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

A

abortExperiment() - Method in class weka.experiment.RemoteExperiment
Set the abort flag
ABS - Static variable in interface weka.core.mathematicalexpression.sym
 
ABS - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
 
AbstractAssociator - Class in weka.associations
Abstract scheme for learning associations.
AbstractAssociator() - Constructor for class weka.associations.AbstractAssociator
 
AbstractClusterer - Class in weka.clusterers
Abstract clusterer.
AbstractClusterer() - Constructor for class weka.clusterers.AbstractClusterer
 
AbstractDataSink - Class in weka.gui.beans
Abstract class for objects that store instances to some destination.
AbstractDataSink() - Constructor for class weka.gui.beans.AbstractDataSink
 
AbstractDataSinkBeanInfo - Class in weka.gui.beans
Bean info class for the AbstractDataSink
AbstractDataSinkBeanInfo() - Constructor for class weka.gui.beans.AbstractDataSinkBeanInfo
 
AbstractDataSource - Class in weka.gui.beans
Abstract class for objects that can provide instances from some source
AbstractDataSource() - Constructor for class weka.gui.beans.AbstractDataSource
Creates a new AbstractDataSource instance.
AbstractDataSourceBeanInfo - Class in weka.gui.beans
Bean info class for AbstractDataSource.
AbstractDataSourceBeanInfo() - Constructor for class weka.gui.beans.AbstractDataSourceBeanInfo
 
AbstractDensityBasedClusterer - Class in weka.clusterers
Abstract clustering model that produces (for each test instance) an estimate of the membership in each cluster (ie.
AbstractDensityBasedClusterer() - Constructor for class weka.clusterers.AbstractDensityBasedClusterer
 
AbstractEvaluator - Class in weka.gui.beans
Abstract class for objects that can provide some kind of evaluation for classifier, clusterers etc.
AbstractEvaluator() - Constructor for class weka.gui.beans.AbstractEvaluator
Constructor
AbstractFileLoader - Class in weka.core.converters
Abstract superclass for all file loaders.
AbstractFileLoader() - Constructor for class weka.core.converters.AbstractFileLoader
 
AbstractFileSaver - Class in weka.core.converters
Abstract class for Savers that save to a file Valid options are: -i input arff file
The input filw in arff format.
AbstractFileSaver() - Constructor for class weka.core.converters.AbstractFileSaver
 
AbstractLoader - Class in weka.core.converters
Abstract class gives default implementation of setSource methods.
AbstractLoader() - Constructor for class weka.core.converters.AbstractLoader
 
AbstractOutput - Class in weka.classifiers.evaluation.output.prediction
A superclass for outputting the classifications of a classifier.
AbstractOutput() - Constructor for class weka.classifiers.evaluation.output.prediction.AbstractOutput
Initializes the output class.
AbstractSaver - Class in weka.core.converters
Abstract class for Saver
AbstractSaver() - Constructor for class weka.core.converters.AbstractSaver
 
AbstractStringDistanceFunction - Class in weka.core
Represents the abstract ancestor for string-based distance functions, like EditDistance.
AbstractStringDistanceFunction() - Constructor for class weka.core.AbstractStringDistanceFunction
Constructor that doesn't set the data
AbstractStringDistanceFunction(Instances) - Constructor for class weka.core.AbstractStringDistanceFunction
Constructor that sets the data
AbstractTestSetProducer - Class in weka.gui.beans
Abstract class for TestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
AbstractTestSetProducer() - Constructor for class weka.gui.beans.AbstractTestSetProducer
Creates a new AbstractTestSetProducer instance.
AbstractTestSetProducerBeanInfo - Class in weka.gui.beans
BeanInfo class for AbstractTestSetProducer
AbstractTestSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTestSetProducerBeanInfo
 
