String) - Static method in class weka.core.PluginManager: Add a plugin.
addPlugin(String, String, String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add a plugin.
addPlugin(String, String, String, boolean) - Static method in class weka.core.PluginManager: Add a plugin.
addPlugin(String, String, String, boolean) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add a plugin.
addPluginResource(String, String, String) - Static method in class weka.core.PluginManager: Add a resource.
addPluginResource(String, String, String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add a resource.
addPluginResource(String, String, String, String) - Static method in class weka.core.PluginManager: Add a resource.
addPluginResourcesFromProperty(String) - Static method in class weka.core.PluginManager: Add resources from a list.
addPreBuiltClassifier(Classifier) - Method in class weka.classifiers.meta.Vote: Add a prebuilt classifier to the list for use in the ensemble
addPrediction(NominalPrediction) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Includes a prediction in the confusion matrix.
addPredictions(ArrayList<Prediction>) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Includes a whole bunch of predictions in the confusion matrix.
addPrimitive(String, Boolean) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPrimitive(String, Double) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPrimitive(String, Integer) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPrimitive(String, String) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.AssociatorCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.BeanVisual: Add a listener for property change events
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassAssignerCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassValuePickerCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClustererCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.EnvironmentField: Deprecated.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.FilterCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.LoaderCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.PredictionAppenderCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SaverCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SerializedModelSaverCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.StripChartCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.ColorEditor
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.CostMatrixEditor: Adds an object to the list of those that wish to be informed when the cost matrix changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.EnvironmentField
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.AbstractSetupPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupModePanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SimpleSetupPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.PreprocessPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericArrayEditor: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericObjectEditor: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.PasswordField
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.PropertySheetPanel: Adds a PropertyChangeListener.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SetInstancesPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SimpleDateFormatEditor: Adds an object to the list of those that wish to be informed when the date format changes.
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.AbstractDataSource: Add a property change listener to this bean
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.DataVisualizer: Add a property change listener to this bean
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart: Add a property change listener to this bean
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.TextViewer: Add a property change listener to this bean
addPropertyChangeListenersSubFlow(PropertyChangeListener) - Method in class weka.gui.beans.MetaBean
addPSFontReplacement(String, String) - Static method in class weka.gui.visualize.PostscriptGraphics: adds the PS font name to replace and its replacement in the replacement hashtable
addQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.QueryPanel: adds the given listener to the list of listeners.
addQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
addRange(int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution: Adds all instances in given range to given bag.
addRelation(Instances) - Method in class weka.core.Attribute: Adds a relation to a relation-valued attribute.
addRemoteExperimentListener(RemoteExperimentListener) - Method in class weka.experiment.RemoteExperiment: Add an object to the list of those interested in recieving update information from the RemoteExperiment
addRemoteExperimentListener(RemoteExperimentListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed: Add an object to the list of those interested in recieving update information from the RemoteExperiment
addRemoteHost(String) - Method in class weka.experiment.RemoteExperiment: Add a host name to the list of remote hosts
addRenderingHints(Map<?, ?>) - Method in class weka.gui.visualize.PostscriptGraphics
addRepaintNotify(Component) - Method in class weka.gui.visualize.ClassPanel: Adds a component that will need to be repainted if the user changes the colour of a label.
addRepaintNotify(Component) - Method in class weka.gui.visualize.LegendPanel: Adds a component that will need to be repainted if the user changes the colour of a label.
ADDRESS - Enum constant in enum class weka.core.TechnicalInformation.Field: Usually the address of the publisher or other type of institution.
addResult(String, StringBuffer) - Method in class weka.gui.ResultHistoryPanel: Adds a new result to the result list.
addResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.ResultPanel: adds the given listener to the list of listeners
addResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
addScriptFinishedListener(ScriptExecutionListener) - Method in class weka.gui.scripting.Script: Adds the given listener to its internal list.
addSettingsMenuItemToProgramMenu(Settings) - Method in class weka.gui.PerspectiveManager: Applications can call this to allow access to the settings editor from the program menu (in addition to the toolbar widget that pops up the settings editor)
addStartupListener(StartUpListener) - Static method in class weka.gui.beans.KnowledgeFlowApp: Add a listener to be notified when startup is complete
addStartupListener(StartUpListener) - Static method in class weka.gui.Main: Add a listener to be notified when startup is complete.
addStep(StepManagerImpl) - Method in class weka.knowledgeflow.Flow: Add the given Step to this flow
addStepOutputListener(StepOutputListener, String) - Method in class weka.knowledgeflow.StepManagerImpl: Register non-step third party to receive data from the managed step for the specified outgoing connection type.
addString(String) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations: Adds a variable declaration for a string variable
addStringValue(String) - Method in class weka.core.Attribute: Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addStringValue(Attribute, int) - Method in class weka.core.Attribute: Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addTab(String) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
addTab(String) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Add a new titled tab to the UI
addTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffSortedTableModel: adds a listener to the list that is notified each time a change to data model occurs
addTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffTableModel: adds a listener to the list that is notified each time a change to data model occurs
addTableModelListener(TableModelListener) - Method in class weka.gui.sql.ResultSetTableModel: adds a listener to the list that is notified each time a change to data model occurs.
addTarget(Target) - Method in class weka.core.pmml.jaxbbindings.Targets
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTestSetProducer: Add a listener for test sets
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Add a test set listener
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.ClassAssigner
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.Filter: Add a test set listener
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.PredictionAppender: Add a test set listener
addTestSetListener(TestSetListener) - Method in interface weka.gui.beans.TestSetProducer: Add a listener for test set events
addTextListener(TextListener) - Method in class weka.gui.beans.Associator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.Classifier: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.Clusterer: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.TextViewer: Add a text listener
addThresholdDataListener(ThresholdDataListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Add a threshold data listener
addTitleUpdatedListener(TitleUpdatedListener) - Method in class weka.gui.scripting.ScriptingPanel: Adds the listener to the internal list.
addToDisabledList(String) - Static method in class weka.core.PluginManager: Add the supplied fully qualified class name to the list of disabled plugins
addToDisabledList(String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add the supplied fully qualified class name to the list of disabled plugins
addToDisabledList(List<String>) - Static method in class weka.core.PluginManager: Add the supplied list of fully qualified class names to the disabled list
addToDisabledList(List<String>) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add the supplied list of fully qualified class names to the disabled list
addToHistory() - Method in class weka.gui.PropertyPanel: Adds the current editor value to the history.
addToHistory(Object) - Method in class weka.gui.PropertyPanel: Adds the specified value to the history.
addToList(Object[], double) - Method in class weka.attributeSelection.BestFirst.LinkedList2: adds an element (Link) to the list.
addToPluginBeanProps(File) - Static method in class weka.gui.beans.BeansProperties
addToPluginBeanProps(File) - Static method in class weka.gui.beans.KnowledgeFlowApp: Add a plugin bean props file
addToResult(Data) - Method in class weka.knowledgeflow.JobEnvironment: Add a non-incremental data object to the result
addToStepProperties(Map<String, Map<String, String>>) - Method in class weka.knowledgeflow.JobEnvironment: Add the supplied map of step properties.
addTrainingInstance(Instance) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Adds a training instance to the visualization dataset.
addTrainingInstanceFromMouseLocation(int, int, int, double) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Adds a training instance to our dataset, based on the coordinates of the mouse on the panel.
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.ClassAssigner
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.Filter: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.PredictionAppender: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in interface weka.gui.beans.TrainingSetProducer: Add a training set listener
addUndoPoint() - Method in interface weka.core.Undoable: adds an undo point to the undo history
addUndoPoint() - Method in class weka.gui.arffviewer.ArffPanel: adds the current state of the instances to the undolist
addUndoPoint() - Method in class weka.gui.arffviewer.ArffSortedTableModel: adds an undo point to the undo history
addUndoPoint() - Method in class weka.gui.arffviewer.ArffTableModel: adds an undo point to the undo history, if the undo support is enabled
addUndoPoint() - Method in class weka.gui.explorer.PreprocessPanel: Backs up the current state of the dataset, so the changes can be undone.
addUntitledTab() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Add a new untitled tab to the UI
addURL(URL) - Static method in class weka.core.ClassloaderUtil: Add URL to CLASSPATH
AddUserFields - Class in weka.filters.unsupervised.attribute: A filter that adds new attributes with user specified type and constant value.
AddUserFields() - Constructor for class weka.filters.unsupervised.attribute.AddUserFields: Constructs a new AddUserFields
AddUserFields.AttributeSpec - Class in weka.filters.unsupervised.attribute: Inner class encapsulating a new user-specified attribute to create.
AddUserFieldsBeanInfo - Class in weka.filters.unsupervised.attribute: Bean info class for the AddUserFields filter.
AddUserFieldsBeanInfo() - Constructor for class weka.filters.unsupervised.attribute.AddUserFieldsBeanInfo
AddUserFieldsCustomizer - Class in weka.gui.filters: Customizer for the AddUserFields filter.
AddUserFieldsCustomizer() - Constructor for class weka.gui.filters.AddUserFieldsCustomizer: Constructor
addValue(double, double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.DiscreteEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.Estimator: Add a new data value to the current estimator.
addValue(double, double) - Method in interface weka.estimators.IncrementalEstimator: Add one value to the current estimator.
addValue(double, double) - Method in class weka.estimators.KernelEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.MahalanobisEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.NormalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.PoissonEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in interface weka.estimators.UnivariateDensityEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in interface weka.estimators.UnivariateIntervalEstimator: Adds a value to the interval estimator.
addValue(double, double) - Method in class weka.estimators.UnivariateKernelEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in class weka.estimators.UnivariateMixtureEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in class weka.estimators.UnivariateNormalEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in interface weka.estimators.UnivariateQuantileEstimator: Adds a value to the interval estimator.
addValue(double, double, double) - Method in interface weka.estimators.ConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DDConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DKConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DNConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.KDConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.KKConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.NDConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.NNConditionalEstimator: Add a new data value to the current estimator.
addValue(Value) - Method in class weka.core.pmml.jaxbbindings.DataField
addValues(Instances, int) - Method in class weka.estimators.Estimator: Initialize the estimator with a new dataset.
addValues(Instances, int, double, double, double) - Method in class weka.estimators.Estimator: Initialize the estimator with all values of one attribute of a dataset.
addValues(Instances, int, int, int) - Method in class weka.estimators.Estimator: Initialize the estimator using only the instances of one class.
addValues(Instances, int, int, int, double, double) - Method in class weka.estimators.Estimator: Initialize the estimator using only the instances of one class.
AddValues - Class in weka.filters.unsupervised.attribute: Adds the labels from the given list to an attribute if they are missing.
AddValues() - Constructor for class weka.filters.unsupervised.attribute.AddValues
addVariable(String, String) - Method in class weka.core.Environment: Add a variable to the internal map of this properties object.
addVariableSystemWide(String, String) - Method in class weka.core.Environment: Add a a variable to the internal map of this properties object and to the global system-wide environment;
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.AbstractDataSource: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.CostBenefitAnalysis
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.DataVisualizer: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.GraphViewer: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.TextViewer: Add a vetoable change listener to this bean
addVisualizableErrorListener(VisualizableErrorListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Add a visualizable error listener
addWeights(Instance, double[]) - Method in class weka.classifiers.trees.j48.Distribution: Adds given instance to all bags weighting it according to given weights.
adjustCenter(double) - Method in class weka.gui.treevisualizer.Node: Will increase or decrease the postion of center.
adjustWeightsTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns the tip text for this property
ADNode - Class in weka.classifiers.bayes.net: The ADNode class implements the ADTree datastructure which increases the speed with which sub-contingency tables can be constructed from a data set in an Instances object.
ADNode() - Constructor for class weka.classifiers.bayes.net.ADNode: Creates new ADNode
advanceCounters() - Method in class weka.experiment.Experiment: Increments iteration counters appropriately.
advanceCounters() - Method in class weka.experiment.RemoteExperiment: overides the one in Experiment
AFFILIATION - Enum constant in enum class weka.core.TechnicalInformation.Field: The authors affiliation.
AFFINITY - Enum constant in enum class weka.core.pmml.jaxbbindings.RESULTFEATURE
AFFINITY - Enum constant in enum class weka.core.pmml.jaxbbindings.RULEFEATURE
aggregate(E) - Method in interface weka.core.Aggregateable: Aggregate an object with this one
aggregate(NaiveBayes) - Method in class weka.classifiers.bayes.NaiveBayes
aggregate(NaiveBayesMultinomialText) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText
aggregate(Classifier) - Method in class weka.classifiers.meta.Vote: Aggregate an object with this one
aggregate(Evaluation) - Method in class weka.classifiers.AggregateableEvaluation: Adds the statistics encapsulated in the supplied Evaluation object into this one.
aggregate(Evaluation) - Method in class weka.classifiers.evaluation.AggregateableEvaluation: Adds the statistics encapsulated in the supplied Evaluation object into this one.
aggregate(Logistic) - Method in class weka.classifiers.functions.Logistic: Aggregate an object with this one
aggregate(SGD) - Method in class weka.classifiers.functions.SGD: Aggregate an object with this one
aggregate(SGDText) - Method in class weka.classifiers.functions.SGDText: Aggregate an object with this one
aggregate(Bagging) - Method in class weka.classifiers.meta.Bagging: Aggregate an object with this one
aggregate(DictionaryBuilder) - Method in class weka.core.DictionaryBuilder
aggregate(DiscreteEstimator) - Method in class weka.estimators.DiscreteEstimator
aggregate(KernelEstimator) - Method in class weka.estimators.KernelEstimator
aggregate(NormalEstimator) - Method in class weka.estimators.NormalEstimator
Aggregate - Class in weka.core.pmml.jaxbbindings: Java class for Aggregate element declaration.
Aggregate() - Constructor for class weka.core.pmml.jaxbbindings.Aggregate
AGGREGATE_NODES - Enum constant in enum class weka.core.pmml.jaxbbindings.MISSINGVALUESTRATEGY
Aggregateable<E> - Interface in weka.core: Interface to something that can aggregate an object of the same type with itself.
AggregateableEvaluation - Class in weka.classifiers: Subclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object.
AggregateableEvaluation - Class in weka.classifiers.evaluation: Subclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object.
AggregateableEvaluation(Evaluation) - Constructor for class weka.classifiers.AggregateableEvaluation: Constructs a new AggregateableEvaluation object based on an Evaluation object
AggregateableEvaluation(Evaluation) - Constructor for class weka.classifiers.evaluation.AggregateableEvaluation: Constructs a new AggregateableEvaluation object based on an Evaluation object
AggregateableEvaluation(Instances) - Constructor for class weka.classifiers.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Instances) - Constructor for class weka.classifiers.evaluation.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.evaluation.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
aggregateCanopies(List<Canopy>, double, double, NormalizableDistance, Filter, int) - Static method in class weka.clusterers.Canopy: Aggregate the canopies from a list of Canopy clusterers together into one final model.
Agrawal - Class in weka.datagenerators.classifiers.classification: Generates a people database and is based on the paper by Agrawal et al.:
R.
Agrawal() - Constructor for class weka.datagenerators.classifiers.classification.Agrawal: initializes the generator with default values
AIC - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
AlgorithmListPanel - Class in weka.gui.experiment: This panel controls setting a list of algorithms for an experiment to iterate over.
AlgorithmListPanel() - Constructor for class weka.gui.experiment.AlgorithmListPanel: Create the algorithm list panel initially disabled.
AlgorithmListPanel(Experiment) - Constructor for class weka.gui.experiment.AlgorithmListPanel: Creates the algorithm list panel with the given experiment.
AlgorithmListPanel.ObjectCellRenderer - Class in weka.gui.experiment: Class required to show the Classifiers nicely in the list
AlgVector - Class in weka.core: Class for performing operations on an algebraic vector of floating-point values.
AlgVector(double[]) - Constructor for class weka.core.AlgVector: Constructs a vector using a given array.
AlgVector(int) - Constructor for class weka.core.AlgVector: Constructs a vector and initializes it with default values.
AlgVector(Instance) - Constructor for class weka.core.AlgVector: Constructs a vector using an instance.
AlgVector(Instances, Random) - Constructor for class weka.core.AlgVector: Constructs a vector using a given data format.
alignBottom(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the bottom most node in the list
alignLeft(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the left most node in the list
alignRight(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the right most node in the list
alignTop(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the top most node in the list
ALL - Enum constant in enum class weka.core.logging.Logger.Level: logs all messages.
ALL - Static variable in class weka.core.Debug: the log level All
allAttributeWeightsIdentical() - Method in class weka.core.Instances: Returns true if all attribute weights are the same and false otherwise.
AllFilter - Class in weka.filters: A simple instance filter that passes all instances directly through.
AllFilter() - Constructor for class weka.filters.AllFilter
allInstanceWeightsIdentical() - Method in class weka.core.Instances: Returns true if all instance weights are the same and false otherwise.
AllJavadoc - Class in weka.core: Applies all known Javadoc-derived classes to a source file.
AllJavadoc() - Constructor for class weka.core.AllJavadoc
allowAccessToFullInputFormat() - Method in class weka.filters.SimpleBatchFilter: Returns whether to allow the determineOutputFormat(Instances) method access to the full dataset rather than just the header.
allowAccessToFullInputFormat() - Method in class weka.filters.supervised.attribute.MergeNominalValues: We need access to the full input data in determineOutputFormat.
allowAccessToFullInputFormat() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: We need access to the full input data in determineOutputFormat.
allowAccessToFullInputFormat() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Returns whether to allow the determineOutputFormat(Instances) method access to the full dataset rather than just the header.
allowed() - Method in class weka.core.xml.PropertyHandler: returns an enumeration of the classnames for which only certain properties (display names) are allowed
allowUnclassifiedInstancesTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property
AlphabeticTokenizer - Class in weka.core.tokenizers: Alphabetic string tokenizer, tokens are to be formed only from contiguous alphabetic sequences.
AlphabeticTokenizer() - Constructor for class weka.core.tokenizers.AlphabeticTokenizer
alphaTipText() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
Alternate - Class in weka.core.pmml.jaxbbindings: Java class for Alternate element declaration.
Alternate() - Constructor for class weka.core.pmml.jaxbbindings.Alternate
AlterRelationName - Class in weka.knowledgeflow.steps: Step that alters the relation name for data received via instance, dataSet, trainingSet and testSet connections
AlterRelationName() - Constructor for class weka.knowledgeflow.steps.AlterRelationName
ALWAYS_SEND_INSTANCES_TO_ALL - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
ALWAYS_SEND_INSTANCES_TO_ALL_KEY - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
amplitudeTipText() - Method in class weka.datagenerators.classifiers.regression.Expression: Returns the tip text for this property
amplitudeTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Returns the tip text for this property
ANALYSIS_WEIGHT - Enum constant in enum class weka.core.pmml.jaxbbindings.FIELDUSAGETYPE
and(Capabilities) - Method in class weka.core.Capabilities: performs an AND conjunction with the capabilities of the given Capabilities object and updates itself
and(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '&' or 'and' logical and operator
AND - Static variable in interface weka.core.expressionlanguage.parser.sym
Annotation - Class in weka.core.pmml.jaxbbindings: Java class for Annotation element declaration.
Annotation() - Constructor for class weka.core.pmml.jaxbbindings.Annotation
ANNOTE - Enum constant in enum class weka.core.TechnicalInformation.Field: An annotation.
Anova - Class in weka.core.pmml.jaxbbindings: Java class for Anova element declaration.
Anova() - Constructor for class weka.core.pmml.jaxbbindings.Anova
AnovaRow - Class in weka.core.pmml.jaxbbindings: Java class for AnovaRow element declaration.
AnovaRow() - Constructor for class weka.core.pmml.jaxbbindings.AnovaRow
Antd(Attribute) - Constructor for class weka.classifiers.rules.JRip.Antd: Constructor
ANTECEDENT - Enum constant in enum class weka.core.pmml.jaxbbindings.RULEFEATURE
AntecedentSequence - Class in weka.core.pmml.jaxbbindings: Java class for AntecedentSequence element declaration.
AntecedentSequence() - Constructor for class weka.core.pmml.jaxbbindings.AntecedentSequence
AnyDistribution - Class in weka.core.pmml.jaxbbindings: Java class for AnyDistribution element declaration.
AnyDistribution() - Constructor for class weka.core.pmml.jaxbbindings.AnyDistribution
APP_ID - Static variable in class weka.gui.GUIChooserApp.GUIChooserDefaults: ID
APP_ID - Static variable in class weka.gui.WorkbenchDefaults
APP_ID - Static variable in class weka.knowledgeflow.KFDefaults
APP_NAME - Static variable in class weka.gui.GUIChooserApp.GUIChooserDefaults: APP name (GUIChooser isn't really an "app" as such
APP_NAME - Static variable in class weka.gui.WorkbenchDefaults
APP_NAME - Static variable in class weka.knowledgeflow.KFDefaults
append(char) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: Appends the specified character to this output stream.
append(char) - Method in class weka.core.Tee: Appends the specified character to this output stream.
append(CharSequence) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: Appends the specified character sequence to this output stream.
append(CharSequence) - Method in class weka.core.Tee: Appends the specified character sequence to this output stream.
append(CharSequence, int, int) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: Appends a subsequence of the specified character sequence to this output stream.
append(CharSequence, int, int) - Method in class weka.core.Tee: Appends a subsequence of the specified character sequence to this output stream.
append(Object) - Method in class weka.gui.sql.InfoPanel: adds the given message to the end of the list
append(String, String) - Method in class weka.gui.sql.InfoPanel: adds the given message to the end of the list (with the associated icon at the beginning)
appendBeans(JComponent, Vector<Object>, int) - Static method in class weka.gui.beans.BeanInstance
appendConnections(Vector<BeanConnection>, int) - Static method in class weka.gui.beans.BeanConnection: Append the supplied connections to the list for the given tab index
appendElements(Collection<? extends E>) - Method in class weka.core.FastVector: Deprecated.

