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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
 
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.
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(ThresholdDataEvent) - Method in class weka.gui.beans.AbstractDataSink
Accept a threshold 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(ThresholdDataEvent) - Method in class weka.gui.beans.CostBenefitAnalysis
Accept a threshold data event and set up the visualization.
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(ThresholdDataEvent) - Method in class weka.gui.beans.Saver
Method reacts to a threshold data event ans 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.TrainingSetMaker
 
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker
Accept a test set
acceptText(TextEvent) - Method in interface weka.gui.beans.TextListener
Accept and process a text event
acceptText(TextEvent) - Method in class weka.gui.beans.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.TestSetMaker
 
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TextViewer
Accept a training set for displaying as text
acceptTrainingSet(TrainingSetEvent) - Method in interface weka.gui.beans.TrainingSetListener
Accept and process a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker
Accept a training set
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.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(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
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.
addCapabilities(String, Capabilities) - Static method in class weka.gui.PropertySheetPanel
generates a string from the capapbilities, suitable to add to the help text.
addCapabilitiesFilterListener(Explorer.CapabilitiesFilterChangeListener) - Method in class weka.gui.explorer.Explorer
adds the listener to the list of objects that listen for changes of the CapabilitiesFilter
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffPanel
Adds a ChangeListener to the panel
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffTable
Adds a ChangeListener to the panel
addChartListener(ChartListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator
Add a chart listener
addCheckBoxActionListener(ActionListener) - Method in class weka.gui.experiment.DistributeExperimentPanel
Enable objects to listen for changes to the check box
addChild(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.
AddCluster() - Constructor for class weka.filters.unsupervised.attribute.AddCluster
 
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
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.
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
 
addMouseListener(MouseListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
Adds a mouse listener.
addMouseListenerToHeader(JTable) - Method in class weka.gui.SortedTableModel
Adds a mouselistener to the header: left-click on the header sorts in ascending manner, using shift-left-click in descending manner.
addNode(String, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Add new node to the network, initializing instances, parentsets, distributions.
addNode(String, int, int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Add node to network at a given position, initializing instances, parentsets, distributions.
addNodeValue(int, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Add node value to a node.
AddNoise - 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.
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(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.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.
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
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.CostBenefitAnalysis
 
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.DataVisualizer
Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.GraphViewer
Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart
Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.TextViewer
Add a vetoable change listener to this bean
addVisualizableErrorListener(VisualizableErrorListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
Add a visualizable error listener
addWeights(Instance, double[]) - Method in class weka.classifiers.trees.j48.Distribution
Adds given instance to all bags weighting it according to given weights.
adjustCenter(double) - Method in class weka.gui.treevisualizer.Node
Will increase or decrease the postion of center.
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_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
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
 
Antd(Attribute) - Constructor for class weka.classifiers.rules.JRip.Antd
Constructor
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.
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.
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.
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
ArffReader(Reader) - Constructor for class weka.core.converters.ArffLoader.ArffReader
Reads the data completely from the reader.
ArffReader(Reader, int) - Constructor for class weka.core.converters.ArffLoader.ArffReader
Reads only the header and reserves the specified space for instances.
ArffReader(Reader, Instances, int) - Constructor for class weka.core.converters.ArffLoader.ArffReader
Reads the data without header according to the specified template.
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.
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
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.
AssociationRule(Collection<FPGrowth.BinaryItem>, Collection<FPGrowth.BinaryItem>, FPGrowth.AssociationRule.METRIC_TYPE, int, int, int, int) - Constructor for class weka.associations.FPGrowth.AssociationRule
Construct a new association rule.
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.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.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_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.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.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.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
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(boolean, boolean, boolean, boolean) - 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.
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
BackgroundDesktopPane(String) - Constructor for class weka.gui.Main.BackgroundDesktopPane
intializes the desktop pane.
backQuoteChars(String) - Static method in class weka.core.Utils
Converts carriage returns and new lines in a string into \r and \n.
backward(PaceMatrix, IntVector, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Backward ordering of columns in terms of response explanation.
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.Loader
 
BATCH - Static variable in interface weka.core.converters.Saver
 
BATCH_FINISHED - Static variable in class weka.gui.beans.IncrementalClassifierEvent
 
BATCH_FINISHED - Static variable in class weka.gui.beans.InstanceEvent
 
BATCH_FINISHED - Static variable in class weka.gui.streams.InstanceEvent
Specifies that the batch of instances is finished
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.MultiFilter
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.SimpleBatchFilter
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.SimpleStreamFilter
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.AttributeSelection
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.ClassOrder
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.Discretize
Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.NominalToBinary
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.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.LinkedList2 - Class in weka.attributeSelection
Class for handling a linked list.
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
BinaryItem(Attribute, int) - Constructor for class weka.associations.FPGrowth.BinaryItem
 
BinarySMO() - Constructor for class weka.classifiers.functions.SMO.BinarySMO
 
BinarySparseInstance - Class in weka.core
Class for storing a binary-data-only instance as a sparse vector.
BinarySparseInstance(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
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.
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
build(String, String) - Method in class weka.gui.HierarchyPropertyParser
Build a tree from the given property with the given delimitor
buildAssociations(Instances) - Method in class weka.associations.Apriori
Method that generates all large itemsets with a minimum support, and from these all association rules with a minimum confidence.
buildAssociations(Instances) - Method in interface weka.associations.Associator
Generates an associator.
buildAssociations(Instances) - Method in class weka.associations.FilteredAssociator
Build the associator on the filtered data.
buildAssociations(Instances) - Method in class weka.associations.FPGrowth
Method that generates all large item sets with a minimum support, and from these all association rules with a minimum metric (i.e.
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.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.SPegasos
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.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.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.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.
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.HierarchicalClusterer
 
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.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.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
CacheTable(int, float) - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable
Constructs a new hashtable with a default capacity and load factor.
CacheTable() - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable
Constructs a new hashtable with a default capacity and load factor.
calcCentroidPivot(int[], Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode
Calculates the centroid pivot of a node.
calcCentroidPivot(int, int, int[], Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode
Calculates the centroid pivot of a node.
calcColumnWidth(int) - Method in class weka.gui.JTableHelper
calcs the optimal column width of the given column
calcColumnWidth(JTable, int) - Static method in class weka.gui.JTableHelper
Calculates the optimal width for the column of the given table.
calcFullMargins(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator
 
calcGraph(int, int) - Method in class weka.gui.AttributeVisualizationPanel
Recalculates the barplot or histogram to display, required usually when the attribute is changed or the component is resized.
calcHeaderWidth(int) - Method in class weka.gui.JTableHelper
calcs the optimal header width of the given column
calcHeaderWidth(JTable, int) - Static method in class weka.gui.JTableHelper
Calculates the optimal width for the header of the given table.
calcMargins(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator
Calc marginal distributions of nodes in Bayesian network Note that a connected network is assumed.
calcNodeScore(int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
Calc Node Score for given parent set
calcOutOfBagTipText() - Method in class weka.classifiers.meta.Bagging
Returns the tip text for this property
calcPivot(BallNode, BallNode, Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode
Calculates the centroid pivot of a node based on its two child nodes (if merging two nodes).
calcPivot(BottomUpConstructor.TempNode, BottomUpConstructor.TempNode, Instances) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor
Calculates the centroid pivot of a node based on its two child nodes.
calcPivot(MiddleOutConstructor.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
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
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
CapabilitiesFilterChangeEvent(Object, Capabilities) - Constructor for class weka.gui.explorer.Explorer.CapabilitiesFilterChangeEvent
Constructs a GOECapabilitiesFilterChangeEvent object.
CapabilitiesFilterDialog() - Constructor for class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog
creates a dialog to choose Capabilities from.
CapabilitiesHandler - Interface in weka.core
Classes implementing this interface return their capabilities in regards to datasets.
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
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
 
centerDataTipText() - Method in class weka.attributeSelection.PrincipalComponents
Returns the tip text for this property
centerDataTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents
Returns the tip text for this property
centerHorizontal(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
 
charSetTipText() - Method in class weka.core.converters.TextDirectoryLoader
the tip text for this property
ChartEvent - Class in weka.gui.beans
Event encapsulating info for plotting a data point on the StripChart
ChartEvent(Object, 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
 
CheckBoxList - Class in weka.gui
An extended JList that contains CheckBoxes.
CheckBoxList() - Constructor for class weka.gui.CheckBoxList
initializes the list with an empty CheckBoxListModel
CheckBoxList(CheckBoxList.CheckBoxListModel) - Constructor for class weka.gui.CheckBoxList
initializes the list with the given CheckBoxListModel
CheckBoxList.CheckBoxListModel - Class in weka.gui
A specialized model.
CheckBoxList.CheckBoxListRenderer - Class in weka.gui
A specialized CellRenderer for the CheckBoxList
CheckBoxListModel() - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel
initializes the model with no data.
CheckBoxListModel(Object[]) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel
Constructs a CheckBoxListModel from an array of objects and then applies setModel to it.
CheckBoxListModel(Vector) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel
Constructs a CheckBoxListModel from a Vector and then applies setModel to it.
CheckBoxListRenderer() - Constructor for class weka.gui.CheckBoxList.CheckBoxListRenderer
 
checkCanonicalUserOptions() - Method in class weka.core.CheckOptionHandler
checks whether the user-supplied options stay the same after settting, getting and re-setting again
CheckClassifier - Class in weka.classifiers
Class for examining the capabilities and finding problems with classifiers.
CheckClassifier() - Constructor for class weka.classifiers.CheckClassifier
 
CheckClusterer - Class in weka.clusterers
Class for examining the capabilities and finding problems with clusterers.
CheckClusterer() - Constructor for class weka.clusterers.CheckClusterer
default constructor
checkDefaultOptions() - Method in class weka.core.CheckOptionHandler
checks whether the default options can be processed completely or some invalid options are returned by the getOptions() method.
checkErrorRateTipText() - Method in class weka.classifiers.rules.JRip
Returns the tip text for this property
CheckEstimator - Class in weka.estimators
Class for examining the capabilities and finding problems with estimators.
CheckEstimator() - Constructor for class weka.estimators.CheckEstimator
 
CheckEstimator.AttrTypes - Class in weka.estimators
class that contains info about the attribute types the estimator can estimate estimator work on one attribute only
CheckEstimator.EstTypes - Class in weka.estimators
public class that contains info about the chosen attribute type estimator work on one attribute only
CheckEstimator.PostProcessor - Class in weka.estimators
a class for postprocessing the test-data
checkForAttributeType(int) - Method in class weka.core.Instances
Checks for attributes of the given type in the dataset
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
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.
ChildFrameMDI(Main, String) - Constructor for class weka.gui.Main.ChildFrameMDI
constructs a new internal frame that knows about its parent.
ChildFrameSDI(GUIChooser, String) - Constructor for class weka.gui.GUIChooser.ChildFrameSDI
constructs a new internal frame that knows about its parent.
ChildFrameSDI(Main, String) - Constructor for class weka.gui.Main.ChildFrameSDI
constructs a new internal frame that knows about its parent.
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_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.Jython
the classname of the Python interpreter
CLASS_PYTHONOBJECTINPUTSTREAM - Static variable in class weka.core.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.
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
0* 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.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.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.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.attributeSelection.ASEvaluation
Tells the evaluator that the attribute selection process is complete.
clean() - Method in class weka.attributeSelection.CfsSubsetEval
 
clean() - Method in class weka.attributeSelection.ConsistencySubsetEval
 
clean() - Method in class weka.attributeSelection.WrapperSubsetEval
 
clean() - Method in class weka.classifiers.functions.supportVector.CachedKernel
Frees the cache used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.Kernel
Frees the memory used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.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.
clean() - Method in interface weka.core.DistanceFunction
Free any references to training instances
clean() - Method in class weka.core.NormalizableDistance
Free any references to training instances
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() - Method in class weka.core.ProtectedProperties
Overrides a method to prevent the properties from being modified.
clear() - Method in class weka.core.Stopwords
removes all stopwords
clear() - Method in class weka.core.Tee
removes all streams and places the default printstream, if any, again in the list.
clear() - Method in class weka.core.Trie
Removes all of the elements from this collection
clear() - Method in class weka.core.xml.MethodHandler
removes all mappings
clear() - Method in class weka.core.xml.XMLBasicSerialization
generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.xml.XMLDocument
sets up an empty DOM document, with the current DOCTYPE and root node.
clear() - Method in class weka.core.xml.XMLSerialization
generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.xml.XMLSerializationMethodHandler
removes all current methods and adds the methods according to the
clear() - Method in class weka.experiment.ResultMatrix
removes the stored data and the ordering, but retains the dimensions of the matrix
clear() - Method in class weka.experiment.ResultMatrixCSV
removes the stored data but retains the dimensions of the matrix
clear() - Method in class weka.experiment.ResultMatrixGnuPlot
removes the stored data but retains the dimensions of the matrix
clear() - Method in class weka.experiment.ResultMatrixHTML
removes the stored data but retains the dimensions of the matrix
clear() - Method in class weka.experiment.ResultMatrixLatex
removes the stored data but retains the dimensions of the matrix
clear() - Method in class weka.experiment.ResultMatrixPlainText
removes the stored data but retains the dimensions of the matrix
clear() - Method in class weka.experiment.ResultMatrixSignificance
removes the stored data but retains the dimensions of the matrix
clear() - Method in class weka.experiment.xml.XMLExperiment
generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.gui.beans.xml.XMLBeans
generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.gui.LogWindow
clears the output
clear() - Method in class weka.gui.sql.ConnectionPanel
sets the parameters back to standard.
clear() - Method in class weka.gui.sql.InfoPanel
clears the content of the panel
clear() - Method in class weka.gui.sql.QueryPanel
clears the textarea.
clear() - Method in class weka.gui.sql.ResultPanel
sets the parameters back to standard
clear() - Method in class weka.gui.sql.SqlViewer
calls the clear method of all sub-panels to set back to default values and free up memory.
clearCache() - Static method in class weka.core.ClassDiscovery
clears the cache for class/classnames relation.
clearHeader() - Method in class weka.experiment.ResultMatrix
removes all the header information
clearLayout() - Method in class weka.gui.beans.KnowledgeFlowApp
 
clearRanking() - Method in class weka.experiment.ResultMatrix
clears the currently stored ranking data
clearRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
Draw a filled rectangle with the background color.
clearResults() - Method in class weka.gui.ResultHistoryPanel
Removes all of the result buffers from the history.
clearSearch() - Method in class weka.gui.arffviewer.ArffPanel
clears the search, i.e.
clearSearch() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
clears the search, i.e.
clearStatus() - Method in class weka.gui.beans.LogPanel
Clear the status area.
clearSummary() - Method in class weka.experiment.ResultMatrix
clears the current summary data
clearUndo() - Method in interface weka.core.Undoable
removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffPanel
removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffSortedTableModel
removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffTableModel
removes the undo history
clearUndoStack() - Method in class weka.classifiers.bayes.net.EditableBayesNet
remove all actions from the undo stack
clip(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
 
clipRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
Not implemented
Clock() - Constructor for class weka.core.Debug.Clock
automatically starts the clock with FORMAT_SECONDS format and CPU time if available
Clock(int) - Constructor for class weka.core.Debug.Clock
automatically starts the clock with the given output format and CPU time if available
Clock(boolean) - Constructor for class weka.core.Debug.Clock
starts the clock depending on start immediately with the FORMAT_SECONDS output format and CPU time if available
Clock(boolean, int) - Constructor for class weka.core.Debug.Clock
starts the clock depending on start immediately, using CPU time if available
clone() - Method in class weka.associations.gsp.Element
Returns a deep clone of an Element.
clone() - Method in class weka.associations.gsp.Sequence
Returns a deep clone of a Sequence.
clone() - Method in class weka.associations.tertius.LiteralSet
Returns a shallow copy of this set.
clone() - Method in class weka.associations.tertius.Rule
Returns a shallow copy of this rule.
clone() - Method in class weka.attributeSelection.ScatterSearchV1.Subset
 
clone() - Method in class weka.classifiers.evaluation.ConfusionMatrix
Creates and returns a clone of this object.
clone() - Method in class weka.classifiers.functions.pace.DiscreteFunction
Clones the discrete function
clone() - Method in class weka.classifiers.functions.pace.PaceMatrix
Clone the PaceMatrix object.
clone() - Method in interface weka.classifiers.IterativeClassifier
Performs a deep copy of the classifier, and a reference copy of the training instances (or a deep copy if required).
clone() - Method in class weka.classifiers.trees.ADTree
Creates a clone that is identical to the current tree, but is independent.
clone() - Method in class weka.classifiers.trees.adtree.PredictionNode
Clones this node.
clone() - Method in class weka.classifiers.trees.adtree.Splitter
Clones this node.
clone() - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Clones this node.
clone() - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Clones this node.
clone() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
Allows to clone a model (shallow copy).
clone() - Method in class weka.classifiers.trees.j48.Distribution
Clones distribution (Deep copy of distribution).
clone() - Method in class weka.core.AlgVector
Creates and returns a clone of this object.
clone() - Method in class weka.core.Capabilities
Creates and returns a copy of this object.
clone() - Method in class weka.core.Matrix
Deprecated.
Creates and returns a clone of this object.
clone() - Method in class weka.core.matrix.DoubleVector
Clones the DoubleVector object.
clone() - Method in class weka.core.matrix.IntVector
Clones the IntVector object.
clone() - Method in class weka.core.matrix.Matrix
Clone the Matrix object.
clone() - Method in class weka.core.PropertyPath.PathElement
returns a clone of the current object
clone() - Method in class weka.core.TestInstances
creates a clone of the current object
clone() - Method in class weka.core.Trie
returns a deep copy of itself
clone() - Method in class weka.core.Trie.TrieNode
creates a deep copy of itself
clone(Estimator) - Static method in class weka.estimators.Estimator
Creates a deep copy of the given estimator using serialization.
CLOPE - Class in weka.clusterers
Yiling Yang, Xudong Guan, Jinyuan You: CLOPE: a fast and effective clustering algorithm for transactional data.
CLOPE() - Constructor for class weka.clusterers.CLOPE
the default constructor
close(ResultSet) - Method in class weka.experiment.DatabaseUtils
closes the ResultSet and the statement that generated the ResultSet to avoid memory leaks in JDBC drivers - in contrast to the JDBC specs, a lot of JDBC drives don't clean up correctly.
close() - Method in class weka.experiment.DatabaseUtils
closes the m_PreparedStatement to avoid memory leaks.
close() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
closes the window, i.e., if the parent is not null and implements the WindowListener interface it calls the windowClosing method
close() - Method in class weka.gui.LogWindow
closes the frame
closeAllFiles() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
closes all open files
closeFile() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
closes the current tab
closeFile(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
closes the current tab
closeFrame() - Method in class weka.gui.SetInstancesPanel
closes the frame, i.e., the visibility is set to false
closestPoint(Instance, Instances, int[]) - Method in class weka.core.EuclideanDistance
Returns the index of the closest point to the current instance.
closeToDefaultTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner
Returns the tip text for this property
closeToTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner
Returns the tip text for this property
closeToToleranceTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner
Returns the tip text for this property
ClusterDefinition - Class in weka.datagenerators
Ancestor to all ClusterDefinitions, i.e., subclasses that handle their own parameters that the cluster generator only passes on.
ClusterDefinition() - Constructor for class weka.datagenerators.ClusterDefinition
initializes the cluster, without a parent cluster (necessary for GOE)
ClusterDefinition(ClusterGenerator) - Constructor for class weka.datagenerators.ClusterDefinition
initializes the cluster
clusterDefinitionsTipText() - Method in class weka.datagenerators.clusterers.SubspaceCluster
Returns the tip text for this property
Clusterer - Interface in weka.clusterers
Interface for clusterers.
Clusterer - Class in weka.gui.beans
Bean that wraps around weka.clusterers
Clusterer() - Constructor for class weka.gui.beans.Clusterer
Creates a new Clusterer instance.
ClustererBeanInfo - Class in weka.gui.beans
BeanInfo class for the Clusterer wrapper bean
ClustererBeanInfo() - Constructor for class weka.gui.beans.ClustererBeanInfo
 
ClustererCustomizer - Class in weka.gui.beans
GUI customizer for the Clusterer wrapper bean
ClustererCustomizer() - Constructor for class weka.gui.beans.ClustererCustomizer
 
ClustererPanel - Class in weka.gui.explorer
This panel allows the user to select and configure a clusterer, and evaluate the clusterer using a number of testing modes (test on the training data, train/test on a percentage split, test on a separate split).
ClustererPanel() - Constructor for class weka.gui.explorer.ClustererPanel
Creates the clusterer panel
ClustererPerformanceEvaluator - Class in weka.gui.beans
A bean that evaluates the performance of batch trained clusterers
ClustererPerformanceEvaluator() - Constructor for class weka.gui.beans.ClustererPerformanceEvaluator
 
ClustererPerformanceEvaluatorBeanInfo - Class in weka.gui.beans
Bean info class for the clusterer performance evaluator
ClustererPerformanceEvaluatorBeanInfo() - Constructor for class weka.gui.beans.ClustererPerformanceEvaluatorBeanInfo
 
clustererTipText() - Method in class weka.classifiers.meta.ClassificationViaClustering
Returns the tip text for this property
clustererTipText() - Method in class weka.clusterers.MakeDensityBasedClusterer
Returns the tip text for this property
clustererTipText() - Method in class weka.clusterers.SingleClustererEnhancer
Returns the tip text for this property
clustererTipText() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator
Returns the tip text for this property
clustererTipText() - Method in class weka.filters.unsupervised.attribute.AddCluster
Returns the tip text for this property
ClusterEvaluation - Class in weka.clusterers
Class for evaluating clustering models.

Valid options are:

-t name of the training file
Specify the training file.

ClusterEvaluation() - Constructor for class weka.clusterers.ClusterEvaluation
Constructor.
ClusterGenerator - Class in weka.datagenerators
Abstract class for cluster data generators.
ClusterGenerator() - Constructor for class weka.datagenerators.ClusterGenerator
initializes the generator
clusteringSeedTipText() - Method in class weka.classifiers.functions.RBFNetwork
Returns the tip text for this property
clusterInstance(Instance) - Method in class weka.clusterers.AbstractClusterer
Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.CLOPE
Classifies a given instance.
clusterInstance(Instance) - Method in interface weka.clusterers.Clusterer
Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.Cobweb
Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.DBSCAN
Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.FarthestFirst
Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.HierarchicalClusterer
 
clusterInstance(Instance) - Method in class weka.clusterers.OPTICS
Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.sIB
Cluster a given instance, this is the method defined in Clusterer interface do nothing but just return the cluster assigned to it
clusterInstance(Instance) - Method in class weka.clusterers.SimpleKMeans
Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.XMeans
Classifies a given instance.
ClusterMembership - Class in weka.filters.unsupervised.attribute
A filter that uses a density-based clusterer to generate cluster membership values; filtered instances are composed of these values plus the class attribute (if set in the input data).
ClusterMembership() - Constructor for class weka.filters.unsupervised.attribute.ClusterMembership
 
clusterPriors() - Method in class weka.clusterers.AbstractDensityBasedClusterer
Returns the prior probability of each cluster.
clusterPriors() - Method in interface weka.clusterers.DensityBasedClusterer
Returns the prior probability of each cluster.
clusterPriors() - Method in class weka.clusterers.EM
Returns the cluster priors.
clusterPriors() - Method in class weka.clusterers.MakeDensityBasedClusterer
Returns the cluster priors.
clusterResultsToString() - Method in class weka.clusterers.ClusterEvaluation
return the results of clustering.
clusters - Variable in class weka.clusterers.CLOPE
Array of clusters
clusterSubTypeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition
Returns the tip text for this property
clusterTypeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition
Returns the tip text for this property
Cobweb - Class in weka.clusterers
Class implementing the Cobweb and Classit clustering algorithms.

Note: the application of node operators (merging, splitting etc.) in terms of ordering and priority differs (and is somewhat ambiguous) between the original Cobweb and Classit papers.
Cobweb() - Constructor for class weka.clusterers.Cobweb
default constructor
cochransCriterion(double[][]) - Static method in class weka.core.ContingencyTables
Tests if Cochran's criterion is fullfilled for the given contingency table.
codingCost() - Method in class weka.classifiers.trees.j48.C45Split
Returns coding cost for split (used in rule learner).
codingCost() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
Returns coding costs of model.
coef0TipText() - Method in class weka.classifiers.functions.LibSVM
Returns the tip text for this property
coefficients() - Method in class weka.classifiers.functions.LinearRegression
Returns the coefficients for this linear model.
coefficients() - Method in class weka.classifiers.functions.Logistic
Returns the coefficients for this logistic model.
coefficients() - Method in class weka.classifiers.functions.PaceRegression
Returns the coefficients for this linear model.
coefficients() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel
Return the array of coefficients
collapse() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree
Collapses a tree to a node if training error doesn't increase.
collapse() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTreeG
Collapses a tree to a node if training error doesn't increase.
COLOR_STDERR - Static variable in class weka.gui.LogWindow
the Color of the style for stderr
COLOR_STDOUT - Static variable in class weka.gui.LogWindow
the color of the style for stdout
Colors - Class in weka.gui.treevisualizer
This class maintains a list that contains all the colornames from the dotty standard and what color (in RGB) they represent
Colors() - Constructor for class weka.gui.treevisualizer.Colors
 
columnResponseExplanation(PaceMatrix, IntVector, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Returns the squared ks-th response value if the j-th column becomes the ks-th after orthogonal transformation.
combinationRuleTipText() - Method in class weka.classifiers.meta.Vote
Returns the tip text for this property
combinations(int, int) - Static method in class weka.classifiers.functions.LeastMedSq
Produces the combination nCr
combinationTipText() - Method in class weka.attributeSelection.ScatterSearchV1
Returns the tip text for this property
combinedDL(double, double) - Method in class weka.classifiers.rules.RuleStats
Compute the combined DL of the ruleset in this class, i.e.
CombineParents() - Method in class weka.attributeSelection.ScatterSearchV1
Combine all the posible pair solutions existing in the Population
combSort11(double[], int[]) - Static method in class weka.core.neighboursearch.NearestNeighbourSearch
sorts the two given arrays.
COMMA - Static variable in interface weka.core.mathematicalexpression.sym
 
COMMA - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
 
CommandlineCompletion() - Constructor for class weka.gui.SimpleCLIPanel.CommandlineCompletion
default constructor.
compactify() - Method in class weka.core.Instances
Compactifies the set of instances.
compare(Object, Object) - Method in class weka.core.ClassDiscovery.StringCompare
Compares its two arguments for order.
compare(Object, Object) - Method in class weka.core.InstanceComparator
compares the two instances, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
compareTo(FPGrowth.AssociationRule) - Method in class weka.associations.FPGrowth.AssociationRule
Compare this rule to the supplied rule.
compareTo(FPGrowth.BinaryItem) - Method in class weka.associations.FPGrowth.BinaryItem
Ensures that items will be sorted in descending order of frequency.
compareTo(Object) - Method in class weka.associations.RuleItem
compares two RuleItems and allows an ordering concerning expected predictive accuracy and time of generation Note: this class has a natural ordering that is inconsistent with equals
compareTo(Object) - Method in class weka.classifiers.trees.j48.GraftSplit
method needed for sorting a collection of GraftSplits by laplace value
compareTo(AttributeLocator) - Method in class weka.core.AttributeLocator
Compares this object with the specified object for order.
compareTo(Object) - Method in class weka.core.Version
checks the version of this class against the given version-string
compareTo(SortedTableModel.SortContainer) - Method in class weka.gui.SortedTableModel.SortContainer
Compares this object with the specified object for order.
comparisonString(int, Instances) - Method in class weka.classifiers.trees.adtree.Splitter
Gets the string describing the comparision the split depends on for a particular branch.
comparisonString(int, Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Gets the string describing the comparision the split depends on for a particular branch.
comparisonString(int, Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Gets the string describing the comparision the split depends on for a particular branch.
ComplementNaiveBayes - Class in weka.classifiers.bayes
Class for building and using a Complement class Naive Bayes classifier.

For more information see,

Jason D.
ComplementNaiveBayes() - Constructor for class weka.classifiers.bayes.ComplementNaiveBayes
 
complexityParameterTipText() - Method in class weka.attributeSelection.SVMAttributeEval
Returns a tip text for this property suitable for display in the GUI
ComponentHelper - Class in weka.gui
A helper class for some common tasks with Dialogs, Icons, etc.
ComponentHelper() - Constructor for class weka.gui.ComponentHelper
 
componentHidden(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
 
componentMoved(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
 
componentResized(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
 
componentShown(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
 
compressOutputTipText() - Method in class weka.core.converters.ArffSaver
Returns the tip text for this property
compressOutputTipText() - Method in class weka.core.converters.XRFFSaver
Returns the tip text for this property
Compute - Interface in weka.experiment
Interface to something that can accept remote connections and execute a task.
computeLoglikelihood(double[], Instances) - Method in class weka.classifiers.bayes.blr.GaussianPriorImpl
This method calls the log-likelihood implemented in the Prior abstract class.
computeLogLikelihood(double[], Instances) - Method in class weka.classifiers.bayes.blr.LaplacePriorImpl
Computes the log-likelihood values using the implementation in the Prior class.
computelogLikelihood(double[], Instances) - Method in class weka.classifiers.bayes.blr.Prior
Function computes the log-likelihood value: -sum{1 to n}{ln(1+exp(-Beta*x(i)*y(i))}
computeMinMaxAtts() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
Set up the bounds of our graphic based by finding the smallest reasonable area in the instance space to surround our data points.
computePenalty(double[], double[]) - Method in class weka.classifiers.bayes.blr.GaussianPriorImpl
This function computes the penalty term specific to Gaussian distribution.
computePenalty(double[], double[]) - Method in class weka.classifiers.bayes.blr.LaplacePriorImpl
This function computes the penalty term specific to Laplacian distribution.
computePenalty(double[], double[]) - Method in class weka.classifiers.bayes.blr.Prior
Skeleton function to compute penalty terms.
cond() - Method in class weka.core.matrix.Matrix
Matrix condition (2 norm)
cond() - Method in class weka.core.matrix.SingularValueDecomposition
Two norm condition number
ConditionalEstimator - Interface in weka.estimators
Interface for conditional probability estimators.
confidenceFactorTipText() - Method in class weka.classifiers.rules.PART
Returns the tip text for this property
confidenceFactorTipText() - Method in class weka.classifiers.trees.J48
Returns the tip text for this property
confidenceFactorTipText() - Method in class weka.classifiers.trees.J48graft
Returns the tip text for this property
confidenceForRule(AprioriItemSet, AprioriItemSet) - Static method in class weka.associations.AprioriItemSet
Outputs the confidence for a rule.
CONFIG - Static variable in class weka.core.Debug
the log level Vonfig
confirmationComparator - Static variable in class weka.associations.tertius.Rule
Comparator used to compare two rules according to their confirmation value.
confirmationThenObservedComparator - Static variable in class weka.associations.tertius.Rule
Comparator used to compare two rules according to their confirmation and then their observed number of counter-instances.
confirmationThresholdTipText() - Method in class weka.associations.Tertius
Returns the tip text for this property.
confirmationValuesTipText() - Method in class weka.associations.Tertius
Returns the tip text for this property.
ConfusionMatrix - Class in weka.classifiers.evaluation
Cells of this matrix correspond to counts of the number (or weight) of predictions for each actual value / predicted value combination.
confusionMatrix() - Method in class weka.classifiers.Evaluation
Returns a copy of the confusion matrix.
ConfusionMatrix(String[]) - Constructor for class weka.classifiers.evaluation.ConfusionMatrix
Creates the confusion matrix with the given class names.
ConjunctiveRule - Class in weka.classifiers.rules
This class implements a single conjunctive rule learner that can predict for numeric and nominal class labels.

