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

A

abortExperiment() - Method in class weka.experiment.RemoteExperiment

Set the abort flag

ABS - Static variable in interface weka.core.mathematicalexpression.sym

ABS - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

AbstractAssociator - Class in weka.associations

Abstract scheme for learning associations.

AbstractAssociator() - Constructor for class weka.associations.AbstractAssociator

AbstractClusterer - Class in weka.clusterers

Abstract clusterer.

AbstractClusterer() - Constructor for class weka.clusterers.AbstractClusterer

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

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

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

AbstractLoader - Class in weka.core.converters

Abstract class gives default implementation of setSource methods.

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

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.

AbstractSaver - Class in weka.core.converters

Abstract class for Saver

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

AbstractStringDistanceFunction - Class in weka.core

Represents the abstract ancestor for string-based distance functions, like EditDistance.

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

Constructor that doesn't set the data

AbstractStringDistanceFunction(Instances) - Constructor for class weka.core.AbstractStringDistanceFunction

Constructor that sets the data

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.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERFileFilter

Whether the given file is accepted by this filter.

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.

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(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(BatchClassifierEvent) - Method in class weka.gui.beans.PredictionAppender

Accept and process a batch classifier event

acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.SerializedModelSaver

Accept and save an incrementally trained classifier.

acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.SerializedModelSaver

Accept and save a batch 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(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

acceptDataPoint(double[]) - Method in class weka.gui.beans.StripChart

Accept a data point 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.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(ThresholdDataEvent) - Method in class weka.gui.beans.ModelPerformanceChart

Display a threshold curve.

acceptDataSet(VisualizableErrorEvent) - Method in class weka.gui.beans.ModelPerformanceChart

Display a scheme error plot.

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.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(ThresholdDataEvent) - Method in interface weka.gui.beans.ThresholdDataListener

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(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

acceptInstance(InstanceEvent) - Method in class weka.gui.beans.AbstractDataSink

Accept an instance

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 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.Saver

Methods reacts to instance events and saves instances incrementally.

acceptInstance(InstanceEvent) - Method in class weka.gui.beans.StripChart

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.

acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.AbstractDataSink

Accept a test set

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.Saver

Method reacts to a test set event and starts the writing process in batch mode

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.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.TextViewer

Accept some text

acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.AbstractDataSink

Accept a training set

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.Saver

Method reacts to a training set event and starts the writing process in batch mode

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

accuracy() - Method in class weka.associations.RuleItem

Gets the expected predictive accuracy of a rule

ACCURACY - Static variable in class weka.classifiers.meta.ThresholdSelector

accuracy

actEntropy - Variable in class weka.classifiers.lazy.kstar.KStarWrapper

used/reused to hold the actual entropy

action_table() - Method in class weka.core.mathematicalexpression.Parser

Access to parse-action table.

action_table() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.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.ensembleLibraryEditor.AddModelsPanel

This will support the button triggered events for this panel.

actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.DefaultModelsPanel

Deals with user input to the various buttons in this GUI

actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.ListModelsPanel

This handles all of the button events.

actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.LoadModelsPanel

This will support the button triggered events for this panel.

actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.tree.GenericObjectNodeEditor

This implements the action listener for the buttons in this editor, If they hit the choose class button then the popup menu for choosing the generic object ype is created.

actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.tree.ModelTreeNodeEditor

The item Listener that gets registered with all node editors that have a widget that had actionPerformed events.

actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.tree.NumberNodeEditor

This is the actionListener that while handle events from the JButton that specifies the type of iterator.

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.

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(Object) - Method in class weka.associations.tertius.SimpleLinkedList

add(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution

Adds given instance to given bag.

add(int, double[]) - Method in class weka.classifiers.trees.j48.Distribution

Adds counts to given bag.

add(double, Object) - Method in class weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueue

Adds a new Object to the queue

add(double, Object, String) - Method in class weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueue

Adds a new Object to the queue

add(AlgVector) - Method in class weka.core.AlgVector

Returns the sum of this vector with another.

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(String) - Method in class weka.core.Stopwords

adds the given word to the stopword list (is automatically converted to lower case and trimmed)

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(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(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) - Method in class weka.core.xml.MethodHandler

adds the specified method for the property with the given displayname to its internal list.

add(Class, Method) - Method in class weka.core.xml.MethodHandler

adds the specified method for the given class to its internal list.

add(double, double) - Method in class weka.experiment.PairedStats

Add an observed pair of values.

add(double[], double[]) - Method in class weka.experiment.PairedStats

Adds an array of observed pair of values.

add(double) - Method in class weka.experiment.Stats

Adds a value to the observed values

add(double, double) - Method in class weka.experiment.Stats

Adds a value that has been seen n times to the observed values

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(int, Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Inserts the specified element at the specified position in this list.

add(Object) - Method in class weka.gui.ensembleLibraryEditor.ModelList.SortedListModel

add(String) - Method in class weka.gui.HierarchyPropertyParser

Add the given item of property to the tree

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(SimpleLinkedList) - Method in class weka.associations.tertius.SimpleLinkedList

addAll(Collection) - Method in class weka.core.neighboursearch.covertrees.Stack

Adds all the given elements in the stack.

addAll(Collection<? extends String>) - Method in class weka.core.Trie

Adds all of the elements in the specified collection to this collection

addAll(Object[]) - Method in class weka.gui.ensembleLibraryEditor.ModelList.SortedListModel

addAllBeansToContainer(JComponent) - 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.

addAndUpdate(Rule) - Method in class weka.classifiers.rules.RuleStats

Add a rule to the ruleset and update the stats

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(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, FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet

Add arc between parent node and each of the nodes in a given list.

addAttributePanelListener(AttributePanelListener) - Method in class weka.gui.visualize.AttributePanel

Add a listener to the list of things listening to this panel

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) - Method in class weka.gui.beans.BeanInstance

Adds this bean to the global list of beans and to the supplied container.

addBefore(Object) - Method in class weka.associations.tertius.SimpleLinkedList.LinkedListIterator

addCancelListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel

This is used to hook an action listener to the cancel button.

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(Splitter, ADTree) - Method in class weka.classifiers.trees.adtree.PredictionNode

Adds a child to this node.

addChild(Edge) - Method in class weka.gui.treevisualizer.Node

Set the value of children.

addChildClique(MarginCalculator.JunctionTreeNode) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode

addChildFrame(Container) - Method in class weka.gui.GUIChooser

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.

addCons(int[]) - Method in class weka.associations.PriorEstimation

generates a class association rule out of a given premise.

addCVParameter(String) - Method in class weka.classifiers.meta.CVParameterSelection

Adds a scheme parameter to the list of parameters to be set by cross-validation

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.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.InstanceStreamToBatchMaker

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

addEditorNodes(String, String) - Method in class weka.gui.ensembleLibraryEditor.tree.PropertyNode

This method figures out what kind of parameter type this node represents and then creates the appropriate set of child nodes for editing.

addElement(Literal) - Method in class weka.associations.tertius.LiteralSet

Add a Literal to this set.

addElement(Object) - Method in class weka.core.FastVector

Adds an element to this vector.

addElement(int, int, double) - Method in class weka.core.Matrix

Deprecated. Add a value to an element.

addElement(double) - Method in class weka.core.matrix.DoubleVector

Adds an element into the vector

addElement(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel

Adds the specified component to the end of this list.