Appends all elements of the supplied vector to this vector.
Appender - Class in weka.gui.beans: A bean that appends multiple incoming data connections into a single data set.
Appender - Class in weka.knowledgeflow.steps: A bean that appends multiple incoming data connections into a single data set.
Appender() - Constructor for class weka.gui.beans.Appender: Constructs a new Appender.
Appender() - Constructor for class weka.knowledgeflow.steps.Appender
AppenderBeanInfo - Class in weka.gui.beans: Bean info class for the appender bean
AppenderBeanInfo() - Constructor for class weka.gui.beans.AppenderBeanInfo
appendPredictedProbabilitiesTipText() - Method in class weka.gui.beans.PredictionAppender: Return a tip text suitable for displaying in a GUI
Application - Class in weka.core.pmml.jaxbbindings: Java class for Application element declaration.
Application() - Constructor for class weka.core.pmml.jaxbbindings.Application
Application(String, String) - Constructor for class weka.core.pmml.jaxbbindings.Application
appliesToNominalClass() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Return true if this evaluation metric can be computed when the class is nominal
appliesToNumericClass() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Return true if this evaluation metric can be computed when the class is numeric
apply(String[]) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Apply this rule to the supplied array of strings.
apply(Instance) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Apply this rule to the supplied instance
apply(Instance) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Apply this rule to the supplied instance
Apply - Class in weka.core.pmml.jaxbbindings: Java class for Apply element declaration.
Apply() - Constructor for class weka.core.pmml.jaxbbindings.Apply
applyClassifier(PMMLModel, Instances) - Static method in class weka.core.pmml.PMMLFactory
applyCostMatrix(Instances, Random) - Method in class weka.classifiers.CostMatrix: Applies the cost matrix to a set of instances.
applyDefaults(Defaults) - Method in class weka.core.Settings: Applies a set of default settings.
applyMinMaxRescaleCast(double) - Method in class weka.core.pmml.TargetMetaInfo: Apply min and max, rescaleFactor, rescaleConstant and castInteger - in that order (where defined).
applyMissingAndOutlierTreatments(double[]) - Method in class weka.core.pmml.MiningSchema: Apply both missing and outlier treatments to an incoming instance.
applyMissingValuesTreatment(double[]) - Method in class weka.core.pmml.MiningSchema: Apply the missing value treatments (if any) to an incoming instance.
applyMissingValueTreatment(double) - Method in class weka.core.pmml.MiningFieldMetaInfo: Apply the missing value treatment method for this field.
applyOutlierTreatment(double) - Method in class weka.core.pmml.MiningFieldMetaInfo: Apply the outlier treatment method for this field.
applyOutlierTreatment(double[]) - Method in class weka.core.pmml.MiningSchema: Apply the outlier treatment methods (if any) to an incoming instance.
applyRules(Instance) - Method in class weka.gui.beans.SubstringReplacerRules
applySettings(Settings) - Method in class weka.core.packageManagement.DefaultPackageManager: Apply settings.
applySettings(Settings) - Method in class weka.core.packageManagement.PackageManager: Apply the supplied settings.
applySettings(Settings) - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: No-op implementation.
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.AttributeSummarizerInteractiveView: Apply user-changed settings
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.DataVisualizerInteractiveView: Apply any user changes in the supplied settings object
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.ModelPerformanceChartInteractiveView: Apply any user changes in the supplied settings object
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.ScatterPlotMatrixInteractiveView: Apply any changes to the settings
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.StripChartInteractiveView: Apply settings from the supplied settings object
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.TextViewerInteractiveView: Applys settings from the supplied settings object
applySettings(Settings, String) - Method in class weka.gui.visualize.AttributePanel: Apply settings
applySettings(Settings, String) - Method in class weka.gui.visualize.MatrixPanel
applySettings(Settings, String) - Method in class weka.gui.visualize.Plot2D: Apply settings
applySettings(Settings, String) - Method in class weka.gui.visualize.VisualizePanel: Apply settings
applyToSettings() - Method in class weka.gui.SettingsEditor
applyToSettings() - Method in class weka.gui.SettingsEditor.SingleSettingsEditor
APPROVE_OPTION - Static variable in class weka.gui.experiment.OutputFormatDialog: Signifies an OK property selection.
APPROVE_OPTION - Static variable in class weka.gui.ListSelectorDialog: Signifies an OK property selection
APPROVE_OPTION - Static variable in class weka.gui.PropertySelectorDialog: Signifies an OK property selection
APPROVE_OPTION - Static variable in class weka.gui.ViewerDialog: Signifies an OK property selection
Apriori - Class in weka.associations: Class implementing an Apriori-type algorithm.
Apriori() - Constructor for class weka.associations.Apriori: Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.
AprioriItemSet - Class in weka.associations: Class for storing a set of items.
AprioriItemSet(int) - Constructor for class weka.associations.AprioriItemSet: Constructor
ARCTAN - Enum constant in enum class weka.core.pmml.jaxbbindings.ACTIVATIONFUNCTION
areaUnderPRC(int) - Method in class weka.classifiers.Evaluation: Returns the area under precision-recall curve (AUPRC) for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
areaUnderPRC(int) - Method in class weka.classifiers.evaluation.Evaluation: Returns the area under precision-recall curve (AUPRC) for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
areaUnderROC(int) - Method in class weka.classifiers.Evaluation: Returns the area under ROC for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
areaUnderROC(int) - Method in class weka.classifiers.evaluation.Evaluation: Returns the area under ROC for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
ARFF_ATTRIBUTE - Static variable in class weka.core.Attribute: The keyword used to denote the start of an arff attribute declaration
ARFF_ATTRIBUTE_DATE - Static variable in class weka.core.Attribute: The keyword used to denote a date attribute
ARFF_ATTRIBUTE_INTEGER - Static variable in class weka.core.Attribute: A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_NUMERIC - Static variable in class weka.core.Attribute: A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_REAL - Static variable in class weka.core.Attribute: A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_RELATIONAL - Static variable in class weka.core.Attribute: The keyword used to denote a relation-valued attribute
ARFF_ATTRIBUTE_STRING - Static variable in class weka.core.Attribute: The keyword used to denote a string attribute
ARFF_DATA - Static variable in class weka.core.Instances: The keyword used to denote the start of the arff data section
ARFF_END_SUBRELATION - Static variable in class weka.core.Attribute: The keyword used to denote the end of the declaration of a subrelation
ARFF_RELATION - Static variable in class weka.core.Instances: The keyword used to denote the start of an arff header
ArffLoader - Class in weka.core.converters: Reads a source that is in arff (attribute relation file format) format.
ArffLoader() - Constructor for class weka.core.converters.ArffLoader
ArffLoader.ArffReader - Class in weka.core.converters: Reads data from an ARFF file, either in incremental or batch mode.
ArffPanel - Class in weka.gui.arffviewer: A Panel representing an ARFF-Table and the associated filename.
ArffPanel() - Constructor for class weka.gui.arffviewer.ArffPanel: initializes the panel with no data
ArffPanel(String, AbstractFileLoader...) - Constructor for class weka.gui.arffviewer.ArffPanel: initializes the panel and loads the specified file
ArffPanel(Instances) - Constructor for class weka.gui.arffviewer.ArffPanel: initializes the panel with the given data
ArffReader(Reader) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Reads the data completely from the reader.
ArffReader(Reader, int) - Constructor for class weka.core.converters.ArffLoader.ArffReader
ArffReader(Reader, int, boolean) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Reads only the header and reserves the specified space for instances.
ArffReader(Reader, Instances, int, int, boolean, String...) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Initializes the reader without reading the header according to the specified template.
ArffReader(Reader, Instances, int, int, String...) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Initializes the reader without reading the header according to the specified template.
ArffReader(Reader, Instances, int, String...) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Reads the data without header according to the specified template.
ArffSaver - Class in weka.core.converters: Writes to a destination in arff text format.
ArffSaver() - Constructor for class weka.core.converters.ArffSaver: Constructor
ArffSortedTableModel - Class in weka.gui.arffviewer: A sorter for the ARFF-Viewer - necessary because of the custom CellRenderer.
ArffSortedTableModel(String, AbstractFileLoader...) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel: initializes the sorter w/o a model, but loads the given file and creates from that a model
ArffSortedTableModel(TableModel) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel: initializes the sorter with the given model
ArffSortedTableModel(Instances) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel: initializes the sorter w/o a model, but uses the given data to create a model from that
ArffTable - Class in weka.gui.arffviewer: A specialized JTable for the Arff-Viewer.
ArffTable() - Constructor for class weka.gui.arffviewer.ArffTable: initializes with no model
ArffTable(TableModel) - Constructor for class weka.gui.arffviewer.ArffTable: initializes with the given model
ArffTableCellRenderer - Class in weka.gui.arffviewer: Handles the background colors for missing values differently than the DefaultTableCellRenderer.
ArffTableCellRenderer() - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer: initializes the Renderer with a standard color
ArffTableCellRenderer(Color, Color) - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer: initializes the Renderer with the given colors
ArffTableCellRenderer(Color, Color, Color, Color) - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer: initializes the Renderer with the given colors
ArffTableModel - Class in weka.gui.arffviewer: The model for the Arff-Viewer.
ArffTableModel(String, AbstractFileLoader...) - Constructor for class weka.gui.arffviewer.ArffTableModel: initializes the object and loads the given file
ArffTableModel(Instances) - Constructor for class weka.gui.arffviewer.ArffTableModel: initializes the model with the given data
ArffViewer - Class in weka.gui.arffviewer: A little tool for viewing ARFF files.
ArffViewer() - Constructor for class weka.gui.arffviewer.ArffViewer: initializes the object
ArffViewerMainPanel - Class in weka.gui.arffviewer: The main panel of the ArffViewer.
ArffViewerMainPanel(Container) - Constructor for class weka.gui.arffviewer.ArffViewerMainPanel: initializes the object
ARIMA - Enum constant in enum class weka.core.pmml.jaxbbindings.TIMESERIESALGORITHM
Array - Class in weka.core.pmml: Class for encapsulating a PMML Array element.
ARRAY - Enum constant in enum class weka.core.json.JSONNode.NodeType: an array.
Array.ArrayType - Enum Class in weka.core.pmml
arrayLeftDivide(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element left division, C = A.\B
arrayLeftDivideEquals(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element left division in place, A = A.\B
arrayRightDivide(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element right division, C = A./B
arrayRightDivideEquals(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element right division in place, A = A./B
arrayTimes(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element multiplication, C = A.*B
arrayTimesEquals(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element multiplication in place, A = A.*B
arrayToString(Object) - Static method in class weka.core.Utils: Returns the given Array in a string representation.
arrayToString(Object[]) - Static method in class weka.experiment.DatabaseUtils: Converts an array of objects to a string by inserting a space between each element.
ArrayType - Class in weka.core.pmml.jaxbbindings: Java class for ArrayType complex type.
ArrayType() - Constructor for class weka.core.pmml.jaxbbindings.ArrayType
ARTICLE - Enum constant in enum class weka.core.TechnicalInformation.Type: An article from a journal or magazine.
AS_EXTREME_VALUES - Enum constant in enum class weka.core.pmml.jaxbbindings.OUTLIERTREATMENTMETHOD
AS_IS - Enum constant in enum class weka.core.pmml.jaxbbindings.INVALIDVALUETREATMENTMETHOD
AS_IS - Enum constant in enum class weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD
AS_IS - Enum constant in enum class weka.core.pmml.jaxbbindings.OUTLIERTREATMENTMETHOD
AS_MEAN - Enum constant in enum class weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD
AS_MEDIAN - Enum constant in enum class weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD
AS_MISSING - Enum constant in enum class weka.core.pmml.jaxbbindings.INVALIDVALUETREATMENTMETHOD
AS_MISSING_VALUES - Enum constant in enum class weka.core.pmml.jaxbbindings.OUTLIERTREATMENTMETHOD
AS_MODE - Enum constant in enum class weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD
AS_VALUE - Enum constant in enum class weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD
ASEvaluation - Class in weka.attributeSelection: Abstract attribute selection evaluation class
ASEvaluation() - Constructor for class weka.attributeSelection.ASEvaluation
ASEvaluator - Class in weka.knowledgeflow.steps: Step that wraps a Weka attribute or subset evaluator.
ASEvaluator() - Constructor for class weka.knowledgeflow.steps.ASEvaluator
ASEvaluatorStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the ASEvaluator step
ASEvaluatorStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.ASEvaluatorStepEditorDialog
ASSearch - Class in weka.attributeSelection: Abstract attribute selection search class.
ASSearch() - Constructor for class weka.attributeSelection.ASSearch
ASSearchStrategy - Class in weka.knowledgeflow.steps: Step that wraps a Weka attribute selection search strategy.
ASSearchStrategy() - Constructor for class weka.knowledgeflow.steps.ASSearchStrategy
assign(Capabilities) - Method in class weka.core.Capabilities: retrieves the data from the given Capabilities object
assign(TestInstances) - Method in class weka.core.TestInstances: updates itself with all the settings from the given TestInstances object
assign(ResultMatrix) - Method in class weka.experiment.ResultMatrix: acquires the data from the given matrix.
assign(Tester) - Method in class weka.experiment.PairedTTester: retrieves all the settings from the given Tester
assign(Tester) - Method in interface weka.experiment.Tester: retrieves all the settings from the given Tester
assignCanopies(Instance) - Method in class weka.clusterers.Canopy: Uses T1 distance to assign canopies to the supplied instance.
assignIDs(int) - Method in class weka.classifiers.trees.j48.ClassifierTree: Assigns a uniqe id to every node in the tree.
assignIDs(int) - Method in class weka.classifiers.trees.lmt.LMTNode: Assigns unique IDs to all nodes in the tree
assignLeafModelNumbers(int) - Method in class weka.classifiers.trees.lmt.LMTNode: Assigns numbers to the logistic regression models at the leaves of the tree
assignSubToCenters(KDTreeNode, Instances, int[], int[]) - Method in class weka.core.neighboursearch.KDTree: Assigns instances of this node to center.
associatedConnections(Vector<Object>, Integer...) - Static method in class weka.gui.beans.BeanConnection: Returns a vector of BeanConnections associated with the supplied vector of BeanInstances, i.e.
ASSOCIATION_RULES - Enum constant in enum class weka.core.pmml.jaxbbindings.MININGFUNCTION
AssociationModel - Class in weka.core.pmml.jaxbbindings: Java class for AssociationModel element declaration.
AssociationModel() - Constructor for class weka.core.pmml.jaxbbindings.AssociationModel
AssociationRule - Class in weka.associations: Abstract class for storing and manipulating an association rule.
AssociationRule - Class in weka.core.pmml.jaxbbindings: Java class for AssociationRule element declaration.
AssociationRule() - Constructor for class weka.associations.AssociationRule
AssociationRule() - Constructor for class weka.core.pmml.jaxbbindings.AssociationRule
AssociationRules - Class in weka.associations: Class encapsulating a list of association rules.
AssociationRules(List<AssociationRule>) - Constructor for class weka.associations.AssociationRules: Constructs a new AssociationRules.
AssociationRules(List<AssociationRule>, Object) - Constructor for class weka.associations.AssociationRules: Constructs a new AssociationRules.
AssociationRules(List<AssociationRule>, String) - Constructor for class weka.associations.AssociationRules: Constructs a new AssociationRules.
AssociationRulesProducer - Interface in weka.associations: Interface to something that can provide a list of AssociationRules.
AssociationRuleVisualizePlugin - Interface in weka.gui.visualize.plugins: Interface implemented by classes loaded dynamically to visualize association results in the explorer.
AssociationsPanel - Class in weka.gui.explorer: This panel allows the user to select, configure, and run a scheme that learns associations.
AssociationsPanel() - Constructor for class weka.gui.explorer.AssociationsPanel: Creates the associator panel
Associator - Class in weka.gui.beans: Bean that wraps around weka.associations.
Associator - Class in weka.knowledgeflow.steps: Step that wraps a Weka associator.
Associator - Interface in weka.associations
Associator() - Constructor for class weka.gui.beans.Associator: Creates a new Associator instance.
Associator() - Constructor for class weka.knowledgeflow.steps.Associator
ASSOCIATOR - Enum constant in enum class weka.Run.SchemeType
AssociatorBeanInfo - Class in weka.gui.beans: BeanInfo class for the Associator wrapper bean
AssociatorBeanInfo() - Constructor for class weka.gui.beans.AssociatorBeanInfo
AssociatorCustomizer - Class in weka.gui.beans: GUI customizer for the associator wrapper bean
AssociatorCustomizer() - Constructor for class weka.gui.beans.AssociatorCustomizer
AssociatorEvaluation - Class in weka.associations: Class for evaluating Associaters.
AssociatorEvaluation() - Constructor for class weka.associations.AssociatorEvaluation: default constructor
associatorTipText() - Method in class weka.associations.SingleAssociatorEnhancer: Returns the tip text for this property
ATT_ARRAY - Static variable in class weka.core.xml.XMLSerialization: the tag whether array or not (yes/no)
ATT_ARRAY_DEFAULT - Static variable in class weka.core.xml.XMLSerialization: default value for attribute ATT_ARRAY
ATT_CLASS - Static variable in class weka.core.xml.XMLInstances: the class attribute
ATT_CLASS - Static variable in class weka.core.xml.XMLSerialization: the tag for the class
ATT_FORMAT - Static variable in class weka.core.xml.XMLInstances: the format attribute (for date attributes)
ATT_INDEX - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the index attribute.
ATT_INDEX - Static variable in class weka.core.xml.XMLInstances: the index attribute
ATT_MISSING - Static variable in class weka.core.xml.XMLInstances: the missing attribute
ATT_NAME - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the "name" attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLDocument: the "name" attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLOptions: the name attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLSerialization: the tag for the name
ATT_NULL - Static variable in class weka.core.xml.XMLSerialization: the tag whether null or not (yes/no)
ATT_NULL_DEFAULT - Static variable in class weka.core.xml.XMLSerialization: default value for attribute ATT_NULL
ATT_PREDICTED - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the predicted attribute.
ATT_PRIMITIVE - Static variable in class weka.core.xml.XMLSerialization: the tag whether primitive or not (yes/no)
ATT_PRIMITIVE_DEFAULT - Static variable in class weka.core.xml.XMLSerialization: default value for attribute ATT_PRIMITIVE
ATT_TYPE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the "type" attribute.
ATT_TYPE - Static variable in class weka.core.xml.XMLInstances: the type attribute
ATT_TYPE - Static variable in class weka.core.xml.XMLOptions: the type attribute.
ATT_VALUE - Static variable in class weka.core.xml.XMLOptions: the value attribute.
ATT_VERSION - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the "version" attribute.
ATT_VERSION - Static variable in class weka.core.xml.XMLDocument: the "version" attribute.
ATT_VERSION - Static variable in class weka.core.xml.XMLInstances: the version attribute
ATT_VERSION - Static variable in class weka.core.xml.XMLSerialization: the version attribute
ATT_WEIGHT - Static variable in class weka.core.xml.XMLInstances: the weight attribute
AttDefaults() - Constructor for class weka.gui.knowledgeflow.AttributeSummaryPerspective.AttDefaults
attIndex() - Method in class weka.classifiers.trees.j48.BinC45Split: Returns index of attribute for which split was generated.
attIndex() - Method in class weka.classifiers.trees.j48.C45Split: Returns index of attribute for which split was generated.
attIndex() - Method in class weka.classifiers.trees.j48.NBTreeSplit: Returns index of attribute for which split was generated.
attList_IrrTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the tip text for this property
attribute(int) - Method in class weka.core.AbstractInstance: Returns the attribute with the given index.
attribute(int) - Method in interface weka.core.Instance: Returns the attribute with the given index.
attribute(int) - Method in class weka.core.Instances: Returns an attribute.
attribute(String) - Method in class weka.core.Instances: Returns an attribute given its name.
Attribute - Class in weka.core: Class for handling an attribute.
Attribute - Class in weka.core.pmml.jaxbbindings: Java class for Attribute element declaration.
Attribute() - Constructor for class weka.core.pmml.jaxbbindings.Attribute
Attribute(String) - Constructor for class weka.core.Attribute: Constructor for a numeric attribute.
Attribute(String, boolean) - Constructor for class weka.core.Attribute: Constructor for a numeric or string attribute.
Attribute(String, boolean, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for a numeric or string attribute, where metadata is supplied.
Attribute(String, int) - Constructor for class weka.core.Attribute: Constructor for a numeric attribute with a particular index.
Attribute(String, String) - Constructor for class weka.core.Attribute: Constructor for a date attribute.
Attribute(String, String, int) - Constructor for class weka.core.Attribute: Constructor for date attributes with a particular index.
Attribute(String, String, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for a date attribute, where metadata is supplied.
Attribute(String, List<String>) - Constructor for class weka.core.Attribute: Constructor for nominal attributes and string attributes.
Attribute(String, List<String>, int) - Constructor for class weka.core.Attribute: Constructor for nominal attributes and string attributes with a particular index.
Attribute(String, List<String>, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for nominal attributes and string attributes, where metadata is supplied.
Attribute(String, Instances) - Constructor for class weka.core.Attribute: Constructor for relation-valued attributes.
Attribute(String, Instances, int) - Constructor for class weka.core.Attribute: Constructor for a relation-valued attribute with a particular index.
Attribute(String, Instances, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for relation-valued attributes.
Attribute(String, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for a numeric attribute, where metadata is supplied.
ATTRIBUTE_SELECTION - Enum constant in enum class weka.Run.SchemeType
attributeAsClass() - Method in class weka.gui.arffviewer.ArffPanel: sets the current attribute as class attribute, i.e.
attributeAsClass() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: sets the current selected Attribute as class attribute, i.e.
attributeAsClassAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: sets the attribute at the given col index as the new class attribute
attributeAsClassAt(int) - Method in class weka.gui.arffviewer.ArffTableModel: sets the attribute at the given col index as the new class attribute, i.e.
attributeCaseFix(String) - Method in class weka.experiment.DatabaseUtils: returns key column headings in their original case.
attributeCaseFix(String) - Method in interface weka.experiment.InstanceQueryAdapter: returns key column headings in their original case.
AttributeEvaluator - Interface in weka.attributeSelection: Interface for classes that evaluate attributes individually.
attributeIndexesTipText() - Method in class weka.filters.unsupervised.attribute.NominalToString: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property.
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.AddValues: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Returns the tip text for this property.
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.SwapValues
attributeIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.core.NormalizableDistance: Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.CartesianProduct: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Copy: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.FirstOrder: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericToDate: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Remove: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Reorder: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.SortLabels: Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
AttributeListPanel - Class in weka.gui: Creates a panel that displays the attributes contained in a set of instances, letting the user select a single attribute for inspection.
AttributeListPanel() - Constructor for class weka.gui.AttributeListPanel: Creates the attribute selection panel with no initial instances.
AttributeLocator - Class in weka.core: This class locates and records the indices of a certain type of attributes, recursively in case of Relational attributes.
AttributeLocator(Instances, int) - Constructor for class weka.core.AttributeLocator: Initializes the AttributeLocator with the given data for the specified type of attribute.
AttributeLocator(Instances, int, int[]) - Constructor for class weka.core.AttributeLocator: initializes the AttributeLocator with the given data for the specified type of attribute.
AttributeLocator(Instances, int, int, int) - Constructor for class weka.core.AttributeLocator: Initializes the AttributeLocator with the given data for the specified type of attribute.
AttributeMetaInfo - Class in weka.core
AttributeMetaInfo(ProtectedProperties, Attribute) - Constructor for class weka.core.AttributeMetaInfo: Creates the meta info object based on the given meta data.
attributeNamePrefixTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
attributeNamePrefixTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
attributeNames() - Method in class weka.classifiers.functions.SMO: Returns the attribute names.
attributeNameTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property.
attributeNameTipText() - Method in class weka.filters.unsupervised.attribute.AddID: Returns the tip text for this property
AttributePanel - Class in weka.gui.visualize: This panel displays one dimensional views of the attributes in a dataset.
AttributePanel() - Constructor for class weka.gui.visualize.AttributePanel
AttributePanel(Color) - Constructor for class weka.gui.visualize.AttributePanel: This constructs an attributePanel.
AttributePanelEvent - Class in weka.gui.visualize: Class encapsulating a change in the AttributePanel's selected x and y attributes.
AttributePanelEvent(boolean, boolean, int) - Constructor for class weka.gui.visualize.AttributePanelEvent: Constructor
AttributePanelListener - Interface in weka.gui.visualize: Interface for classes that want to listen for Attribute selection changes in the attribute panel
attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.StringToNominal
ATTRIBUTES - Static variable in class weka.core.json.JSONInstances: the attributes object.
AttributeSelectedClassifier - Class in weka.classifiers.meta: Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.
AttributeSelectedClassifier() - Constructor for class weka.classifiers.meta.AttributeSelectedClassifier: Default constructor.
AttributeSelection - Class in weka.attributeSelection: Attribute selection class.
AttributeSelection - Class in weka.filters.supervised.attribute: A supervised attribute filter that can be used to select attributes.
AttributeSelection() - Constructor for class weka.attributeSelection.AttributeSelection: constructor.
AttributeSelection() - Constructor for class weka.filters.supervised.attribute.AttributeSelection: Constructor
attributeSelectionChange(AttributePanelEvent) - Method in interface weka.gui.visualize.AttributePanelListener: Called when the user clicks on an attribute bar
attributeSelectionMethodTipText() - Method in class weka.classifiers.functions.LinearRegression: Returns the tip text for this property
AttributeSelectionPanel - Class in weka.gui: 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 - Class in weka.gui.explorer: This panel allows the user to select and configure an attribute evaluator and a search method, set the attribute of the current dataset to be used as the class, and perform attribute selection using one of two selection modes (select using all the training data or perform a n-fold cross validation---on each trial selecting features using n-1 folds of the data).
AttributeSelectionPanel() - Constructor for class weka.gui.AttributeSelectionPanel: Creates the attribute selection panel with no initial instances.
AttributeSelectionPanel() - Constructor for class weka.gui.explorer.AttributeSelectionPanel: Creates the classifier panel
AttributeSelectionPanel(boolean, boolean, boolean, boolean) - Constructor for class weka.gui.AttributeSelectionPanel: Creates the attribute selection panel with no initial instances.
AttributeSelectionPanel.TestMode - Enum Class in weka.gui.explorer
AttributeSetEvaluator - Class in weka.attributeSelection: Abstract attribute set evaluator.
AttributeSetEvaluator() - Constructor for class weka.attributeSelection.AttributeSetEvaluator
attributeSparse(int) - Method in class weka.core.AbstractInstance: Returns the attribute with the given index in the sparse representation.
attributeSparse(int) - Method in interface weka.core.Instance: Returns the attribute with the given index in the sparse representation.
AttributeSpec() - Constructor for class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Default constructor
AttributeSpec(String) - Constructor for class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Constructor that takes an attribute specification in internal format
attributeSpecsTipText() - Method in class weka.filters.unsupervised.attribute.AddUserFields: Returns the tip text for this property.
attributeStats(int) - Method in class weka.core.Instances: Calculates summary statistics on the values that appear in this set of instances for a specified attribute.
AttributeStats - Class in weka.core: A Utility class that contains summary information on an the values that appear in a dataset for a particular attribute.
AttributeStats() - Constructor for class weka.core.AttributeStats
attributesTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the tip text for this property.
attributesTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Tip text for this property suitable for displaying in the GUI.
attributesToString() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Make a string from the attribues list.
AttributeSummarizer - Class in weka.gui.beans: Bean that encapsulates displays bar graph summaries for attributes in a data set.
AttributeSummarizer - Class in weka.knowledgeflow.steps: Step that collects data to display in a summary overview of attribute distributions
AttributeSummarizer() - Constructor for class weka.gui.beans.AttributeSummarizer: Creates a new AttributeSummarizer instance.
AttributeSummarizer() - Constructor for class weka.knowledgeflow.steps.AttributeSummarizer
AttributeSummarizerBeanInfo - Class in weka.gui.beans: Bean info class for the attribute summarizer bean
AttributeSummarizerBeanInfo() - Constructor for class weka.gui.beans.AttributeSummarizerBeanInfo
AttributeSummarizerCustomizer - Class in weka.gui.beans: GUI customizer for attribute summarizer.
AttributeSummarizerCustomizer() - Constructor for class weka.gui.beans.AttributeSummarizerCustomizer: Constructor
AttributeSummarizerInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive viewer for the AttributeSummarizer step
AttributeSummarizerInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.AttributeSummarizerInteractiveView
AttributeSummarizerStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the attribute summarizer step
AttributeSummarizerStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.AttributeSummarizerStepEditorDialog
AttributeSummaryPanel - Class in weka.gui: This panel displays summary statistics about an attribute: name, type number/% of missing/unique values, number of distinct values.
AttributeSummaryPanel() - Constructor for class weka.gui.AttributeSummaryPanel: Creates the instances panel with no initial instances.
AttributeSummaryPerspective - Class in weka.gui.knowledgeflow: Knowledge Flow perspective that provides a matrix of AttributeVisualizationPanels
AttributeSummaryPerspective() - Constructor for class weka.gui.knowledgeflow.AttributeSummaryPerspective: Constructor
AttributeSummaryPerspective.AttDefaults - Class in weka.gui.knowledgeflow: Default settings for the AttributeSummaryPerspective
attributeToDoubleArray(int) - Method in class weka.core.Instances: Gets the value of all instances in this dataset for a particular attribute.
AttributeTransformer - Interface in weka.attributeSelection: Abstract attribute transformer.
attributeTypeTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property
attributeTypeTipText() - Method in class weka.filters.unsupervised.attribute.RemoveType: Returns the tip text for this property
attributeTypeToString(int) - Static method in class weka.core.CheckScheme: returns a string representation of the attribute type
attributeValues - Variable in class weka.classifiers.evaluation.output.prediction.InMemory.PredictionContainer: the associated attribute values (attribute-name - value).
AttributeVisualizationPanel - Class in weka.gui: Creates a panel that shows a visualization of an attribute in a dataset.
AttributeVisualizationPanel() - Constructor for class weka.gui.AttributeVisualizationPanel: Constructor - If used then the class will not show the class selection combo box.
AttributeVisualizationPanel(boolean) - Constructor for class weka.gui.AttributeVisualizationPanel: Constructor.
attrIndexRangeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
attrSplit(int, Instances) - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Finds the best splitting point for an attribute in the instances
attrSplit(int, Instances) - Method in interface weka.classifiers.trees.m5.SplitEvaluate: Finds the best splitting point for an attribute in the instances
attrSplit(int, Instances) - Method in class weka.classifiers.trees.m5.YongSplitInfo: Finds the best splitting point for an attribute in the instances
AUTHOR - Enum constant in enum class weka.core.TechnicalInformation.Field: The name(s) of the author(s), in the format described in the LaTeX book.
autoBuildTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
autoKeyGenerationTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
AVERAGE - Enum constant in enum class weka.core.pmml.jaxbbindings.CONTSCORINGMETHOD
AVERAGE - Enum constant in enum class weka.core.pmml.jaxbbindings.MULTIPLEMODELMETHOD
AVERAGE_RULE - Static variable in class weka.classifiers.meta.Vote: combination rule: Average of Probabilities
AveragingResultProducer - Class in weka.experiment: Takes the results from a ResultProducer and submits the average to the result listener.
AveragingResultProducer() - Constructor for class weka.experiment.AveragingResultProducer
avgCost() - Method in class weka.classifiers.Evaluation: Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.
avgCost() - Method in class weka.classifiers.evaluation.Evaluation: Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.
avgProb - Variable in class weka.classifiers.lazy.kstar.KStarWrapper: used/reused to hold the average transformation probability
AXIS_COLOR - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Axis colour default
AXIS_COLOUR_KEY - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Axis colour key