A rule consists of antecedents "AND"ed together and the consequent (class value) for the classification/regression.
ConjunctiveRule() - Constructor for class weka.classifiers.rules.ConjunctiveRule
 
connect(NeuralConnection, NeuralConnection) - Static method in class weka.classifiers.functions.neural.NeuralConnection
Connects two units together.
CONNECT - Static variable in class weka.gui.sql.event.ConnectionEvent
it was a connect try
CONNECTED - Static variable in class weka.classifiers.functions.neural.NeuralConnection
This flag is set once the unit has a connection.
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractDataSink
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractDataSink
Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.AbstractEvaluator
Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractEvaluator
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTestSetProducer
Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTestSetProducer
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTrainingSetProducer
Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTrainingSetProducer
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.Associator
Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Associator
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in interface weka.gui.beans.BeanCommon
Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(String) - Method in interface weka.gui.beans.BeanCommon
Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.ClassAssigner
Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ClassAssigner
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.Classifier
Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Classifier
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.ClassValuePicker
Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ClassValuePicker
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.Clusterer
Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Clusterer
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.CostBenefitAnalysis
Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.CostBenefitAnalysis
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.Filter
Returns true if, at this time, the object will accept a connection with respect to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Filter
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Loader
Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor.
connectionAllowed(String) - Method in class weka.gui.beans.Loader
Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.MetaBean
Returns true if, at this time, the object will accept a connection with respect to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.MetaBean
 
connectionAllowed(String) - Method in class weka.gui.beans.PredictionAppender
Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.PredictionAppender
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.SerializedModelSaver
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor.
connectionAllowed(String) - Method in class weka.gui.beans.SerializedModelSaver
Returns true if, at this time, the object will accept a connection according to the supplied event name.
connectionAllowed(String) - Method in class weka.gui.beans.StripChart
Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.StripChart
Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.TextViewer
Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.TextViewer
Returns true if, at this time, the object will accept a connection via the named event
connectionChange(ConnectionEvent) - Method in interface weka.gui.sql.event.ConnectionListener
This method gets called when the connection is either established or disconnected.
connectionChange(ConnectionEvent) - Method in class weka.gui.sql.QueryPanel
This method gets called when the connection is either established or disconnected.
connectionChange(ConnectionEvent) - Method in class weka.gui.sql.SqlViewer
This method gets called when the connection is either established or disconnected.
ConnectionEvent - Class in weka.gui.sql.event
An event that is generated when a connection is established or dropped.
ConnectionEvent(Object, int, DbUtils) - Constructor for class weka.gui.sql.event.ConnectionEvent
constructs the event
ConnectionEvent(Object, int, DbUtils, Exception) - Constructor for class weka.gui.sql.event.ConnectionEvent
constructs the event
ConnectionListener - Interface in weka.gui.sql.event
A listener for connect/disconnect events.
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractDataSink
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractEvaluator
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTestSetProducer
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainingSetProducer
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Associator
Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in interface weka.gui.beans.BeanCommon
Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.ClassAssigner
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Classifier
Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in class weka.gui.beans.ClassValuePicker
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Clusterer
Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in interface weka.gui.beans.ConnectionNotificationConsumer
Notify this object that it has been registered as a listener with a source with respect to the supplied event name.
connectionNotification(String, Object) - Method in class weka.gui.beans.CostBenefitAnalysis
Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.Filter
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in class weka.gui.beans.Loader
Notify this object that it has been registered as a listener with a source for receiving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.MetaBean
Notify this object that it has been registered as a listener with a source with respect to the named event.
connectionNotification(String, Object) - Method in class weka.gui.beans.PredictionAppender
Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.SerializedModelSaver
Notify this object that it has been registered as a listener with a source with respect to the supplied event name.
connectionNotification(String, Object) - Method in class weka.gui.beans.StripChart
Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.TextViewer
Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
ConnectionNotificationConsumer - Interface in weka.gui.beans
Interface for Beans that can receive (dis-)connection events generated when (dis-)connecting data processing nodes in the Weka KnowledgeFlow.
ConnectionPanel - Class in weka.gui.sql
Enables the user to insert a database URL, plus user/password to connect to this database.
ConnectionPanel(JFrame) - Constructor for class weka.gui.sql.ConnectionPanel
initializes the panel.
CONNECTIONS - Static variable in class weka.gui.beans.BeanConnection
The list of connections
connectToDatabase() - Method in class weka.core.converters.DatabaseLoader
Opens a connection to the database
connectToDatabase() - Method in class weka.core.converters.DatabaseSaver
Opens a connection to the database.
connectToDatabase() - Method in class weka.experiment.DatabaseUtils
Opens a connection to the database.
consequence() - Method in class weka.associations.RuleItem
Gets the consequence of a rule
conservativeForwardSelectionTipText() - Method in class weka.attributeSelection.GreedyStepwise
Returns the tip text for this property
ConsistencySubsetEval - Class in weka.attributeSelection
ConsistencySubsetEval :

Evaluates the worth of a subset of attributes by the level of consistency in the class values when the training instances are projected onto the subset of attributes.
ConsistencySubsetEval() - Constructor for class weka.attributeSelection.ConsistencySubsetEval
Constructor.
ConsistencySubsetEval.hashKey - Class in weka.attributeSelection
Class providing keys to the hash table.
ConsoleLogger - Class in weka.core.logging
A simple logger that outputs the logging information in the console.
ConsoleLogger() - Constructor for class weka.core.logging.ConsoleLogger
 
CONST_AUTOMATIC_SHAPE - Static variable in class weka.gui.visualize.Plot2D
 
Constant - Class in weka.core.pmml
Class encapsulating a Constant Expression.
Constant(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.Constant
Construct an new Constant Expression.
constructWithCopy(double[][]) - Static method in class weka.core.matrix.Matrix
Construct a matrix from a copy of a 2-D array.
containChildBallsTipText() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor
Returns the tip text for this property.
containedBy(Instance) - Method in class weka.associations.ItemSet
Checks if an instance contains an item set.
contains(Literal) - Method in class weka.associations.tertius.LiteralSet
Test if this LiteralSet contains a given Literal.
contains(int) - Method in class weka.classifiers.bayes.net.ParentSet
test if node is contained in parent set
contains(int) - Method in class weka.classifiers.functions.supportVector.SMOset
Checks whether an element is in the set.
contains(DataObject) - Method in interface weka.clusterers.forOPTICSAndDBScan.Databases.Database
Tests if the database contains the dataObject_Query
contains(DataObject) - Method in class weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
Tests if the database contains the dataObject_Query
contains(Object) - Method in class weka.core.FastVector
added by akibriya
contains(PrintStream) - Method in class weka.core.Tee
checks whether the given PrintStream is already in the list.
contains(Object) - Method in class weka.core.Trie
Returns true if this collection contains the specified element.
contains(String) - Method in class weka.core.Trie.TrieNode
checks whether a suffix can be found in its children
contains(String) - Method in class weka.core.xml.MethodHandler
checks whether a method is stored for the given property
contains(Class) - Method in class weka.core.xml.MethodHandler
checks whether a method is stored for the given class
contains(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel
Tests whether the specified object is a component in this list.
contains(String) - Method in class weka.gui.HierarchyPropertyParser
Whether the HierarchyPropertyParser contains the given string
containsAll(Collection<?>) - Method in class weka.core.Trie
Returns true if this collection contains all of the elements in the specified collection.
containsEnvVariables(String) - Static method in class weka.core.Environment
Tests for the presence of environment variables.
containsItems(ArrayList<Attribute>, boolean) - Method in class weka.associations.FPGrowth.AssociationRule
 
containsKey(double) - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable
Tests if the specified double is a key in this hashtable.
containsKey(double) - Method in class weka.classifiers.lazy.kstar.KStarCache
Checks if the specified key maps with an entry in the cache table
containsOverOneEvent() - Method in class weka.associations.gsp.Element
Checks if an Element contains over one event.
containsPrefix(String) - Method in class weka.core.Trie
checks whether the given prefix is stored in the trie
containsValue(double) - Method in class weka.core.pmml.FieldMetaInfo.Interval
Returns true if this interval contains the supplied value.
containsWindow(Class) - Method in class weka.gui.Main
checks, whether an instance of the given window class is already in the Window list.
containsWindow(String) - Method in class weka.gui.Main
checks, whether a window with the given title is already in the Window list.
context() - Method in class weka.gui.HierarchyPropertyParser
The context of the current node, i.e.
ContingencyTables - Class in weka.core
Class implementing some statistical routines for contingency tables.
ContingencyTables() - Constructor for class weka.core.ContingencyTables
 
CONTINUOUS - Static variable in class weka.datagenerators.clusterers.SubspaceCluster
cluster subtype: continuous
ConverterFileChooser - Class in weka.gui
A specialized JFileChooser that lists all available file Loaders and Savers.
ConverterFileChooser() - Constructor for class weka.gui.ConverterFileChooser
onstructs a FileChooser pointing to the user's default directory.
ConverterFileChooser(File) - Constructor for class weka.gui.ConverterFileChooser
Constructs a FileChooser using the given File as the path.
ConverterFileChooser(String) - Constructor for class weka.gui.ConverterFileChooser
Constructs a FileChooser using the given path.
ConverterUtils - Class in weka.core.converters
Utility routines for the converter package.
ConverterUtils() - Constructor for class weka.core.converters.ConverterUtils
 
ConverterUtils.DataSink - Class in weka.core.converters
Helper class for saving data to files.
ConverterUtils.DataSource - Class in weka.core.converters
Helper class for loading data from files and URLs.
convertInfixToPostfix(String) - Method in class weka.core.AttributeExpression
Converts a string containing a mathematical expression in infix form to postfix form.
convertInstance(Instance) - Method in interface weka.attributeSelection.AttributeTransformer
Transforms an instance in the format of the original data to the transformed space
convertInstance(Instance) - Method in class weka.attributeSelection.LatentSemanticAnalysis
Transform an instance in original (unnormalized) format
convertInstance(Instance) - Method in class weka.attributeSelection.PrincipalComponents
Transform an instance in original (unormalized) format.
convertNewLines(String) - Static method in class weka.core.Utils
Converts carriage returns and new lines in a string into \r and \n.
convertNominalTipText() - Method in class weka.classifiers.trees.LMT
Returns the tip text for this property
convertNominalToBinaryTipText() - Method in class weka.classifiers.functions.LibLINEAR
Returns the tip text for this property
convertNumericAttToNominal(int, ArrayList<String>) - Method in class weka.core.pmml.MiningSchema
Convert a numeric attribute in the mining schema to nominal.
convertStringAttsToNominal() - Method in class weka.core.pmml.MiningSchema
Method to convert any string attributes in the mining schema Instances to nominal attributes.
convertToAttribX(double) - Method in class weka.gui.visualize.Plot2D
convert a Panel x coordinate to a raw x value.
convertToAttribY(double) - Method in class weka.gui.visualize.Plot2D
convert a Panel y coordinate to a raw y value.
convertToPanelX(double) - Method in class weka.gui.visualize.Plot2D
Convert an raw x value to Panel x coordinate.
convertToPanelY(double) - Method in class weka.gui.visualize.Plot2D
Convert an raw y value to Panel y coordinate.
convertToRelativePath(File) - Static method in class weka.core.Utils
Converts a File's absolute path to a path relative to the user (ie start) directory.
convictionForRule(AprioriItemSet, AprioriItemSet, int, int) - Method in class weka.associations.AprioriItemSet
Outputs the conviction for a rule.
copy() - Method in class weka.associations.tertius.IndividualInstance
 
copy(ParentSet) - Method in class weka.classifiers.bayes.net.ParentSet
Copy makes current parents set equal to other parent set
copy() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
Return a shallow copy of this kernel
copy() - Method in class weka.classifiers.rules.JRip.Antd
Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.NominalAntd
Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.NumericAntd
Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.RipperRule
Get a shallow copy of this rule
copy() - Method in class weka.classifiers.rules.Rule
Get a shallow copy of this rule
copy() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo
Makes a copy of this CorrelationSplitInfo object
copy() - Method in interface weka.classifiers.trees.m5.SplitEvaluate
makes a copy of the SplitEvaluate object
copy() - Method in class weka.classifiers.trees.m5.YongSplitInfo
Makes a copy of this SplitInfo object
copy() - Method in class weka.core.Attribute
Produces a shallow copy of this attribute.
copy(String) - Method in class weka.core.Attribute
Produces a shallow copy of this attribute with a new name.
copy() - Method in class weka.core.BinarySparseInstance
Produces a shallow copy of this instance.
copy() - Method in interface weka.core.Copyable
This method produces a shallow copy of an object.
copy() - Method in class weka.core.FastVector
Produces a shallow copy of this vector.
copy() - Method in class weka.core.Instance
Produces a shallow copy of this instance.
copy() - Method in class weka.core.matrix.DoubleVector
Makes a deep copy of the vector
copy() - Method in class weka.core.matrix.IntVector
Makes a deep copy of the vector
copy() - Method in class weka.core.matrix.Matrix
Make a deep copy of a matrix
copy() - Method in class weka.core.SparseInstance
Produces a shallow copy of this instance.
Copy - Class in weka.filters.unsupervised.attribute
An instance filter that copies a range of attributes in the dataset.
Copy() - Constructor for class weka.filters.unsupervised.attribute.Copy
 