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).

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(String) - Static method in class weka.core.ClassloaderUtil

Add file to CLASSPATH

addFile(File) - Static method in class weka.core.ClassloaderUtil

Add file to CLASSPATH

addFirst(Object) - Method in class weka.associations.tertius.SimpleLinkedList

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(String) - Method in class weka.core.xml.PropertyHandler

adds the given display name of a property to the ignore list.

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.

addIncrementalClassifierListener(IncrementalClassifierListener) - Method in class weka.gui.beans.Classifier

Add an incremental classifier listener

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.

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.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.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.InstanceStreamToBatchMaker

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.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,

AddInstanceToBestCluster(Instance) - Method in class weka.clusterers.CLOPE

Add instance to best cluster

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.

addLiteral(Literal) - Method in class weka.associations.tertius.Predicate

addModel(EnsembleLibraryModel) - Method in class weka.classifiers.EnsembleLibrary

adds a LibraryModel to the Library

addModel(String) - Method in class weka.classifiers.EnsembleLibrary

adds a LibraryModel to the Library

addModel(EnsembleLibraryModel) - Method in class weka.gui.ensembleLibraryEditor.ListModelsPanel

Adds a model to the current library

AddModelsPanel - Class in weka.gui.ensembleLibraryEditor

The purpose of this class is to create a user interface that will provide an intuitive method of building "playlists" of weka classifiers to be trained.

AddModelsPanel(ListModelsPanel) - Constructor for class weka.gui.ensembleLibraryEditor.AddModelsPanel

This constructor simply stores the reference to the ListModelsPanel and builf the user interface.

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

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 - Class in weka.filters.unsupervised.attribute

An instance filter that changes a percentage of a given attributes values.

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

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.

addNumbers(Number, Number) - Method in class weka.gui.ensembleLibraryEditor.tree.NumberNode

adds two objects that are instances of one of the child classes of java.lang.Number

addObject(String, Object) - Method in class weka.gui.ResultHistoryPanel

Adds an object to the results list

addOkListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel

This is used to hook an action listener to the ok button.

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)

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)

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

addPrediction(NominalPrediction) - Method in class weka.classifiers.evaluation.ConfusionMatrix

Includes a prediction in the confusion matrix.

addPredictions(FastVector) - Method in class weka.classifiers.evaluation.ConfusionMatrix

Includes a whole bunch of predictions in the confusion matrix.

addPropertyChangeListener(PropertyChangeListener) - Method in class weka.classifiers.EnsembleLibrary

Adds an object to the list of those that wish to be informed when the library changes.

addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.AbstractDataSource

Add a property change listener to this bean

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.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(String, PropertyChangeListener) - Method in class weka.gui.beans.DataVisualizer

Add a property change listener to this bean

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(String, PropertyChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart

Add a property change listener to this bean

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(String, PropertyChangeListener) - Method in class weka.gui.beans.TextViewer

Add a property change listener to this bean

addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer

Add a property change listener

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.EnsembleLibraryEditor

Adds an object to the list of those that wish to be informed when the library 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.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.

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.

addReference(Instance) - Method in class weka.classifiers.trees.adtree.ReferenceInstances

Adds one instance reference to the end of the set.

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.

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.

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.

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.

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.

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.

addToList(Object[], double) - Method in class weka.attributeSelection.BestFirst.LinkedList2

adds an element (Link) to the list.

addToList(Object[], double) - Method in class weka.attributeSelection.LFSMethods.LinkedList2

adds an element (Link) to the list.

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.

addURL(URL) - Static method in class weka.core.ClassloaderUtil

Add URL to CLASSPATH

addValue(double, double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes

Add a new data value to the current 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) - Method in class weka.estimators.DiscreteEstimator

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) - 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, double) - Method in class weka.estimators.KDConditionalEstimator

Add a new data 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, double) - Method in class weka.estimators.KKConditionalEstimator

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, 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(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.

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 instance of one class.

addValues(Instances, int, int, int, double, double) - Method in class weka.estimators.Estimator

Initialize the estimator using only the instance 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.

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.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.

addWorkingDirectoryListener(PropertyChangeListener) - Method in class weka.classifiers.meta.ensembleSelection.EnsembleSelectionLibrary

Adds an object to the list of those that wish to be informed when the eotking directory changes.

adjustCenter(double) - Method in class weka.gui.treevisualizer.Node

Will increase or decrease the postion of center.

adjustSize(SERObject) - Method in class weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel

Adjusts the size of this panel in respect of the shown content

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

ADTree - Class in weka.classifiers.trees

Class for generating an alternating decision tree.

ADTree() - Constructor for class weka.classifiers.trees.ADTree

advanceCounters() - Method in class weka.experiment.Experiment

Increments iteration counters appropriately.

advanceCounters() - Method in class weka.experiment.RemoteExperiment

overides the one in Experiment

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

ALGORITHM_BACKWARD - Static variable in class weka.classifiers.meta.EnsembleSelection

ALGORITHM_BEST - Static variable in class weka.classifiers.meta.EnsembleSelection

ALGORITHM_BUILD_LIBRARY - Static variable in class weka.classifiers.meta.EnsembleSelection

ALGORITHM_FORWARD - Static variable in class weka.classifiers.meta.EnsembleSelection

The "enumeration" of the algorithms we can use.

ALGORITHM_FORWARD_BACKWARD - Static variable in class weka.classifiers.meta.EnsembleSelection

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

the type of algorithm: Haar wavelet

ALGORITHM_PLS1 - Static variable in class weka.filters.supervised.attribute.PLSFilter

the type of algorithm: PLS1

ALGORITHM_SIMPLS - Static variable in class weka.filters.supervised.attribute.PLSFilter

the type of algorithm: SIMPLS

AlgorithmListPanel - Class in weka.gui.experiment

This panel controls setting a list of algorithms for an experiment to iterate over.

AlgorithmListPanel(Experiment) - Constructor for class weka.gui.experiment.AlgorithmListPanel

Creates the algorithm list panel with the given experiment.

AlgorithmListPanel() - Constructor for class weka.gui.experiment.AlgorithmListPanel

Create the algorithm list panel initially disabled.

AlgorithmListPanel.ObjectCellRenderer - Class in weka.gui.experiment

Class required to show the Classifiers nicely in the list

AlgorithmListPanel.ObjectCellRenderer() - Constructor for class weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer

algorithmTipText() - Method in class weka.classifiers.meta.EnsembleSelection

Returns the tip text for this property

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

Returns the tip text for this property

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

Returns the tip text for this property

ALGORITHMTYPE_ARITHMETIC - Static variable in class weka.classifiers.mi.MILR

collective MI assumption, arithmetic mean for posteriors

ALGORITHMTYPE_DEFAULT - Static variable in class weka.classifiers.mi.MILR

standard MI assumption

ALGORITHMTYPE_GEOMETRIC - Static variable in class weka.classifiers.mi.MILR

collective MI assumption, geometric mean for posteriors

algorithmTypeTipText() - Method in class weka.classifiers.mi.MILR

Returns the tip text for this property

AlgVector - Class in weka.core

Class for performing operations on an algebraic vector of floating-point values.