B

B_ENTROPY - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
B_SPHERE - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants: Blend setting modes
BACKGROUND_COLOR - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Scatter plot background colour default
BACKGROUND_COLOUR_KEY - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Scatter plot background colour key
BackgroundDesktopPane(String) - Constructor for class weka.gui.Main.BackgroundDesktopPane: intializes the desktop pane.
backQuoteChars(String) - Static method in class weka.core.Utils: Converts carriage returns and new lines in a string into \r and \n.
BACKUP_EXTENSION - Static variable in class weka.gui.scripting.Script: the backup extension.
Bagging - Class in weka.classifiers.meta: Class for bagging a classifier to reduce variance.
Bagging() - Constructor for class weka.classifiers.meta.Bagging: Constructor.
bagSizePercentTipText() - Method in class weka.classifiers.meta.Bagging: Returns the tip text for this property
balanceClassTipText() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Returns the tip text for this property
BallNode - Class in weka.core.neighboursearch.balltrees: Class representing a node of a BallTree.
BallNode(int) - Constructor for class weka.core.neighboursearch.balltrees.BallNode: Constructor.
BallNode(int, int, int) - Constructor for class weka.core.neighboursearch.balltrees.BallNode: Creates a new instance of BallNode.
BallNode(int, int, int, Instance, double) - Constructor for class weka.core.neighboursearch.balltrees.BallNode: Creates a new instance of BallNode.
BallSplitter - Class in weka.core.neighboursearch.balltrees: Abstract class for splitting a ball tree's BallNode.
BallSplitter() - Constructor for class weka.core.neighboursearch.balltrees.BallSplitter: default constructor.
BallSplitter(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.balltrees.BallSplitter: Creates a new instance of BallSplitter.
ballSplitterTipText() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Returns the tip text for this property.
BallTree - Class in weka.core.neighboursearch: Class implementing the BallTree/Metric Tree algorithm for nearest neighbour search.
The connection to dataset is only a reference.
BallTree() - Constructor for class weka.core.neighboursearch.BallTree: Creates a new instance of BallTree.
BallTree(Instances) - Constructor for class weka.core.neighboursearch.BallTree: Creates a new instance of BallTree.
BallTreeConstructor - Class in weka.core.neighboursearch.balltrees: Abstract class for constructing a BallTree .
BallTreeConstructor() - Constructor for class weka.core.neighboursearch.balltrees.BallTreeConstructor: Creates a new instance of BallTreeConstructor.
ballTreeConstructorTipText() - Method in class weka.core.neighboursearch.BallTree: Returns the tip text for this property.
BAR_BACKGROUND_COLOUR - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Attribute bar background colour key
BAR_BACKGROUND_COLOUR_KEY - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Attribute bar background colour key
BASE_ICON_PATH - Static variable in class weka.gui.knowledgeflow.KFGUIConsts: Base path for step icons
BASE_ICON_PATH - Static variable in class weka.gui.knowledgeflow.StepVisual: Standard base path for Step icons
baseClassifiersImplementMoreEfficientBatchPrediction() - Method in class weka.classifiers.meta.Stacking: Returns true if any of the base classifiers are able to generate batch predictions efficiently and all of them implement BatchPredictor.
BaseCumHazardTables - Class in weka.core.pmml.jaxbbindings: Java class for BaseCumHazardTables element declaration.
BaseCumHazardTables() - Constructor for class weka.core.pmml.jaxbbindings.BaseCumHazardTables
BaseExecutionEnvironment - Class in weka.knowledgeflow: Base class for execution environments
BaseExecutionEnvironment() - Constructor for class weka.knowledgeflow.BaseExecutionEnvironment
BaseExecutionEnvironment.BaseExecutionEnvironmentDefaults - Class in weka.knowledgeflow: Defaults for the base execution environment
BaseExecutionEnvironmentDefaults() - Constructor for class weka.knowledgeflow.BaseExecutionEnvironment.BaseExecutionEnvironmentDefaults
BaseInteractiveViewer - Class in weka.gui.knowledgeflow: Base class than clients can extend when implementing StepInteractiveViewer.
BaseInteractiveViewer() - Constructor for class weka.gui.knowledgeflow.BaseInteractiveViewer: Constructor
Baseline - Class in weka.core.pmml.jaxbbindings: Java class for Baseline element declaration.
Baseline() - Constructor for class weka.core.pmml.jaxbbindings.Baseline
BaselineCell - Class in weka.core.pmml.jaxbbindings: Java class for BaselineCell element declaration.
BaselineCell() - Constructor for class weka.core.pmml.jaxbbindings.BaselineCell
BaselineModel - Class in weka.core.pmml.jaxbbindings: Java class for BaselineModel element declaration.
BaselineModel() - Constructor for class weka.core.pmml.jaxbbindings.BaselineModel
BaselineStratum - Class in weka.core.pmml.jaxbbindings: Java class for BaselineStratum element declaration.
BaselineStratum() - Constructor for class weka.core.pmml.jaxbbindings.BaselineStratum
BASELINETESTSTATISTIC - Enum Class in weka.core.pmml.jaxbbindings: Java class for BASELINE-TEST-STATISTIC.
BaseSimpleDataVisualizer - Class in weka.knowledgeflow.steps: Abstract base class for simple data visualization steps that just collect data sets for visualization.
BaseSimpleDataVisualizer() - Constructor for class weka.knowledgeflow.steps.BaseSimpleDataVisualizer
BaseStep - Class in weka.knowledgeflow.steps: Base class for implementations of Step to use.
BaseStep() - Constructor for class weka.knowledgeflow.steps.BaseStep: Constructor
BaseStepExtender - Interface in weka.knowledgeflow.steps: A minimal set of methods, duplicated from the Step interface, that a simple subclass of BaseStep would need to implement in order to function as a start and/or main processing step in the Knowledge Flow.
baseTipText() - Method in class weka.core.neighboursearch.CoverTree: Returns the tip text for this property.
BASIC - Enum constant in enum class weka.knowledgeflow.LoggingLevel
BasicAction(String, String, String, Character) - Constructor for class weka.gui.scripting.FileScriptingPanel.BasicAction: Constructor for setting up an action.
BATCH - Static variable in interface weka.core.converters.Loader
BATCH - Static variable in interface weka.core.converters.Saver
BATCH_FINISHED - Static variable in class weka.gui.beans.IncrementalClassifierEvent
BATCH_FINISHED - Static variable in class weka.gui.beans.InstanceEvent
BATCH_FINISHED - Static variable in class weka.gui.streams.InstanceEvent: Specifies that the batch of instances is finished
BATCH_SIZE_DEFAULT - Static variable in class weka.classifiers.AbstractClassifier: Default preferred batch size for batch predictions
BatchAssociationRulesEvent - Class in weka.gui.beans: Class encapsulating a set of association rules.
BatchAssociationRulesEvent(Object, AssociationRules) - Constructor for class weka.gui.beans.BatchAssociationRulesEvent: Creates a new BatchAssociationRulesEvent instance.
BatchAssociationRulesListener - Interface in weka.gui.beans: Interface to something that can process a BatchAssociationRulesEvent.
BatchClassifierEvent - Class in weka.gui.beans: Class encapsulating a built classifier and a batch of instances to test on.
BatchClassifierEvent(Object, Classifier, DataSetEvent, DataSetEvent, int, int) - Constructor for class weka.gui.beans.BatchClassifierEvent: Creates a new BatchClassifierEvent instance.
BatchClassifierEvent(Object, Classifier, DataSetEvent, DataSetEvent, int, int, int, int) - Constructor for class weka.gui.beans.BatchClassifierEvent: Creates a new BatchClassifierEvent instance.
BatchClassifierListener - Interface in weka.gui.beans: Interface to something that can process a BatchClassifierEvent
BatchClustererEvent - Class in weka.gui.beans: Class encapsulating a built clusterer and a batch of instances to test on.
BatchClustererEvent(Object, Clusterer, DataSetEvent, int, int, int) - Constructor for class weka.gui.beans.BatchClustererEvent: Creates a new BatchClustererEvent instance.
BatchClustererListener - Interface in weka.gui.beans: Interface to something that can process a BatchClustererEvent
BatchConverter - Interface in weka.core.converters: Marker interface for a loader/saver that can retrieve instances in batch mode
batchFilterFile(Filter, String[]) - Static method in class weka.filters.Filter: Method for testing filters ability to process multiple batches.
batchFinished() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText
batchFinished() - Method in class weka.classifiers.functions.SGDText
batchFinished() - Method in interface weka.classifiers.UpdateableBatchProcessor: Signal that the training data is finished (for now).
batchFinished() - Method in class weka.filters.Filter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.MultiFilter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.SimpleBatchFilter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.SimpleStreamFilter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.AttributeSelection: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.ClassOrder: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.Discretize: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.NominalToBinary: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.PartitionMembership: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.Resample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.SpreadSubsample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddCluster: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddID: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddNoise: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Center: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Discretize: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.MathExpression: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.NominalToString: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Normalize: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RemoveType: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Standardize: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.StringToNominal: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.Randomize: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveRange: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.Resample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.gui.streams.InstanceJoiner: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.gui.streams.InstanceSavePanel
batchFinished() - Method in class weka.gui.streams.InstanceTable
batchFinished() - Method in class weka.gui.streams.InstanceViewer
BatchPredictor - Interface in weka.core: Interface to something that can produce predictions in a batch manner when presented with a set of Instances.
batchSizeTipText() - Method in class weka.classifiers.AbstractClassifier: Returns the tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Tool tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.Bagging: Tool tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Tool tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.FilteredClassifier: Tool tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.RandomCommittee: Tool tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.RandomSubSpace: Tool tip text for this property
BAYES - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable: score types
BayesInput - Class in weka.core.pmml.jaxbbindings: Java class for BayesInput element declaration.
BayesInput() - Constructor for class weka.core.pmml.jaxbbindings.BayesInput
BayesInputs - Class in weka.core.pmml.jaxbbindings: Java class for BayesInputs element declaration.
BayesInputs() - Constructor for class weka.core.pmml.jaxbbindings.BayesInputs
BayesNet - Class in weka.classifiers.bayes: Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
BayesNet - Class in weka.datagenerators.classifiers.classification: Generates random instances based on a Bayes network.
BayesNet - Static variable in interface weka.core.Drawable
BayesNet() - Constructor for class weka.classifiers.bayes.BayesNet
BayesNet() - Constructor for class weka.datagenerators.classifiers.classification.BayesNet: initializes the generator
BayesNetEstimator - Class in weka.classifiers.bayes.net.estimate: BayesNetEstimator is the base class for estimating the conditional probability tables of a Bayes network once the structure has been learned.
BayesNetEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.BayesNetEstimator
BayesNetGenerator - Class in weka.classifiers.bayes.net: Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
BayesNetGenerator() - Constructor for class weka.classifiers.bayes.net.BayesNetGenerator: Constructor for BayesNetGenerator.
BayesOutput - Class in weka.core.pmml.jaxbbindings: Java class for BayesOutput element declaration.
BayesOutput() - Constructor for class weka.core.pmml.jaxbbindings.BayesOutput
BDeu - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
BEAN_EXECUTING - Static variable in class weka.gui.beans.BeanInstance
BeanCommon - Interface in weka.gui.beans: Interface specifying routines that all weka beans should implement in order to allow the bean environment to exercise some control over the bean and also to allow the bean to exercise some control over connections.
BeanConnection - Class in weka.gui.beans: Class for encapsulating a connection between two beans.
BeanConnection(BeanInstance, BeanInstance, EventSetDescriptor, Integer...) - Constructor for class weka.gui.beans.BeanConnection: Creates a new BeanConnection instance.
BeanCustomizer - Interface in weka.gui.beans: Extends java.beans.Customizer and provides a method to register a listener interested in notification about whether the customizer has modified the object that it is customizing.
BeanCustomizer.ModifyListener - Interface in weka.gui.beans: Interface for something that is interested in the modified status of a source object (typically a BeanCustomizer that is editing an object)
BeanInstance - Class in weka.gui.beans: Class that manages a set of beans.
BeanInstance(JComponent, Object, int, int, Integer...) - Constructor for class weka.gui.beans.BeanInstance: Creates a new BeanInstance instance.
BeanInstance(JComponent, String, int, int, Integer...) - Constructor for class weka.gui.beans.BeanInstance: Creates a new BeanInstance instance given the fully qualified name of the bean
BeansProperties - Class in weka.gui.beans: Utility class encapsulating various properties for the KnowledgeFlow and providing methods to register and deregister plugin Bean components
BeansProperties() - Constructor for class weka.gui.beans.BeansProperties
BeanVisual - Class in weka.gui.beans: BeanVisual encapsulates icons and label for a given bean.
BeanVisual(String, String, String) - Constructor for class weka.gui.beans.BeanVisual: Constructor
BestFirst - Class in weka.attributeSelection: BestFirst:

Searches the space of attribute subsets by greedy hillclimbing augmented with a backtracking facility.
BestFirst() - Constructor for class weka.attributeSelection.BestFirst: Constructor
BestFirst.Link2 - Class in weka.attributeSelection: Class for a node in a linked list.
BestFirst.LinkedList2 - Class in weka.attributeSelection: Class for handling a linked list.
bestSplit(SplitMetric, Map<String, WeightMass>, String) - Method in class weka.classifiers.trees.ht.ConditionalSufficientStats: Return the best split
bestSplit(SplitMetric, Map<String, WeightMass>, String) - Method in class weka.classifiers.trees.ht.GaussianConditionalSufficientStats
bestSplit(SplitMetric, Map<String, WeightMass>, String) - Method in class weka.classifiers.trees.ht.NominalConditionalSufficientStats
bias() - Method in class weka.classifiers.functions.SGDText
bias() - Method in class weka.classifiers.functions.SMO: Returns the bias of each binary SMO.
biasToUniformClassTipText() - Method in class weka.filters.supervised.instance.Resample: Returns the tip text for this property.
BIBTEX_ENDTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc: the end comment tag for inserting the generated BibTex
BIBTEX_STARTTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc: the start comment tag for inserting the generated BibTex
BIFFileTipText() - Method in class weka.classifiers.bayes.BayesNet
BIFFormatException - Exception in weka.gui.graphvisualizer: This is the Exception thrown by BIFParser, if there was an error in parsing the XMLBIF string or input stream.
BIFFormatException(String) - Constructor for exception weka.gui.graphvisualizer.BIFFormatException
BIFParser - Class in weka.gui.graphvisualizer: This class parses an inputstream or a string in XMLBIF ver.
BIFParser(InputStream, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Constructor for class weka.gui.graphvisualizer.BIFParser: Constructor (if our input is an InputStream)
BIFParser(String, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Constructor for class weka.gui.graphvisualizer.BIFParser: Constructor (if our input is a String)
BIFReader - Class in weka.classifiers.bayes.net: Builds a description of a Bayes Net classifier stored in XML BIF 0.3 format.

For more details on XML BIF see:

Fabio Cozman, Marek Druzdzel, Daniel Garcia (1998).
BIFReader() - Constructor for class weka.classifiers.bayes.net.BIFReader: the default constructor
binarizeNumericAttributesTipText() - Method in class weka.attributeSelection.InfoGainAttributeEval: Returns the tip text for this property
BINARY - Static variable in class weka.gui.beans.SerializedModelSaver
BINARY_ATTRIBUTES - Enum constant in enum class weka.core.Capabilities.Capability: can handle binary attributes
BINARY_CLASS - Enum constant in enum class weka.core.Capabilities.Capability: can handle binary classes
binaryAttributesNominalTipText() - Method in class weka.filters.supervised.attribute.NominalToBinary: Returns the tip text for this property
binaryAttributesNominalTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the tip text for this property
BinaryItem - Class in weka.associations: Class that encapsulates an item whose backing Attribute is binary or unary.
BinaryItem(Attribute, int) - Constructor for class weka.associations.BinaryItem: Constructor.
BinarySimilarity - Class in weka.core.pmml.jaxbbindings: Java class for binarySimilarity element declaration.
BinarySimilarity() - Constructor for class weka.core.pmml.jaxbbindings.BinarySimilarity
BinarySMO() - Constructor for class weka.classifiers.functions.SMO.BinarySMO
BinarySparseInstance - Class in weka.core: Class for storing a binary-data-only instance as a sparse vector.
BinarySparseInstance(double, double[]) - Constructor for class weka.core.BinarySparseInstance: Constructor that generates a sparse instance from the given parameters.
BinarySparseInstance(double, int[], int) - Constructor for class weka.core.BinarySparseInstance: Constructor that inititalizes instance variable with given values.
BinarySparseInstance(int) - Constructor for class weka.core.BinarySparseInstance: Constructor of an instance that sets weight to one, all values to 1, and the reference to the dataset to null.
BinarySparseInstance(Instance) - Constructor for class weka.core.BinarySparseInstance: Constructor that generates a sparse instance from the given instance.
BinarySparseInstance(SparseInstance) - Constructor for class weka.core.BinarySparseInstance: Constructor that copies the info from the given instance.
binarySplitsTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
binarySplitsTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
binaryToKOML(String, String) - Static method in class weka.core.xml.SerialUIDChanger: converts a binary file into a KOML XML file
BinC45ModelSelection - Class in weka.classifiers.trees.j48: Class for selecting a C4.5-like binary (!) split for a given dataset.
BinC45ModelSelection(int, Instances, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.BinC45ModelSelection: Initializes the split selection method with the given parameters.
BinC45Split - Class in weka.classifiers.trees.j48: Class implementing a binary C4.5-like split on an attribute.
BinC45Split(int, int, double, boolean) - Constructor for class weka.classifiers.trees.j48.BinC45Split: Initializes the split model.
binomialStandardError(double, int) - Static method in class weka.core.Statistics: Computes standard error for observed values of a binomial random variable.
binRangePrecisionTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
binRangePrecisionTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
binsTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
binsTipText() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Returns the tip text for this property
BIRCHCluster - Class in weka.datagenerators.clusterers: Cluster data generator designed for the BIRCH System