Copyable - Interface in weka.core
Interface implemented by classes that can produce "shallow" copies of their objects.
copyArea(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
Not implemented
copyContent() - Method in class weka.gui.arffviewer.ArffPanel
copies the content of the selection to the clipboard
copyContent() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
copies the content of the selection to the clipboard
copyElements() - Method in class weka.core.FastVector
Clones the vector and shallow copies all its elements.
copyInto(Object[]) - Method in class weka.gui.CheckBoxList.CheckBoxListModel
Copies the components of this list into the specified array.
copyRelationalValues(Instance, Instances, AttributeLocator) - Static method in class weka.core.RelationalLocator
Copies relational values contained in the instance copied to a new dataset.
copyRelationalValues(Instance, boolean, Instances, AttributeLocator, Instances, AttributeLocator) - Static method in class weka.core.RelationalLocator
Takes relational values referenced by an Instance and copies them from a source dataset to a destination dataset.
Copyright - Class in weka.core
A class for providing centralized Copyright information.
Copyright() - Constructor for class weka.core.Copyright
 
copyStringValues(Instance, Instances, AttributeLocator) - Static method in class weka.core.StringLocator
Copies string values contained in the instance copied to a new dataset.
copyStringValues(Instance, boolean, Instances, AttributeLocator, Instances, AttributeLocator) - Static method in class weka.core.StringLocator
Takes string values referenced by an Instance and copies them from a source dataset to a destination dataset.
copyToClipboard() - Method in class weka.gui.sql.InfoPanel
copies the currently selected error message to the clipboard
CORE_FILE_LOADERS - Static variable in class weka.core.converters.ConverterUtils
the core loaders - hardcoded list necessary for RMI/Remote Experiments (comma-separated list).
CORE_FILE_SAVERS - Static variable in class weka.core.converters.ConverterUtils
the core savers - hardcoded list necessary for RMI/Remote Experiments (comma-separated list).
coreDistance(int, double, DataObject) - Method in interface weka.clusterers.forOPTICSAndDBScan.Databases.Database
Calculates the coreDistance for the specified DataObject.
coreDistance(int, double, DataObject) - Method in class weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
Calculates the coreDistance for the specified DataObject.
correct() - Method in class weka.classifiers.evaluation.ConfusionMatrix
Gets the number of correct classifications (that is, for which a correct prediction was made).
correct() - Method in class weka.classifiers.Evaluation
Gets the number of instances correctly classified (that is, for which a correct prediction was made).
correlation(double[], double[], int) - Static method in class weka.core.Utils
Returns the correlation coefficient of two double vectors.
correlation - Variable in class weka.experiment.PairedStats
The correlation coefficient
correlationCoefficient() - Method in class weka.classifiers.Evaluation
Returns the correlation coefficient if the class is numeric.
CorrelationSplitInfo - Class in weka.classifiers.trees.m5
Finds split points using correlation.
CorrelationSplitInfo(int, int, int) - Constructor for class weka.classifiers.trees.m5.CorrelationSplitInfo
Constructs an object which contains the split information
COS - Static variable in interface weka.core.mathematicalexpression.sym
 
COS - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
 
CostBenefitAnalysis - Class in weka.gui.beans
Bean that aids in analyzing cost/benefit tradeoffs.
CostBenefitAnalysis() - Constructor for class weka.gui.beans.CostBenefitAnalysis
Constructor.
CostBenefitAnalysisBeanInfo - Class in weka.gui.beans
Bean info class for the cost/benefit analysis
CostBenefitAnalysisBeanInfo() - Constructor for class weka.gui.beans.CostBenefitAnalysisBeanInfo
 
CostCurve - Class in weka.classifiers.evaluation
Generates points illustrating probablity cost tradeoffs that can be obtained by varying the threshold value between classes.
CostCurve() - Constructor for class weka.classifiers.evaluation.CostCurve
 
CostMatrix - Class in weka.classifiers
Class for storing and manipulating a misclassification cost matrix.
CostMatrix(int) - Constructor for class weka.classifiers.CostMatrix
Creates a default cost matrix of a particular size.
CostMatrix(CostMatrix) - Constructor for class weka.classifiers.CostMatrix
Creates a cost matrix that is a copy of another.
CostMatrix(Reader) - Constructor for class weka.classifiers.CostMatrix
Reads a matrix from a reader.
CostMatrixEditor - Class in weka.gui
Class for editing CostMatrix objects.
CostMatrixEditor() - Constructor for class weka.gui.CostMatrixEditor
Constructs a new CostMatrixEditor.
costMatrixSourceTipText() - Method in class weka.attributeSelection.CostSensitiveASEvaluation
 
costMatrixSourceTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
 
costMatrixSourceTipText() - Method in class weka.classifiers.meta.MetaCost
Returns the tip text for this property
costMatrixTipText() - Method in class weka.attributeSelection.CostSensitiveASEvaluation
 
costMatrixTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
 
costMatrixTipText() - Method in class weka.classifiers.meta.MetaCost
Returns the tip text for this property
CostSensitiveASEvaluation - Class in weka.attributeSelection
Abstract base class for cost-sensitive subset and attribute evaluators.
CostSensitiveASEvaluation() - Constructor for class weka.attributeSelection.CostSensitiveASEvaluation
 
CostSensitiveAttributeEval - Class in weka.attributeSelection
A meta subset evaluator that makes its base subset evaluator cost-sensitive.
CostSensitiveAttributeEval() - Constructor for class weka.attributeSelection.CostSensitiveAttributeEval
Default constructor.
CostSensitiveClassifier - Class in weka.classifiers.meta
A metaclassifier that makes its base classifier cost-sensitive.
CostSensitiveClassifier() - Constructor for class weka.classifiers.meta.CostSensitiveClassifier
Default constructor.
CostSensitiveClassifierSplitEvaluator - Class in weka.experiment
SplitEvaluator that produces results for a classification scheme on a nominal class attribute, including weighted misclassification costs.
CostSensitiveClassifierSplitEvaluator() - Constructor for class weka.experiment.CostSensitiveClassifierSplitEvaluator
 
CostSensitiveSubsetEval - Class in weka.attributeSelection
A meta subset evaluator that makes its base subset evaluator cost-sensitive.
CostSensitiveSubsetEval() - Constructor for class weka.attributeSelection.CostSensitiveSubsetEval
Default constructor.
costTipText() - Method in class weka.classifiers.functions.LibLINEAR
Returns the tip text for this property
costTipText() - Method in class weka.classifiers.functions.LibSVM
Returns the tip text for this property
count() - Method in class weka.associations.RuleGeneration
Gets the actual maximum value of the generation time
count - Variable in class weka.experiment.PairedStats
The number of data points seen
count - Variable in class weka.experiment.Stats
The number of values seen
countBagCiters(Instance) - Method in class weka.classifiers.mi.CitationKNN
calculates the citers associated to a bag
countBagReferences(Instance) - Method in class weka.classifiers.mi.CitationKNN
Calculates the references of the exemplar bag
countData() - Method in class weka.classifiers.rules.RuleStats
Filter the data according to the ruleset and compute the basic stats: coverage/uncoverage, true/false positive/negatives of each rule
countData(int, Instances, double[][]) - Method in class weka.classifiers.rules.RuleStats
Count data from the position index in the ruleset assuming that given data are not covered by the rules in position 0...(index-1), and the statistics of these rules are provided.
This procedure is typically useful when a temporary object of RuleStats is constructed in order to efficiently calculate the relative DL of rule in position index, thus all other stuff is not needed.
counter() - Method in class weka.associations.ItemSet
Gets the counter
counterInstance(Instance, Instance) - Method in class weka.associations.tertius.LiteralSet
Test if an individual instance, given a part instance of this individual, is a counter-instance of this LiteralSet.
counterInstance(Instance) - Method in class weka.associations.tertius.LiteralSet
Test if an instance is a counter-instance of this LiteralSet.
counterInstance(Instance) - Method in class weka.associations.tertius.Rule
Test if an instance is a counter-instance of this rule.
countsForInstance(Instance) - Method in class weka.classifiers.bayes.BayesNet
Calculates the counts for Dirichlet distribution for the class membership probabilities for the given test instance.
covers(Instance) - Method in class weka.classifiers.rules.JRip.Antd
 
covers(Instance) - Method in class weka.classifiers.rules.JRip.NominalAntd
Whether the instance is covered by this antecedent
covers(Instance) - Method in class weka.classifiers.rules.JRip.NumericAntd
Whether the instance is covered by this antecedent
covers(Instance) - Method in class weka.classifiers.rules.JRip.RipperRule
Whether the instance covered by this rule
covers(Instance) - Method in class weka.classifiers.rules.Rule
Whether the instance covered by this rule
CoverTree - Class in weka.core.neighboursearch
Class implementing the CoverTree datastructure.
The class is very much a translation of the c source code made available by the authors.

For more information and original source code see:

Alina Beygelzimer, Sham Kakade, John Langford: Cover trees for nearest neighbor.
CoverTree() - Constructor for class weka.core.neighboursearch.CoverTree
default constructor.
CoverTree.CoverTreeNode - Class in weka.core.neighboursearch
class representing a node of the cover tree.
CoverTreeNode() - Constructor for class weka.core.neighboursearch.CoverTree.CoverTreeNode
Constructor for the class.
CoverTreeNode(Integer, double, double, Stack<CoverTree.CoverTreeNode>, int, int) - Constructor for class weka.core.neighboursearch.CoverTree.CoverTreeNode
Constructor.
CramersV(double[][]) - Static method in class weka.core.ContingencyTables
Computes Cramer's V for a contingency table.
create(Reader) - Method in class weka.gui.treevisualizer.TreeBuild
This will build A node structure from the dotty format passed.
create() - Method in class weka.gui.visualize.PostscriptGraphics
Clone a PostscriptGraphics object
createExperimentIndex() - Method in class weka.experiment.DatabaseUtils
Attempts to create the experiment index table.
createExperimentIndexEntry(ResultProducer) - Method in class weka.experiment.DatabaseUtils
Attempts to insert a results entry for the table into the experiment index.
createNewVisualizerWindow(Classifier, Instances) - Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer
Creates a new GUI window with all of the BoundaryVisualizer trappings,
CreatePopulation(int) - Method in class weka.attributeSelection.ScatterSearchV1
Create the initial Population
createResultsTable(ResultProducer, String) - Method in class weka.experiment.DatabaseUtils
Creates a results table for the supplied result producer.
createSingleton(String[]) - Static method in class weka.gui.beans.KnowledgeFlowApp
Create the singleton instance of the KnowledgeFlow
createSingleton() - Static method in class weka.gui.GUIChooser
Create a singleton instance of the GUIChooser
createSingleton(String[]) - Static method in class weka.gui.Main
Create the singleton instance of the Main GUI.
createSubsampleWithoutReplacement(Random, int, int, int, int[]) - Method in class weka.filters.supervised.instance.Resample
creates the subsample without replacement.
createSubsampleWithoutReplacement(Random, int, int) - Method in class weka.filters.unsupervised.instance.Resample
creates the subsample without replacement
createSubsampleWithReplacement(Random, int, int, int, int[]) - Method in class weka.filters.supervised.instance.Resample
creates the subsample with replacement.
createSubsampleWithReplacement(Random, int, int) - Method in class weka.filters.unsupervised.instance.Resample
creates the subsample with replacement
criticalValueTipText() - Method in class weka.classifiers.bayes.AODEsr
Returns the tip text for this property
crossoverProbTipText() - Method in class weka.attributeSelection.GeneticSearch
Returns the tip text for this property
crossValidate(NaiveBayesUpdateable, Instances, Random) - Static method in class weka.classifiers.trees.j48.NBTreeNoSplit
Utility method for fast 5-fold cross validation of a naive bayes model
CrossValidateAttributes() - Method in class weka.attributeSelection.AttributeSelection
Perform a cross validation for attribute selection.
crossValidateModel(Classifier, Instances, int, Random, Object...) - Method in class weka.classifiers.Evaluation
Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(String, Instances, int, String[], Random) - Method in class weka.classifiers.Evaluation
Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(DensityBasedClusterer, Instances, int, Random) - Static method in class weka.clusterers.ClusterEvaluation
Perform a cross-validation for DensityBasedClusterer on a set of instances.
crossValidateModel(String, Instances, int, String[], Random) - Static method in class weka.clusterers.ClusterEvaluation
Performs a cross-validation for a DensityBasedClusterer clusterer on a set of instances.
crossValidateTipText() - Method in class weka.classifiers.lazy.IBk
Returns the tip text for this property.
CrossValidationFoldMaker - Class in weka.gui.beans
Bean for splitting instances into training ant test sets according to a cross validation
CrossValidationFoldMaker() - Constructor for class weka.gui.beans.CrossValidationFoldMaker
 
CrossValidationFoldMakerBeanInfo - Class in weka.gui.beans
BeanInfo class for the cross validation fold maker bean
CrossValidationFoldMakerBeanInfo() - Constructor for class weka.gui.beans.CrossValidationFoldMakerBeanInfo
 
CrossValidationFoldMakerCustomizer - Class in weka.gui.beans
GUI Customizer for the cross validation fold maker bean
CrossValidationFoldMakerCustomizer() - Constructor for class weka.gui.beans.CrossValidationFoldMakerCustomizer
 
CrossValidationResultProducer - Class in weka.experiment
Generates for each run, carries out an n-fold cross-validation, using the set SplitEvaluator to generate some results.
CrossValidationResultProducer() - Constructor for class weka.experiment.CrossValidationResultProducer
 
crossValTipText() - Method in class weka.classifiers.rules.DecisionTable
Returns the tip text for this property
CSVLoader - Class in weka.core.converters
Reads a source that is in comma separated or tab separated format.
CSVLoader() - Constructor for class weka.core.converters.CSVLoader
default constructor.
CSVResultListener - Class in weka.experiment
Takes results from a result producer and assembles them into comma separated value form.
CSVResultListener() - Constructor for class weka.experiment.CSVResultListener
Sets temporary file.
CSVSaver - Class in weka.core.converters
Writes to a destination that is in csv format

Valid options are:

CSVSaver() - Constructor for class weka.core.converters.CSVSaver
Constructor
cTipText() - Method in class weka.classifiers.functions.SMO
Returns the tip text for this property
cTipText() - Method in class weka.classifiers.functions.SMOreg
Returns the tip text for this property
cTipText() - Method in class weka.classifiers.mi.MISMO
Returns the tip text for this property
cTipText() - Method in class weka.classifiers.mi.MISVM
Returns the tip text for this property
cumulate() - Method in class weka.core.matrix.DoubleVector
Returns a vector that stores the cumulated values of the original vector
cumulateInPlace() - Method in class weka.core.matrix.DoubleVector
Cumulates the original vector in place
cumulativeCV(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
CumulativeCV returns the accuracy calculated using cumulative cross validation.
CustomizerCloseRequester - Interface in weka.gui.beans
Customizers who want to be able to close the customizer window themselves can implement this window.
customizerClosing() - Method in class weka.gui.beans.ClassAssignerCustomizer
 
customizerClosing() - Method in class weka.gui.beans.ClassifierCustomizer
 
customizerClosing() - Method in class weka.gui.beans.ClassValuePickerCustomizer
 
customizerClosing() - Method in interface weka.gui.beans.CustomizerClosingListener
Customizer classes that want to know when they are being disposed of can implement this method.
CustomizerClosingListener - Interface in weka.gui.beans
 
CustomPanelSupplier - Interface in weka.gui
An interface for objects that are capable of supplying their own custom GUI components.
cutOffFactorTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
cutoffTipText() - Method in class weka.clusterers.Cobweb
Returns the tip text for this property
cutpointsToString(double[], boolean[]) - Static method in class weka.estimators.EstimatorUtils
Returns a string representing the cutpoints
CV_BASED - Static variable in class weka.classifiers.bayes.BayesianLogisticRegression
 
CVBasedHyperparameter() - Method in class weka.classifiers.bayes.BayesianLogisticRegression
Method computes the best hyperparameter value by doing cross -validation on the training data and compute the likelihood.
CVParameterSelection - Class in weka.classifiers.meta
Class for performing parameter selection by cross-validation for any classifier.