AlgVector(int) - Constructor for class weka.core.AlgVector

Constructs a vector and initializes it with default values.

AlgVector(double[]) - Constructor for class weka.core.AlgVector

Constructs a vector using a given array.

AlgVector(Instances, Random) - Constructor for class weka.core.AlgVector

Constructs a vector using a given data format.

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

Constructs a vector using an instance.

alignBottom(FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet

align set of nodes with the bottom most node in the list

alignLeft(FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet

align set of nodes with the left most node in the list

alignRight(FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet

align set of nodes with the right most node in the list

alignTop(FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet

align set of nodes with the top most node in the list

ALL - Static variable in class weka.core.Debug

the log level All

AllFilter - Class in weka.filters

A simple instance filter that passes all instances directly through.

AllFilter() - Constructor for class weka.filters.AllFilter

AllJavadoc - Class in weka.core

Applies all known Javadoc-derived classes to a source file.

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

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

alphaTipText() - Method in class weka.classifiers.functions.Winnow

Returns the tip text for this property

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

and(Capabilities) - Method in class weka.core.Capabilities

performs an AND conjunction with the capabilities of the given Capabilities object and updates itself

AND - Static variable in interface weka.core.mathematicalexpression.sym

AND - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

AODE - Class in weka.classifiers.bayes

AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes.

AODE() - Constructor for class weka.classifiers.bayes.AODE

AODEsr - Class in weka.classifiers.bayes

AODEsr augments AODE with Subsumption Resolution.AODEsr detects specializations between two attribute values at classification time and deletes the generalization attribute value.
For more information, see:
Fei Zheng, Geoffrey I.

AODEsr() - Constructor for class weka.classifiers.bayes.AODEsr

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)

append(Object) - Method in class weka.gui.sql.InfoPanel

adds the given message to the end of the list

appendElements(FastVector) - Method in class weka.core.FastVector

Appends all elements of the supplied vector to this vector.

appendPredictedProbabilitiesTipText() - Method in class weka.gui.beans.PredictionAppender

Return a tip text suitable for displaying in a GUI

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.

applyFileSizeFilters() - Method in class weka.gui.ensembleLibraryEditor.DefaultModelsPanel

Removes models from the list that fit the regular expressions defining models that have large file sizes

applyFilters(Pattern[]) - Method in class weka.gui.ensembleLibraryEditor.DefaultModelsPanel

This is the code common to the previous three methods.

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.

applyTestTimeFilters() - Method in class weka.gui.ensembleLibraryEditor.DefaultModelsPanel

Removes models from the list that fit the regular expressions defining models that have large test times

applyTrainTimeFilters() - Method in class weka.gui.ensembleLibraryEditor.DefaultModelsPanel

Removes models from the list that fit the regular expressions defining models that have large train times

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.

aprioriGen(FastVector) - Static method in class weka.associations.gsp.Sequence

Generates all possible candidate k-Sequences and prunes the ones that contain an infrequent (k-1)-Sequence.

AprioriItemSet - Class in weka.associations

Class for storing a set of items.

AprioriItemSet(int) - Constructor for class weka.associations.AprioriItemSet

Constructor

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.

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.

ArffLoader.ArffReader(Reader) - Constructor for class weka.core.converters.ArffLoader.ArffReader

Reads the data completely from the reader.

ArffLoader.ArffReader(Reader, int) - Constructor for class weka.core.converters.ArffLoader.ArffReader

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

ArffLoader.ArffReader(Reader, Instances, int) - Constructor for class weka.core.converters.ArffLoader.ArffReader

Reads the data without header according to the specified template.

ArffLoader.ArffReader(Reader, Instances, int, int) - Constructor for class weka.core.converters.ArffLoader.ArffReader

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

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) - 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

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) - 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(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

ArffSortedTableModel(TableModel) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel

initializes the sorter with the given model

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) - 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

Array - Class in weka.core.pmml

Class for encapsulating a PMML Array element.

Array.ArrayType - Enum 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.

artificialSizeTipText() - Method in class weka.classifiers.meta.Decorate

Returns the tip text for this property

ASEvaluation - Class in weka.attributeSelection

Abstract attribute selection evaluation class

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

ASSearch - Class in weka.attributeSelection

Abstract attribute selection search class.

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

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(Tester) - Method in class weka.experiment.PairedTTester

retrieves all the settings from the given Tester

assign(ResultMatrix) - Method in class weka.experiment.ResultMatrix

acquires the data from the given matrix.

assign(Tester) - Method in interface weka.experiment.Tester

retrieves all the settings from the given Tester

assignIDs(int) - Method in class weka.classifiers.trees.ft.FTtree

Assigns unique IDs to all nodes in the tree

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.ft.FTtree

Assigns numbers to the logistic regression models at the leaves of 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) - Static method in class weka.gui.beans.BeanConnection

Returns a vector of BeanConnections associated with the supplied vector of BeanInstances, i.e.

associationAttributeClasses(double[][]) - Method in class weka.attributeSelection.SignificanceAttributeEval

evaluates an individual attribute by measuring the attribute-classes association

associationClassesAttribute(double[][]) - Method in class weka.attributeSelection.SignificanceAttributeEval

evaluates an individual attribute by measuring the classes-attribute association

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 - Interface in weka.associations

Associator - Class in weka.gui.beans

Bean that wraps around weka.associations

Associator() - Constructor for class weka.gui.beans.Associator

Creates a new Associator instance.

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

aSubsumesB(RuleItem, RuleItem) - Static method in class weka.associations.CaRuleGeneration

Methods that decides whether or not rule a subsumes rule b.

aSubsumesB(RuleItem, RuleItem) - Static method in class weka.associations.RuleGeneration

Methods that decides whether or not rule a subsumes rule b.

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

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() - Method in class weka.classifiers.trees.j48.GraftSplit

Attribute - Class in weka.core

Class for handling an attribute.

Attribute(String) - Constructor for class weka.core.Attribute

Constructor for a numeric attribute.

Attribute(String, ProtectedProperties) - Constructor for class weka.core.Attribute

Constructor for a numeric attribute, where metadata is supplied.

Attribute(String, String) - Constructor for class weka.core.Attribute

Constructor for a date attribute.

Attribute(String, String, ProtectedProperties) - Constructor for class weka.core.Attribute

Constructor for a date attribute, where metadata is supplied.

Attribute(String, FastVector) - Constructor for class weka.core.Attribute

Constructor for nominal attributes and string attributes.

Attribute(String, FastVector, 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, ProtectedProperties) - Constructor for class weka.core.Attribute

Constructor for relation-valued attributes.

Attribute(String, int) - Constructor for class weka.core.Attribute

Constructor for a numeric attribute with a particular index.

Attribute(String, String, int) - Constructor for class weka.core.Attribute

Constructor for date attributes with a particular index.

Attribute(String, FastVector, int) - Constructor for class weka.core.Attribute

Constructor for nominal attributes and string attributes with a particular index.