Dataset is generated with instances in K clusters.
Instances are 2-d data points.
Each cluster is characterized by the number of data points in itits radius and its center.
BIRCHCluster() - Constructor for class weka.datagenerators.clusterers.BIRCHCluster: initializes the generator with default values
BIRD_IMAGE1 - Static variable in class weka.core.RepositoryIndexGenerator
BIRD_IMAGE2 - Static variable in class weka.core.RepositoryIndexGenerator
Block - Class in weka.knowledgeflow.steps: A step that waits for a specified step to finish processing before allowing incoming data to proceed downstream.
Block() - Constructor for class weka.knowledgeflow.steps.Block
blocker(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron: A function used to stop the code that called buildclassifier from continuing on before the user has finished the decision tree.
BlockStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the Block step
BlockStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.BlockStepEditorDialog
BMAEstimator - Class in weka.classifiers.bayes.net.estimate: BMAEstimator estimates conditional probability tables of a Bayes network using Bayes Model Averaging (BMA).
BMAEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.BMAEstimator
BMPWriter - Class in weka.gui.visualize: This class takes any JComponent and outputs it to a BMP-file.
BMPWriter() - Constructor for class weka.gui.visualize.BMPWriter: initializes the object.
BMPWriter(JComponent) - Constructor for class weka.gui.visualize.BMPWriter: initializes the object with the given Component.
BMPWriter(JComponent, File) - Constructor for class weka.gui.visualize.BMPWriter: initializes the object with the given Component and filename.
BOOK - Enum constant in enum class weka.core.TechnicalInformation.Type: A book with an explicit publisher.
BOOKLET - Enum constant in enum class weka.core.TechnicalInformation.Type: A work that is printed and bound, but without a named publisher or sponsoring institution.
BOOKTITLE - Enum constant in enum class weka.core.TechnicalInformation.Field: Title of a book, part of which is being cited.
BOOL - Static variable in class weka.experiment.DatabaseUtils: Type mapping for BOOL used for reading experiment results.
BOOLEAN - Enum constant in enum class weka.core.pmml.jaxbbindings.DATATYPE
BOOLEAN - Static variable in interface weka.core.expressionlanguage.parser.sym
BOOLEAN - Static variable in interface weka.core.json.sym
booleanColsTipText() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Returns the tip text for this property
BooleanConstant(boolean) - Constructor for class weka.core.expressionlanguage.common.Primitives.BooleanConstant
BooleanVariable(String) - Constructor for class weka.core.expressionlanguage.common.Primitives.BooleanVariable
BottomUpConstructor - Class in weka.core.neighboursearch.balltrees: The class that constructs a ball tree bottom up.
BottomUpConstructor() - Constructor for class weka.core.neighboursearch.balltrees.BottomUpConstructor: Creates a new instance of BottomUpConstructor.
BoundaryPanel - Class in weka.gui.boundaryvisualizer: BoundaryPanel.
BoundaryPanel(int, int) - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanel: Creates a new BoundaryPanel instance.
BoundaryPanelDistributed - Class in weka.gui.boundaryvisualizer: This class extends BoundaryPanel with code for distributing the processing necessary to create a visualization among a list of remote machines.
BoundaryPanelDistributed(int, int) - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanelDistributed: Creates a new BoundaryPanelDistributed instance.
BoundaryPlotter - Class in weka.knowledgeflow.steps: A step that computes visualization data for class/cluster decision boundaries.
BoundaryPlotter() - Constructor for class weka.knowledgeflow.steps.BoundaryPlotter: Constructor
BoundaryPlotter.RenderingUpdateListener - Interface in weka.knowledgeflow.steps: Interface for something that wants to be informed of rendering progress updates
BoundaryPlotterInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive viewer component for the boundary plotter step
BoundaryPlotterInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.BoundaryPlotterInteractiveView
BoundaryPlotterStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Editor dialog for the boundary plotter step
BoundaryPlotterStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.BoundaryPlotterStepEditorDialog
BoundaryValueMeans - Class in weka.core.pmml.jaxbbindings: Java class for BoundaryValueMeans element declaration.
BoundaryValueMeans() - Constructor for class weka.core.pmml.jaxbbindings.BoundaryValueMeans
BoundaryValues - Class in weka.core.pmml.jaxbbindings: Java class for BoundaryValues element declaration.
BoundaryValues() - Constructor for class weka.core.pmml.jaxbbindings.BoundaryValues
BoundaryVisualizer - Class in weka.gui.boundaryvisualizer: BoundaryVisualizer.
BoundaryVisualizer() - Constructor for class weka.gui.boundaryvisualizer.BoundaryVisualizer: Creates a new BoundaryVisualizer instance.
BracketNode() - Constructor for class weka.knowledgeflow.steps.FlowByExpression.BracketNode
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.Split: Returns the name of the branch that the supplied instance would go down
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.SplitNode: Return the branch that the supplied instance goes down
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.UnivariateNominalMultiwaySplit
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.UnivariateNumericBinarySplit
breakTiesRandomlyTipText() - Method in class weka.classifiers.trees.RandomForest: Returns the tip text for this property
breakTiesRandomlyTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property
breakUp(String, int) - Static method in class weka.core.Utils: Breaks up the string, if wider than "columns" characters.
BrowserHelper - Class in weka.gui: A little helper class for browser related stuff.
BrowserHelper() - Constructor for class weka.gui.BrowserHelper
bufferedImageMapToSerializableByteMap(Map<String, BufferedImage>) - Static method in class weka.knowledgeflow.steps.ImageViewer: Utility method to convert a map of BufferedImage to a map of byte arrays (that hold each image as png bytes)
bufferSizeTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
build(String, String) - Method in class weka.gui.HierarchyPropertyParser: Build a tree from the given property with the given delimitor
buildAssociations(Instances) - Method in class weka.associations.Apriori: Method that generates all large itemsets with a minimum support, and from these all association rules with a minimum confidence.
buildAssociations(Instances) - Method in interface weka.associations.Associator: Generates an associator.
buildAssociations(Instances) - Method in class weka.associations.FilteredAssociator: Build the associator on the filtered data.
buildAssociations(Instances) - Method in class weka.associations.FPGrowth: Method that generates all large item sets with a minimum support, and from these all association rules with a minimum metric (i.e.
buildCalibrationModelsTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
buildClassifier(Instances) - Method in class weka.classifiers.bayes.BayesNet: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayes: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable: Generates the classifier.
buildClassifier(Instances) - Method in interface weka.classifiers.Classifier: Generates a classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.GaussianProcesses: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.LinearRegression: Builds a regression model for the given data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.Logistic: Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.functions.MultilayerPerceptron: Call this function to build and train a neural network for the training data provided.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SGD: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SGDText: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SimpleLinearRegression: Builds a simple linear regression model given the supplied training data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SimpleLogistic: Builds the logistic regression using LogitBoost.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SMO: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SMOreg: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegOptimizer: learn SVM parameters from data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegSMO: learn SVM parameters from data using Smola's SMO algorithm.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: learn SVM parameters from data using Keerthi's SMO algorithm.
buildClassifier(Instances) - Method in class weka.classifiers.functions.VotedPerceptron: Builds the ensemble of perceptrons.
buildClassifier(Instances) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer: Stump method for building the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.IBk: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.KStar: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.LWL: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AdaBoostM1: Method used to build the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AdditiveRegression: Method used to build the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Build the classifier on the dimensionally reduced data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Bagging: Bagging method.
buildClassifier(Instances) - Method in class weka.classifiers.meta.ClassificationViaRegression: Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Builds the model of the base learner.
buildClassifier(Instances) - Method in class weka.classifiers.meta.CVParameterSelection: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.FilteredClassifier: Build the classifier on the filtered data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.LogitBoost: Method used to build the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiClassClassifier: Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiClassClassifierUpdateable
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiScheme: Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomCommittee: Builds the committee of randomizable classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomizableFilteredClassifier: Build the classifier on the filtered data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomSubSpace: builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RegressionByDiscretization: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Stacking: Builds a classifier using stacking.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Vote: Builds all classifiers in the ensemble
buildClassifier(Instances) - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.misc.InputMappedClassifier: Build the classifier
buildClassifier(Instances) - Method in class weka.classifiers.misc.SerializedClassifier: loads only the serialized classifier
buildClassifier(Instances) - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer: Stump method for building the classifiers
buildClassifier(Instances) - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner: Stump method for building the classifiers
buildClassifier(Instances) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Throw an exception - PMML models are pre-built.
buildClassifier(Instances) - Method in class weka.classifiers.rules.DecisionTable: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.JRip: Builds Ripper in the order of class frequencies.
buildClassifier(Instances) - Method in class weka.classifiers.rules.OneR: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.PART: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.part.MakeDecList: Builds dec list.
buildClassifier(Instances) - Method in class weka.classifiers.rules.ZeroR: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.DecisionStump: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.HoeffdingTree: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split: Creates a C4.5-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.J48: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree: Method for building a pruneable classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45Split: Creates a C4.5-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Builds the classifier split model for the given set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.ClassifierTree: Method for building a classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree: Method for building a naive bayes classifier tree
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Build the no-split node
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Creates a NBTree-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NoSplit: Creates a "no-split"-split for a given set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.PruneableClassifierTree: Method for building a pruneable classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.LMT: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.LMTNode: Method for building a logistic model tree (only called for the root node).
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.LogisticBase: Builds the logistic regression model usiing LogitBoost.
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Method not in use
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Builds a simple linear regression model given the supplied training data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.M5Base: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.Rule: Generates a single rule or m5 model tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.RuleNode: Build this node (find an attribute and split point)
buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomTree: Builds classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.REPTree: Builds classifier.
buildClassifier(Instances, double[][], double[][]) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Builds the split.
buildClusterer(Instances) - Method in class weka.clusterers.AbstractClusterer: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.Canopy
buildClusterer(Instances) - Method in interface weka.clusterers.Clusterer: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.Cobweb: Builds the clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.EM: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.FarthestFirst: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.FilteredClusterer: Build the clusterer on the filtered data.
buildClusterer(Instances) - Method in class weka.clusterers.HierarchicalClusterer
buildClusterer(Instances) - Method in class weka.clusterers.MakeDensityBasedClusterer: Builds a clusterer for a set of instances.
buildClusterer(Instances) - Method in class weka.clusterers.SimpleKMeans: Generates a clusterer.
buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.C45PruneableDecList: Builds the partial tree without hold out set.
buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.ClassifierDecList: Builds the partial tree without hold out set.
buildDecList(Instances, Instances, boolean) - Method in class weka.classifiers.rules.part.PruneableDecList: Builds the partial tree with hold out set
buildEstimator(Estimator, String[], boolean) - Static method in class weka.estimators.Estimator: Build an estimator using the options.
buildEstimator(Estimator, Instances, int, int, int, boolean) - Static method in class weka.estimators.Estimator
buildEvaluator(Instances) - Method in class weka.attributeSelection.ASEvaluation: Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.CfsSubsetEval: Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.ClassifierAttributeEval: Initializes a ClassifierAttribute attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.ClassifierSubsetEval: Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.CorrelationAttributeEval: Initializes an information gain attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.GainRatioAttributeEval: Initializes a gain ratio attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.InfoGainAttributeEval: Initializes an information gain attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.OneRAttributeEval: Initializes a OneRAttribute attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.PrincipalComponents: Initializes principal components and performs the analysis
buildEvaluator(Instances) - Method in class weka.attributeSelection.ReliefFAttributeEval: Initializes a ReliefF attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Initializes a symmetrical uncertainty attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.WrapperSubsetEval: Generates a attribute evaluator.
buildGenerator(Instances) - Method in interface weka.gui.boundaryvisualizer.DataGenerator: Build the data generator
buildGenerator(Instances) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator: Initialize the generator using the supplied instances
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.CachedKernel: builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.Kernel: builds the kernel with the given data
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel: builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.Puk: builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.RBFKernel: Builds the kernel.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.StringKernel: builds the kernel with the given data.
buildModel(int, double[], double[]) - Method in class weka.estimators.UnivariateMixtureEstimator: Build mixture model.
buildRegressionTreeTipText() - Method in class weka.classifiers.trees.m5.M5Base: Returns the tip text for this property
buildRule(Instances) - Method in class weka.classifiers.rules.part.ClassifierDecList: Method for building a pruned partial tree.
buildRule(Instances, Instances) - Method in class weka.classifiers.rules.part.PruneableDecList: Method for building a pruned partial tree.
buildStructure() - Method in class weka.classifiers.bayes.BayesNet: buildStructure determines the network structure/graph of the network.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.fixed.FromFile
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.fixed.NaiveBayes
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.global.TAN: buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: buildStructure determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.TAN: buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm: buildStructure determines the network structure/graph of the network.
buildTree() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Builds the ball tree.
buildTree() - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Builds the ball tree bottom up.
buildTree() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Builds a ball tree middle out.
buildTree() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Builds the ball tree top down.
buildTree(Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree: Builds the tree structure.
buildTree(Instances, SimpleLinearRegression[][], double, double, Instances) - Method in class weka.classifiers.trees.lmt.LMTNode: Method for building the tree structure.
buildTree(Instances, Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree: Builds the tree structure with hold out set
BUILT_IN_EVAL_METRICS - Static variable in class weka.classifiers.Evaluation
BUILT_IN_EVAL_METRICS - Static variable in class weka.classifiers.evaluation.Evaluation
BuiltInArithmetic - Class in weka.core.pmml: Built-in function for +, -, *, /.
BuiltInArithmetic(BuiltInArithmetic.Operator) - Constructor for class weka.core.pmml.BuiltInArithmetic: Construct a new Arithmetic built-in pmml function.
BuiltInMath - Class in weka.core.pmml: Built-in function for min, max, sum, avg, log10, ln, sqrt, abs, exp, pow, threshold, floor, ceil and round.
BuiltInMath(BuiltInMath.MathFunc) - Constructor for class weka.core.pmml.BuiltInMath: Construct a new built-in pmml Math function.
BuiltInString - Class in weka.core.pmml: Built-in function for uppercase, substring and trimblanks.
BVDecompose - Class in weka.classifiers: Class for performing a Bias-Variance decomposition on any classifier using the method specified in:

Ron Kohavi, David H.
BVDecompose() - Constructor for class weka.classifiers.BVDecompose
BVDecomposeSegCVSub - Class in weka.classifiers: This class performs Bias-Variance decomposion on any classifier using the sub-sampled cross-validation procedure as specified in (1).
The Kohavi and Wolpert definition of bias and variance is specified in (2).
The Webb definition of bias and variance is specified in (3).

Geoffrey I.
BVDecomposeSegCVSub() - Constructor for class weka.classifiers.BVDecomposeSegCVSub
BYTE - Static variable in class weka.experiment.DatabaseUtils: Type mapping for BYTE used for reading experiment results.
byteArrayImageMapToBufferedImageMap(Map<String, byte[]>) - Static method in class weka.knowledgeflow.steps.ImageViewer: Utility method to convert a map of byte[] png image data to a map of BufferedImage

C

C45Loader - Class in weka.core.converters: Reads a file that is C45 format.
C45Loader() - Constructor for class weka.core.converters.C45Loader
C45ModelSelection - Class in weka.classifiers.trees.j48: Class for selecting a C4.5-type split for a given dataset.
C45ModelSelection(int, Instances, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45ModelSelection: Initializes the split selection method with the given parameters.
C45PruneableClassifierTree - Class in weka.classifiers.trees.j48: Class for handling a tree structure that can be pruned using C4.5 procedures.
C45PruneableClassifierTree(ModelSelection, boolean, float, boolean, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45PruneableClassifierTree: Constructor for pruneable tree structure.
C45PruneableDecList - Class in weka.classifiers.rules.part: Class for handling a partial tree structure pruned using C4.5's pruning heuristic.
C45PruneableDecList(ModelSelection, double, int) - Constructor for class weka.classifiers.rules.part.C45PruneableDecList: Constructor for pruneable tree structure.
C45Saver - Class in weka.core.converters: Writes to a destination that is in the format used by the C4.5 algorithm.
Therefore it outputs a names and a data file.
C45Saver() - Constructor for class weka.core.converters.C45Saver: Constructor
C45Split - Class in weka.classifiers.trees.j48: Class implementing a C4.5-type split on an attribute.
C45Split(int, int, double, boolean) - Constructor for class weka.classifiers.trees.j48.C45Split: Initializes the split model.
CachedKernel - Class in weka.classifiers.functions.supportVector: Base class for RBFKernel and PolyKernel that implements a simple LRU.
CachedKernel() - Constructor for class weka.classifiers.functions.supportVector.CachedKernel: default constructor - does nothing.
cacheKeyNameTipText() - Method in class weka.experiment.DatabaseResultListener: Returns the tip text for this property
cacheSizeTipText() - Method in class weka.classifiers.functions.supportVector.CachedKernel: Returns the tip text for this property
cacheSizeTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the tip text for this property
CacheTable() - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Constructs a new hashtable with a default capacity and load factor.
CacheTable(int, float) - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Constructs a new hashtable with a default capacity and load factor.
calcCentroidPivot(int[], Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the centroid pivot of a node.
calcCentroidPivot(int, int, int[], Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the centroid pivot of a node.
calcColumnWidth(int) - Method in class weka.gui.JTableHelper: calcs the optimal column width of the given column
calcColumnWidth(JTable, int) - Static method in class weka.gui.JTableHelper: Calculates the optimal width for the column of the given table.
calcFullMargins(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator
calcGraph(int, int) - Method in class weka.gui.AttributeVisualizationPanel: Recalculates the barplot or histogram to display, required usually when the attribute is changed or the component is resized.
calcHeaderWidth(int) - Method in class weka.gui.JTableHelper: calcs the optimal header width of the given column
calcHeaderWidth(JTable, int) - Static method in class weka.gui.JTableHelper: Calculates the optimal width for the header of the given table.
calcMargins(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator: Calc marginal distributions of nodes in Bayesian network Note that a connected network is assumed.
calcNodeScore(int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Calc Node Score for given parent set
calcOutOfBagTipText() - Method in class weka.classifiers.meta.Bagging: Returns the tip text for this property
calcPivot(BallNode, BallNode, Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the centroid pivot of a node based on its two child nodes (if merging two nodes).
calcPivot(BottomUpConstructor.TempNode, BottomUpConstructor.TempNode, Instances) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Calculates the centroid pivot of a node based on its two child nodes.
calcPivot(MiddleOutConstructor.MyIdxList, MiddleOutConstructor.MyIdxList, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Calculates the centroid pivot of a node based on the list of points that it contains (tbe two lists of its children are provided).
calcPivot(MiddleOutConstructor.TempNode, MiddleOutConstructor.TempNode, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: /** Calculates the centroid pivot of a node based on its two child nodes (if merging two nodes).
calcRadius(int[], Instances, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the radius of node.
calcRadius(int, int, int[], Instances, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the radius of a node.
calcRadius(BallNode, BallNode, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the radius of a node based on its two child nodes (if merging two nodes).
calcRadius(BottomUpConstructor.TempNode, BottomUpConstructor.TempNode) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Calculates the radius of a node based on its two child nodes.
calcRadius(MiddleOutConstructor.MyIdxList, MiddleOutConstructor.MyIdxList, Instance, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Calculates the radius of a node based on the list of points that it contains (the two lists of its children are provided).
calcRadius(MiddleOutConstructor.TempNode, MiddleOutConstructor.TempNode) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Calculates the radius of a node based on its two child nodes (if merging two nodes).
calcScore(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: performCV returns the accuracy calculated using cross validation.
calcScoreWithExtraParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Calc Node Score With Added Parent
calcScoreWithExtraParent(int, int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Calc Node Score With AddedParent
calcScoreWithMissingParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Calc Node Score With Parent Deleted
calcScoreWithMissingParent(int, int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Calc Node Score With Parent Deleted
calcScoreWithReversedParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Calc Node Score With Arrow reversed
calculateAdjRSquared(double, int, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the adjusted R-squared value for a linear regression model.
calculateAlphas() - Method in class weka.classifiers.trees.lmt.LMTNode: Updates the alpha field for all nodes.
calculateDerived() - Method in class weka.experiment.PairedStats: Calculates the derived statistics (significance etc).
calculateDerived() - Method in class weka.experiment.PairedStatsCorrected: Calculates the derived statistics (significance etc).
calculateDerived() - Method in class weka.experiment.Stats: Tells the object to calculate any statistics that don't have their values automatically updated during add.
calculateFStat(double, int, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the F-statistic for a linear regression model.
calculateRSquared(Instances, double) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the R-squared value for a linear regression model, where sum of squared residuals is already calculated.
calculateSSR(Instances, Attribute, double, double) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the sum of squared residuals of the simple linear regression model: y = a + bx.
calculateStatistics(Instance, int, int, int) - Method in class weka.experiment.PairedCorrectedTTester: Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStatistics(Instance, int, int, int) - Method in class weka.experiment.PairedTTester: Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStatistics(Instance, int, int, int) - Method in interface weka.experiment.Tester: Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStdDevsTipText() - Method in class weka.experiment.AveragingResultProducer: Returns the tip text for this property
calculateStdErrorOfCoef(Instances, boolean[], double, int, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns an array of the standard errors of the coefficients in a multiple linear regression.
calculateStdErrorOfCoef(Instances, Attribute, double, double, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the standard errors of slope and intercept for a simple linear regression model: y = a + bx.
calculateTStats(double[], double[], int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns an array of the t-statistic of each coefficient in a multiple linear regression model.
calibratorTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
call() - Method in class weka.knowledgeflow.StepTask: Executor service calls this method to do the work
CallbackNotifierDelegate - Interface in weka.knowledgeflow: Interface to something that can notify a Step that a Task submitted by ExecutionEnvironment.submitTask() has finished.
canAcceptConnection(Class<?>) - Method in class weka.gui.beans.MetaBean: Checks to see if any of the inputs to this group implements the supplied listener class
cancel() - Method in class weka.core.converters.AbstractFileSaver: Cancels the incremental saving process.
cancel() - Method in class weka.core.converters.AbstractSaver: Cancels the incremental saving process if the write mode is CANCEL.
cancel() - Method in class weka.core.converters.DatabaseSaver: Cancels the incremental saving process and tries to drop the table if the write mode is CANCEL.
CANCEL_OPTION - Static variable in class weka.gui.experiment.OutputFormatDialog: Signifies a cancelled property selection.
CANCEL_OPTION - Static variable in class weka.gui.ListSelectorDialog: Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class weka.gui.PropertySelectorDialog: Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class weka.gui.ViewerDialog: Signifies a cancelled property selection
canMoveDown(JList) - Static method in class weka.gui.JListHelper: checks whether the selected items can be moved down
canMoveUp(JList) - Static method in class weka.gui.JListHelper: checks whether the selected items can be moved up
Canopy - Class in weka.clusterers: Cluster data using the capopy clustering algorithm, which requires just one pass over the data.
Canopy() - Constructor for class weka.clusterers.Canopy
CANOPY - Static variable in class weka.clusterers.SimpleKMeans
canopyMaxNumCanopiesToHoldInMemoryTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
canopyMinimumCanopyDensityTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
canopyPeriodicPruningRateTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
canopyT1TipText() - Method in class weka.clusterers.SimpleKMeans: Tip text for this property
canopyT2TipText() - Method in class weka.clusterers.SimpleKMeans: Tip text for this property
canPlot(boolean) - Method in class weka.gui.explorer.AbstractPlotInstances: Returns whether all the data is available and the plot instances can be used for plotting.
canProduceRules() - Method in class weka.associations.Apriori: Returns true if this AssociationRulesProducer can actually produce rules.
canProduceRules() - Method in interface weka.associations.AssociationRulesProducer: Returns true if this AssociationRulesProducer can actually produce rules.
canProduceRules() - Method in class weka.associations.FilteredAssociator: Returns true if this AssociationRulesProducer can actually produce rules.
canProduceRules() - Method in class weka.associations.FPGrowth: Returns true if this AssociationRulesProducer can actually produce rules.
canRedo() - Method in class weka.classifiers.bayes.net.EditableBayesNet: return whether there is something on the undo stack that can be performed
canUndo() - Method in class weka.classifiers.bayes.net.EditableBayesNet: return whether there is something on the undo stack that can be performed
canUndo() - Method in interface weka.core.Undoable: returns whether an undo is possible, i.e.
canUndo() - Method in class weka.gui.arffviewer.ArffPanel: returns whether an undo is possible
canUndo() - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns whether an undo is possible, i.e.
canUndo() - Method in class weka.gui.arffviewer.ArffTableModel: returns whether an undo is possible, i.e.
capabilities() - Method in class weka.core.Capabilities: Returns an Iterator over the stored capabilities
Capabilities - Class in weka.core: A class that describes the capabilites (e.g., handling certain types of attributes, missing values, types of classes, etc.) of a specific classifier.
Capabilities - Class in weka.gui.simplecli: Outputs the capabilities of the specified class.
Capabilities() - Constructor for class weka.gui.simplecli.Capabilities
Capabilities(CapabilitiesHandler) - Constructor for class weka.core.Capabilities: initializes the capabilities for the given owner
Capabilities.Capability - Enum Class in weka.core: enumeration of all capabilities
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.AssociationsPanel: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.AttributeSelectionPanel: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.ClassifierPanel: method gets called in case of a change event.
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.ClustererPanel: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in interface weka.gui.explorer.Explorer.CapabilitiesFilterChangeListener: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.PreprocessPanel: method gets called in case of a change event
CapabilitiesFilterChangeEvent(Object, Capabilities) - Constructor for class weka.gui.explorer.Explorer.CapabilitiesFilterChangeEvent: Constructs a GOECapabilitiesFilterChangeEvent object.
CapabilitiesFilterDialog() - Constructor for class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog: creates a dialog to choose Capabilities from.
CapabilitiesHandler - Interface in weka.core: Classes implementing this interface return their capabilities in regards to datasets.
CapabilitiesIgnorer - Interface in weka.core: Classes implementing this interface make it possible to turn off capabilities checking.
CapabilitiesUtils - Class in weka.core: Helper class for Capabilities.
CapabilitiesUtils() - Constructor for class weka.core.CapabilitiesUtils
capacity() - Method in class weka.core.matrix.DoubleVector: Gets the capacity of the vector.
capacity() - Method in class weka.core.matrix.IntVector: Returns the capacity of the vector
cardinalityTipText() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Returns the tip text for this property
caretUpdate(CaretEvent) - Method in class weka.gui.LogWindow: Called when the caret position is updated.
caretUpdate(CaretEvent) - Method in class weka.gui.sql.ConnectionPanel: Called when the caret position is updated.
caretUpdate(CaretEvent) - Method in class weka.gui.sql.QueryPanel: Called when the caret position is updated.
CartesianProduct - Class in weka.filters.unsupervised.attribute: A filter for performing the Cartesian product of a set of nominal attributes.
CartesianProduct() - Constructor for class weka.filters.unsupervised.attribute.CartesianProduct
carTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
CARuleMiner - Interface in weka.associations: Interface for learning class association rules.
CaseInsensitiveComparator() - Constructor for class weka.filters.unsupervised.attribute.SortLabels.CaseInsensitiveComparator
CaseSensitiveComparator() - Constructor for class weka.filters.unsupervised.attribute.SortLabels.CaseSensitiveComparator
cast(Object) - Static method in class weka.core.Utils: Casting an object without "unchecked" compile-time warnings.
cat(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Combine two vectors together
CATEGORICAL - Enum constant in enum class weka.core.pmml.FieldMetaInfo.Optype
CATEGORICAL - Enum constant in enum class weka.core.pmml.jaxbbindings.OPTYPE
CategoricalPredictor - Class in weka.core.pmml.jaxbbindings: Java class for CategoricalPredictor element declaration.
CategoricalPredictor() - Constructor for class weka.core.pmml.jaxbbindings.CategoricalPredictor
Categories - Class in weka.core.pmml.jaxbbindings: Java class for Categories element declaration.
Categories() - Constructor for class weka.core.pmml.jaxbbindings.Categories
category() - Element in annotation interface weka.core.OptionMetadata: Optional category for the parameter.
category() - Element in annotation interface weka.gui.beans.KFStep: The top-level folder in the JTree that this plugin bean should appear in
category() - Element in annotation interface weka.knowledgeflow.steps.KFStep: The top-level folder in the JTree that this step should appear in
Category - Class in weka.core.pmml.jaxbbindings: Java class for Category element declaration.
Category() - Constructor for class weka.core.pmml.jaxbbindings.Category
CATSCORINGMETHOD - Enum Class in weka.core.pmml.jaxbbindings: Java class for CAT-SCORING-METHOD.
CAUCHIT - Enum constant in enum class weka.core.pmml.jaxbbindings.CUMULATIVELINKFUNCTION
CAUCHIT - Enum constant in enum class weka.core.pmml.jaxbbindings.REGRESSIONNORMALIZATIONMETHOD
Center - Class in weka.filters.unsupervised.attribute: Centers all numeric attributes in the given dataset to have zero mean (apart from the class attribute, if set).
Center() - Constructor for class weka.filters.unsupervised.attribute.Center
centerDataTipText() - Method in class weka.attributeSelection.PrincipalComponents: Returns the tip text for this property
centerDataTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Returns the tip text for this property
centerHorizontal(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: center set of nodes half way between left and right most node in the list
centerInstances(Instances, int[], double) - Method in class weka.core.neighboursearch.KDTree: Assigns instances to centers using KDTree.
centerVertical(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: center set of nodes half way between top and bottom most node in the list
CfsSubsetEval - Class in weka.attributeSelection: CfsSubsetEval :

Evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them.

Subsets of features that are highly correlated with the class while having low intercorrelation are preferred.

For more information see:

M.
CfsSubsetEval() - Constructor for class weka.attributeSelection.CfsSubsetEval: Constructor
ChangeDateFormat - Class in weka.filters.unsupervised.attribute: Changes the date format used by a date attribute.
ChangeDateFormat() - Constructor for class weka.filters.unsupervised.attribute.ChangeDateFormat
changeLength(double) - Method in class weka.core.AlgVector: Changes the length of a vector.
changeUID(long, long, String, String) - Static method in class weka.core.xml.SerialUIDChanger: changes the oldUID into newUID from the given file (binary/KOML) into the other one (binary/KOML).
CHAPTER - Enum constant in enum class weka.core.TechnicalInformation.Field: A chapter (or section or whatever) number.
CharacterDelimitedTokenizer - Class in weka.core.tokenizers: Abstract superclass for tokenizers that take characters as delimiters.
CharacterDelimitedTokenizer() - Constructor for class weka.core.tokenizers.CharacterDelimitedTokenizer
Characteristic - Class in weka.core.pmml.jaxbbindings: Java class for Characteristic element declaration.
Characteristic() - Constructor for class weka.core.pmml.jaxbbindings.Characteristic
Characteristics - Class in weka.core.pmml.jaxbbindings: Java class for Characteristics element declaration.
Characteristics() - Constructor for class weka.core.pmml.jaxbbindings.Characteristics
CharacterNGramTokenizer - Class in weka.core.tokenizers: Splits a string into an n-gram with min and max grams.
CharacterNGramTokenizer() - Constructor for class weka.core.tokenizers.CharacterNGramTokenizer
charSetTipText() - Method in class weka.core.converters.TextDirectoryLoader: the tip text for this property
ChartEvent - Class in weka.gui.beans: Event encapsulating info for plotting a data point on the StripChart
ChartEvent(Object) - Constructor for class weka.gui.beans.ChartEvent: Creates a new ChartEvent instance.
ChartEvent(Object, Vector<String>, double, double, double[], boolean) - Constructor for class weka.gui.beans.ChartEvent: Creates a new ChartEvent instance.
chartingEvalWindowSizeTipText() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Return a tip text string for this property
chartingEvalWindowSizeTipText() - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Return a tip text string for this property
ChartListener - Interface in weka.gui.beans: Interface to something that can process a ChartEvent
Chebychev - Class in weka.core.pmml.jaxbbindings: Java class for chebychev element declaration.
Chebychev() - Constructor for class weka.core.pmml.jaxbbindings.Chebychev
ChebyshevDistance - Class in weka.core: Implements the Chebyshev distance.
ChebyshevDistance() - Constructor for class weka.core.ChebyshevDistance: Constructs an Chebyshev Distance object, Instances must be still set.
ChebyshevDistance(Instances) - Constructor for class weka.core.ChebyshevDistance: Constructs an Chebyshev Distance object and automatically initializes the ranges.
check(double) - Method in class weka.classifiers.trees.j48.Distribution: Checks if at least two bags contain a minimum number of instances.
Check - Class in weka.core: Abstract general class for testing in Weka.
Check() - Constructor for class weka.core.Check
CheckAssociator - Class in weka.associations: Class for examining the capabilities and finding problems with associators.
CheckAssociator() - Constructor for class weka.associations.CheckAssociator
CheckAttributeSelection - Class in weka.attributeSelection: Class for examining the capabilities and finding problems with attribute selection schemes.
CheckAttributeSelection() - Constructor for class weka.attributeSelection.CheckAttributeSelection
CheckBoxList - Class in weka.gui: An extended JList that contains CheckBoxes.
CheckBoxList() - Constructor for class weka.gui.CheckBoxList: initializes the list with an empty CheckBoxListModel
CheckBoxList(CheckBoxList.CheckBoxListModel) - Constructor for class weka.gui.CheckBoxList: initializes the list with the given CheckBoxListModel
CheckBoxList.CheckBoxListModel - Class in weka.gui: A specialized model.
CheckBoxList.CheckBoxListRenderer - Class in weka.gui: A specialized CellRenderer for the CheckBoxList
CheckBoxListModel() - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel: initializes the model with no data.
CheckBoxListModel(Object[]) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel: Constructs a CheckBoxListModel from an array of objects and then applies setModel to it.
CheckBoxListModel(Vector) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel: Constructs a CheckBoxListModel from a Vector and then applies setModel to it.
CheckBoxListRenderer() - Constructor for class weka.gui.CheckBoxList.CheckBoxListRenderer
checkCanonicalUserOptions() - Method in class weka.core.CheckOptionHandler: checks whether the user-supplied options stay the same after settting, getting and re-setting again
CheckClassifier - Class in weka.classifiers: Class for examining the capabilities and finding problems with classifiers.
CheckClassifier() - Constructor for class weka.classifiers.CheckClassifier
CheckClusterer - Class in weka.clusterers: Class for examining the capabilities and finding problems with clusterers.
CheckClusterer() - Constructor for class weka.clusterers.CheckClusterer: default constructor
checkConstraint(Package) - Method in class weka.core.packageManagement.PackageConstraint: Check the target package against the constraint embodied in this PackageConstraint.
checkConstraint(Package) - Method in class weka.core.packageManagement.VersionPackageConstraint: Check the target package against the constraint embodied in this PackageConstraint.
checkConstraint(Package) - Method in class weka.core.packageManagement.VersionRangePackageConstraint: Check the target package against the constraint embodied in this PackageConstraint.
checkConstraint(PackageConstraint) - Method in class weka.core.packageManagement.PackageConstraint: Check the target package constraint against the constraint embodied in this package constraint.
checkConstraint(PackageConstraint) - Method in class weka.core.packageManagement.VersionPackageConstraint: Check the target package constraint against the constraint embodied in this package constraint.
checkConstraint(PackageConstraint) - Method in class weka.core.packageManagement.VersionRangePackageConstraint
checkDefaultOptions() - Method in class weka.core.CheckOptionHandler: checks whether the default options can be processed completely or some invalid options are returned by the getOptions() method.
checkErrorRateTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
CheckEstimator - Class in weka.estimators: Class for examining the capabilities and finding problems with estimators.
CheckEstimator() - Constructor for class weka.estimators.CheckEstimator
CheckEstimator.AttrTypes - Class in weka.estimators: class that contains info about the attribute types the estimator can estimate estimator work on one attribute only
CheckEstimator.EstTypes - Class in weka.estimators: public class that contains info about the chosen attribute type estimator work on one attribute only
CheckEstimator.PostProcessor - Class in weka.estimators: a class for postprocessing the test-data
checkForAttributeType(int) - Method in class weka.core.Instances: Checks for attributes of the given type in the dataset
checkForMissingFiles(Package, File, PrintStream...) - Static method in class weka.core.WekaPackageLibIsolatingClassLoader: Checks to see if there are any missing files/directories for a given package.
checkForMissingFiles(Package, File, PrintStream...) - Static method in class weka.core.WekaPackageManager: Checks to see if there are any missing files/directories for a given package.
checkForNewPackages(PrintStream...) - Static method in class weka.core.WekaPackageManager: Check for new packages on the server and refresh the local cache if needed
checkForRemainingOptions(String[]) - Static method in class weka.core.Utils: Checks if the given array contains any non-empty options.
checkForStringAttributes() - Method in class weka.core.Instances: Checks for string attributes in the dataset
checkForThirdPartyClass(String, WekaPackageLibIsolatingClassLoader) - Static method in class weka.core.SerializationHelper: Checks to see if the supplied package class loader (or any of its dependent package class loaders) has the given third party class.
checkGlobalInfo() - Method in class weka.core.CheckGOE: checks whether the object declares a globalInfo method.
CheckGOE - Class in weka.core: Simple command line checking of classes that are editable in the GOE.
CheckGOE() - Constructor for class weka.core.CheckGOE: default constructor
checkIndicesList(MiddleOutConstructor.MyIdxList, int, int) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Checks whether if the points in an index list are in some specified of the master index array.
checkInstance(Instance) - Method in class weka.core.Instances: Checks if the given instance is compatible with this dataset.
CheckKernel - Class in weka.classifiers.functions.supportVector: Class for examining the capabilities and finding problems with kernels.
CheckKernel() - Constructor for class weka.classifiers.functions.supportVector.CheckKernel
checkListOptions() - Method in class weka.core.CheckOptionHandler: checks whether the listOptions method works
checkModel() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Checks if generated model is valid.
checkModel(int) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Checks if there are at least 2 subsets that contain >= minNumInstances.
CheckOptionHandler - Class in weka.core: Simple command line checking of classes that implement OptionHandler.
CheckOptionHandler() - Constructor for class weka.core.CheckOptionHandler
checkRemainingOptions() - Method in class weka.core.CheckOptionHandler: checks whether the user-supplied options can be processed completely or some "left-over" options remain
checkResettingOptions() - Method in class weka.core.CheckOptionHandler: checks whether the optionhandler can be re-setted again to default options after the user-supplied options have been set.
CheckScheme - Class in weka.core: Abstract general class for testing schemes in Weka.
CheckScheme() - Constructor for class weka.core.CheckScheme
CheckScheme.PostProcessor - Class in weka.core: a class for postprocessing the test-data
checkSetOptions() - Method in class weka.core.CheckOptionHandler: checks whether the user-supplied options can be processed at all
CheckSource - Class in weka.classifiers: A simple class for checking the source generated from Classifiers implementing the weka.classifiers.Sourcable interface.
CheckSource - Class in weka.filters: A simple class for checking the source generated from Filters implementing the weka.filters.Sourcable interface.
CheckSource() - Constructor for class weka.classifiers.CheckSource
CheckSource() - Constructor for class weka.filters.CheckSource
checkStatus(Object) - Method in interface weka.experiment.Compute: Check on the status of a Task
checkStatus(Object) - Method in class weka.experiment.RemoteEngine: Returns status information on a particular task
checksTurnedOffTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
checksTurnedOffTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the tip text for this property
checkToolTips() - Method in class weka.core.CheckGOE: checks whether the object declares tip text method for all its properties.
checkWindowShouldBeClosed(WindowEvent) - Method in class weka.gui.GUIChooserApp: Asks the user whether the window that generated the window evident given as the argument should really be closed.
CHI_SQUARE_DISTRIBUTION - Enum constant in enum class weka.core.pmml.jaxbbindings.BASELINETESTSTATISTIC
CHI_SQUARE_INDEPENDENCE - Enum constant in enum class weka.core.pmml.jaxbbindings.BASELINETESTSTATISTIC
ChildFrameMDI(Main, String) - Constructor for class weka.gui.Main.ChildFrameMDI: constructs a new internal frame that knows about its parent.
ChildFrameSDI(GUIChooserApp, String) - Constructor for class weka.gui.GUIChooserApp.ChildFrameSDI: constructs a new internal frame that knows about its parent.
ChildFrameSDI(Main, String) - Constructor for class weka.gui.Main.ChildFrameSDI: constructs a new internal frame that knows about its parent.
ChildParent - Class in weka.core.pmml.jaxbbindings: Java class for ChildParent element declaration.
ChildParent() - Constructor for class weka.core.pmml.jaxbbindings.ChildParent
childrenValues() - Method in class weka.gui.HierarchyPropertyParser: The value in the children nodes.
chisqDistribution - Static variable in class weka.core.matrix.Maths: Distribution type: chi-squared
chiSquared(double[][], boolean) - Static method in class weka.core.ContingencyTables: Returns chi-squared probability for a given matrix.
chiSquaredProbability(double, double) - Static method in class weka.core.Statistics: Returns chi-squared probability for given value and degrees of freedom.
chiVal(double[][], boolean) - Static method in class weka.core.ContingencyTables: Computes chi-squared statistic for a contingency table.
chol() - Method in class weka.core.matrix.Matrix: Cholesky Decomposition
CholeskyDecomposition - Class in weka.core.matrix: Cholesky Decomposition.
CholeskyDecomposition(Matrix) - Constructor for class weka.core.matrix.CholeskyDecomposition: Cholesky algorithm for symmetric and positive definite matrix.
chooseIndex() - Method in class weka.classifiers.rules.part.ClassifierDecList: Method for choosing a subset to expand.
chooseLastIndex() - Method in class weka.classifiers.rules.part.ClassifierDecList: Choose last index (ie.
CISearchAlgorithm - Class in weka.classifiers.bayes.net.search.ci: The CISearchAlgorithm class supports Bayes net structure search algorithms that are based on conditional independence test (as opposed to for example score based of cross validation based search algorithms).
CISearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.ci.CISearchAlgorithm
CityBlock - Class in weka.core.pmml.jaxbbindings: Java class for cityBlock element declaration.
CityBlock() - Constructor for class weka.core.pmml.jaxbbindings.CityBlock
CLASS - Static variable in class weka.core.json.JSONInstances: the class attribute indicator.
CLASS - Static variable in class weka.knowledgeflow.JSONFlowUtils
CLASS_GROOVYCLASSLOADER - Static variable in class weka.core.scripting.Groovy: the classname of the Groovy classloader.
CLASS_IS_LAST - Static variable in class weka.core.TestInstances: can be used for settting the class attribute index to last
CLASS_PYTHONINERPRETER - Static variable in class weka.core.scripting.Jython: the classname of the Python interpreter
CLASS_PYTHONOBJECTINPUTSTREAM - Static variable in class weka.core.scripting.Jython: the classname of the Python ObjectInputStream
ClassAssigner - Class in weka.filters.unsupervised.attribute: Filter that can set and unset the class index.
ClassAssigner - Class in weka.gui.beans: Bean that assigns a class attribute to a data set.
ClassAssigner - Class in weka.knowledgeflow.steps: Knowledge Flow step for assigning a class attribute in incoming data
ClassAssigner() - Constructor for class weka.filters.unsupervised.attribute.ClassAssigner
ClassAssigner() - Constructor for class weka.gui.beans.ClassAssigner
ClassAssigner() - Constructor for class weka.knowledgeflow.steps.ClassAssigner
ClassAssignerBeanInfo - Class in weka.gui.beans: BeanInfo class for the class assigner bean
ClassAssignerBeanInfo() - Constructor for class weka.gui.beans.ClassAssignerBeanInfo
ClassAssignerCustomizer - Class in weka.gui.beans: GUI customizer for the class assigner bean
ClassAssignerCustomizer() - Constructor for class weka.gui.beans.ClassAssignerCustomizer
ClassAssignerStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the ClassAssigner step
ClassAssignerStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.ClassAssignerStepEditorDialog
classAttribute() - Method in class weka.core.AbstractInstance: Returns class attribute.
classAttribute() - Method in interface weka.core.Instance: Returns class attribute.
classAttribute() - Method in class weka.core.Instances: Returns the class attribute.
classAttributeNames() - Method in class weka.classifiers.functions.SMO
ClassBalancer - Class in weka.filters.supervised.instance: Reweights the instances in the data so that each class has the same total weight.
ClassBalancer() - Constructor for class weka.filters.supervised.instance.ClassBalancer
ClassCache - Class in weka.core: A singleton that stores all classes on the classpath.
ClassCache() - Constructor for class weka.core.ClassCache: Initializes the cache.
ClassCache.ClassFileFilter - Class in weka.core: For filtering classes.
ClassCache.DirectoryFilter - Class in weka.core: For filtering classes.
classColumnTipText() - Method in class weka.gui.beans.ClassAssigner: Tool tip text for this property
ClassConditionalProbabilities - Class in weka.filters.supervised.attribute: Converts the values of nominal and/or numeric attributes into class conditional probabilities.
ClassConditionalProbabilities() - Constructor for class weka.filters.supervised.attribute.ClassConditionalProbabilities
ClassDiscovery - Class in weka.core: This class is used for discovering classes that implement a certain interface or a derived from a certain class.
ClassDiscovery() - Constructor for class weka.core.ClassDiscovery
ClassDiscovery.StringCompare - Class in weka.core: compares two strings.
classDistributionIsPure() - Method in class weka.classifiers.trees.ht.HNode: Returns true if the class distribution is pure
CLASSES_TO_CLUSTERS_EVAL - Enum constant in enum class weka.gui.explorer.ClustererPanel.TestMode
ClassFileFilter() - Constructor for class weka.core.ClassCache.ClassFileFilter
classFirst(boolean) - Method in class weka.experiment.Experiment: Sets whether the first attribute is treated as the class for all datasets involved in the experiment.
classFlagTipText() - Method in class weka.datagenerators.ClusterGenerator: Returns the tip text for this property
CLASSIFICATION - Enum constant in enum class weka.core.pmml.jaxbbindings.MININGFUNCTION
ClassificationGenerator - Class in weka.datagenerators: Abstract class for data generators for classifiers.
ClassificationGenerator() - Constructor for class weka.datagenerators.ClassificationGenerator: initializes with default values
ClassificationViaRegression - Class in weka.classifiers.meta: Class for doing classification using regression methods.
ClassificationViaRegression() - Constructor for class weka.classifiers.meta.ClassificationViaRegression: Default constructor.
Classifier - Class in weka.gui.beans: Bean that wraps around weka.classifiers
Classifier - Class in weka.knowledgeflow.steps: Step that wraps a Weka classifier.
Classifier - Interface in weka.classifiers: Classifier interface.
Classifier() - Constructor for class weka.gui.beans.Classifier: Creates a new Classifier instance.
Classifier() - Constructor for class weka.knowledgeflow.steps.Classifier
CLASSIFIER - Enum constant in enum class weka.Run.SchemeType
ClassifierAttributeEval - Class in weka.attributeSelection: ClassifierAttributeEval :

Evaluates the worth of an attribute by using a user-specified classifier.
ClassifierAttributeEval() - Constructor for class weka.attributeSelection.ClassifierAttributeEval: Constructor.
ClassifierBeanInfo - Class in weka.gui.beans: BeanInfo class for the Classifier wrapper bean
ClassifierBeanInfo() - Constructor for class weka.gui.beans.ClassifierBeanInfo
ClassifierCustomizer - Class in weka.gui.beans: GUI customizer for the classifier wrapper bean
ClassifierCustomizer() - Constructor for class weka.gui.beans.ClassifierCustomizer
ClassifierDecList - Class in weka.classifiers.rules.part: Class for handling a rule (partial tree) for a decision list.
ClassifierDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.ClassifierDecList: Constructor - just calls constructor of class DecList.
ClassifierErrorsPlotInstances - Class in weka.gui.explorer: A class for generating plottable visualization errors.
ClassifierErrorsPlotInstances() - Constructor for class weka.gui.explorer.ClassifierErrorsPlotInstances
ClassifierPanel - Class in weka.gui.explorer: This panel allows the user to select and configure a classifier, set the attribute of the current dataset to be used as the class, and evaluate the classifier using a number of testing modes (test on the training data, train/test on a percentage split, n-fold cross-validation, test on a separate split).
ClassifierPanel() - Constructor for class weka.gui.explorer.ClassifierPanel: Creates the classifier panel.
ClassifierPanel.TestMode - Enum Class in weka.gui.explorer
ClassifierPanelLaunchHandlerPlugin - Interface in weka.gui.explorer: Interface to plugin that can take the current state of the Classifier panel and execute it.
ClassifierPerformanceEvaluator - Class in weka.gui.beans: A bean that evaluates the performance of batch trained classifiers
ClassifierPerformanceEvaluator - Class in weka.knowledgeflow.steps: Step that implements batch classifier evaluation
ClassifierPerformanceEvaluator() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluator
ClassifierPerformanceEvaluator() - Constructor for class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Constructor
ClassifierPerformanceEvaluatorBeanInfo - Class in weka.gui.beans: Bean info class for the classifier performance evaluator
ClassifierPerformanceEvaluatorBeanInfo() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo
ClassifierPerformanceEvaluatorCustomizer - Class in weka.gui.beans: GUI customizer for the classifier performance evaluator component
ClassifierPerformanceEvaluatorCustomizer() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer: Constructor
ClassifierPerformanceEvaluatorStepEditorDialog - Class in weka.gui.knowledgeflow.steps: GUI step editor dialog for the ClassifierPerformanceEvaluator step
ClassifierPerformanceEvaluatorStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.ClassifierPerformanceEvaluatorStepEditorDialog: Constructor
classifiers() - Method in class weka.classifiers.meta.LogitBoost: Returns the array of classifiers that have been built.
ClassifierSplitEvaluator - Class in weka.experiment: A SplitEvaluator that produces results for a classification scheme on a nominal class attribute.
ClassifierSplitEvaluator() - Constructor for class weka.experiment.ClassifierSplitEvaluator: No args constructor.
ClassifierSplitModel - Class in weka.classifiers.trees.j48: Abstract class for classification models that can be used recursively to split the data.
ClassifierSplitModel() - Constructor for class weka.classifiers.trees.j48.ClassifierSplitModel
classifiersTipText() - Method in class weka.classifiers.meta.MultiScheme: Returns the tip text for this property
classifiersTipText() - Method in class weka.classifiers.MultipleClassifiersCombiner: Returns the tip text for this property
ClassifierSubsetEval - Class in weka.attributeSelection: Classifier subset evaluator:

Evaluates attribute subsets on training data or a separate hold out testing set.
ClassifierSubsetEval() - Constructor for class weka.attributeSelection.ClassifierSubsetEval
classifierTipText() - Method in class weka.attributeSelection.ClassifierAttributeEval: Returns the tip text for this property
classifierTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns the tip text for this property
classifierTipText() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the tip text for this property
classifierTipText() - Method in class weka.classifiers.SingleClassifierEnhancer: Returns the tip text for this property
classifierTipText() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns the tip text for this property
classifierTipText() - Method in class weka.experiment.RegressionSplitEvaluator: Returns the tip text for this property
classifierTipText() - Method in class weka.filters.supervised.attribute.AddClassification: Returns the tip text for this property.
classifierTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the tip text for this property
ClassifierTree - Class in weka.classifiers.trees.j48: Class for handling a tree structure used for classification.
ClassifierTree(ModelSelection) - Constructor for class weka.classifiers.trees.j48.ClassifierTree: Constructor.
CLASSIFY_CHILD - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent: Asks for another learning scheme to classify this node.
classifyInstance(Instance) - Method in class weka.classifiers.AbstractClassifier: Classifies the given test instance.
classifyInstance(Instance) - Method in interface weka.classifiers.Classifier: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcesses: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.LinearRegression: Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.functions.SimpleLinearRegression: Generate a prediction for the supplied instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.SMOreg: Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AdditiveRegression: Classify an instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns a predicted class for the test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.Vote: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.misc.InputMappedClassifier
classifyInstance(Instance) - Method in class weka.classifiers.rules.OneR: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.PART: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.part.MakeDecList: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.ZeroR: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.j48.ClassifierTree: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.J48: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.LMT: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Generate a prediction for the supplied instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.M5Base: Calculates a prediction for an instance using a set of rules or an M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Predicts the class of the supplied instance using the linear model.
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.Rule: Calculates a prediction for an instance using this rule or M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.RuleNode: Classify an instance using this node.
classIndex() - Method in class weka.core.AbstractInstance: Returns the class attribute's index.
classIndex() - Method in interface weka.core.Instance: Returns the class attribute's index.
classIndex() - Method in class weka.core.Instances: Returns the class attribute's index.
classIndexTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
classIndexTipText() - Method in class weka.associations.FilteredAssociator: Returns the tip text for this property
classIndexTipText() - Method in class weka.core.converters.JSONSaver: Returns the tip text for this property.
classIndexTipText() - Method in class weka.core.converters.LibSVMSaver: Returns the tip text for this property
classIndexTipText() - Method in class weka.core.converters.SVMLightSaver: Returns the tip text for this property.
classIndexTipText() - Method in class weka.core.converters.XRFFSaver: Returns the tip text for this property
classIndexTipText() - Method in class weka.filters.unsupervised.attribute.ClassAssigner: Returns the tip text for this property.
classIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the tip text for this property
classIsMissing() - Method in class weka.core.AbstractInstance: Tests if an instance's class is missing.
classIsMissing() - Method in interface weka.core.Instance: Tests if an instance's class is missing.
ClassLabels - Class in weka.core.pmml.jaxbbindings: Java class for ClassLabels element declaration.
ClassLabels() - Constructor for class weka.core.pmml.jaxbbindings.ClassLabels
ClassloaderUtil - Class in weka.core: Utility class that can add jar files to the classpath dynamically.
ClassloaderUtil() - Constructor for class weka.core.ClassloaderUtil
className(int) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Gets the name of one of the classes.
classNameTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns the tip text for this property
ClassOrder - Class in weka.filters.supervised.attribute: Changes the order of the classes so that the class values are no longer of in the order specified in the header.
ClassOrder() - Constructor for class weka.filters.supervised.attribute.ClassOrder
classOrderTipText() - Method in class weka.filters.supervised.attribute.ClassOrder: Returns the tip text for this property
ClassPanel - Class in weka.gui.visualize: This panel displays coloured labels for nominal attributes and a spectrum for numeric attributes.
ClassPanel() - Constructor for class weka.gui.visualize.ClassPanel
ClassPanel(Color) - Constructor for class weka.gui.visualize.ClassPanel
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.BinC45Split: Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.C45Split: Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Return the probability for a class value
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Return the probability for a class value
classProbLaplace(int, Instance, int) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Gets class probability for instance.
ClassRunner(SimpleCLIPanel, Class<?>, String[]) - Constructor for class weka.gui.SimpleCLIPanel.ClassRunner: Sets up the class runner thread.
classValue() - Method in class weka.core.AbstractInstance: Returns an instance's class value in internal format.
classValue() - Method in interface weka.core.Instance: Returns an instance's class value as a floating-point number.
classValueIndexTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
ClassValuePicker - Class in weka.gui.beans
ClassValuePicker - Class in weka.knowledgeflow.steps: Step that allows the selection of the class label that is to be considered as the "positive" class when computing threshold curves.
ClassValuePicker() - Constructor for class weka.gui.beans.ClassValuePicker
ClassValuePicker() - Constructor for class weka.knowledgeflow.steps.ClassValuePicker
ClassValuePickerBeanInfo - Class in weka.gui.beans: BeanInfo class for the class value picker bean
ClassValuePickerBeanInfo() - Constructor for class weka.gui.beans.ClassValuePickerBeanInfo
ClassValuePickerCustomizer - Class in weka.gui.beans
ClassValuePickerCustomizer() - Constructor for class weka.gui.beans.ClassValuePickerCustomizer
ClassValuePickerStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Editor dialog for the ClassValuePicker step.
ClassValuePickerStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.ClassValuePickerStepEditorDialog
clean() - Method in class weka.attributeSelection.ASEvaluation: Tells the evaluator that the attribute selection process is complete.
clean() - Method in class weka.attributeSelection.CfsSubsetEval
clean() - Method in class weka.attributeSelection.WrapperSubsetEval
clean() - Method in class weka.classifiers.functions.supportVector.CachedKernel: Frees the cache used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.Kernel: Frees the memory used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel: Frees the cache used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Frees the memory used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.StringKernel: Frees the memory used by the kernel.
clean() - Method in interface weka.core.DistanceFunction: Free any references to training instances
clean() - Method in class weka.core.FilteredDistance: Free any references to training instances
clean() - Method in class weka.core.NormalizableDistance
cleanup() - Method in class weka.classifiers.trees.j48.BinC45ModelSelection: Sets reference to training data to null.
cleanup() - Method in class weka.classifiers.trees.j48.C45ModelSelection: Sets reference to training data to null.
cleanup() - Method in class weka.classifiers.trees.j48.NBTreeModelSelection: Sets reference to training data to null.
cleanup() - Method in class weka.classifiers.trees.lmt.LogisticBase: Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.lmt.ResidualModelSelection: Method not in use
cleanup(Instances) - Method in class weka.classifiers.rules.part.ClassifierDecList: Cleanup in order to save memory.
cleanup(Instances) - Method in class weka.classifiers.trees.j48.ClassifierTree: Cleanup in order to save memory.
cleanUp() - Method in class weka.classifiers.rules.RuleStats: Frees up memory after classifier has been built.
cleanUp() - Method in class weka.clusterers.Canopy: Save memory
cleanUp() - Method in class weka.gui.explorer.AbstractPlotInstances: For freeing up memory.
cleanUp() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: For freeing up memory.
cleanUp() - Method in class weka.gui.explorer.ClustererAssignmentsPlotInstances: For freeing up memory.
cleanUp(String) - Static method in class weka.core.ClassCache: Fixes the classname, turns "/" and "\" into "." and removes ".class".
cleanUp(Instances) - Method in class weka.classifiers.rules.JRip.RipperRule: Removes redundant tests in the rule.
cleanUpAfterSwitch() - Method in class weka.gui.experiment.AbstractSetupPanel: Hook method for cleaning up the interface after a switch.
cleanUpAfterSwitch() - Method in class weka.gui.experiment.SetupPanel: Hook method for cleaning up the interface after a switch.
cleanUpAfterSwitch() - Method in class weka.gui.experiment.SimpleSetupPanel: Hook method for cleaning up the interface after a switch.
clear() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Clears this hashtable so that it contains no keys.
clear() - Method in class weka.classifiers.xml.XMLClassifier: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.neighboursearch.covertrees.Stack: Removes all the elements from the stack.
clear() - Method in class weka.core.ProtectedProperties: Overrides a method to prevent the properties from being modified.
clear() - Method in class weka.core.Stopwords: removes all stopwords
clear() - Method in class weka.core.Tee: removes all streams and places the default printstream, if any, again in the list.
clear() - Method in class weka.core.Trie: Removes all of the elements from this collection
clear() - Method in class weka.core.xml.MethodHandler: removes all mappings
clear() - Method in class weka.core.xml.XMLBasicSerialization: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.xml.XMLDocument: sets up an empty DOM document, with the current DOCTYPE and root node.
clear() - Method in class weka.core.xml.XMLSerialization: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.xml.XMLSerializationMethodHandler: removes all current methods and adds the methods according to the
clear() - Method in class weka.experiment.ResultMatrix: removes the stored data and the ordering, but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.ResultMatrixCSV: removes the stored data but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.ResultMatrixGnuPlot: removes the stored data but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.ResultMatrixLatex: removes the stored data but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.xml.XMLExperiment: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.gui.beans.xml.XMLBeans: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.gui.GenericObjectEditorHistory: Clears the history.
clear() - Method in class weka.gui.LogWindow: clears the output
clear() - Method in class weka.gui.sql.ConnectionPanel: sets the parameters back to standard.
clear() - Method in class weka.gui.sql.InfoPanel: clears the content of the panel
clear() - Method in class weka.gui.sql.QueryPanel: clears the textarea.
clear() - Method in class weka.gui.sql.ResultPanel: sets the parameters back to standard
clear() - Method in class weka.gui.sql.SqlViewer: calls the clear method of all sub-panels to set back to default values and free up memory.
clearAllConnections() - Method in class weka.knowledgeflow.StepManagerImpl: Clear all connections to/from the step managed by this manager.
clearAllStepOutputListeners() - Method in class weka.knowledgeflow.StepManagerImpl: Clear all registered StepOutputListeners
clearAttributeSpecs() - Method in class weka.filters.unsupervised.attribute.AddUserFields: Clear the list of attribute specifications
clearCache() - Static method in class weka.core.ClassDiscovery: clears the cache for class/classnames queries.
clearClassCache() - Static method in class weka.core.ClassDiscovery: Calls clearCache() and resets the cache of classes on the classpath (i.e.
clearDesignPaletteSelection() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Clear the current selection in the design palette
clearHeader() - Method in class weka.experiment.ResultMatrix: removes all the header information.
clearLayout() - Method in class weka.gui.beans.KnowledgeFlowApp
clearPayload() - Method in class weka.knowledgeflow.Data: Clear all payload elements from this Data object
clearPlotData() - Method in class weka.knowledgeflow.steps.DataVisualizer
clearPlotData() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Clear all plot data (both onscreen and offscreen)
clearRanking() - Method in class weka.experiment.ResultMatrix: clears the currently stored ranking data.
clearRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw a filled rectangle with the background color.
clearResultData() - Method in class weka.knowledgeflow.JobEnvironment
clearResults() - Method in class weka.gui.ResultHistoryPanel: Removes all of the result buffers from the history.
clearSearch() - Method in class weka.gui.arffviewer.ArffPanel: clears the search, i.e.
clearSearch() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: clears the search, i.e.
clearStatus() - Method in class weka.gui.beans.LogPanel: Clear the status area.
clearStepOutputListeners(String) - Method in class weka.knowledgeflow.StepManagerImpl: Clear all the StepOutputListeners that are registered to receive the supplied connection type.
clearStepProperties() - Method in class weka.knowledgeflow.JobEnvironment: Clear all step properties
clearSummary() - Method in class weka.experiment.ResultMatrix: clears the current summary data.
clearUndo() - Method in interface weka.core.Undoable: removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffPanel: removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffSortedTableModel: removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffTableModel: removes the undo history
clearUndoStack() - Method in class weka.classifiers.bayes.net.EditableBayesNet: remove all actions from the undo stack
clip(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
clipRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
Clock() - Constructor for class weka.core.Debug.Clock: automatically starts the clock with FORMAT_SECONDS format and CPU time if available
Clock(boolean) - Constructor for class weka.core.Debug.Clock: starts the clock depending on start immediately with the FORMAT_SECONDS output format and CPU time if available
Clock(boolean, int) - Constructor for class weka.core.Debug.Clock: starts the clock depending on start immediately, using CPU time if available
Clock(int) - Constructor for class weka.core.Debug.Clock: automatically starts the clock with the given output format and CPU time if available
CLOGLOG - Enum constant in enum class weka.core.pmml.jaxbbindings.CUMULATIVELINKFUNCTION
CLOGLOG - Enum constant in enum class weka.core.pmml.jaxbbindings.LINKFUNCTION
CLOGLOG - Enum constant in enum class weka.core.pmml.jaxbbindings.REGRESSIONNORMALIZATIONMETHOD
clone() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Creates and returns a clone of this object.
clone() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Allows to clone a model (shallow copy).
clone() - Method in class weka.classifiers.trees.j48.Distribution: Clones distribution (Deep copy of distribution).
clone() - Method in class weka.core.AlgVector: Creates and returns a clone of this object.
clone() - Method in class weka.core.Capabilities: Creates and returns a copy of this object.
clone() - Method in class weka.core.Matrix: Deprecated.

Creates and returns a clone of this object.
clone() - Method in class weka.core.matrix.DoubleVector: Clones the DoubleVector object.
clone() - Method in class weka.core.matrix.IntVector: Clones the IntVector object.
clone() - Method in class weka.core.matrix.Matrix: Clone the Matrix object.
clone() - Method in class weka.core.packageManagement.DefaultPackage: Clone this package.
clone() - Method in class weka.core.packageManagement.Package
clone() - Method in class weka.core.PropertyPath.PathElement: returns a clone of the current object
clone() - Method in class weka.core.TestInstances: creates a clone of the current object
clone() - Method in class weka.core.Trie: returns a deep copy of itself
clone() - Method in class weka.core.Trie.TrieNode: creates a deep copy of itself
clone(Estimator) - Static method in class weka.estimators.Estimator: Creates a deep copy of the given estimator using serialization.
close() - Method in class weka.experiment.DatabaseUtils: closes the m_PreparedStatement to avoid memory leaks.
close() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: 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 weka.gui.LogWindow: closes the frame
close(ResultSet) - Method in class weka.experiment.DatabaseUtils: closes the ResultSet and the statement that generated the ResultSet to avoid memory leaks in JDBC drivers - in contrast to the JDBC specs, a lot of JDBC drives don't clean up correctly.
CloseableTabTitle - Class in weka.gui: Tab title widget that allows the user to click a little cross in order to close the tab
CloseableTabTitle(JTabbedPane, String, CloseableTabTitle.ClosingCallback) - Constructor for class weka.gui.CloseableTabTitle: Constructor.
CloseableTabTitle.ClosingCallback - Interface in weka.gui: Interface for a callback for notification of a tab's close widget being clicked
closeAllFiles() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: closes all open files
closeAllTabs() - Method in class weka.gui.beans.KnowledgeFlowApp
closeAllTabs() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Close all the open tabs
CLOSEDCLOSED - Enum constant in enum class weka.core.pmml.FieldMetaInfo.Interval.Closure
CLOSEDOPEN - Enum constant in enum class weka.core.pmml.FieldMetaInfo.Interval.Closure
closeFile() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: closes the current tab
closeFile(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: closes the current tab
closeFrame() - Method in class weka.gui.SetInstancesPanel: closes the frame, i.e., the visibility is set to false.
closePressed() - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Called when the close button is pressed.
closePressed() - Method in class weka.gui.knowledgeflow.steps.BoundaryPlotterInteractiveView: Called when the viewer's window is closed
closePressed() - Method in class weka.gui.knowledgeflow.steps.StripChartInteractiveView: Called when the close button is pressed
closePressed() - Method in class weka.gui.knowledgeflow.steps.TextViewerInteractiveView: Called when the close button is pressed
closestPoint(Instance, Instances, int[]) - Method in class weka.core.EuclideanDistance: Returns the index of the closest point to the current instance.
closeToDefaultTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
closeToTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
closeToToleranceTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
closing() - Method in interface weka.gui.knowledgeflow.StepEditorDialog.ClosingListener
closingCancel() - Method in interface weka.gui.beans.GOECustomizer: Gets called when the customizer is closing under a CANCEL condition
closingCancel() - Method in class weka.gui.filters.AddUserFieldsCustomizer: Actions to perform when the user has closed the dialog with the Cancel button
closingCancel() - Method in class weka.gui.PropertySheetPanel: Pass on a CANCEL closing notificiation to the customizer (if one is in use).
closingOK() - Method in interface weka.gui.beans.GOECustomizer: Gets called when the customizer is closing under an OK condition
closingOK() - Method in class weka.gui.filters.AddUserFieldsCustomizer: Actions to perform when the user has closed the dialog with the OK button.
closingOK() - Method in class weka.gui.PropertySheetPanel: Pass on an OK closing notification to the customizer (if one is in use)
Cls - Class in weka.gui.simplecli: Clears the output area.
Cls() - Constructor for class weka.gui.simplecli.Cls
Cluster - Class in weka.core.pmml.jaxbbindings: Java class for Cluster element declaration.
Cluster() - Constructor for class weka.core.pmml.jaxbbindings.Cluster
CLUSTER_AFFINITY - Enum constant in enum class weka.core.pmml.jaxbbindings.RESULTFEATURE
CLUSTER_ID - Enum constant in enum class weka.core.pmml.jaxbbindings.RESULTFEATURE
ClusterDefinition - Class in weka.datagenerators: Ancestor to all ClusterDefinitions, i.e., subclasses that handle their own parameters that the cluster generator only passes on.
ClusterDefinition() - Constructor for class weka.datagenerators.ClusterDefinition: initializes the cluster, without a parent cluster (necessary for GOE)
ClusterDefinition(ClusterGenerator) - Constructor for class weka.datagenerators.ClusterDefinition: initializes the cluster by setting the parent and the defaults
clusterDefinitionsTipText() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Returns the tip text for this property
Clusterer - Class in weka.gui.beans: Bean that wraps around weka.clusterers
Clusterer - Class in weka.knowledgeflow.steps: Step that wraps a Weka clusterer.
Clusterer - Interface in weka.clusterers: Interface for clusterers.
Clusterer() - Constructor for class weka.gui.beans.Clusterer: Creates a new Clusterer instance.
Clusterer() - Constructor for class weka.knowledgeflow.steps.Clusterer
CLUSTERER - Enum constant in enum class weka.Run.SchemeType
ClustererAssignmentsPlotInstances - Class in weka.gui.explorer: A class for generating plottable cluster assignments.
ClustererAssignmentsPlotInstances() - Constructor for class weka.gui.explorer.ClustererAssignmentsPlotInstances
ClustererBeanInfo - Class in weka.gui.beans: BeanInfo class for the Clusterer wrapper bean
ClustererBeanInfo() - Constructor for class weka.gui.beans.ClustererBeanInfo
ClustererCustomizer - Class in weka.gui.beans: GUI customizer for the Clusterer wrapper bean
ClustererCustomizer() - Constructor for class weka.gui.beans.ClustererCustomizer
ClustererPanel - Class in weka.gui.explorer: This panel allows the user to select and configure a clusterer, and evaluate the clusterer using a number of testing modes (test on the training data, train/test on a percentage split, test on a separate split).
ClustererPanel() - Constructor for class weka.gui.explorer.ClustererPanel: Creates the clusterer panel
ClustererPanel.TestMode - Enum Class in weka.gui.explorer
ClustererPanelLaunchHandlerPlugin - Interface in weka.gui.explorer: Interface to plugin that can take the current state of the Clusterer panel and execute it.
ClustererPerformanceEvaluator - Class in weka.gui.beans: A bean that evaluates the performance of batch trained clusterers
ClustererPerformanceEvaluator - Class in weka.knowledgeflow.steps: A step that evaluates the performance of batch trained clusterers
ClustererPerformanceEvaluator() - Constructor for class weka.gui.beans.ClustererPerformanceEvaluator
ClustererPerformanceEvaluator() - Constructor for class weka.knowledgeflow.steps.ClustererPerformanceEvaluator
ClustererPerformanceEvaluatorBeanInfo - Class in weka.gui.beans: Bean info class for the clusterer performance evaluator
ClustererPerformanceEvaluatorBeanInfo() - Constructor for class weka.gui.beans.ClustererPerformanceEvaluatorBeanInfo
clustererTipText() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns the tip text for this property
clustererTipText() - Method in class weka.clusterers.SingleClustererEnhancer: Returns the tip text for this property
clustererTipText() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns the tip text for this property
clustererTipText() - Method in class weka.filters.unsupervised.attribute.AddCluster: Returns the tip text for this property.
ClusterEvaluation - Class in weka.clusterers: Class for evaluating clustering models.
ClusterEvaluation() - Constructor for class weka.clusterers.ClusterEvaluation: Constructor.
ClusterGenerator - Class in weka.datagenerators: Abstract class for cluster data generators.
ClusterGenerator() - Constructor for class weka.datagenerators.ClusterGenerator: initializes the generator
CLUSTERING - Enum constant in enum class weka.core.pmml.jaxbbindings.MININGFUNCTION
ClusteringField - Class in weka.core.pmml.jaxbbindings: Java class for ClusteringField element declaration.
ClusteringField() - Constructor for class weka.core.pmml.jaxbbindings.ClusteringField
ClusteringModel - Class in weka.core.pmml.jaxbbindings: Java class for ClusteringModel element declaration.
ClusteringModel() - Constructor for class weka.core.pmml.jaxbbindings.ClusteringModel
ClusteringModelQuality - Class in weka.core.pmml.jaxbbindings: Java class for ClusteringModelQuality element declaration.
ClusteringModelQuality() - Constructor for class weka.core.pmml.jaxbbindings.ClusteringModelQuality
clusterInstance(Instance) - Method in class weka.clusterers.AbstractClusterer: Classifies a given instance.
clusterInstance(Instance) - Method in interface weka.clusterers.Clusterer: Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.Cobweb: Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.FarthestFirst: Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.HierarchicalClusterer
clusterInstance(Instance) - Method in class weka.clusterers.SimpleKMeans: Classifies a given instance.
ClusterMembership - Class in weka.filters.unsupervised.attribute: A filter that uses a density-based clusterer to generate cluster membership values; filtered instances are composed of these values plus the class attribute (if set in the input data).
ClusterMembership() - Constructor for class weka.filters.unsupervised.attribute.ClusterMembership
clusterPriors() - Method in class weka.clusterers.AbstractDensityBasedClusterer: Returns the prior probability of each cluster.
clusterPriors() - Method in interface weka.clusterers.DensityBasedClusterer: Returns the prior probability of each cluster.
clusterPriors() - Method in class weka.clusterers.EM: Returns the cluster priors.
clusterPriors() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns the cluster priors.
clusterResultsToString() - Method in class weka.clusterers.ClusterEvaluation: return the results of clustering.
clusterSubTypeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
clusterTypeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
CNode(int) - Constructor for class weka.clusterers.Cobweb.CNode: Creates an empty CNode instance.
CNode(int, Instance) - Constructor for class weka.clusterers.Cobweb.CNode: Creates a new leaf CNode instance.
Cobweb - Class in weka.clusterers: Class implementing the Cobweb and Classit clustering algorithms.