For more information, see:

R.
CVParameterSelection() - Constructor for class weka.classifiers.meta.CVParameterSelection
 
CVParametersTipText() - Method in class weka.classifiers.meta.CVParameterSelection
Returns the tip text for this property
CVResultsString() - Method in class weka.attributeSelection.AttributeSelection
returns a string summarizing the results of repeated attribute selection runs on splits of a dataset.
CVTypeTipText() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
 

D

D_CONVCHCLOSER - Static variable in class weka.clusterers.XMeans
have a closer look at converge children.
D_CURR - Static variable in class weka.clusterers.XMeans
for current debug.
D_FOLLOWSPLIT - Static variable in class weka.clusterers.XMeans
follows the splitting of the centers.
D_GENERAL - Static variable in class weka.clusterers.XMeans
general debugging.
D_ITERCOUNT - Static variable in class weka.clusterers.XMeans
follow iterations.
D_KDTREE - Static variable in class weka.clusterers.XMeans
check on kdtree.
D_METH_MISUSE - Static variable in class weka.clusterers.XMeans
functions were maybe misused.
D_PRINTCENTERS - Static variable in class weka.clusterers.XMeans
print the centers.
D_RANDOMVECTOR - Static variable in class weka.clusterers.XMeans
check on random vectors.
Dagging - Class in weka.classifiers.meta
This meta classifier creates a number of disjoint, stratified folds out of the data and feeds each chunk of data to a copy of the supplied base classifier.
Dagging() - Constructor for class weka.classifiers.meta.Dagging
Constructor.
Database - Interface in weka.clusterers.forOPTICSAndDBScan.Databases
Database.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Aug 20, 2004
Time: 1:03:43 PM
$ Revision 1.4 $
database_distanceTypeTipText() - Method in class weka.clusterers.DBSCAN
Returns the tip text for this property
database_distanceTypeTipText() - Method in class weka.clusterers.OPTICS
Returns the tip text for this property
database_TypeTipText() - Method in class weka.clusterers.DBSCAN
Returns the tip text for this property
database_TypeTipText() - Method in class weka.clusterers.OPTICS
Returns the tip text for this property
DatabaseConnection - Class in weka.core.converters
Connects to a database.
DatabaseConnection() - Constructor for class weka.core.converters.DatabaseConnection
Sets up the database drivers
DatabaseConnectionDialog - Class in weka.gui
A dialog to enter URL, username and password for a database connection.
DatabaseConnectionDialog(Frame) - Constructor for class weka.gui.DatabaseConnectionDialog
Create database connection dialog.
DatabaseConnectionDialog(Frame, String, String) - Constructor for class weka.gui.DatabaseConnectionDialog
Create database connection dialog.
DatabaseConnectionDialog(Frame, String, String, boolean) - Constructor for class weka.gui.DatabaseConnectionDialog
Create database connection dialog.
DatabaseConverter - Interface in weka.core.converters
Marker interface for a loader/saver that uses a database
databaseForName(String, Instances) - Method in class weka.clusterers.DBSCAN
Returns a new Class-Instance of the specified database
databaseForName(String, Instances) - Method in class weka.clusterers.OPTICS
Returns a new Class-Instance of the specified database
DatabaseLoader - Class in weka.core.converters
Reads Instances from a Database.
DatabaseLoader() - Constructor for class weka.core.converters.DatabaseLoader
Constructor
databaseOutputTipText() - Method in class weka.clusterers.OPTICS
Returns the tip text for this property.
DatabaseResultListener - Class in weka.experiment
Takes results from a result producer and sends them to a database.
DatabaseResultListener() - Constructor for class weka.experiment.DatabaseResultListener
Sets up the database drivers
DatabaseResultProducer - Class in weka.experiment
Examines a database and extracts out the results produced by the specified ResultProducer and submits them to the specified ResultListener.
DatabaseResultProducer() - Constructor for class weka.experiment.DatabaseResultProducer
Creates the DatabaseResultProducer, letting the parent constructor do it's thing.
DatabaseSaver - Class in weka.core.converters
Writes to a database (tested with MySQL, InstantDB, HSQLDB).
DatabaseSaver() - Constructor for class weka.core.converters.DatabaseSaver
Constructor.
databaseURLTipText() - Method in class weka.experiment.DatabaseUtils
Returns the tip text for this property.
DatabaseUtils - Class in weka.experiment
DatabaseUtils provides utility functions for accessing the experiment database.
DatabaseUtils() - Constructor for class weka.experiment.DatabaseUtils
Reads properties and sets up the database drivers.
dataDL(double, double, double, double, double) - Static method in class weka.classifiers.rules.RuleStats
The description length of data given the parameters of the data based on the ruleset.
DataFormatListener - Interface in weka.gui.beans
Listener interface that customizer classes that are interested in data format changes can implement.
DataGenerator - Class in weka.datagenerators
Abstract superclass for data generators that generate data for classifiers and clusterers.
DataGenerator() - Constructor for class weka.datagenerators.DataGenerator
initializes with default settings.
DataGenerator - Interface in weka.gui.boundaryvisualizer
Interface to something that can generate new instances based on a set of input instances
DataGeneratorPanel - Class in weka.gui.explorer
A panel for generating artificial data via DataGenerators.
DataGeneratorPanel() - Constructor for class weka.gui.explorer.DataGeneratorPanel
creates the panel
DataNearBalancedND - Class in weka.classifiers.meta.nestedDichotomies
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random data-balanced tree structure.

For more info, check

Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems.
DataNearBalancedND() - Constructor for class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Constructor.
DataObject - Interface in weka.clusterers.forOPTICSAndDBScan.DataObjects
DataObject.java
Authors: Rainer Holzmann, Zhanna Melnikova-Albrecht, Matthias Schubert
Date: Aug 19, 2004
Time: 5:48:59 PM
$ Revision 1.4 $
dataObjectForName(String, Instance, String, Database) - Method in class weka.clusterers.DBSCAN
Returns a new Class-Instance of the specified database
dataObjectForName(String, Instance, String, Database) - Method in class weka.clusterers.OPTICS
Returns a new Class-Instance of the specified database
dataObjectIterator() - Method in interface weka.clusterers.forOPTICSAndDBScan.Databases.Database
Returns an iterator over all the dataObjects in the database
dataObjectIterator() - Method in class weka.clusterers.forOPTICSAndDBScan.Databases.SequentialDatabase
Returns an iterator over all the dataObjects in the database
dataSeqIDTipText() - Method in class weka.associations.GeneralizedSequentialPatterns
Returns the dataSeqID option tip text for the Weka GUI.
dataset() - Method in class weka.core.Instance
Returns the dataset this instance has access to.
DATASET_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer
The name of the key field containing the dataset name
DATASET_FIELD_NAME - Static variable in class weka.experiment.RandomSplitResultProducer
The name of the key field containing the dataset name
DataSetEvent - Class in weka.gui.beans
Event encapsulating a data set
DataSetEvent(Object, Instances) - Constructor for class weka.gui.beans.DataSetEvent
 
DatasetListPanel - Class in weka.gui.experiment
This panel controls setting a list of datasets for an experiment to iterate over.
DatasetListPanel(Experiment) - Constructor for class weka.gui.experiment.DatasetListPanel
Creates the dataset list panel with the given experiment.
DatasetListPanel() - Constructor for class weka.gui.experiment.DatasetListPanel
Create the dataset list panel initially disabled.
DataSink(String) - Constructor for class weka.core.converters.ConverterUtils.DataSink
initializes the sink to save the data to the given file.
DataSink(Saver) - Constructor for class weka.core.converters.ConverterUtils.DataSink
initializes the sink to save the data to the given Saver (expected to be fully configured).
DataSink(OutputStream) - Constructor for class weka.core.converters.ConverterUtils.DataSink
initializes the sink to save the data in the stream (always in ARFF format).
DataSink - Interface in weka.gui.beans
Indicator interface to something that can store instances to some destination
DataSource(String) - Constructor for class weka.core.converters.ConverterUtils.DataSource
Tries to load the data from the file.
DataSource(Instances) - Constructor for class weka.core.converters.ConverterUtils.DataSource
Initializes the datasource with the given dataset.
DataSource(Loader) - Constructor for class weka.core.converters.ConverterUtils.DataSource
Initializes the datasource with the given Loader.
DataSource(InputStream) - Constructor for class weka.core.converters.ConverterUtils.DataSource
Initializes the datasource with the given input stream.
DataSource - Interface in weka.gui.beans
Interface to something that is capable of being a source for data - either batch or incremental data
DataSourceListener - Interface in weka.gui.beans
Interface to something that can accept DataSetEvents
DATATYPE_LAYOUT - Static variable in class weka.gui.beans.xml.XMLBeans
the data that is about to be read/written contains a complete layout
DATATYPE_USERCOMPONENTS - Static variable in class weka.gui.beans.xml.XMLBeans
the data that is about to be read/written contains user-components, i.e., Metabeans
DataVisualizer - Class in weka.gui.beans
Bean that encapsulates weka.gui.visualize.VisualizePanel
DataVisualizer() - Constructor for class weka.gui.beans.DataVisualizer
 
DataVisualizerBeanInfo - Class in weka.gui.beans
Bean info class for the data visualizer
DataVisualizerBeanInfo() - Constructor for class weka.gui.beans.DataVisualizerBeanInfo
 
DATE - Static variable in class weka.core.Attribute
Constant set for attributes with date values.
DATE - Static variable in class weka.experiment.DatabaseUtils
Type mapping for DATE used for reading experiment results.
dateAttributesTipText() - Method in class weka.core.converters.CSVLoader
Returns the tip text for this property.
dateFormatTipText() - Method in class weka.core.converters.CSVLoader
Returns the tip text for this property.
dateFormatTipText() - Method in class weka.filters.unsupervised.attribute.Add
Returns the tip text for this property.
dateFormatTipText() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
 
DbConnectionDialog(String, String) - Method in class weka.gui.DatabaseConnectionDialog
Display the database connection dialog
DbConnectionDialog(String, String, boolean) - Method in class weka.gui.DatabaseConnectionDialog
Display the database connection dialog
DBO() - Constructor for class weka.core.Debug.DBO
 
DBSCAN - Class in weka.clusterers
Basic implementation of DBSCAN clustering algorithm that should *not* be used as a reference for runtime benchmarks: more sophisticated implementations exist! Clustering of new instances is not supported.
DBSCAN() - Constructor for class weka.clusterers.DBSCAN
 
DbUtils - Class in weka.gui.sql
A little bit extended DatabaseUtils class.
DbUtils() - Constructor for class weka.gui.sql.DbUtils
initializes the object.
dchisq(double) - Static method in class weka.core.matrix.Maths
Returns the density of the Chi-squared distribution.
dchisq(double, double) - Static method in class weka.core.matrix.Maths
Returns the density of the noncentral Chi-squared distribution.
dchisq(double, DoubleVector) - Static method in class weka.core.matrix.Maths
Returns the density of the noncentral Chi-squared distribution.
dchisqLog(double) - Static method in class weka.core.matrix.Maths
Returns the log-density of the noncentral Chi-square distribution.
dchisqLog(double, double) - Static method in class weka.core.matrix.Maths
Returns the log-density value of a noncentral Chi-square distribution.
dchisqLog(double, DoubleVector) - Static method in class weka.core.matrix.Maths
Returns the log-density of a set of noncentral Chi-squared distributions.
DDConditionalEstimator - Class in weka.estimators
Conditional probability estimator for a discrete domain conditional upon a discrete domain.
DDConditionalEstimator(int, int, boolean) - Constructor for class weka.estimators.DDConditionalEstimator
Constructor
Debug - Class in weka.core
A helper class for debug output, logging, clocking, etc.
Debug() - Constructor for class weka.core.Debug
default constructor, prints only to stdout
Debug(String) - Constructor for class weka.core.Debug
logs the output to the specified file (and stdout).
Debug(String, int, int) - Constructor for class weka.core.Debug
logs the output
DEBUG - Static variable in class weka.gui.LogWindow
whether we're debugging - enables output on stdout
Debug.Clock - Class in weka.core
A little helper class for clocking and outputting times.
Debug.DBO - Class in weka.core
contains debug methods
Debug.Log - Class in weka.core
A helper class for logging stuff.
Debug.Random - Class in weka.core
This extended Random class enables one to print the generated random numbers etc., before they are returned.
Debug.SimpleLog - Class in weka.core
A little, simple helper class for logging stuff.
Debug.Timestamp - Class in weka.core
A class that can be used for timestamps in files, The toString() method simply returns the associated Date object in a timestamp format.
debugLevelTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
debugTipText() - Method in class weka.associations.GeneralizedSequentialPatterns
Returns the tip text for this property
debugTipText() - Method in class weka.attributeSelection.RaceSearch
Returns the tip text for this property
debugTipText() - Method in class weka.attributeSelection.ScatterSearchV1
Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.bayes.BayesianLogisticRegression
Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.Classifier
Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.functions.LinearRegression
Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.functions.Logistic
Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.functions.PaceRegression
Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.functions.supportVector.Kernel
Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.meta.MultiScheme
Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.rules.JRip
Returns the tip text for this property
debugTipText() - Method in class weka.clusterers.EM
Returns the tip text for this property
debugTipText() - Method in class weka.clusterers.HierarchicalClusterer
Returns the tip text for this property
debugTipText() - Method in class weka.clusterers.sIB
Returns the tip text for this property
debugTipText() - Method in class weka.core.converters.TextDirectoryLoader
the tip text for this property
debugTipText() - Method in class weka.datagenerators.DataGenerator
Returns the tip text for this property
debugTipText() - Method in class weka.estimators.Estimator
Returns the tip text for this property
debugTipText() - Method in class weka.experiment.DatabaseUtils
Returns the tip text for this property.
debugTipText() - Method in class weka.filters.SimpleFilter
Returns the tip text for this property
debugTipText() - Method in class weka.filters.unsupervised.attribute.AddExpression
Returns the tip text for this property
debugVectorsFileTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
decayTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
 
decimalsTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner
Returns the tip text for this property
DecisionStump - Class in weka.classifiers.trees
Class for building and using a decision stump.
DecisionStump() - Constructor for class weka.classifiers.trees.DecisionStump
 
DecisionTable - Class in weka.classifiers.rules
Class for building and using a simple decision table majority classifier.