Attribute(String, Instances, int) - Constructor for class weka.core.Attribute

Constructor for a relation-valued attribute with a particular index.

attribute(int) - Method in class 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 - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

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.

AttributeEvaluator - Interface in weka.attributeSelection

Interface for classes that evaluate attributes individually.

attributeEvaluatorTipText() - Method in class weka.attributeSelection.FilteredAttributeEval

Returns the tip text for this property

attributeEvaluatorTipText() - Method in class weka.attributeSelection.RaceSearch

Returns the tip text for this property

attributeEvaluatorTipText() - Method in class weka.attributeSelection.RankSearch

Returns the tip text for this property

AttributeExpression - Class in weka.core

A general purpose class for parsing mathematical expressions involving attribute values.

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

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.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.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.unsupervised.attribute.AbstractTimeSeries

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.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.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.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.RELAGGS

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.Reorder

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.

attributeList(BitSet) - Method in class weka.attributeSelection.ScatterSearchV1

converts a BitSet into a list of attribute indexes

attributeList(BitSet) - Method in class weka.attributeSelection.TabuSearch

converts a BitSet into a list of attribute indexes

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, 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.

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.

attributeNames() - Method in class weka.classifiers.mi.MISMO

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

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() - Constructor for class weka.attributeSelection.AttributeSelection

constructor.

AttributeSelection - Class in weka.filters.supervised.attribute

A supervised attribute filter that can be used to select attributes.

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() - Constructor for class weka.gui.AttributeSelectionPanel

Creates the attribute selection panel with no initial instances.

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.explorer.AttributeSelectionPanel

Creates the classifier panel

AttributeSetEvaluator - Class in weka.attributeSelection

Abstract attribute set evaluator.

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

attributeSparse(int) - Method in class weka.core.Instance

Returns the attribute with the given index.

attributeSparse(int) - Method in class weka.core.SparseInstance

Returns the attribute associated with the internal index.

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

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.

attributesTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput

Returns the tip text for this property.

attributesToString() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition

Make a string from the attribues list.

attributeString(Instances) - Method in class weka.classifiers.trees.adtree.Splitter

Gets the string describing the attributes the split depends on.

attributeString(Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit

Gets the string describing the attributes the split depends on.

attributeString(Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit

Gets the string describing the attributes the split depends on.

AttributeSummarizer - Class in weka.gui.beans

Bean that encapsulates displays bar graph summaries for attributes in a data set.

AttributeSummarizer() - Constructor for class weka.gui.beans.AttributeSummarizer

Creates a new AttributeSummarizer instance.

AttributeSummarizerBeanInfo - Class in weka.gui.beans

Bean info class for the attribute summarizer bean

AttributeSummarizerBeanInfo() - Constructor for class weka.gui.beans.AttributeSummarizerBeanInfo

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.

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

AttributeValueLiteral - Class in weka.associations.tertius

AttributeValueLiteral(Predicate, String, int, int, int) - Constructor for class weka.associations.tertius.AttributeValueLiteral

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

attsToEliminatePerIterationTipText() - Method in class weka.attributeSelection.SVMAttributeEval

Returns a tip text for this property suitable for display in the GUI

autoBuildTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron

autoKeyGenerationTipText() - Method in class weka.core.converters.DatabaseSaver

Returns the tip text for this property.

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.

avgProb - Variable in class weka.classifiers.lazy.kstar.KStarWrapper

used/reused to hold the average transformation probability

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

backfitData(Instances) - Method in class weka.classifiers.trees.RandomTree

Backfits the given data into the tree.

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.

backward(PaceMatrix, IntVector, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix

Backward ordering of columns in terms of response explanation.

backwardEliminate(Instances, int) - Method in class weka.classifiers.meta.ensembleSelection.ModelBag

Find the model whose removal will help the ensemble's performance the most, and remove it.

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

bagSizePercentTipText() - Method in class weka.classifiers.meta.MetaCost

Returns the tip text for this property

balanceClassTipText() - Method in class weka.datagenerators.classifiers.classification.Agrawal

Returns the tip text for this property

balancedTipText() - Method in class weka.classifiers.functions.Winnow

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.

baseTipText() - Method in class weka.core.neighboursearch.CoverTree

Returns the tip text for this property.

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

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.filters.Filter

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.instance.Resample

Signify that this batch of input to the filter is finished.

batchFinished() - Method in class weka.filters.supervised.instance.SMOTE

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.MultiInstanceToPropositional

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.PropositionalToMultiInstance

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

BAYES - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable

score types

BayesianLogisticRegression - Class in weka.classifiers.bayes

Implements Bayesian Logistic Regression for both Gaussian and Laplace Priors.

For more information, see

Alexander Genkin, David D.

BayesianLogisticRegression() - Constructor for class weka.classifiers.bayes.BayesianLogisticRegression

BayesNet - Class in weka.classifiers.bayes

Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.

BayesNet() - Constructor for class weka.classifiers.bayes.BayesNet

BayesNet - Static variable in interface weka.core.Drawable

BayesNet - Class in weka.datagenerators.classifiers.classification

Generates random instances based on a Bayes network.

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.

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) - Constructor for class weka.gui.beans.BeanConnection

Creates a new BeanConnection instance.

BeanInstance - Class in weka.gui.beans

Class that manages a set of beans.

BeanInstance(JComponent, Object, int, int) - Constructor for class weka.gui.beans.BeanInstance

Creates a new BeanInstance instance.

BeanInstance(JComponent, String, int, int) - Constructor for class weka.gui.beans.BeanInstance

Creates a new BeanInstance instance given the fully qualified name of the bean

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.Link2(Object[], double) - Constructor for class weka.attributeSelection.BestFirst.Link2

Constructor

BestFirst.LinkedList2 - Class in weka.attributeSelection

Class for handling a linked list.

BestFirst.LinkedList2(int) - Constructor for class weka.attributeSelection.BestFirst.LinkedList2

betaTipText() - Method in class weka.classifiers.functions.Winnow

Returns the tip text for this property

BetaVector - Variable in class weka.classifiers.bayes.BayesianLogisticRegression

Array for storing coefficients of Bayesian regression model.

BFTree - Class in weka.classifiers.trees

Class for building a best-first decision tree classifier.

BFTree() - Constructor for class weka.classifiers.trees.BFTree

bias() - Method in class weka.classifiers.functions.SMO

Returns the bias of each binary SMO.

bias() - Method in class weka.classifiers.mi.MISMO

Returns the bias of each binary SMO.

biasTipText() - Method in class weka.classifiers.functions.LibLINEAR

Returns the tip text for this property

biasTipText() - Method in class weka.classifiers.misc.VFI

Returns the tip text for this property

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(String, FastVector, FastVector) - Constructor for class weka.gui.graphvisualizer.BIFParser

Constructor (if our input is a String)

BIFParser(InputStream, FastVector, FastVector) - Constructor for class weka.gui.graphvisualizer.BIFParser

Constructor (if our input is an InputStream)

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

bigF(double, double) - Static method in class weka.classifiers.bayes.BayesianLogisticRegression

This is a convient function that defines and upper bound (Delta>0) for values of r(i) reachable by updates in the trust region.

binarizeNumericAttributesTipText() - Method in class weka.attributeSelection.ChiSquaredAttributeEval

Returns the tip text for this property

binarizeNumericAttributesTipText() - Method in class weka.attributeSelection.InfoGainAttributeEval

Returns the tip text for this property

BINARY - Static variable in class weka.gui.beans.SerializedModelSaver

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

BinarySparseInstance - Class in weka.core

Class for storing a binary-data-only instance as a sparse vector.