Note: the application of node operators (merging, splitting etc.) in terms of ordering and priority differs (and is somewhat ambiguous) between the original Cobweb and Classit papers.
Cobweb() - Constructor for class weka.clusterers.Cobweb: default constructor
Cobweb.CNode - Class in weka.clusterers: Inner class handling node operations for Cobweb.
cochransCriterion(double[][]) - Static method in class weka.core.ContingencyTables: Tests if Cochran's criterion is fullfilled for the given contingency table.
codingCost() - Method in class weka.classifiers.trees.j48.C45Split: Returns coding cost for split (used in rule learner).
codingCost() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Returns coding costs of model.
Coefficient - Class in weka.core.pmml.jaxbbindings: Java class for Coefficient element declaration.
Coefficient() - Constructor for class weka.core.pmml.jaxbbindings.Coefficient
coefficients() - Method in class weka.classifiers.functions.LinearRegression: Returns the coefficients for this linear model.
coefficients() - Method in class weka.classifiers.functions.Logistic: Returns the coefficients for this logistic model.
coefficients() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Return the array of coefficients
Coefficients - Class in weka.core.pmml.jaxbbindings: Java class for Coefficients element declaration.
Coefficients() - Constructor for class weka.core.pmml.jaxbbindings.Coefficients
COEFFICIENTS - Enum constant in enum class weka.core.pmml.jaxbbindings.SVMREPRESENTATION
collapse() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree: Collapses a tree to a node if training error doesn't increase.
collapseTreeTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
colNameWidthTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
COLON - Static variable in interface weka.core.json.sym
COLOR_STDERR - Static variable in class weka.gui.LogWindow: the Color of the style for stderr
COLOR_STDOUT - Static variable in class weka.gui.LogWindow: the color of the style for stdout
ColorEditor - Class in weka.gui: A property editor for colors that uses JColorChooser as the underlying editor.
ColorEditor() - Constructor for class weka.gui.ColorEditor
Colors - Class in weka.gui.treevisualizer: This class maintains a list that contains all the colornames from the dotty standard and what color (in RGB) they represent
Colors() - Constructor for class weka.gui.treevisualizer.Colors
combinationRuleTipText() - Method in class weka.classifiers.meta.Vote: Returns the tip text for this property
combinedDL(double, double) - Method in class weka.classifiers.rules.RuleStats: Compute the combined DL of the ruleset in this class, i.e.
combSort11(double[], int[]) - Static method in class weka.core.neighboursearch.NearestNeighbourSearch: sorts the two given arrays.
COMMA - Static variable in interface weka.core.expressionlanguage.parser.sym
COMMA - Static variable in interface weka.core.json.sym
COMMANDLINE - Enum constant in enum class weka.Run.SchemeType
CommandlineCompletion() - Constructor for class weka.gui.SimpleCLIPanel.CommandlineCompletion: default constructor.
commandLineParamIsFlag() - Element in annotation interface weka.core.OptionMetadata: True if the command line version of this parameter is a flag (i.e.
commandLineParamName() - Element in annotation interface weka.core.OptionMetadata: The name of the command line version of this parameter (without leading -).
commandLineParamSynopsis() - Element in annotation interface weka.core.OptionMetadata: The synopsis to display on in the command line help for this parameter (e.g.
CommandlineRunnable - Interface in weka.core: Interface to something that can be run from the command line.
Comment - Enum constant in enum class weka.gui.scripting.SyntaxDocument.ATTR_TYPE: a comment.
compactify() - Method in class weka.core.Instances: Compactifies the set of instances.
compare(String, String) - Method in class weka.core.ClassDiscovery.StringCompare: Compares its two arguments for order.
compare(String, String) - Static method in class weka.core.packageManagement.VersionPackageConstraint: Returns a VersionComparison that represents the comparison between the supplied version 1 and version 2.
compare(String, String) - Method in class weka.filters.unsupervised.attribute.SortLabels.CaseInsensitiveComparator: compares the two strings, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
compare(String, String) - Method in class weka.filters.unsupervised.attribute.SortLabels.CaseSensitiveComparator: compares the two strings, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
compare(Instance, Instance) - Method in class weka.core.InstanceComparator: compares the two instances, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
compare(Sorter.InstanceHolder, Sorter.InstanceHolder) - Method in class weka.knowledgeflow.steps.Sorter.SortRule: Compare two instances according to the rule
COMPAREFUNCTION - Enum Class in weka.core.pmml.jaxbbindings: Java class for COMPARE-FUNCTION.
compareTo(String) - Method in class weka.core.Version: checks the version of this class against the given version-string
compareTo(AssociationRule) - Method in class weka.associations.AssociationRule: Compare this rule to the supplied rule.
compareTo(Item) - Method in class weka.associations.Item: Ensures that items will be sorted in descending order of frequency.
compareTo(SplitCandidate) - Method in class weka.classifiers.trees.ht.SplitCandidate
compareTo(AttributeLocator) - Method in class weka.core.AttributeLocator: Compares this object with the specified object for order.
compareTo(AbstractSetupPanel) - Method in class weka.gui.experiment.AbstractSetupPanel: Uses the name for comparison.
compareTo(AbstractCommand) - Method in class weka.gui.simplecli.AbstractCommand: Performs comparison just on the name.
compareTo(SortedTableModel.SortContainer) - Method in class weka.gui.SortedTableModel.SortContainer: Compares this object with the specified object for order.
ComparisonMeasure - Class in weka.core.pmml.jaxbbindings: Java class for ComparisonMeasure element declaration.
ComparisonMeasure() - Constructor for class weka.core.pmml.jaxbbindings.ComparisonMeasure
Comparisons - Class in weka.core.pmml.jaxbbindings: Java class for Comparisons element declaration.
Comparisons() - Constructor for class weka.core.pmml.jaxbbindings.Comparisons
ComponentHelper - Class in weka.gui: A helper class for some common tasks with Dialogs, Icons, etc.
ComponentHelper() - Constructor for class weka.gui.ComponentHelper
componentHidden(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
componentMoved(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
componentResized(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
componentShown(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
CompoundPredicate - Class in weka.core.pmml.jaxbbindings: Java class for CompoundPredicate element declaration.
CompoundPredicate() - Constructor for class weka.core.pmml.jaxbbindings.CompoundPredicate
CompoundRule - Class in weka.core.pmml.jaxbbindings: Java class for CompoundRule element declaration.
CompoundRule() - Constructor for class weka.core.pmml.jaxbbindings.CompoundRule
compressOutputTipText() - Method in class weka.core.converters.ArffSaver: Returns the tip text for this property
compressOutputTipText() - Method in class weka.core.converters.JSONSaver: Returns the tip text for this property.
compressOutputTipText() - Method in class weka.core.converters.XRFFSaver: Returns the tip text for this property
Compute - Interface in weka.experiment: Interface to something that can accept remote connections and execute a task.
computeAttributeImportanceTipText() - Method in class weka.classifiers.trees.RandomForest: Returns the tip text for this property
computeAverageImpurityDecreasePerAttribute(double[]) - Method in class weka.classifiers.trees.RandomForest: Computes the average impurity decrease per attribute over the trees
computeMinMaxAtts() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set up the bounds of our graphic based by finding the smallest reasonable area in the instance space to surround our data points.
CON_AUX_DATA_BATCH_ASSOCIATION_RULES - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_CHART_DATA_POINT - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_CHART_LEGEND - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_CHART_MAX - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_CHART_MIN - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_CLASS_ATTRIBUTE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_ENVIRONMENT_PROPERTIES - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_ENVIRONMENT_RESULTS - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_ENVIRONMENT_VARIABLES - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_GRAPH_TITLE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_GRAPH_TYPE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_INCREMENTAL_STREAM_END - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_INSTANCE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_IS_INCREMENTAL - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_LABEL - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_MAX_SET_NUM - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_PRIMARY_PAYLOAD_NOT_THREAD_SAFE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_SET_NUM - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_TEST_INSTANCE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_TESTSET - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_TEXT_TITLE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_TRAININGSET - Static variable in interface weka.knowledgeflow.StepManager
CON_BATCH_ASSOCIATOR - Static variable in interface weka.knowledgeflow.StepManager
CON_BATCH_CLASSIFIER - Static variable in interface weka.knowledgeflow.StepManager
CON_BATCH_CLUSTERER - Static variable in interface weka.knowledgeflow.StepManager
CON_CHART - Static variable in interface weka.knowledgeflow.StepManager
CON_DATASET - Static variable in interface weka.knowledgeflow.StepManager
CON_ENVIRONMENT - Static variable in interface weka.knowledgeflow.StepManager
CON_GRAPH - Static variable in interface weka.knowledgeflow.StepManager
CON_IMAGE - Static variable in interface weka.knowledgeflow.StepManager
CON_INCREMENTAL_CLASSIFIER - Static variable in interface weka.knowledgeflow.StepManager
CON_INCREMENTAL_CLUSTERER - Static variable in interface weka.knowledgeflow.StepManager
CON_INFO - Static variable in interface weka.knowledgeflow.StepManager
CON_INSTANCE - Static variable in interface weka.knowledgeflow.StepManager
CON_JOB_FAILURE - Static variable in interface weka.knowledgeflow.StepManager
CON_JOB_SUCCESS - Static variable in interface weka.knowledgeflow.StepManager
CON_TESTSET - Static variable in interface weka.knowledgeflow.StepManager
CON_TEXT - Static variable in interface weka.knowledgeflow.StepManager
CON_THRESHOLD_DATA - Static variable in interface weka.knowledgeflow.StepManager
CON_TRAININGSET - Static variable in interface weka.knowledgeflow.StepManager
CON_VISUALIZABLE_ERROR - Static variable in interface weka.knowledgeflow.StepManager
Con1 - Class in weka.core.pmml.jaxbbindings: Java class for Con element declaration.
Con1() - Constructor for class weka.core.pmml.jaxbbindings.Con1
cond() - Method in class weka.core.matrix.Matrix: Matrix condition (2 norm)
cond() - Method in class weka.core.matrix.SingularValueDecomposition: Two norm condition number
ConditionalDensityEstimator - Interface in weka.classifiers: Interface for numeric prediction schemes that can output conditional density estimates.
ConditionalEstimator - Interface in weka.estimators: Interface for conditional probability estimators.
ConditionalSufficientStats - Class in weka.classifiers.trees.ht: Records sufficient stats for an attribute
ConditionalSufficientStats() - Constructor for class weka.classifiers.trees.ht.ConditionalSufficientStats
conditionForBranch(String) - Method in class weka.classifiers.trees.ht.Split: Returns the condition for the supplied branch name
conditionForBranch(String) - Method in class weka.classifiers.trees.ht.UnivariateNominalMultiwaySplit
conditionForBranch(String) - Method in class weka.classifiers.trees.ht.UnivariateNumericBinarySplit
CONFERENCE - Enum constant in enum class weka.core.TechnicalInformation.Type: The same as inproceedings.
CONFIDENCE - Enum constant in enum class weka.associations.DefaultAssociationRule.METRIC_TYPE
CONFIDENCE - Enum constant in enum class weka.core.pmml.jaxbbindings.RULEFEATURE
confidenceFactorTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
confidenceFactorTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
confidenceForRule(AprioriItemSet, AprioriItemSet) - Static method in class weka.associations.AprioriItemSet: Outputs the confidence for a rule.
CONFIG - Static variable in class weka.core.Debug: the log level Vonfig
ConfigurationEvent - Class in weka.gui.beans: Matching event for ConfigurationListener.
ConfigurationEvent(Object) - Constructor for class weka.gui.beans.ConfigurationEvent
ConfigurationListener - Interface in weka.gui.beans: Matching listener for ConfigurationEvent.
ConfigurationProducer - Interface in weka.gui.beans: Marker interface for components that can share their configuration.
configureRangeFromRangeStringOrAttributeNameList(Instances, String) - Static method in class weka.core.Utils: Returns a configured Range object given a 1-based range index string (such as 1-20,35,last) or a comma-separated list of attribute names.
confusionMatrix() - Method in class weka.classifiers.Evaluation: Returns a copy of the confusion matrix.
confusionMatrix() - Method in class weka.classifiers.evaluation.Evaluation: Returns a copy of the confusion matrix.
ConfusionMatrix - Class in weka.classifiers.evaluation: Cells of this matrix correspond to counts of the number (or weight) of predictions for each actual value / predicted value combination.
ConfusionMatrix - Class in weka.core.pmml.jaxbbindings: Java class for ConfusionMatrix element declaration.
ConfusionMatrix() - Constructor for class weka.core.pmml.jaxbbindings.ConfusionMatrix
ConfusionMatrix(String[]) - Constructor for class weka.classifiers.evaluation.ConfusionMatrix: Creates the confusion matrix with the given class names.
ConjugateGradientOptimization - Class in weka.core: This subclass of Optimization.java implements conjugate gradient descent rather than BFGS updates, by overriding findArgmin(), with the same tests for convergence, and applies the same line search code.
ConjugateGradientOptimization() - Constructor for class weka.core.ConjugateGradientOptimization: Constructor that sets MAXITS to 2000 by default and the parameter in the second weak Wolfe condition to 0.1.
connect(NeuralConnection, NeuralConnection) - Static method in class weka.classifiers.functions.neural.NeuralConnection: Connects two units together.
CONNECT - Static variable in class weka.gui.sql.event.ConnectionEvent: it was a connect try
CONNECTED - Static variable in class weka.classifiers.functions.neural.NeuralConnection: This flag is set once the unit has a connection.
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractDataSink: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractEvaluator: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Appender: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Associator: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in interface weka.gui.beans.BeanCommon: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ClassAssigner: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Classifier: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ClassValuePicker: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Clusterer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.CostBenefitAnalysis: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.DataVisualizer: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Filter: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.FlowByExpression
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ImageSaver
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ImageViewer
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Join: Returns true if the named connection can be made at this time
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Loader: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor.
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.MetaBean: Returns true if, at this time, the object will accept a connection with respect to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ModelPerformanceChart: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.PredictionAppender: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.SerializedModelSaver: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor.
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Sorter: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.StripChart: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.SubstringLabeler: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.SubstringReplacer: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.TextSaver
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.TextViewer: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractDataSink: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.AbstractEvaluator: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.Appender: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.Associator: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(String) - Method in interface weka.gui.beans.BeanCommon: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.ClassAssigner: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.Classifier: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(String) - Method in class weka.gui.beans.ClassValuePicker: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.Clusterer: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(String) - Method in class weka.gui.beans.CostBenefitAnalysis: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.DataVisualizer: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.Filter: Returns true if, at this time, the object will accept a connection with respect to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.FlowByExpression
connectionAllowed(String) - Method in class weka.gui.beans.ImageSaver
connectionAllowed(String) - Method in class weka.gui.beans.ImageViewer
connectionAllowed(String) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(String) - Method in class weka.gui.beans.Join: Returns true if the named connection can be made at this time
connectionAllowed(String) - Method in class weka.gui.beans.Loader: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.MetaBean
connectionAllowed(String) - Method in class weka.gui.beans.ModelPerformanceChart: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.PredictionAppender: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.SerializedModelSaver: Returns true if, at this time, the object will accept a connection according to the supplied event name.
connectionAllowed(String) - Method in class weka.gui.beans.Sorter: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.StripChart: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.SubstringLabeler: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.SubstringReplacer: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.TextSaver
connectionAllowed(String) - Method in class weka.gui.beans.TextViewer: Returns true if, at this time, the object will accept a connection via the named event
connectionChange(ConnectionEvent) - Method in interface weka.gui.sql.event.ConnectionListener: This method gets called when the connection is either established or disconnected.
connectionChange(ConnectionEvent) - Method in class weka.gui.sql.QueryPanel: This method gets called when the connection is either established or disconnected.
connectionChange(ConnectionEvent) - Method in class weka.gui.sql.SqlViewer: This method gets called when the connection is either established or disconnected.
ConnectionEvent - Class in weka.gui.sql.event: An event that is generated when a connection is established or dropped.
ConnectionEvent(Object, int, DbUtils) - Constructor for class weka.gui.sql.event.ConnectionEvent: constructs the event
ConnectionEvent(Object, int, DbUtils, Exception) - Constructor for class weka.gui.sql.event.ConnectionEvent: constructs the event
ConnectionListener - Interface in weka.gui.sql.event: A listener for connect/disconnect events.
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractDataSink: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractEvaluator: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTestSetProducer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Appender: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.Associator: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in interface weka.gui.beans.BeanCommon: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.ClassAssigner: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Classifier: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in class weka.gui.beans.ClassValuePicker: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Clusterer: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in interface weka.gui.beans.ConnectionNotificationConsumer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name.
connectionNotification(String, Object) - Method in class weka.gui.beans.CostBenefitAnalysis: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.CrossValidationFoldMaker: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.DataVisualizer: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.Filter: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.FlowByExpression
connectionNotification(String, Object) - Method in class weka.gui.beans.ImageSaver
connectionNotification(String, Object) - Method in class weka.gui.beans.ImageViewer
connectionNotification(String, Object) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in class weka.gui.beans.Join: Deals with a new connection
connectionNotification(String, Object) - Method in class weka.gui.beans.Loader: Notify this object that it has been registered as a listener with a source for receiving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.MetaBean: Notify this object that it has been registered as a listener with a source with respect to the named event.
connectionNotification(String, Object) - Method in class weka.gui.beans.ModelPerformanceChart: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.PredictionAppender: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.SerializedModelSaver: Notify this object that it has been registered as a listener with a source with respect to the supplied event name.
connectionNotification(String, Object) - Method in class weka.gui.beans.Sorter: Notify this object that it has been registered as a listener with a source for receiving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.StripChart: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.SubstringLabeler: Notify this object that it has been registered as a listener with a source for receiving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.SubstringReplacer: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.TextSaver
connectionNotification(String, Object) - Method in class weka.gui.beans.TextViewer: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.TrainTestSplitMaker: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
ConnectionNotificationConsumer - Interface in weka.gui.beans: Interface for Beans that can receive (dis-)connection events generated when (dis-)connecting data processing nodes in the Weka KnowledgeFlow.
ConnectionPanel - Class in weka.gui.sql: Enables the user to insert a database URL, plus user/password to connect to this database.
ConnectionPanel(JFrame) - Constructor for class weka.gui.sql.ConnectionPanel: initializes the panel.
CONNECTIONS - Static variable in class weka.knowledgeflow.JSONFlowUtils
connectSteps(StepManagerImpl, StepManagerImpl, String) - Method in class weka.gui.knowledgeflow.VisibleLayout: Connect the supplied source step to the supplied target step using the specified connection type
connectSteps(StepManagerImpl, StepManagerImpl, String) - Method in class weka.knowledgeflow.Flow: Connect the supplied source and target steps using the given connectionType.
connectSteps(StepManagerImpl, StepManagerImpl, String, boolean) - Method in class weka.knowledgeflow.Flow: Connect the supplied source and target steps using the given connectionType.
connectToDatabase() - Method in class weka.core.converters.DatabaseLoader: Opens a connection to the database
connectToDatabase() - Method in class weka.core.converters.DatabaseSaver: Opens a connection to the database.
connectToDatabase() - Method in class weka.experiment.DatabaseUtils: Opens a connection to the database.
CONSEQUENT - Enum constant in enum class weka.core.pmml.jaxbbindings.RULEFEATURE
ConsequentSequence - Class in weka.core.pmml.jaxbbindings: Java class for ConsequentSequence element declaration.
ConsequentSequence() - Constructor for class weka.core.pmml.jaxbbindings.ConsequentSequence
conservativeForwardSelectionTipText() - Method in class weka.attributeSelection.GreedyStepwise: Returns the tip text for this property
ConsoleLogger - Class in weka.core.logging: A simple logger that outputs the logging information in the console.
ConsoleLogger() - Constructor for class weka.core.logging.ConsoleLogger
CONST - Static variable in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Constant for Gaussian density.
CONST - Static variable in class weka.estimators.UnivariateKernelEstimator: Constant for Gaussian density.
CONST - Static variable in class weka.estimators.UnivariateNormalEstimator: Constant for Gaussian density
CONST_AUTOMATIC_SHAPE - Static variable in class weka.gui.visualize.Plot2D
Constant - Class in weka.core.pmml: Class encapsulating a Constant Expression.
Constant - Class in weka.core.pmml.jaxbbindings: Java class for Constant element declaration.
Constant() - Constructor for class weka.core.pmml.jaxbbindings.Constant
Constant(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.Constant: Construct an new Constant Expression.
CONSTANT - Static variable in class weka.classifiers.lazy.LWL
Constraints - Class in weka.core.pmml.jaxbbindings: Java class for Constraints element declaration.
Constraints() - Constructor for class weka.core.pmml.jaxbbindings.Constraints
constructMappedInstance(Instance) - Method in class weka.classifiers.misc.InputMappedClassifier
constructWithCopy(double[][]) - Static method in class weka.core.matrix.Matrix: Construct a matrix from a copy of a 2-D array.
containChildBallsTipText() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns the tip text for this property.
containedBy(Instance) - Method in class weka.associations.ItemSet: Checks if an instance contains an item set.
containedByTreatZeroAsMissing(Instance) - Method in class weka.associations.ItemSet: Checks if an instance contains an item set.
contains(double) - Method in class weka.core.pmml.Array: Returns true if the array contains this real value.
contains(float) - Method in class weka.core.pmml.Array: Returns true if the array contains this real value.
contains(int) - Method in class weka.classifiers.bayes.net.ParentSet: test if node is contained in parent set
contains(int) - Method in class weka.classifiers.functions.supportVector.SMOset: Checks whether an element is in the set.
contains(int) - Method in class weka.core.pmml.Array: Returns true if the array contains this integer value.
contains(PrintStream) - Method in class weka.core.Tee: checks whether the given PrintStream is already in the list.
contains(Class<?>) - Method in class weka.core.xml.MethodHandler: checks whether a method is stored for the given class
contains(Object) - Method in class weka.core.Trie: Returns true if this collection contains the specified element.
contains(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Tests whether the specified object is a component in this list.
contains(String) - Method in class weka.core.pmml.Array: Returns true if the array contains this string value.
contains(String) - Method in class weka.core.Trie.TrieNode: checks whether a suffix can be found in its children
contains(String) - Method in class weka.core.xml.MethodHandler: checks whether a method is stored for the given property
contains(String) - Method in class weka.gui.HierarchyPropertyParser: Whether the HierarchyPropertyParser contains the given string
CONTAINS - Enum constant in enum class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause.ExpressionType
containsAll(Collection<?>) - Method in class weka.core.Trie: Returns true if this collection contains all of the elements in the specified collection.
containsEnvVariables(String) - Static method in class weka.core.Environment: Tests for the presence of environment variables.
containsItems(ArrayList<Item>, boolean) - Method in class weka.associations.AssociationRule
containsKey(double) - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Tests if the specified double is a key in this hashtable.
containsKey(double) - Method in class weka.classifiers.lazy.kstar.KStarCache: Checks if the specified key maps with an entry in the cache table
containsPrefix(String) - Method in class weka.core.Trie: checks whether the given prefix is stored in the trie
containsValue(double) - Method in class weka.core.pmml.FieldMetaInfo.Interval: Returns true if this interval contains the supplied value.
containsWindow(Class<?>) - Method in class weka.gui.Main: checks, whether an instance of the given window class is already in the Window list.
containsWindow(String) - Method in class weka.gui.Main: checks, whether a window with the given title is already in the Window list.
CONTENTS - Enum constant in enum class weka.core.TechnicalInformation.Field: A Table of Contents.
context() - Method in class weka.gui.HierarchyPropertyParser: The context of the current node, i.e.
ContingencyTables - Class in weka.core: Class implementing some statistical routines for contingency tables.
ContingencyTables() - Constructor for class weka.core.ContingencyTables
CONTINUOUS - Enum constant in enum class weka.core.pmml.FieldMetaInfo.Optype
CONTINUOUS - Enum constant in enum class weka.core.pmml.jaxbbindings.OPTYPE
CONTINUOUS - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: cluster subtype: continuous
CONTSCORINGMETHOD - Enum Class in weka.core.pmml.jaxbbindings: Java class for CONT-SCORING-METHOD.
ContStats - Class in weka.core.pmml.jaxbbindings: Java class for ContStats element declaration.
ContStats() - Constructor for class weka.core.pmml.jaxbbindings.ContStats
ConverterFileChooser - Class in weka.gui: A specialized JFileChooser that lists all available file Loaders and Savers.
ConverterFileChooser() - Constructor for class weka.gui.ConverterFileChooser: onstructs a FileChooser pointing to the user's default directory.
ConverterFileChooser(File) - Constructor for class weka.gui.ConverterFileChooser: Constructs a FileChooser using the given File as the path.
ConverterFileChooser(String) - Constructor for class weka.gui.ConverterFileChooser: Constructs a FileChooser using the given path.
ConverterResources - Class in weka.core.converters: Helper class for dealing with Converter resources.
ConverterResources() - Constructor for class weka.core.converters.ConverterResources
ConverterUtils - Class in weka.core.converters: Utility routines for the converter package.
ConverterUtils() - Constructor for class weka.core.converters.ConverterUtils
ConverterUtils.DataSink - Class in weka.core.converters: Helper class for saving data to files.
ConverterUtils.DataSource - Class in weka.core.converters: Helper class for loading data from files and URLs.
convertInstance(Instance) - Method in interface weka.attributeSelection.AttributeTransformer: Transforms an instance in the format of the original data to the transformed space
convertInstance(Instance) - Method in class weka.attributeSelection.PrincipalComponents: Transform an instance in original (unormalized) format.
convertNewLines(String) - Static method in class weka.core.Utils: Converts carriage returns and new lines in a string into \r and \n.
convertNominalTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
convertNumericAttToNominal(int, ArrayList<String>) - Method in class weka.core.pmml.MiningSchema: Convert a numeric attribute in the mining schema to nominal.
convertStringAttsToNominal() - Method in class weka.core.pmml.MiningSchema: Method to convert any string attributes in the mining schema Instances to nominal attributes.
convertToAttribX(double) - Method in class weka.gui.visualize.Plot2D: convert a Panel x coordinate to a raw x value.
convertToAttribY(double) - Method in class weka.gui.visualize.Plot2D: convert a Panel y coordinate to a raw y value.
convertToPanelX(double) - Method in class weka.gui.visualize.Plot2D: Convert an raw x value to Panel x coordinate.
convertToPanelY(double) - Method in class weka.gui.visualize.Plot2D: Convert an raw y value to Panel y coordinate.
convertToRelativePath(File) - Static method in class weka.core.Utils: Converts a File's absolute path to a path relative to the user (ie start) directory.
CONVICTION - Enum constant in enum class weka.associations.DefaultAssociationRule.METRIC_TYPE
convictionForRule(AprioriItemSet, AprioriItemSet, int, int) - Method in class weka.associations.AprioriItemSet: Outputs the conviction for a rule.
COORDINATES - Static variable in class weka.knowledgeflow.JSONFlowUtils
copy() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Return a shallow copy of this kernel
copy() - Method in class weka.classifiers.rules.JRip.Antd: Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.NominalAntd: Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.NumericAntd: Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.RipperRule: Get a shallow copy of this rule
copy() - Method in class weka.classifiers.rules.Rule: Get a shallow copy of this rule
copy() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Makes a copy of this CorrelationSplitInfo object
copy() - Method in interface weka.classifiers.trees.m5.SplitEvaluate: makes a copy of the SplitEvaluate object
copy() - Method in class weka.classifiers.trees.m5.YongSplitInfo: Makes a copy of this SplitInfo object
copy() - Method in class weka.core.Attribute: Produces a shallow copy of this attribute.
copy() - Method in class weka.core.BinarySparseInstance: Produces a shallow copy of this instance.
copy() - Method in interface weka.core.Copyable: This method produces a shallow copy of an object.
copy() - Method in class weka.core.DenseInstance: Produces a shallow copy of this instance.
copy() - Method in class weka.core.FastVector: Deprecated.