For more information see:

Ron Kohavi: The Power of Decision Tables.
DecisionTable() - Constructor for class weka.classifiers.rules.DecisionTable
Constructor for a DecisionTable
DecisionTableHashKey - Class in weka.classifiers.rules
Class providing hash table keys for DecisionTable
DecisionTableHashKey(Instance, int, boolean) - Constructor for class weka.classifiers.rules.DecisionTableHashKey
Constructor for a hashKey
DecisionTableHashKey(double[]) - Constructor for class weka.classifiers.rules.DecisionTableHashKey
Constructor for a hashKey
decompose() - Method in class weka.classifiers.BVDecompose
Carry out the bias-variance decomposition
decompose() - Method in class weka.classifiers.BVDecomposeSegCVSub
Carry out the bias-variance decomposition using the sub-sampled cross-validation method.
Decorate - Class in weka.classifiers.meta
DECORATE is a meta-learner for building diverse ensembles of classifiers by using specially constructed artificial training examples.
Decorate() - Constructor for class weka.classifiers.meta.Decorate
Constructor.
decreaseFrequency(int) - Method in class weka.associations.FPGrowth.BinaryItem
Decrease the frequency of this item.
decreaseFrequency() - Method in class weka.associations.FPGrowth.BinaryItem
Decrement the frequency of this item.
DEFAULT_COLORS - Static variable in class weka.gui.boundaryvisualizer.BoundaryPanel
default colours for classes
DEFAULT_FORMAT - Static variable in class weka.core.Debug.Timestamp
the default format
DEFAULT_FORMAT - Static variable in class weka.gui.SimpleDateFormatEditor
the default format
DEFAULT_HEIGHT - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel
the default for height
DEFAULT_LEFT - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel
the default for left
DEFAULT_SEPARATORS - Static variable in class weka.core.TestInstances
the default word separators used in strings
DEFAULT_SHAPE_SIZE - Static variable in class weka.gui.visualize.Plot2D
 
DEFAULT_TOP - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel
the default for top
DEFAULT_WIDTH - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel
the default for width
DEFAULT_WORDS - Static variable in class weka.core.TestInstances
the default list of words used in strings
defaultEvaluatorString() - Method in class weka.attributeSelection.CostSensitiveASEvaluation
Return the name of the default evaluator.
defaultEvaluatorString() - Method in class weka.attributeSelection.CostSensitiveAttributeEval
Return the name of the default evaluator.
defaultOutput() - Method in class weka.datagenerators.DataGenerator
Gets the writer, which is used for outputting to stdout.
defaultWeightTipText() - Method in class weka.classifiers.functions.Winnow
Returns the tip text for this property
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.Agrawal
Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.BayesNet
Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.LED24
Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.RandomRBF
Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.RDG1
Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.regression.Expression
Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.regression.MexicanHat
Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.clusterers.BIRCHCluster
Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.clusterers.SubspaceCluster
Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.DataGenerator
Initializes the format for the dataset produced.
DefineFunction - Class in weka.core.pmml
Class encapsulating DefineFunction (used in TransformationDictionary).
DefineFunction(Element, TransformationDictionary) - Constructor for class weka.core.pmml.DefineFunction
 
degreeTipText() - Method in class weka.classifiers.functions.LibSVM
Returns the tip text for this property
del(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution
Deletes given instance from given bag.
delete(int) - Method in class weka.classifiers.functions.supportVector.SMOset
Deletes an element from the set.
delete() - Method in class weka.core.Instances
Removes all instances from the set.
delete(int) - Method in class weka.core.Instances
Removes an instance at the given position from the set.
deleteArc(String, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Delete arc between two nodes.
deleteArc(int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Delete arc between two nodes.
deleteAttribute() - Method in class weka.gui.arffviewer.ArffPanel
deletes the currently selected attribute
deleteAttribute(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
deletes the current selected Attribute or several chosen ones
deleteAttributeAt(int) - Method in class weka.core.Instance
Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in class weka.core.Instances
Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel
deletes the attribute at the given col index
deleteAttributeAt(int) - Method in class weka.gui.arffviewer.ArffTableModel
deletes the attribute at the given col index.
deleteAttributeAt(int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel
deletes the attribute at the given col index
deleteAttributes() - Method in class weka.gui.arffviewer.ArffPanel
deletes the chosen attributes
deleteAttributes(int[]) - Method in class weka.gui.arffviewer.ArffSortedTableModel
deletes the attributes at the given indices
deleteAttributes(int[]) - Method in class weka.gui.arffviewer.ArffTableModel
deletes the attributes at the given indices
deleteAttributeType(int) - Method in class weka.core.Instances
Deletes all attributes of the given type in the dataset.
deleteEmptyBinsTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization
Returns the tip text for this property
deleteEvent(String) - Method in class weka.associations.gsp.Element
Deletes the first or last event of an Element.
deleteGraftedCases(Instances) - Method in class weka.classifiers.trees.j48.GraftSplit
deletes the cases in data that belong to leaf pointed to by the test (i.e.
deleteInfrequentSequences(FastVector, long) - Static method in class weka.associations.gsp.Sequence
Deletes Sequences of a given set which don't meet the minimum support count threshold.
deleteInstance() - Method in class weka.gui.arffviewer.ArffPanel
deletes the currently selected instance
deleteInstance(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
deletes the current selected Instance or several chosen ones
deleteInstanceAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel
deletes the instance at the given index
deleteInstanceAt(int) - Method in class weka.gui.arffviewer.ArffTableModel
deletes the instance at the given index
deleteInstanceAt(int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel
deletes the instance at the given index
deleteInstances() - Method in class weka.gui.arffviewer.ArffPanel
deletes all the currently selected instances
deleteInstances(int[]) - Method in class weka.gui.arffviewer.ArffSortedTableModel
deletes the instances at the given positions
deleteInstances(int[]) - Method in class weka.gui.arffviewer.ArffTableModel
deletes the instances at the given positions
deleteItemSets(FastVector, int, int) - Static method in class weka.associations.ItemSet
Deletes all item sets that don't have minimum support.
deleteItemSets(FastVector, int, int) - Static method in class weka.associations.LabeledItemSet
Deletes all item sets that don't have minimum support and have more than maximum support
deleteLastParent(Instances) - Method in class weka.classifiers.bayes.net.ParentSet
Delete last added parent from parent set and update internals (specifically the cardinality of the parent set)
deleteNode(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
deleteNode(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
deleteParent(int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet
delete node from parent set
deleteSelection(FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Delete nodes with indexes in selection from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
deleteStringAttributes() - Method in class weka.core.Instances
Deletes all string attributes in the dataset.
deleteWithMissing(int) - Method in class weka.core.Instances
Removes all instances with missing values for a particular attribute from the dataset.
deleteWithMissing(Attribute) - Method in class weka.core.Instances
Removes all instances with missing values for a particular attribute from the dataset.
deleteWithMissingClass() - Method in class weka.core.Instances
Removes all instances with a missing class value from the dataset.
delimitersTipText() - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer
Returns the tip text for this property
delNodeValue(int, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Delete node value from a node.
delRange(int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution
Deletes all instances in given range from given bag.
Delta - Variable in class weka.classifiers.bayes.BayesianLogisticRegression
Trust Region Radius
DeltaBeta - Variable in class weka.classifiers.bayes.BayesianLogisticRegression
Array to store Regression Coefficient updates.
DeltaR - Variable in class weka.classifiers.bayes.BayesianLogisticRegression
This vector is used to store the increments on the R(i).
deltaTipText() - Method in class weka.associations.Apriori
Returns the tip text for this property
deltaTipText() - Method in class weka.associations.FPGrowth
Returns the tip text for this property
deltaTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
 
deltaTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
 
DeltaUpdate - Variable in class weka.classifiers.bayes.BayesianLogisticRegression
Trust Region Radius Update
DensityBasedClusterer - Interface in weka.clusterers
Interface for clusterers that can estimate the density for a given instance.
DensityBasedClustererSplitEvaluator - Class in weka.experiment
A SplitEvaluator that produces results for a density based clusterer.
DensityBasedClustererSplitEvaluator() - Constructor for class weka.experiment.DensityBasedClustererSplitEvaluator
 
densityBasedClustererTipText() - Method in class weka.filters.unsupervised.attribute.ClusterMembership
Returns a description of this option suitable for display as a tip text in the gui.
dependencies() - Method in class weka.core.Capabilities
Returns an Iterator over the stored dependencies
depth() - Method in class weka.gui.HierarchyPropertyParser
Get the depth of the tree, i.e.
DerivedFieldMetaInfo - Class in weka.core.pmml
 
DerivedFieldMetaInfo(Element, ArrayList<Attribute>, TransformationDictionary) - Constructor for class weka.core.pmml.DerivedFieldMetaInfo
 
descendantPopulationSizeTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
 
descendantPopulationSizeTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
 
description() - Method in class weka.associations.tertius.Predicate
 
description() - Method in class weka.core.Option
Returns the option's description.
deserialize(InputStream) - Static method in class weka.core.Jython
deserializes the Python Object from the stream
deSerialize(String) - Static method in class weka.core.xml.XStream
Deserializes an object from the supplied XML string
designatedClassTipText() - Method in class weka.classifiers.meta.ThresholdSelector
 
desiredSizeTipText() - Method in class weka.classifiers.meta.Decorate
Returns the tip text for this property
desiredWeightOfInstancesPerIntervalTipText() - Method in class weka.filters.unsupervised.attribute.Discretize
Returns the tip text for this property
det() - Method in class weka.core.matrix.LUDecomposition
Determinant
det() - Method in class weka.core.matrix.Matrix
Matrix determinant
detectionPerAttributeTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange
Returns the tip text for this property
determineBounds() - Method in class weka.gui.visualize.Plot2D
Determine the min and max values for axis and colouring attributes
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.AveragingResultProducer
Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.CSVResultListener
Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.DatabaseResultListener
Determines if there are any constraints (imposed by the destination) on any additional measures produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer
Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in interface weka.experiment.ResultListener
Determines if there are any constraints (imposed by the destination) on additional result columns to be produced by resultProducers.
determineValues(Instances) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues
determines the values to retain, it is always at least 1 and up to the maximum number of distinct values
DIAMOND_SHAPE - Static variable in class weka.gui.visualize.Plot2D
 
differencesProbability - Variable in class weka.experiment.PairedStats
The probability of obtaining the observed differences
differencesSignificance - Variable in class weka.experiment.PairedStats
A significance indicator: 0 if the differences are not significant > 0 if x significantly greater than y < 0 if x significantly less than y
differencesStats - Variable in class weka.experiment.PairedStats
The stats associated with the paired differences
DIRECTED - Static variable in interface weka.gui.graphvisualizer.GraphConstants
Types of Edges
directionTipText() - Method in class weka.attributeSelection.BestFirst
Returns the tip text for this property
disable(Capabilities.Capability) - Method in class weka.core.Capabilities
disables the given capability Disabling NOMINAL_ATTRIBUTES also disables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
disable(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities
disables the given capability.
disableAll() - Method in class weka.core.Capabilities
disables all attribute and class types (including dependencies)
disableAllAttributeDependencies() - Method in class weka.core.Capabilities
disables all attribute type dependencies
disableAllAttributes() - Method in class weka.core.Capabilities
disables all attribute types
disableAllClassDependencies() - Method in class weka.core.Capabilities
disables all class type dependencies
disableAllClasses() - Method in class weka.core.Capabilities
disables all class types
disabled_getEquivalent() - Method in class weka.associations.Tertius
Get the value of equivalent.
disabled_getPartFile() - Method in class weka.associations.Tertius
Get the value of partFile.
disabled_getSameClause() - Method in class weka.associations.Tertius
Get the value of sameClause.
disabled_getSubsumption() - Method in class weka.associations.Tertius
Get the value of subsumption.
disabled_setEquivalent(boolean) - Method in class weka.associations.Tertius
Set the value of equivalent.
disabled_setPartFile(File) - Method in class weka.associations.Tertius
Set the value of partFile.
disabled_setSameClause(boolean) - Method in class weka.associations.Tertius
Set the value of sameClause.
disabled_setSubsumption(boolean) - Method in class weka.associations.Tertius
Set the value of subsumption.
disableDependency(Capabilities.Capability) - Method in class weka.core.Capabilities
disables the dependency of the given capability Disabling NOMINAL_ATTRIBUTES also disables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
disableNot(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities
disables the given "not to have" capability.
disconnect(NeuralConnection, NeuralConnection) - Static method in class weka.classifiers.functions.neural.NeuralConnection
Disconnects two units.
DISCONNECT - Static variable in class weka.gui.sql.event.ConnectionEvent
it was a disconnect
disconnectFromDatabase() - Method in class weka.experiment.DatabaseUtils
Closes the connection to the database.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractDataSink
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractEvaluator
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event named
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTestSetProducer
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainingSetProducer
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Associator
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in interface weka.gui.beans.BeanCommon
Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ClassAssigner
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Classifier
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ClassValuePicker
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Clusterer
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in interface weka.gui.beans.ConnectionNotificationConsumer
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name This method should be implemented synchronized.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.CostBenefitAnalysis
Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Filter
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Loader
Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.MetaBean
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.PredictionAppender
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.SerializedModelSaver
Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.StripChart
Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.TextViewer
Notify this object that it has been deregistered as a listener with a source for named event.
DiscreteEstimator - Class in weka.estimators
Simple symbolic probability estimator based on symbol counts.
DiscreteEstimator(int, boolean) - Constructor for class weka.estimators.DiscreteEstimator
Constructor
DiscreteEstimator(int, double) - Constructor for class weka.estimators.DiscreteEstimator
Constructor
DiscreteEstimatorBayes - Class in weka.classifiers.bayes.net.estimate
Symbolic probability estimator based on symbol counts and a prior.
DiscreteEstimatorBayes(int, double) - Constructor for class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
Constructor
DiscreteEstimatorFullBayes - Class in weka.classifiers.bayes.net.estimate
Symbolic probability estimator based on symbol counts and a prior.
DiscreteEstimatorFullBayes(int, double, double, DiscreteEstimatorBayes, DiscreteEstimatorBayes, double) - Constructor for class weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes
Constructor
DiscreteFunction - Class in weka.classifiers.functions.pace
Class for handling discrete functions.
DiscreteFunction() - Constructor for class weka.classifiers.functions.pace.DiscreteFunction
Constructs an empty discrete function
DiscreteFunction(DoubleVector) - Constructor for class weka.classifiers.functions.pace.DiscreteFunction
Constructs a discrete function with the point values provides and the function values are all 1/n.
DiscreteFunction(DoubleVector, DoubleVector) - Constructor for class weka.classifiers.functions.pace.DiscreteFunction
Constructs a discrete function with both the point values and function values provided.
Discretize - Class in weka.core.pmml
Class encapsulating a Discretize Expression.
Discretize(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.Discretize
Constructs a Discretize Expression
Discretize - Class in weka.filters.supervised.attribute
An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
Discretize() - Constructor for class weka.filters.supervised.attribute.Discretize
Constructor - initialises the filter
Discretize - Class in weka.filters.unsupervised.attribute
An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
Discretize() - Constructor for class weka.filters.unsupervised.attribute.Discretize
Constructor - initialises the filter
Discretize(String) - Constructor for class weka.filters.unsupervised.attribute.Discretize
Another constructor, sets the attribute indices immediately
discretizeBinTipText() - Method in class weka.classifiers.mi.MIBoost
Returns the tip text for this property
displayModelInOldFormatTipText() - Method in class weka.classifiers.bayes.NaiveBayes
Returns the tip text for this property
displayModelInOldFormatTipText() - Method in class weka.clusterers.EM
Returns the tip text for this property
displayResultset(int) - Method in class weka.experiment.PairedTTester
Checks whether the resultset with the given index shall be displayed.
displayResultset(int) - Method in interface weka.experiment.Tester
Checks whether the resultset with the given index shall be displayed.
displayRulesTipText() - Method in class weka.classifiers.rules.DecisionTable
Returns the tip text for this property
displayStdDevsTipText() - Method in class weka.clusterers.SimpleKMeans
Returns the tip text for this property
dispose() - Method in class weka.gui.GUIChooser.ChildFrameSDI
de-registers the child frame with the parent first.
dispose() - Method in class weka.gui.Main.ChildFrameMDI
de-registers the child frame with the parent first.
dispose() - Method in class weka.gui.Main.ChildFrameSDI
de-registers the child frame with the parent first.
dispose() - Method in class weka.gui.visualize.PostscriptGraphics
Not implemented
disposeSplash() - Static method in class weka.gui.SplashWindow
Closes the splash window.
distance(Instance, Instance) - Method in class weka.classifiers.mi.CitationKNN
distance between two instances
distance(DataObject) - Method in interface weka.clusterers.forOPTICSAndDBScan.DataObjects.DataObject
Calculates the distance between dataObject and this.dataObject
distance(DataObject) - Method in class weka.clusterers.forOPTICSAndDBScan.DataObjects.EuclideanDataObject
Calculates the euclidian-distance between dataObject and this.dataObject
distance(DataObject) - Method in class weka.clusterers.forOPTICSAndDBScan.DataObjects.ManhattanDataObject
Calculates the manhattan-distance between dataObject and this.dataObject
distance(Instance, Instance, double, PerformanceStats) - Method in class weka.core.AbstractStringDistanceFunction
Calculates the distance between two instances.
distance(Instance, Instance) - Method in interface weka.core.DistanceFunction
Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in interface weka.core.DistanceFunction
Calculates the distance between two instances.
distance(Instance, Instance, double) - Method in interface weka.core.DistanceFunction
Calculates the distance between two instances.
distance(Instance, Instance, double, PerformanceStats) - Method in interface weka.core.DistanceFunction
Calculates the distance between two instances.
distance(Instance, Instance) - Method in class weka.core.EuclideanDistance
Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in class weka.core.EuclideanDistance
Calculates the distance (or similarity) between two instances.
distance(Instance, Instance) - Method in class weka.core.NormalizableDistance
Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in class weka.core.NormalizableDistance
Calculates the distance between two instances.
distance(Instance, Instance, double) - Method in class weka.core.NormalizableDistance
Calculates the distance between two instances.
distance(Instance, Instance, double, PerformanceStats) - Method in class weka.core.NormalizableDistance
Calculates the distance between two instances.
distanceFTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
DistanceFunction - Interface in weka.core
Interface for any class that can compute and return distances between two instances.
distanceFunctionTipText() - Method in class weka.clusterers.HierarchicalClusterer
 