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.

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.

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

binarySplitsTipText() - Method in class weka.classifiers.trees.J48graft

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

binaryWordTipText() - Method in class weka.classifiers.bayes.DMNBtext

Returns the tip text for this property

BinC45ModelSelection - Class in weka.classifiers.trees.j48

Class for selecting a C4.5-like binary (!) split for a given dataset.

BinC45ModelSelection(int, Instances) - 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) - Constructor for class weka.classifiers.trees.j48.BinC45Split

Initializes the split model.

binomialDistribution(double, double, double) - Static method in class weka.associations.RuleGeneration

calculates the probability using a binomial distribution.

binomialStandardError(double, int) - Static method in class weka.core.Statistics

Computes standard error for observed values of a binomial random variable.

binomP(double, double, double) - Method in class weka.classifiers.lazy.LBR

Significance test binomp:

binSplitTipText() - Method in class weka.classifiers.trees.FT

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

binValueTipText() - Method in class weka.clusterers.XMeans

Returns the tip text for this property.

biprob(double, double, double) - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTreeG

Significance test

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

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.

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

Body - Class in weka.associations.tertius

Class representing the body of a rule.

Body() - Constructor for class weka.associations.tertius.Body

Constructor without storing the counter-instances.

Body(Instances) - Constructor for class weka.associations.tertius.Body

Constructor storing the counter-instances.

bodyContains(Literal) - Method in class weka.associations.tertius.Rule

Test if the body of the rule contains a literal.

BOOL - Static variable in class weka.experiment.DatabaseUtils

Type mapping for BOOL used for reading experiment results.

BOOLEAN - Static variable in interface weka.core.mathematicalexpression.sym

BOOLEAN - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

booleanColsTipText() - Method in class weka.datagenerators.ClusterGenerator

Returns the tip text for this property

boost() - Method in class weka.classifiers.trees.ADTree

Performs a single boosting iteration, using two-class optimized method.

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.

BoundaryVisualizer - Class in weka.gui.boundaryvisualizer

BoundaryVisualizer.

BoundaryVisualizer() - Constructor for class weka.gui.boundaryvisualizer.BoundaryVisualizer

Creates a new BoundaryVisualizer instance.

boundsFileTipText() - Method in class weka.classifiers.misc.FLR

Returns the tip text for this property

branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.Splitter

Gets the index of the branch that an instance applies to.

branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit

Gets the index of the branch that an instance applies to.

branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit

Gets the index of the branch that an instance applies to.

BrowserHelper - Class in weka.gui

A little helper class for browser related stuff.

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

bubbleSubsetSort(List<ScatterSearchV1.Subset>) - Method in class weka.attributeSelection.ScatterSearchV1

Sort a List of subsets according to their merits

bubbleSubsetSort(List<TabuSearch.Subset>) - Method in class weka.attributeSelection.TabuSearch

Sort a List of subsets according to their merits

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.GeneralizedSequentialPatterns

Extracts all sequential patterns out of a given sequential data set and prints out the results.

buildAssociations(Instances) - Method in class weka.associations.HotSpot

Build the tree

buildAssociations(Instances) - Method in class weka.associations.PredictiveApriori

Method that generates all large itemsets with a minimum support, and from these all association rules.

buildAssociations(Instances) - Method in class weka.associations.Tertius

Method that launches the search to find the rules with the highest confirmation.

buildClassifier(Instances) - Method in class weka.classifiers.bayes.AODE

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.bayes.AODEsr

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.bayes.BayesianLogisticRegression

(1) Set the data to the class attribute m_Instances. (2)Call the method initialize() to initialize the values.

buildClassifier(Instances) - Method in class weka.classifiers.bayes.BayesNet

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.bayes.ComplementNaiveBayes

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.bayes.DMNBtext

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.bayes.HNB

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.NaiveBayesMultinomialUpdateable

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesSimple

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.bayes.WAODE

Generates the classifier.

buildClassifier(Instances) - Method in class 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.IsotonicRegression

Builds an isotonic regression model given the supplied training data.

buildClassifier(Instances) - Method in class weka.classifiers.functions.LeastMedSq

Build lms regression

buildClassifier(Instances) - Method in class weka.classifiers.functions.LibLINEAR

builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.functions.LibSVM

builds 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.PaceRegression

Builds a pace regression model for the given data.

buildClassifier(Instances) - Method in class weka.classifiers.functions.PLSClassifier

builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.functions.RBFNetwork

Builds 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.functions.Winnow

Builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer

Stump method for building the classifiers.

buildClassifier(Instances) - Method in class weka.classifiers.lazy.IB1

Generates the classifier.

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.LBR

For lazy learning, building classifier is only to prepare their inputs until classification time.

buildClassifier(Instances) - Method in class weka.classifiers.lazy.LWL

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.AdaBoostM1

Boosting method.

buildClassifier(Instances) - Method in class weka.classifiers.meta.AdditiveRegression

Build the classifier on the supplied data

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.ClassificationViaClustering

builds the classifier

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.Dagging

Bagging method.

buildClassifier(Instances) - Method in class weka.classifiers.meta.Decorate

Build Decorate classifier

buildClassifier(Instances) - Method in class weka.classifiers.meta.END

Builds the committee of randomizable classifiers.

buildClassifier(Instances) - Method in class weka.classifiers.meta.EnsembleSelection

Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.

buildClassifier(Instances) - Method in class weka.classifiers.meta.FilteredClassifier

Build the classifier on the filtered data.

buildClassifier(Instances) - Method in class weka.classifiers.meta.GridSearch

builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.meta.LogitBoost

Builds the boosted classifier

buildClassifier(Instances) - Method in class weka.classifiers.meta.MetaCost

Builds the model of the base learner.

buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiBoostAB

Method for building this classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiClassClassifier

Builds the classifiers.

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.nestedDichotomies.ClassBalancedND

Builds tree recursively.

buildClassifier(Instances) - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND

Builds tree recursively.

buildClassifier(Instances) - Method in class weka.classifiers.meta.nestedDichotomies.ND

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.OrdinalClassClassifier

Builds the classifiers.

buildClassifier(Instances) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomCommittee

Builds the committee of randomizable classifiers.