Produces a shallow copy of this vector.
copy() - Method in class weka.core.matrix.DoubleVector: Makes a deep copy of the vector
copy() - Method in class weka.core.matrix.IntVector: Makes a deep copy of the vector
copy() - Method in class weka.core.matrix.Matrix: Make a deep copy of a matrix
copy() - Method in class weka.core.SparseInstance: Produces a shallow copy of this instance.
copy(double[]) - Method in class weka.core.BinarySparseInstance: Copies the instance but fills up its values based on the given array of doubles.
copy(double[]) - Method in class weka.core.DenseInstance: Copies the instance but fills up its values based on the given array of doubles.
copy(double[]) - Method in interface weka.core.Instance: Copies the instance but fills up its values based on the given array of doubles.
copy(double[]) - Method in class weka.core.SparseInstance: Copies the instance but fills up its values based on the given array of doubles.
copy(File, File) - Static method in class weka.gui.scripting.ScriptUtils: Copies the file/directory (recursively).
copy(String) - Method in class weka.core.Attribute: Produces a shallow copy of this attribute with a new name.
copy(ParentSet) - Method in class weka.classifiers.bayes.net.ParentSet: Copy makes current parents set equal to other parent set
Copy - Class in weka.filters.unsupervised.attribute: An instance filter that copies a range of attributes in the dataset.
Copy() - Constructor for class weka.filters.unsupervised.attribute.Copy
COPY_BUTTON - Enum constant in enum class weka.gui.knowledgeflow.MainKFPerspectiveToolBar.Widgets
Copyable - Interface in weka.core: Interface implemented by classes that can produce "shallow" copies of their objects.
copyArea(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
copyContent() - Method in class weka.gui.arffviewer.ArffPanel: copies the content of the selection to the clipboard
copyContent() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: copies the content of the selection to the clipboard
copyElements() - Method in class weka.core.FastVector: Deprecated.

Clones the vector and shallow copies all its elements.
copyFlow() - Method in class weka.knowledgeflow.Flow: Make a copy of this Flow
copyFlowToClipboard(Flow) - Method in class weka.gui.knowledgeflow.MainKFPerspective
copyInto(Object[]) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Copies the components of this list into the specified array.
copyRelationalValues(Instance, boolean, Instances, AttributeLocator, Instances, AttributeLocator) - Static method in class weka.core.RelationalLocator: Takes relational values referenced by an Instance and copies them from a source dataset to a destination dataset.
copyRelationalValues(Instance, Instances, AttributeLocator) - Static method in class weka.core.RelationalLocator: Copies relational values contained in the instance copied to a new dataset.
Copyright - Class in weka.core: A class for providing centralized Copyright information.
Copyright() - Constructor for class weka.core.Copyright
COPYRIGHT - Enum constant in enum class weka.core.TechnicalInformation.Field: Copyright information.
copyStepsToClipboard(List<StepVisual>) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Copy the supplied steps to the clipboard
copyStringValues(Instance, boolean, Instances, AttributeLocator, Instances, AttributeLocator) - Static method in class weka.core.StringLocator: Takes string values referenced by an Instance and copies them from a source dataset to a destination dataset.
copyStringValues(Instance, Instances, AttributeLocator) - Static method in class weka.core.StringLocator: Copies string values contained in the instance copied to a new dataset.
copyToBuffer(Vector<Object>) - Method in class weka.gui.beans.KnowledgeFlowApp: Utility routine that serializes the supplied Vector of BeanInstances to XML
copyToClipboard() - Method in class weka.gui.sql.InfoPanel: copies the currently selected error message to the clipboard
CORE_FILE_LOADERS - Static variable in class weka.core.converters.ConverterResources: the core loaders - hardcoded list necessary for RMI/Remote Experiments (comma-separated list).
CORE_FILE_SAVERS - Static variable in class weka.core.converters.ConverterResources: the core savers - hardcoded list necessary for RMI/Remote Experiments (comma-separated list).
correct() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Gets the number of correct classifications (that is, for which a correct prediction was made).
correct() - Method in class weka.classifiers.Evaluation: Gets the number of instances correctly classified (that is, for which a correct prediction was made).
correct() - Method in class weka.classifiers.evaluation.Evaluation: Gets the number of instances correctly classified (that is, for which a correct prediction was made).
correlation - Variable in class weka.experiment.PairedStats: The correlation coefficient
correlation(double[], double[], int) - Static method in class weka.core.Utils: Returns the correlation coefficient of two double vectors.
CorrelationAttributeEval - Class in weka.attributeSelection: CorrelationAttributeEval :

Evaluates the worth of an attribute by measuring the correlation (Pearson's) between it and the class.

Nominal attributes are considered on a value by value basis by treating each value as an indicator.
CorrelationAttributeEval() - Constructor for class weka.attributeSelection.CorrelationAttributeEval
correlationCoefficient() - Method in class weka.classifiers.Evaluation: Returns the correlation coefficient if the class is numeric.
correlationCoefficient() - Method in class weka.classifiers.evaluation.Evaluation: Returns the correlation coefficient if the class is numeric.
CorrelationFields - Class in weka.core.pmml.jaxbbindings: Java class for CorrelationFields element declaration.
CorrelationFields() - Constructor for class weka.core.pmml.jaxbbindings.CorrelationFields
CorrelationMethods - Class in weka.core.pmml.jaxbbindings: Java class for CorrelationMethods element declaration.
CorrelationMethods() - Constructor for class weka.core.pmml.jaxbbindings.CorrelationMethods
Correlations - Class in weka.core.pmml.jaxbbindings: Java class for Correlations element declaration.
Correlations() - Constructor for class weka.core.pmml.jaxbbindings.Correlations
CorrelationSplitInfo - Class in weka.classifiers.trees.m5: Finds split points using correlation.
CorrelationSplitInfo(int, int, int) - Constructor for class weka.classifiers.trees.m5.CorrelationSplitInfo: Constructs an object which contains the split information
CorrelationValues - Class in weka.core.pmml.jaxbbindings: Java class for CorrelationValues element declaration.
CorrelationValues() - Constructor for class weka.core.pmml.jaxbbindings.CorrelationValues
COSINE - Enum constant in enum class weka.core.pmml.jaxbbindings.ACTIVATIONFUNCTION
CostBenefitAnalysis - Class in weka.gui.beans: Bean that aids in analyzing cost/benefit tradeoffs.
CostBenefitAnalysis - Class in weka.knowledgeflow.steps: Step for storing and viewing threshold data in a cost-benefit visualization
CostBenefitAnalysis() - Constructor for class weka.gui.beans.CostBenefitAnalysis: Constructor.
CostBenefitAnalysis() - Constructor for class weka.knowledgeflow.steps.CostBenefitAnalysis
CostBenefitAnalysisBeanInfo - Class in weka.gui.beans: Bean info class for the cost/benefit analysis
CostBenefitAnalysisBeanInfo() - Constructor for class weka.gui.beans.CostBenefitAnalysisBeanInfo
CostBenefitAnalysisInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive view for the CostBenefitAnalysis step
CostBenefitAnalysisInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.CostBenefitAnalysisInteractiveView
CostBenefitAnalysisPanel - Class in weka.gui: Panel for displaying the cost-benefit plots and all control widgets.
CostBenefitAnalysisPanel() - Constructor for class weka.gui.CostBenefitAnalysisPanel
CostCurve - Class in weka.classifiers.evaluation: Generates points illustrating probablity cost tradeoffs that can be obtained by varying the threshold value between classes.
CostCurve() - Constructor for class weka.classifiers.evaluation.CostCurve
CostMatrix - Class in weka.classifiers: Class for storing and manipulating a misclassification cost matrix.
CostMatrix(int) - Constructor for class weka.classifiers.CostMatrix: Creates a default cost matrix of a particular size.
CostMatrix(Reader) - Constructor for class weka.classifiers.CostMatrix: Reads a matrix from a reader.
CostMatrix(CostMatrix) - Constructor for class weka.classifiers.CostMatrix: Creates a cost matrix that is a copy of another.
CostMatrixEditor - Class in weka.gui: Class for editing CostMatrix objects.
CostMatrixEditor() - Constructor for class weka.gui.CostMatrixEditor: Constructs a new CostMatrixEditor.
costMatrixSourceTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
costMatrixTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
CostSensitiveClassifier - Class in weka.classifiers.meta: A metaclassifier that makes its base classifier cost sensitive.
CostSensitiveClassifier() - Constructor for class weka.classifiers.meta.CostSensitiveClassifier: Default constructor.
CostSensitiveClassifierSplitEvaluator - Class in weka.experiment: SplitEvaluator that produces results for a classification scheme on a nominal class attribute, including weighted misclassification costs.
CostSensitiveClassifierSplitEvaluator() - Constructor for class weka.experiment.CostSensitiveClassifierSplitEvaluator
count - Variable in class weka.experiment.PairedStats: The number of data points seen
count - Variable in class weka.experiment.Stats: The number of values seen
Count(double) - Constructor for class weka.classifiers.functions.SGDText.Count
countData() - Method in class weka.classifiers.rules.RuleStats: Filter the data according to the ruleset and compute the basic stats: coverage/uncoverage, true/false positive/negatives of each rule
countData(int, Instances, double[][]) - Method in class weka.classifiers.rules.RuleStats: Count data from the position index in the ruleset assuming that given data are not covered by the rules in position 0...(index-1), and the statistics of these rules are provided.
This procedure is typically useful when a temporary object of RuleStats is constructed in order to efficiently calculate the relative DL of rule in position index, thus all other stuff is not needed.
counter() - Method in class weka.associations.ItemSet: Gets the counter
Counts - Class in weka.core.pmml.jaxbbindings: Java class for Counts element declaration.
Counts() - Constructor for class weka.core.pmml.jaxbbindings.Counts
countsForInstance(Instance) - Method in class weka.classifiers.bayes.BayesNet: Calculates the counts for Dirichlet distribution for the class membership probabilities for the given test instance.
COUNTTABLETYPE - Class in weka.core.pmml.jaxbbindings: Java class for COUNT-TABLE-TYPE complex type.
COUNTTABLETYPE() - Constructor for class weka.core.pmml.jaxbbindings.COUNTTABLETYPE
countWidthTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
Covariances - Class in weka.core.pmml.jaxbbindings: Java class for Covariances element declaration.
Covariances() - Constructor for class weka.core.pmml.jaxbbindings.Covariances
CovariateList - Class in weka.core.pmml.jaxbbindings: Java class for CovariateList element declaration.
CovariateList() - Constructor for class weka.core.pmml.jaxbbindings.CovariateList
coverageOfTestCasesByPredictedRegions() - Method in class weka.classifiers.Evaluation: Gets the coverage of the test cases by the predicted regions at the confidence level specified when evaluation was performed.
coverageOfTestCasesByPredictedRegions() - Method in class weka.classifiers.evaluation.Evaluation: Gets the coverage of the test cases by the predicted regions at the confidence level specified when evaluation was performed.
covers(Instance) - Method in class weka.classifiers.rules.JRip.Antd
covers(Instance) - Method in class weka.classifiers.rules.JRip.NominalAntd: Whether the instance is covered by this antecedent
covers(Instance) - Method in class weka.classifiers.rules.JRip.NumericAntd: Whether the instance is covered by this antecedent
covers(Instance) - Method in class weka.classifiers.rules.JRip.RipperRule: Whether the instance covered by this rule
covers(Instance) - Method in class weka.classifiers.rules.Rule: Whether the instance covered by this rule
CoverTree - Class in weka.core.neighboursearch: Class implementing the CoverTree datastructure.
The class is very much a translation of the c source code made available by the authors.

For more information and original source code see:

Alina Beygelzimer, Sham Kakade, John Langford: Cover trees for nearest neighbor.
CoverTree() - Constructor for class weka.core.neighboursearch.CoverTree: default constructor.
CoverTree.CoverTreeNode - Class in weka.core.neighboursearch: class representing a node of the cover tree.
CoverTreeNode() - Constructor for class weka.core.neighboursearch.CoverTree.CoverTreeNode: Constructor for the class.
CoverTreeNode(Integer, double, double, Stack<CoverTree.CoverTreeNode>, int, int) - Constructor for class weka.core.neighboursearch.CoverTree.CoverTreeNode: Constructor.
CramersV(double[][]) - Static method in class weka.core.ContingencyTables: Computes Cramer's V for a contingency table.
create() - Static method in class weka.core.packageManagement.PackageManager
create() - Method in class weka.gui.visualize.PostscriptGraphics: Clone a PostscriptGraphics object
create(Reader) - Method in class weka.gui.treevisualizer.TreeBuild: This will build A node structure from the dotty format passed.
create(List<Object>, List<Integer>) - Static method in class weka.core.pmml.Array
create(Element) - Static method in class weka.core.pmml.Array: Static factory method for creating non-sparse or sparse array types as needed.
createAggregate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Aggregate
createAlternate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Alternate
createAnnotation() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Annotation
createAnova() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Anova
createAnovaRow() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AnovaRow
createAntecedentSequence() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AntecedentSequence
createAnyDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AnyDistribution
createApplication() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Application
createApply() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Apply
createARIMA(Object) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<Object>}
createArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<ArrayType>}
createArrayType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ArrayType
createAssociationModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AssociationModel
createAssociationRule() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AssociationRule
createAttribute() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Attribute
createBaseCumHazardTables() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaseCumHazardTables
createBaseline() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Baseline
createBaselineCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaselineCell
createBaselineModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaselineModel
createBaselineStratum() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaselineStratum
createBayesInput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BayesInput
createBayesInputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BayesInputs
createBayesOutput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BayesOutput
createBinarySimilarity() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BinarySimilarity
createBoundaryValueMeans() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BoundaryValueMeans
createBoundaryValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BoundaryValues
createCategoricalPredictor() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CategoricalPredictor
createCategories() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Categories
createCategory() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Category
createCharacteristic() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Characteristic
createCharacteristics() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Characteristics
createChebychev() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Chebychev
createChildParent() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ChildParent
createCityBlock() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CityBlock
createClassLabels() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClassLabels
createCluster() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Cluster
createClusteringField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClusteringField
createClusteringModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClusteringModel
createClusteringModelQuality() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClusteringModelQuality
createCoefficient() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Coefficient
createCoefficients() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Coefficients
createComparisonMeasure() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ComparisonMeasure
createComparisons() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Comparisons
createCompoundPredicate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CompoundPredicate
createCompoundRule() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CompoundRule
createCon() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Con1
createConfusionMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ConfusionMatrix
createConsequentSequence() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ConsequentSequence
createConstant() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Constant
createConstraints() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Constraints
createContStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ContStats
createCorrelationFields() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CorrelationFields
createCorrelationMethods() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CorrelationMethods
createCorrelations() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Correlations
createCorrelationValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CorrelationValues
createCounts() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Counts
createCountTable(COUNTTABLETYPE) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<COUNTTABLETYPE>}
createCOUNTTABLETYPE() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of COUNTTABLETYPE
createCovariances() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Covariances
createCovariateList() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CovariateList
createDataDictionary() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DataDictionary
createDataField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DataField
createDecision() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Decision
createDecisions() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Decisions
createDecisionTree() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DecisionTree
createDefineFunction() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DefineFunction
createDelimiter() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Delimiter
createDerivedField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DerivedField
createDiscretize() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Discretize
createDiscretizeBin() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DiscretizeBin
createDiscrStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DiscrStats
createDocumentTermMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DocumentTermMatrix
createEuclidean() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Euclidean
createEventValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of EventValues
createExperimentIndex() - Method in class weka.experiment.DatabaseUtils: Attempts to create the experiment index table.
createExperimentIndexEntry(ResultProducer) - Method in class weka.experiment.DatabaseUtils: Attempts to insert a results entry for the table into the experiment index.
createExponentialSmoothing() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ExponentialSmoothing
createExtension() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Extension
createFactorList() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FactorList
createFalse() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of False
createFieldColumnPair() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldColumnPair
createFieldRef() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldRef
createFieldValue() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldValue
createFieldValueCount() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldValueCount
createGaussianDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of GaussianDistribution
createGeneralRegressionModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of GeneralRegressionModel
createHeader() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Header
createIndices(List<Integer>) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<List<Integer>>}
createInlineTable() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of InlineTable
createInstanceField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of InstanceField
createInstanceFields() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of InstanceFields
createINTEntries(List<Integer>) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<List<Integer>>}
createInterval() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Interval
createINTSparseArray() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of INTSparseArray
createItem() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Item
createItemRef() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ItemRef
createItemset() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Itemset
createJaccard() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Jaccard
createKNNInput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of KNNInput
createKNNInputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of KNNInputs
createKohonenMap() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of KohonenMap
createLevel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Level
createLiftData() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LiftData
createLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LiftGraph
createLinearKernelType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LinearKernelType
createLinearNorm() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LinearNorm
createLink(String, String) - Static method in class weka.gui.BrowserHelper: Generates a label with a clickable link.
createLocalTransformations() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LocalTransformations
createMapValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MapValues
createMatCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MatCell
createMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Matrix
createMiningBuildTask() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningBuildTask
createMiningField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningField
createMiningModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningModel
createMiningSchema() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningSchema
createMinkowski() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Minkowski
createMissingValueWeights() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MissingValueWeights
createModelExplanation() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelExplanation
createModelLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelLiftGraph
createModelStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelStats
createModelVerification() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelVerification
createMultivariateStat() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MultivariateStat
createMultivariateStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MultivariateStats
createNaiveBayesModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NaiveBayesModel
createNamedIndexedStore(String) - Method in class weka.knowledgeflow.steps.PairedDataHelper: Create a indexed store with a given name
createNearestNeighborModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NearestNeighborModel
createNeuralInput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralInput
createNeuralInputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralInputs
createNeuralLayer() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralLayer
createNeuralNetwork() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralNetwork
createNeuralOutput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralOutput
createNeuralOutputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralOutputs
createNeuron() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Neuron
createNewVisualizerWindow(Classifier, Instances) - Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Creates a new GUI window with all of the BoundaryVisualizer trappings,
createNode() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Node
createNormalizedCountTable(COUNTTABLETYPE) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<COUNTTABLETYPE>}
createNormContinuous() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NormContinuous
createNormDiscrete() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NormDiscrete
createNumericInfo() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NumericInfo
createNumericPredictor() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NumericPredictor
createOptimumLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of OptimumLiftGraph
createOutput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Output
createOutputField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of OutputField
createPairCounts() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PairCounts
createParameter() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Parameter
createParameterField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ParameterField
createParameterList() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ParameterList
createParamMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ParamMatrix
createPartition() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Partition
createPartitionFieldStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PartitionFieldStats
createPCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PCell
createPCovCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PCovCell
createPCovMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PCovMatrix
createPMML() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PMML
createPoissonDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PoissonDistribution
createPolynomialKernelType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PolynomialKernelType
createPPCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PPCell
createPPMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PPMatrix
createPredictiveModelQuality() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PredictiveModelQuality
createPredictor() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Predictor
createPredictorTerm() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PredictorTerm
createQuantile() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Quantile
createRadialBasisKernelType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RadialBasisKernelType
createRandomLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RandomLiftGraph
createREALEntries(List<Double>) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<List<Double>>}
createREALSparseArray() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of REALSparseArray
createRegression() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Regression
createRegressionModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RegressionModel
createRegressionTable() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RegressionTable
createResultField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ResultField
createResultsTable(ResultProducer, String) - Method in class weka.experiment.DatabaseUtils: Creates a results table for the supplied result producer.
createROC() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ROC
createROCGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ROCGraph
createRow() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Row
createRuleSelectionMethod() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RuleSelectionMethod
createRuleSet() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RuleSet
createRuleSetModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RuleSetModel
createScorecard() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Scorecard
createScoreDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ScoreDistribution
createSeasonalityExpoSmooth() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SeasonalityExpoSmooth
createSeasonalTrendDecomposition(Object) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<Object>}
createSegment() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Segment
createSegmentation() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Segmentation
createSequence() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Sequence
createSequenceModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SequenceModel
createSequenceReference() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SequenceReference
createSequenceRule() - Method in class weka.core.pmml.jaxbbindings.