distanceFunctionTipText() - Method in class weka.clusterers.SimpleKMeans
Returns the tip text for this property.
distanceFunctionTipText() - Method in class weka.core.neighboursearch.NearestNeighbourSearch
Returns the tip text for this property.
distanceIsBranchLengthTipText() - Method in class weka.clusterers.HierarchicalClusterer
 
distanceSet(Instance, Instance) - Method in class weka.classifiers.mi.CitationKNN
Calculates the distance between two instances
distanceWeightingTipText() - Method in class weka.classifiers.lazy.IBk
Returns the tip text for this property.
distinctCount - Variable in class weka.core.AttributeStats
The number of distinct values
distMultTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster
Returns the tip text for this property
distributedExperimentSelected() - Method in class weka.gui.experiment.DistributeExperimentPanel
Returns true if the distribute experiment checkbox is selected
DistributeExperimentPanel - Class in weka.gui.experiment
This panel enables an experiment to be distributed to multiple hosts; it also allows remote host names to be specified.
DistributeExperimentPanel() - Constructor for class weka.gui.experiment.DistributeExperimentPanel
Constructor
DistributeExperimentPanel(Experiment) - Constructor for class weka.gui.experiment.DistributeExperimentPanel
Creates the panel with the supplied initial experiment.
distribution() - Method in class weka.classifiers.evaluation.NominalPrediction
Gets the predicted probabilities
distribution() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
Returns the distribution of class values induced by the model.
Distribution - Class in weka.classifiers.trees.j48
Class for handling a distribution of class values.
Distribution(int, int) - Constructor for class weka.classifiers.trees.j48.Distribution
Creates and initializes a new distribution.
Distribution(double[][]) - Constructor for class weka.classifiers.trees.j48.Distribution
Creates and initializes a new distribution using the given array.
Distribution(Instances) - Constructor for class weka.classifiers.trees.j48.Distribution
Creates a distribution with only one bag according to instances in source.
Distribution(Instances, ClassifierSplitModel) - Constructor for class weka.classifiers.trees.j48.Distribution
Creates a distribution according to given instances and split model.
Distribution(Distribution) - Constructor for class weka.classifiers.trees.j48.Distribution
Creates distribution with only one bag by merging all bags of given distribution.
Distribution(Distribution, int) - Constructor for class weka.classifiers.trees.j48.Distribution
Creates distribution with two bags by merging all bags apart of the indicated one.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.AODE
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.AODEsr
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.BayesNet
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.DMNBtext
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.DMNBtext.DNBBinary
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.HNB
Calculates the class membership probabilities for the given test instance
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayes
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayesSimple
Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.WAODE
Calculates the class membership probabilities for the given test instance
distributionForInstance(Instance) - Method in class weka.classifiers.Classifier
Predicts the class memberships for a given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.LibLINEAR
Computes the distribution for a given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.LibSVM
Computes the distribution for a given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.Logistic
Computes the distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.functions.MultilayerPerceptron
Call this function to predict the class of an instance once a classification model has been built with the buildClassifier call.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.RBFNetwork
Computes the distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SimpleLogistic
Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SMO
Estimates class probabilities for given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SPegasos
Computes the distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.functions.VotedPerceptron
Outputs the distribution for the given output.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.IBk
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.KStar
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.LBR
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.LWL
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.AdaBoostM1
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.AttributeSelectedClassifier
Classifies a given instance after attribute selection
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Bagging
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.ClassificationViaRegression
Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.CostSensitiveClassifier
Returns class probabilities.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.CVParameterSelection
Predicts the class distribution for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Dagging
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Decorate
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.END
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.FilteredClassifier
Classifies a given instance after filtering.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Grading
Returns class probabilities for a given instance using the stacked classifier.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.GridSearch
Computes the distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.meta.LogitBoost
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MetaCost
Classifies a given instance after filtering.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MultiClassClassifier
Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MultiScheme
Returns class probabilities.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Predicts the class distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Predicts the class distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.meta.nestedDichotomies.ND
Predicts the class distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.meta.OrdinalClassClassifier
Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
Computes class distribution of an instance using the best committee.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.RandomCommittee
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.RandomSubSpace
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.RotationForest
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Stacking
Returns class probabilities.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.StackingC
Classifies a given instance using the stacked classifier.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.ThresholdSelector
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Vote
Classifies a given instance using the selected combination rule.
distributionForInstance(Instance) - Method in class weka.classifiers.mi.CitationKNN
Computes the distribution for a given exemplar
distributionForInstance(Instance) - Method in class weka.classifiers.mi.MDD
Computes the distribution for a given exemplar
distributionForInstance(Instance) - Method in class weka.classifiers.mi.MIBoost
Computes the distribution for a given exemplar
distributionForInstance(Instance) - Method in class weka.classifiers.mi.MIDD
Computes the distribution for a given exemplar
distributionForInstance(Instance) - Method in class weka.classifiers.mi.MIEMDD
Computes the distribution for a given exemplar
distributionForInstance(Instance) - Method in class weka.classifiers.mi.MILR
Computes the distribution for a given exemplar
distributionForInstance(Instance) - Method in class weka.classifiers.mi.MIOptimalBall
Computes the distribution for a given multiple instance
distributionForInstance(Instance) - Method in class weka.classifiers.mi.MISMO
Estimates class probabilities for given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.mi.MISVM
Computes the distribution for a given exemplar
distributionForInstance(Instance) - Method in class weka.classifiers.mi.MIWrapper
Computes the distribution for a given exemplar
distributionForInstance(Instance) - Method in class weka.classifiers.mi.SimpleMI
Computes the distribution for a given exemplar
distributionForInstance(Instance) - Method in class weka.classifiers.misc.HyperPipes
Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.misc.SerializedClassifier
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.misc.VFI
Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.GeneralRegression
Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.NeuralNetwork
Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.Regression
Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.ConjunctiveRule
Computes class distribution for the given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.DecisionTable
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.DTNB
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.JRip
Classify the test instance with the rule learner and provide the class distributions
distributionForInstance(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList
Returns class probabilities for a weighted instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.PART
Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.part.MakeDecList
Returns the class distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.ZeroR
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.ADTree
Returns the class probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.BFTree
Computes class probabilities for instance using the decision tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.DecisionStump
Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.FT
Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.ft.FTInnerNode
Returns the class probabilities for an instance given by the Functional tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.ft.FTLeavesNode
Returns the class probabilities for an instance given by the Functional Leaves tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.ft.FTNode
Returns the class probabilities for an instance given by the Functional Tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.ft.FTtree
Returns the class probabilities for an instance given by the Functional tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.Id3
Computes class distribution for instance using decision tree.
distributionForInstance(Instance, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree
Returns class probabilities for a weighted instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.J48
Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.J48graft
Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.LADTree
Returns the class probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.LMT
Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.lmt.LMTNode
Returns the class probabilities for an instance given by the logistic model tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.lmt.LogisticBase
Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.NBTree
Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.RandomForest
Returns the class probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.RandomTree
Computes class distribution of an instance using the tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.REPTree
Computes class distribution of an instance using the tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.SimpleCart
Computes class probabilities for instance using the decision tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.UserClassifier
Call this function to get a double array filled with the probability of how likely each class type is the class of the instance.
distributionForInstance(Instance) - Method in class weka.clusterers.AbstractClusterer
Predicts the cluster memberships for a given instance.
distributionForInstance(Instance) - Method in class weka.clusterers.AbstractDensityBasedClusterer
Returns the cluster probability distribution for an instance.
distributionForInstance(Instance) - Method in interface weka.clusterers.Clusterer
Predicts the cluster memberships for a given instance.
distributionForInstance(Instance) - Method in interface weka.clusterers.DensityBasedClusterer
Returns the cluster probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.clusterers.FilteredClusterer
Classifies a given instance after filtering.
distributionForInstance(Instance) - Method in class weka.clusterers.HierarchicalClusterer
 
distributionsByOriginalIndex(double[]) - Method in class weka.filters.supervised.attribute.ClassOrder
Convert the given class distribution back to the distributions with the original internal class index
distributionSpreadTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample
Returns the tip text for this property
distributionTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection
Returns the tip text for this property
divergence(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader
calculates the divergence between the probability distribution represented by this network and that of another, that is, \sum_{x\in X} P(x)log P(x)/Q(x) where X is the set of values the nodes in the network can take, P(x) the probability of this network for configuration x Q(x) the probability of the other network for configuration x
divide(Instances, boolean) - Static method in class weka.associations.LabeledItemSet
Splits the class attribute away.
dividedBy(DoubleVector) - Method in class weka.core.matrix.DoubleVector
Divided by another DoubleVector element by element
dividedByEquals(DoubleVector) - Method in class weka.core.matrix.DoubleVector
Divided by another DoubleVector element by element in place
DIVISION - Static variable in interface weka.core.mathematicalexpression.sym
 
DIVISION - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
 
DKConditionalEstimator - Class in weka.estimators
Conditional probability estimator for a discrete domain conditional upon a numeric domain.
DKConditionalEstimator(int, double) - Constructor for class weka.estimators.DKConditionalEstimator
Constructor
dl(int) - Method in class weka.core.Debug.DBO
Return true if the debug level is set same method as outpuTypeSet but better name
DMNBtext - Class in weka.classifiers.bayes
Class for building and using a Discriminative Multinomial Naive Bayes classifier.
DMNBtext() - Constructor for class weka.classifiers.bayes.DMNBtext
 
DMNBtext.DNBBinary - Class in weka.classifiers.bayes
 
DNBBinary() - Constructor for class weka.classifiers.bayes.DMNBtext.DNBBinary
 
DNConditionalEstimator - Class in weka.estimators
Conditional probability estimator for a discrete domain conditional upon a numeric domain.
DNConditionalEstimator(int, double) - Constructor for class weka.estimators.DNConditionalEstimator
Constructor
dnorm(double) - Static method in class weka.core.matrix.Maths
Returns the density of the standard normal.
dnorm(double, double, double) - Static method in class weka.core.matrix.Maths
Returns the density value of a standard normal.
dnorm(double, DoubleVector, double) - Static method in class weka.core.matrix.Maths
Returns the density values of a set of normal distributions with different means.
dnormLog(double) - Static method in class weka.core.matrix.Maths
Returns the log-density of the standard normal.
dnormLog(double, double, double) - Static method in class weka.core.matrix.Maths
Returns the log-density value of a standard normal.
dnormLog(double, DoubleVector, double) - Static method in class weka.core.matrix.Maths
Returns the log-density values of a set of normal distributions with different means.
do_action(int, lr_parser, Stack, int) - Method in class weka.core.mathematicalexpression.Parser
Invoke a user supplied parse action.
do_action(int, lr_parser, Stack, int) - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser
Invoke a user supplied parse action.
doCommandlineCompletion(KeyEvent) - Method in class weka.gui.SimpleCLIPanel
performs commandline completion on packages and classnames.
DOCTYPE - Static variable in class weka.core.xml.XMLInstances
the DTD
DOCTYPE - Static variable in class weka.core.xml.XMLOptions
the DTD for the XML file.
DOCTYPE - Static variable in class weka.core.xml.XMLSerialization
the DOCTYPE for the serialization
doGrafting(Instances) - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTreeG
Initializes variables for grafting.
doHistory(KeyEvent) - Method in class weka.gui.SimpleCLIPanel
Changes the currently displayed command line when certain keys are pressed.
doMetaConnection(BeanInstance, BeanInstance, EventSetDescriptor, JComponent) - Static method in class weka.gui.beans.BeanConnection
 
done() - Method in interface weka.classifiers.IterativeClassifier
Signal end of iterating, useful for any house-keeping/cleanup
done() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier
Signal that a scoring run has been completed.
done() - Method in class weka.classifiers.trees.ADTree
Frees memory that is no longer needed for a final model - will no longer be able to increment the classifier after calling this.
done() - Method in class weka.classifiers.trees.LADTree
 
doNotOperateOnPerClassBasisTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
Returns the tip text for this property.
doNotReplaceMissingValuesTipText() - Method in class weka.classifiers.functions.LibLINEAR
Returns the tip text for this property
doNotReplaceMissingValuesTipText() - Method in class weka.classifiers.functions.LibSVM
Returns the tip text for this property
doNotWeightBagsTipText() - Method in class weka.filters.unsupervised.attribute.PropositionalToMultiInstance
Returns the tip text for this property
dontFilterAfterFirstBatchTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
Returns the tip text for this property.
dontNormalizeTipText() - Method in class weka.classifiers.functions.SPegasos
Returns the tip text for this property
dontNormalizeTipText() - Method in class weka.core.NormalizableDistance
Returns the tip text for this property.
dontReplaceMissingTipText() - Method in class weka.classifiers.functions.SPegasos
Returns the tip text for this property
dontReplaceMissingValuesTipText() - Method in class weka.clusterers.SimpleKMeans
Returns the tip text for this property
doRun(int) - Method in class weka.experiment.AveragingResultProducer
Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.CrossValidationResultProducer
Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.DatabaseResultProducer
Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.LearningRateResultProducer
Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.RandomSplitResultProducer
Gets the results for a specified run number.
doRun(int) - Method in interface weka.experiment.ResultProducer
Gets the results for a specified run number.
doRunKeys(int) - Method in class weka.experiment.AveragingResultProducer
Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.CrossValidationResultProducer
Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.DatabaseResultProducer
Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.LearningRateResultProducer
Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.RandomSplitResultProducer
Gets the keys for a specified run number.
doRunKeys(int) - Method in interface weka.experiment.ResultProducer
Gets the keys for a specified run number.
doTests() - Method in class weka.associations.CheckAssociator
Begin the tests, reporting results to System.out
doTests() - Method in class weka.attributeSelection.CheckAttributeSelection
Begin the tests, reporting results to System.out
doTests() - Method in class weka.classifiers.CheckClassifier
Begin the tests, reporting results to System.out
doTests() - Method in class weka.classifiers.functions.supportVector.CheckKernel
Begin the tests, reporting results to System.out
doTests() - Method in class weka.clusterers.CheckClusterer
Begin the tests, reporting results to System.out
doTests() - Method in class weka.core.Check
Begin the tests, reporting results to System.out
doTests() - Method in class weka.core.CheckGOE
Runs some diagnostic tests on the object.
doTests() - Method in class weka.core.CheckOptionHandler
Runs some diagnostic tests on an optionhandler object.
doTests() - Method in class weka.core.CheckScheme
Begin the tests, reporting results to System.out
doTests() - Method in class weka.estimators.CheckEstimator
Begin the tests, reporting results to System.out
dotMultiply(AlgVector) - Method in class weka.core.AlgVector
Returns the inner (or dot) product of two vectors
DotParser - Class in weka.gui.graphvisualizer
This class parses input in DOT format, and builds the datastructures that are passed to it.
DotParser(Reader, FastVector, FastVector) - Constructor for class weka.gui.graphvisualizer.DotParser
Dot parser Constructor
DOUBLE - Static variable in class weka.experiment.DatabaseUtils
Type mapping for DOUBLE used for reading experiment results.
DOUBLE - Static variable in interface weka.gui.graphvisualizer.GraphConstants
Types of Edges
doubleToString(double, int) - Static method in class weka.core.Utils
Rounds a double and converts it into String.
doubleToString(double, int, int) - Static method in class weka.core.Utils
Rounds a double and converts it into a formatted decimal-justified String.
DoubleVector - Class in weka.core.matrix
A vector specialized on doubles.
DoubleVector() - Constructor for class weka.core.matrix.DoubleVector
Constructs a null vector.
DoubleVector(int) - Constructor for class weka.core.matrix.DoubleVector
Constructs an n-vector of zeros.
DoubleVector(int, double) - Constructor for class weka.core.matrix.DoubleVector
Constructs a constant n-vector.
DoubleVector(double[]) - Constructor for class weka.core.matrix.DoubleVector
Constructs a vector directly from a double array
dp(String) - Method in class weka.core.Debug.DBO
prints out text if verbose is on.
dp(int, String) - Method in class weka.core.Debug.DBO
prints out text but only if debug level is set.
dpln(String) - Method in class weka.core.Debug.DBO
prints out text + endofline if verbose is on.
dpln(int, String) - Method in class weka.core.Debug.DBO
prints out text + endofline but only if parameter debug type is set.
draw(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
 
draw3DRect(int, int, int, int, boolean) - Method in class weka.gui.visualize.PostscriptGraphics
Draw an outlined rectangle with 3D effect in current pen color.
Drawable - Interface in weka.core
Interface to something that can be drawn as a graph.
drawArc(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
Not implemented
drawBytes(byte[], int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
simply calls drawString(String,int,int)
drawChars(char[], int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
simply calls drawString(String,int,int)
drawGlyphVector(GlyphVector, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
 
drawHighlight(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection
Call this function to draw the node highlighted.
drawImage(Image, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
calls drawImage(Image,int,int,int,int,Color,ImageObserver)
drawImage(Image, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
calls drawImage(Image,int,int,Color,ImageObserver) with Color.WHITE as background color
drawImage(Image, int, int, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
PS see http://astronomy.swin.edu.au/~pbourke/geomformats/postscript/ Java http://show.docjava.com:8086/book/cgij/doc/ip/graphics/SimpleImageFrame.java.html
drawImage(Image, int, int, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
calls drawImage(Image,int,int,int,int,Color,ImageObserver) with the color WHITE as background
drawImage(Image, int, int, int, int, int, int, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
Not implemented
drawImage(Image, int, int, int, int, int, int, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
calls drawImage(Image,int,int,int,int,int,int,int,int,Color,ImageObserver) with Color.WHITE as background color
drawImage(BufferedImage, BufferedImageOp, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
 
drawImage(Image, AffineTransform, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
 
drawInputLines(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection
Call this function to draw the nodes input connections.
drawLine(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
Draw a line in current pen color.
drawNode(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection
Call this function to draw the node.
drawOutputLines(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection
Call this function to draw the nodes output connections.
drawOval(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
Draw an Oval outline in current pen color.
drawPolygon(int[], int[], int) - Method in class weka.gui.visualize.PostscriptGraphics
Not implemented
drawPolyline(int[], int[], int) - Method in class weka.gui.visualize.PostscriptGraphics
Not implemented
drawRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
Draw an outlined rectangle in current pen color.
drawRenderableImage(RenderableImage, AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
 
drawRenderedImage(RenderedImage, AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
 
drawRoundRect(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
Not implemented
drawString(AttributedCharacterIterator, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
Not implemented
drawString(String, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
Draw text in current pen color.
drawString(AttributedCharacterIterator, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
 
drawString(String, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
 
DTD_ANY - Static variable in class weka.core.xml.XMLDocument
the ANY placeholder.
DTD_AT_LEAST_ONE - Static variable in class weka.core.xml.XMLDocument
the at least one marker.
DTD_ATTLIST - Static variable in class weka.core.xml.XMLDocument
the AttList definition.
DTD_CDATA - Static variable in class weka.core.xml.XMLDocument
the CDATA placeholder.
DTD_DOCTYPE - Static variable in class weka.core.xml.XMLDocument
the DocType definition.
DTD_ELEMENT - Static variable in class weka.core.xml.XMLDocument
the Element definition.
DTD_IMPLIED - Static variable in class weka.core.xml.XMLDocument
the #IMPLIED placeholder.
DTD_OPTIONAL - Static variable in class weka.core.xml.XMLDocument
the optional marker.
DTD_PCDATA - Static variable in class weka.core.xml.XMLDocument
the #PCDATA placeholder.
DTD_REQUIRED - Static variable in class weka.core.xml.XMLDocument
the #REQUIRED placeholder.
DTD_SEPARATOR - Static variable in class weka.core.xml.XMLDocument
the option separator.
DTD_ZERO_OR_MORE - Static variable in class weka.core.xml.XMLDocument
the zero or more marker.
DTNB - Class in weka.classifiers.rules
Class for building and using a decision table/naive bayes hybrid classifier.
DTNB() - Constructor for class weka.classifiers.rules.DTNB
 
DUMMY_STRING_VAL - Static variable in class weka.core.Attribute
Dummy first value for String attributes (useful for sparse instances)
dumpDistribution() - Method in class weka.classifiers.trees.j48.Distribution
Prints distribution.
dumpLabel(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
Prints label for subset index of instances (eg class).
dumpLabelG(int, Instances) - Method in class weka.classifiers.trees.j48.GraftSplit
Prints label for subset index of instances (eg class).
dumpModel(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
Prints the split model.

E

EAST_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual
 
Edge - Class in weka.gui.treevisualizer
This class is used in conjunction with the Node class to form a tree structure.
Edge(String, String, String) - Constructor for class weka.gui.treevisualizer.Edge
This constructs an Edge with the specified label and parent , child serial tags.
edit() - Method in class weka.gui.explorer.PreprocessPanel
edits the current instances object in the viewer
EditableBayesNet - Class in weka.classifiers.bayes.net
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
EditableBayesNet() - Constructor for class weka.classifiers.bayes.net.EditableBayesNet
standard constructor *
EditableBayesNet(Instances) - Constructor for class weka.classifiers.bayes.net.EditableBayesNet
constructor, creates empty network with nodes based on the attributes in a data set
EditableBayesNet(BIFReader) - Constructor for class weka.classifiers.bayes.net.EditableBayesNet
constructor, copies Bayesian network structure from a Bayesian network encapsulated in a BIFReader
EditableBayesNet(boolean) - Constructor for class weka.classifiers.bayes.net.EditableBayesNet
constructor that potentially initializes instances as well
editableProperties() - Method in class weka.gui.PropertySheetPanel
Gets the number of editable properties for the current target.
EditDistance - Class in weka.core
Computes the Levenshtein edit distance between two strings.
EditDistance() - Constructor for class weka.core.EditDistance
 
EditDistance(Instances) - Constructor for class weka.core.EditDistance
 
eig() - Method in class weka.core.matrix.Matrix
Eigenvalue Decomposition
EigenvalueDecomposition - Class in weka.core.matrix
Eigenvalues and eigenvectors of a real matrix.
eigenvalueDecomposition(double[][], double[]) - Method in class weka.core.Matrix
Deprecated.
Performs Eigenvalue Decomposition using Householder QR Factorization Matrix must be symmetrical.
EigenvalueDecomposition(Matrix) - Constructor for class weka.core.matrix.EigenvalueDecomposition
Check for symmetry, then construct the eigenvalue decomposition
Element - Class in weka.associations.gsp
Class representing an Element, i.e., a set of events/items.
Element() - Constructor for class weka.associations.gsp.Element
Constructor
Element(int) - Constructor for class weka.associations.gsp.Element
Constructor accepting an initial size of the events Array as parameter.
element(int) - Method in class weka.core.neighboursearch.covertrees.Stack
Returns the ith element in the stack.
elementAt(int) - Method in class weka.core.FastVector
Returns the element at the given position.
elementAt(int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel
Returns the component at the specified index.
elements() - Method in class weka.core.FastVector
Returns an enumeration of this vector.
elements(int) - Method in class weka.core.FastVector
Returns an enumeration of this vector, skipping the element with the given index.
elements - Variable in class weka.core.neighboursearch.covertrees.Stack
The elements inside the stack.
elements() - Method in class weka.core.Stopwords
Returns a sorted enumeration over all stored stopwords
eliminateColinearAttributesTipText() - Method in class weka.classifiers.functions.LinearRegression
Returns the tip text for this property
EM - Class in weka.clusterers
Simple EM (expectation maximisation) class.

EM assigns a probability distribution to each instance which indicates the probability of it belonging to each of the clusters.
EM() - Constructor for class weka.clusterers.EM
Constructor.
empiricalBayesEstimate(double) - Method in class weka.classifiers.functions.pace.NormalMixture
Returns the empirical Bayes estimate of a single value.
empiricalBayesEstimate(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
Returns the empirical Bayes estimate of a vector.
empiricalProbability(DoubleVector, PaceMatrix) - Method in class weka.classifiers.functions.pace.MixtureDistribution
Computes the empirical probabilities of the data over a set of intervals.
empty() - Method in class weka.core.Queue
Checks if queue is empty.
enable(Capabilities.Capability) - Method in class weka.core.Capabilities
enables the given capability.
enable(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities
enables the given capability.
enableAll() - Method in class weka.core.Capabilities
enables all attribute and class types (including dependencies)
enableAllAttributeDependencies() - Method in class weka.core.Capabilities
enables all attribute type dependencies
enableAllAttributes() - Method in class weka.core.Capabilities
enables all attribute types
enableAllClassDependencies() - Method in class weka.core.Capabilities
enables all class type dependencies
enableAllClasses() - Method in class weka.core.Capabilities
enables all class types
enableDependency(Capabilities.Capability) - Method in class weka.core.Capabilities
enables the dependency flag for the given capability Enabling NOMINAL_ATTRIBUTES also enables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
enableNot(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities
enables the given "not to have" capability.
enclosureCharactersTipText() - Method in class weka.core.converters.CSVLoader
Returns the tip text for this property.
END - Class in weka.classifiers.meta
A meta classifier for handling multi-class datasets with 2-class classifiers by building an ensemble of nested dichotomies.

For more info, check

Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems.
END() - Constructor for class weka.classifiers.meta.END
Constructor.
entropicAutoBlendTipText() - Method in class weka.classifiers.lazy.KStar
Returns the tip text for this property
ENTROPY - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
 
entropy(double[]) - Static method in class weka.core.ContingencyTables
Computes the entropy of the given array.
EntropyBasedSplitCrit - Class in weka.classifiers.trees.j48
"Abstract" class for computing splitting criteria based on the entropy of a class distribution.
EntropyBasedSplitCrit() - Constructor for class weka.classifiers.trees.j48.EntropyBasedSplitCrit
 
entropyConditionedOnColumns(double[][]) - Static method in class weka.core.ContingencyTables
Computes conditional entropy of the rows given the columns.
entropyConditionedOnRows(double[][]) - Static method in class weka.core.ContingencyTables
Computes conditional entropy of the columns given the rows.
entropyConditionedOnRows(double[][], double[][], double) - Static method in class weka.core.ContingencyTables
Computes conditional entropy of the columns given the rows of the test matrix with respect to the train matrix.
entropyGain() - Method in class weka.classifiers.trees.lmt.ResidualSplit
Computes entropy gain for current split.
entropyOverColumns(double[][]) - Static method in class weka.core.ContingencyTables
Computes the columns' entropy for the given contingency table.
entropyOverRows(double[][]) - Static method in class weka.core.ContingencyTables
Computes the rows' entropy for the given contingency table.
EntropySplitCrit - Class in weka.classifiers.trees.j48
Class for computing the entropy for a given distribution.
EntropySplitCrit() - Constructor for class weka.classifiers.trees.j48.EntropySplitCrit
 
enumerateAttributes() - Method in class weka.core.Instance
Returns an enumeration of all the attributes.
enumerateAttributes() - Method in class weka.core.Instances
Returns an enumeration of all the attributes.
enumerateInstances() - Method in class weka.core.Instances
Returns an enumeration of all instances in the dataset.
enumerateLiterals() - Method in class weka.associations.tertius.LiteralSet
Enumerate the literals contained in this set.
enumerateMeasures() - Method in class weka.classifiers.bayes.BayesNet
Returns an enumeration of the measure names.
enumerateMeasures() - Method in class weka.classifiers.functions.SimpleLogistic
Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.functions.SMOreg
Returns an enumeration of the measure names.
enumerateMeasures() - Method in class weka.classifiers.lazy.IBk
Returns an enumeration of the additional measure names produced by the neighbour search algorithm, plus the chosen K in case cross-validation is enabled.
enumerateMeasures() - Method in class weka.classifiers.lazy.LWL
Returns an enumeration of the additional measure names produced by the neighbour search algorithm.
enumerateMeasures() - Method in class weka.classifiers.meta.AdditiveRegression
Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.meta.Bagging
Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.classifiers.meta.GridSearch
Returns an enumeration of the measure names.
enumerateMeasures() - Method in class weka.classifiers.rules.DecisionTable
Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.rules.DTNB
Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.rules.JRip
Returns an enumeration of the additional measure names