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.RotationForest

builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.Stacking

Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.

buildClassifier(Instances) - Method in class weka.classifiers.meta.ThresholdSelector

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.meta.Vote

Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.

buildClassifier(Instances) - Method in class weka.classifiers.mi.CitationKNN

Builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.mi.MDD

Builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.mi.MIBoost

Builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.mi.MIDD

Builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.mi.MIEMDD

Builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.mi.MILR

Builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.mi.MINND

As normal Nearest Neighbour algorithm does, it's lazy and simply records the exemplar information (i.e.

buildClassifier(Instances) - Method in class weka.classifiers.mi.MIOptimalBall

Builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.mi.MISMO

Method for building the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.mi.MISVM

Builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.mi.MIWrapper

Builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.mi.SimpleMI

Builds the classifier

buildClassifier(Instances) - Method in class weka.classifiers.mi.TLD

buildClassifier(Instances) - Method in class weka.classifiers.mi.TLDSimple

buildClassifier(Instances) - Method in class weka.classifiers.misc.FLR

Builds the FLR Classifier

buildClassifier(Instances) - Method in class weka.classifiers.misc.HyperPipes

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.misc.SerializedClassifier

loads only the serialized classifier

buildClassifier(Instances) - Method in class weka.classifiers.misc.VFI

Generates the classifier.

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.ConjunctiveRule

Builds a single rule learner with REP dealing with nominal classes or numeric classes.

buildClassifier(Instances) - Method in class weka.classifiers.rules.DecisionTable

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.rules.DTNB

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.NNge

Generates a classifier.

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.Prism

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.rules.Ridor

Builds a ripple-down manner rule learner.

buildClassifier(Instances) - Method in class weka.classifiers.rules.ZeroR

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.scripting.GroovyClassifier

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.scripting.JythonClassifier

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.ADTree

Builds a classifier for a set of instances.

buildClassifier(Instances) - Method in class weka.classifiers.trees.BFTree

Method for building a BestFirst decision tree classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.DecisionStump

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.FT

Builds the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.ft.FTInnerNode

Method for building a Functional Inner tree (only called for the root node).

buildClassifier(Instances) - Method in class weka.classifiers.trees.ft.FTLeavesNode

Method for building a Functional Leaves tree (only called for the root node).

buildClassifier(Instances) - Method in class weka.classifiers.trees.ft.FTNode

Method for building a Functional tree (only called for the root node).

buildClassifier(Instances) - Method in class weka.classifiers.trees.ft.FTtree

Method for building a Functional Tree (only called for the root node).

buildClassifier(Instances) - Method in class weka.classifiers.trees.Id3

Builds Id3 decision tree 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.C45PruneableClassifierTreeG

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.GraftSplit

builds m_graftdistro using the passed data

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.J48graft

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.LADTree

Builds a classifier for a set of instances.

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, double[][], double[][]) - Method in class weka.classifiers.trees.lmt.ResidualSplit

Builds the split.

buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit

Method not in use

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.NBTree

Generates the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomForest

Builds a classifier for a set of instances.

buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomTree

Builds classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.REPTree

Builds classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.SimpleCart

Build the classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.UserClassifier

Call this function to build a decision tree for the training data provided.

buildClassifierForNode(ND.NDTree, Instances) - Method in class weka.classifiers.meta.nestedDichotomies.ND

Builds the classifier for one node.

buildClassifierTree(Classifier) - Method in class weka.gui.ensembleLibraryEditor.AddModelsPanel

This method necessarily seperates the process of building the tree object from the rest of the GUI construction.

buildClusterer(Instances) - Method in class weka.clusterers.AbstractClusterer

Generates a clusterer.

buildClusterer(Instances) - Method in class weka.clusterers.CLOPE

Generate Clustering via CLOPE

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.DBScan

Generate Clustering via DBScan

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.MakeDensityBasedClusterer

Builds a clusterer for a set of instances.

buildClusterer(Instances) - Method in class weka.clusterers.OPTICS

Generate Clustering via OPTICS

buildClusterer(Instances) - Method in class weka.clusterers.sIB

Generates a clusterer.

buildClusterer(Instances) - Method in class weka.clusterers.SimpleKMeans

Generates a clusterer.

buildClusterer(Instances) - Method in class weka.clusterers.XMeans

Generates the X-Means clusterer.

buildCNN() - Method in class weka.classifiers.mi.CitationKNN

generates all the variables associated to the citation classifier

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

buildDistribution(double, double) - Method in class weka.associations.PriorEstimation

updates the distribution of the confidence values.

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.ChiSquaredAttributeEval

Initializes a chi-squared attribute evaluator.

buildEvaluator(Instances) - Method in class weka.attributeSelection.ClassifierSubsetEval

Generates a attribute evaluator.

buildEvaluator(Instances) - Method in class weka.attributeSelection.ConsistencySubsetEval

Generates a attribute evaluator.

buildEvaluator(Instances) - Method in class weka.attributeSelection.CostSensitiveASEvaluation

Generates a attribute evaluator.

buildEvaluator(Instances) - Method in class weka.attributeSelection.FilteredAttributeEval

Initializes a filtered attribute evaluator.

buildEvaluator(Instances) - Method in class weka.attributeSelection.FilteredSubsetEval

Initializes a filtered 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.LatentSemanticAnalysis

Initializes the singular values/vectors and performs the analysis

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.SignificanceAttributeEval

Initializes the Significance attribute evaluator.

buildEvaluator(Instances) - Method in class weka.attributeSelection.SVMAttributeEval

Initializes the evaluator.

buildEvaluator(Instances) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Initializes a symmetrical uncertainty attribute evaluator.

buildEvaluator(Instances) - Method in class weka.attributeSelection.SymmetricalUncertAttributeSetEval

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.Puk

builds the kernel with the given data.

buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.RBFKernel

builds the kernel with the given data.

buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.StringKernel

builds the kernel with the given data.

buildKernel(Instances) - Method in class weka.classifiers.mi.supportVector.MIRBFKernel

builds the kernel with the given data.

buildLogisticModelsTipText() - Method in class weka.classifiers.functions.SMO

Returns the tip text for this property

buildLogisticModelsTipText() - Method in class weka.classifiers.mi.MISMO

Returns the tip text for this property

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(Instances, SimpleLinearRegression[][], double, double) - Method in class weka.classifiers.trees.ft.FTInnerNode

Method for building the tree structure.

buildTree(Instances, SimpleLinearRegression[][], double, double) - Method in class weka.classifiers.trees.ft.FTLeavesNode

Method for building the tree structure.

buildTree(Instances, SimpleLinearRegression[][], double, double) - Method in class weka.classifiers.trees.ft.FTNode

Method for building the tree structure.

buildTree(Instances, SimpleLinearRegression[][], double, double) - Method in class weka.classifiers.trees.ft.FTtree

Abstract method for building the tree structure.

buildTree(Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree

Builds the tree structure.

buildTree(Instances, Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree

Builds the tree structure with hold out set

buildTree(Instances, SimpleLinearRegression[][], double, double) - Method in class weka.classifiers.trees.lmt.LMTNode

Method for building the tree structure.

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.

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.

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) - 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) - Constructor for class weka.classifiers.trees.j48.C45PruneableClassifierTree

Constructor for pruneable tree structure.

C45PruneableClassifierTreeG - Class in weka.classifiers.trees.j48

Class for handling a tree structure that can be pruned using C4.5 procedures and have nodes grafted on.

C45PruneableClassifierTreeG(ModelSelection, boolean, float, boolean, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45PruneableClassifierTreeG

Constructor for pruneable tree structure.

C45PruneableClassifierTreeG(ModelSelection, Instances, ClassifierSplitModel, boolean, float, boolean, boolean, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45PruneableClassifierTreeG

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) - 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.LibSVM

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

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() - 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.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).

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).

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.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).

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).

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

calculateAlphas() - Method in class weka.classifiers.trees.lmt.LMTNode

Updates the alpha field for all nodes.

calculateAlphas() - Method in class weka.classifiers.trees.SimpleCart

Updates the alpha field for all nodes.

calculateConfirmation() - Method in class weka.associations.tertius.Rule

Calculate the confirmation of this rule.

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.

calculateDistance(Instances) - Method in class weka.classifiers.mi.MIOptimalBall

calculate the distances from each instance in a positive bag to each bag.

calculateOptimistic() - Method in class weka.associations.tertius.Rule

Calculate the optimistic estimate of this rule.

calculatePriorSum(boolean, double) - Method in class weka.associations.PriorEstimation

calculates the numerator and the denominator of the prior equation

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

calculateTreshhold() - Method in class weka.attributeSelection.ScatterSearchV1

Calculate the treshold of a dataSet given an evaluator

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

canDeselect(DefaultMutableTreeNode) - Method in class weka.gui.ensembleLibraryEditor.tree.PropertyNode

informs a requesting child node whether or not it has permission to be deselected.

canKeep(Instance, Literal) - Method in class weka.associations.tertius.Body

Test if an instance can be kept as a counter-instance, if a new literal is added to this body.

canKeep(Instance, Literal) - Method in class weka.associations.tertius.Head

Test if an instance can be kept as a counter-instance, if a new literal is added to this head.

canKeep(Instance, Literal) - Method in class weka.associations.tertius.LiteralSet

Test if an instance can be kept as a counter-instance, given a new literal.

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

canRedo() - Method in class weka.classifiers.bayes.net.EditableBayesNet

return whether there is something on the undo stack that can be performed

canSelect(NumberNode) - Method in class weka.gui.ensembleLibraryEditor.tree.PropertyNode

This method informs a child number node whether or not it is allowed to be selected.

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 - 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(CapabilitiesHandler) - Constructor for class weka.core.Capabilities

initializes the capabilities for the given owner

capabilities() - Method in class weka.core.Capabilities

Returns an Iterator over the stored capabilities

Capabilities.Capability - Enum 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

CapabilitiesHandler - Interface in weka.core

Classes implementing this interface return their capabilities in regards to datasets.

capacity() - Method in class weka.core.FastVector

Returns the capacity of the vector.

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

cardinality() - Method in class weka.attributeSelection.TabuSearch.Subset

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.

carTipText() - Method in class weka.associations.Apriori

Returns the tip text for this property

carTipText() - Method in class weka.associations.PredictiveApriori

Returns the tip text for this property

CaRuleGeneration - Class in weka.associations

Class implementing the rule generation procedure of the predictive apriori algorithm for class association rules.

CaRuleGeneration(ItemSet) - Constructor for class weka.associations.CaRuleGeneration

Constructor

CARuleMiner - Interface in weka.associations

Interface for learning class association rules.

cat(DoubleVector) - Method in class weka.core.matrix.DoubleVector

Combine two vectors together

cbind(PaceMatrix) - Method in class weka.classifiers.functions.pace.PaceMatrix

Returns a new matrix which binds two matrices with columns.

CEIL - Static variable in interface weka.core.mathematicalexpression.sym

CEIL - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym

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

centerHorizontal(FastVector) - 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(FastVector) - 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

change() - Method in class weka.associations.RuleGeneration

Gets if the list fo the best rules has been changed

Change - Variable in class weka.classifiers.bayes.BayesianLogisticRegression

This variable is used to keep track of change in the value of delta summation of r(i).

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).

CharacterDelimitedTokenizer - Class in weka.core.tokenizers

Abstract superclass for tokenizers that take characters as delimiters.

CharacterDelimitedTokenizer() - Constructor for class weka.core.tokenizers.CharacterDelimitedTokenizer

ChartEvent - Class in weka.gui.beans

Event encapsulating info for plotting a data point on the StripChart

ChartEvent(Object, Vector, double, double, double[], boolean) - Constructor for class weka.gui.beans.ChartEvent

Creates a new ChartEvent instance.

ChartEvent(Object) - Constructor for class weka.gui.beans.ChartEvent

Creates a new ChartEvent instance.

ChartListener - Interface in weka.gui.beans

Interface to something that can process a ChartEvent

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

checkBounds() - Method in class weka.classifiers.misc.FLR

Checks the metric space

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.CheckBoxListModel() - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel

initializes the model with no data.

CheckBoxList.CheckBoxListModel(Object[]) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel

Constructs a CheckBoxListModel from an array of objects and then applies setModel to it.

CheckBoxList.CheckBoxListModel(Vector) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel

Constructs a CheckBoxListModel from a Vector and then applies setModel to it.

CheckBoxList.CheckBoxListRenderer - Class in weka.gui

A specialized CellRenderer for the CheckBoxList

CheckBoxList.CheckBoxListRenderer() - Constructor for class weka.gui.CheckBoxList.CheckBoxListRenderer

CheckBoxNode - Class in weka.gui.ensembleLibraryEditor.tree

This class is responsible for implementing the underlying logic of tree nodes representing a single nominal value.

CheckBoxNode(String, boolean, String) - Constructor for class weka.gui.ensembleLibraryEditor.tree.CheckBoxNode

The constructor initializes the members of this node.

CheckBoxNodeEditor - Class in weka.gui.ensembleLibraryEditor.tree

This class is responsible for creating a simple checkBox editor for the CheckBoxNode class.

CheckBoxNodeEditor(CheckBoxNode) - Constructor for class weka.gui.ensembleLibraryEditor.tree.CheckBoxNodeEditor

The constructor builds the simple CheckBox GUI based on the information in the node that is passed to it.

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

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.EstTypes() - Constructor for class weka.estimators.CheckEstimator.EstTypes

Constructor

CheckEstimator.EstTypes(boolean, boolean, boolean) - Constructor for class weka.estimators.CheckEstimator.EstTypes

Constructor

CheckEstimator.PostProcessor - Class in weka.estimators

a class for postprocessing the test-data

CheckEstimator.PostProcessor() - Constructor for class weka.estimators.CheckEstimator.PostProcessor

checkForAttributeType(int) - Method in class weka.core.Instances

Checks for attributes of the given type in the dataset

checkForMissing(Instance, Instances) - Method in class weka.classifiers.functions.PaceRegression

Checks if an instance has a missing value.

checkForNominalAttributes(Instances) - Method in class weka.clusterers.XMeans

Checks for nominal attributes in the dataset.

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

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.

Usage:

CheckGOE -W classname -- test options

Valid options are:

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.

Usage:

CheckOptionHandler -W optionHandlerClassName -- test options

Valid options are:

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

CheckScheme.PostProcessor() - Constructor for class weka.core.CheckScheme.PostProcessor

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() - Constructor for class weka.classifiers.CheckSource

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.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.classifiers.functions.supportVector.Kernel

Returns the tip text for this property

checksTurnedOffTipText() - Method in class weka.classifiers.mi.MISMO

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.

children() - Method in class weka.classifiers.trees.adtree.PredictionNode

Enumerates the children of this node.

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

ChisqMixture - Class in weka.classifiers.functions.pace

Class for manipulating chi-square mixture distributions.

ChisqMixture() - Constructor for class weka.classifiers.functions.pace.ChisqMixture

Contructs an empty ChisqMixture

chiSquared(double[][], boolean) - Static method in class weka.core.ContingencyTables

Returns chi-squared probability for a given matrix.

ChiSquaredAttributeEval - Class in weka.attributeSelection

ChiSquaredAttributeEval :

Evaluates the worth of an attribute by computing the value of the chi-squared statistic with respect to the class.

Valid options are:

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

Constructor

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

CitationKNN - Class in weka.classifiers.mi

Modified version of the Citation kNN multi instance classifier.

For more information see:

Jun Wang, Zucker, Jean-Daniel: Solving Multiple-Instance Problem: A Lazy Learning Approach.

CitationKNN() - Constructor for class weka.classifiers.mi.CitationKNN

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

ClassAssigner - Class in weka.gui.beans

Bean that assigns a class attribute to a data set.

ClassAssigner() - Constructor for class weka.gui.beans.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

classAttribute() - Method in class 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

classAttributeNames() - Method in class weka.classifiers.mi.MISMO

Returns the names of the class attributes.

ClassBalancedND - Class in weka.classifiers.meta.nestedDichotomies

A meta classifier for handling multi-class datasets with 2-class classifiers by building a random class-balanced tree structure.

For more info, check

Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems.

ClassBalancedND() - Constructor for class weka.classifiers.meta.nestedDichotomies.ClassBalancedND

Constructor.

classColumnTipText() - Method in class weka.gui.beans.ClassAssigner

Tool tip text for this property

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.

ClassDiscovery.StringCompare() - Constructor for class weka.core.ClassDiscovery.StringCompare

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

ClassificationGenerator - Class in weka.datagenerators

Abstract class for data generators for classifiers.

ClassificationGenerator() - Constructor for class weka.datagenerators.ClassificationGenerator

initializes with default values

classificationTipText() - Method in class weka.associations.Tertius

Returns the tip text for this property.

ClassificationViaClustering - Class in weka.classifiers.meta

A simple meta-classifier that uses a clusterer for classification.

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

default constructor

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.classifiers

Abstract classifier.

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

Classifier - Class in weka.gui.beans

Bean that wraps around weka.classifiers

Classifier() - Constructor for class weka.gui.beans.Classifier

Creates a new Classifier instance.

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.

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

ClassifierPerformanceEvaluator - Class in weka.gui.beans

A bean that evaluates the performance of batch trained classifiers

ClassifierPerformanceEvaluator() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluator

ClassifierPerformanceEvaluatorBeanInfo - Class in weka.gui.beans

Bean info class for the classifier performance evaluator

ClassifierPerformanceEvaluatorBeanInfo() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo

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 seperate hold out testing set.

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

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.bayes.BayesianLogisticRegression

Classifies the given instance using the Bayesian Logistic Regression function.

classifyInstance(Instance) - Method in class weka.classifiers.bayes.ComplementNaiveBayes

Classifies a given instance.

classifyInstance(Instance) - Method in class 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.IsotonicRegression

Generate a prediction for the supplied instance.

classifyInstance(Instance) - Method in class weka.classifiers.functions.LeastMedSq

Classify a given instance using the best generated LinearRegression Classifier.

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.PaceRegression

Classifies the given instance using the linear regression function.

classifyInstance(Instance) - Method in class weka.classifiers.functions.PLSClassifier

Classifies the given test instance.

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.functions.Winnow

Outputs the prediction for the given instance.

classifyInstance(Instance) - Method in class weka.classifiers.lazy.IB1

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.AdditiveRegression

Classify an instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.ClassificationViaClustering

Classifies the given test instance.

classifyInstance(Instance) - Method in class weka.classifiers.meta.GridSearch

Classifies the given 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.mi.MINND

Use Kullback Leibler distance to find the nearest neighbours of the given exemplar.

classifyInstance(Instance) - Method in class weka.classifiers.mi.TLD

classifyInstance(Instance) - Method in class weka.classifiers.mi.TLDSimple

classifyInstance(Instance) - Method in class weka.classifiers.misc.FLR

Classifies a given instance using the FLR Classifier model

classifyInstance(Instance) - Method in class weka.classifiers.rules.NNge

Classifies a given instance.

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.Prism

Classifies a given instance.

classifyInstance(Instance) - Method in class weka.classifiers.rules.Ridor

Classify the test instance with the rule learner

classifyInstance(Instance) - Method in class weka.classifiers.rules.ZeroR

Classifies a given instance.

classifyInstance(Instance) - Method in class weka.classifiers.scripting.GroovyClassifier

Classifies a given instance.

classifyInstance(Instance) - Method in class weka.classifiers.scripting.JythonClassifier

Classifies a given instance.

classifyInstance(Instance) - Method in class weka.classifiers.trees.FT

Classifies an instance.

classifyInstance(Instance) - Method in class weka.classifiers.trees.Id3

Classifies a given test instance using the decision tree.

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.J48graft

Classifies an instance.

classifyInstance(Instance) - Method in class weka.classifiers.trees.LMT

Classifies an 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.

classifyInstance(Instance) - Method in class weka.classifiers.trees.NBTree

Classifies an instance.

ClassIndex - Variable in class weka.classifiers.bayes.BayesianLogisticRegression

The class index from the training data

classIndex() - Method in class 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.associations.PredictiveApriori

Returns the tip text for this property

classIndexTipText() - Method in class weka.associations.Tertius

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.Instance

Tests if an instance's class is missing.

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.GraftSplit

returns the probability for instance for the specified class

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.

classSgn(double) - Static method in class weka.classifiers.bayes.BayesianLogisticRegression

This class is used to mask the internal class labels.

classValue() - Method in class weka.core.Instance

Returns an instance's class value in internal format.

ClassValuePicker - Class in weka.gui.beans

ClassValuePicker() - Constructor for class weka.gui.beans.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

classValueTipText() - Method in class weka.filters.supervised.instance.SMOTE

Returns the tip text for this property.

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.PolyKernel

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 class weka.classifiers.mi.supportVector.MIPolyKernel

Frees the cache used by the kernel.

cleanse(Instance) - Method in class weka.classifiers.mi.MINND

Cleanse the given exemplar according to the valid and noise data statistics

cleanup(Instances) - Method in class weka.classifiers.rules.part.ClassifierDecList

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.classifiers.trees.ft.FTtree

Cleanup in order to save memory.

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(Instances) - Method in class weka.classifiers.trees.j48.ClassifierTree

Cleanup in order to save memory.

cleanup() - Method in class weka.classifiers.trees.j48.NBTreeModelSelection

Sets reference to training data to null.

cleanup() - Method in class weka.classifiers.trees.lmt.LMTNode

Cleanup in order to save memory.

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

clear() - Method in class weka.associations.tertius.SimpleLinkedList

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() - M