AbstractTimeSeries - Class in weka.filters.unsupervised.attribute
An abstract instance filter that assumes instances form time-series data and performs some merging of attribute values in the current instance with attribute attribute values of some previous (or future) instance.
AbstractTimeSeries() - Constructor for class weka.filters.unsupervised.attribute.AbstractTimeSeries
 
AbstractTrainAndTestSetProducer - Class in weka.gui.beans
Abstract base class for TrainAndTestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
AbstractTrainAndTestSetProducer() - Constructor for class weka.gui.beans.AbstractTrainAndTestSetProducer
Creates a new AbstractTrainAndTestSetProducer instance.
AbstractTrainAndTestSetProducerBeanInfo - Class in weka.gui.beans
Bean info class for AbstractTrainAndTestSetProducers
AbstractTrainAndTestSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo
 
AbstractTrainingSetProducer - Class in weka.gui.beans
Abstract class for TrainingSetProducers that contains default implementations of add/remove listener methods and default visual representation
AbstractTrainingSetProducer() - Constructor for class weka.gui.beans.AbstractTrainingSetProducer
Creates a new AbstractTrainingSetProducer instance.
AbstractTrainingSetProducerBeanInfo - Class in weka.gui.beans
BeanInfo class for AbstractTrainingSetProducer
AbstractTrainingSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTrainingSetProducerBeanInfo
 
accept(File) - Method in class weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.SERFileFilter
Whether the given file is accepted by this filter.
accept(File) - Method in class weka.gui.ExtensionFileFilter
Returns true if the supplied file should be accepted (i.e.: if it has the required extension or is a directory).
accept(File, String) - Method in class weka.gui.ExtensionFileFilter
Returns true if the file in the given directory with the given name should be accepted.
ACCEPT - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
States that the user has accepted the tree.
acceptClassifier(BatchClassifierEvent) - Method in interface weka.gui.beans.BatchClassifierListener
Accept a BatchClassifierEvent
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
Accept a classifier to be evaluated
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.IncrementalClassifierEvaluator
Accepts and processes a classifier encapsulated in an incremental classifier event
acceptClassifier(IncrementalClassifierEvent) - Method in interface weka.gui.beans.IncrementalClassifierListener
Accept the event
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.PredictionAppender
Accept and process an incremental classifier event
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.PredictionAppender
Accept and process a batch classifier event
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.SerializedModelSaver
Accept and save an incrementally trained classifier.
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.SerializedModelSaver
Accept and save a batch trained classifier.
acceptClusterer(BatchClustererEvent) - Method in interface weka.gui.beans.BatchClustererListener
Accept a BatchClustererEvent
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.ClustererPerformanceEvaluator
Accept a clusterer to be evaluated
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.PredictionAppender
Accept and process a batch clusterer event
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.SerializedModelSaver
Accept and save a batch trained clusterer.
acceptConfiguration(ConfigurationEvent) - Method in interface weka.gui.beans.ConfigurationListener
Implementers do not have to do anything in this method (see the above documentation).
acceptDataPoint(ChartEvent) - Method in interface weka.gui.beans.ChartListener
 
acceptDataPoint(ChartEvent) - Method in class weka.gui.beans.StripChart
Accept a data point (encapsulated in a chart event) to plot
acceptDataPoint(double[]) - Method in class weka.gui.beans.StripChart
Accept a data point to plot
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.AbstractDataSink
Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
Subclass must implement
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Associator
 
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.ClassAssigner
 
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.ClassValuePicker
 
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker
Accept a data set
acceptDataSet(DataSetEvent) - Method in interface weka.gui.beans.DataSourceListener
 
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.DataVisualizer
Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Filter
Accept a data set
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.ModelPerformanceChart
Display a threshold curve.
acceptDataSet(VisualizableErrorEvent) - Method in class weka.gui.beans.ModelPerformanceChart
Display a scheme error plot.
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Saver
Method reacts to a dataset event and starts the writing process in batch mode
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TestSetMaker
Accepts and processes a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TextViewer
Accept a data set for displaying as text
acceptDataSet(ThresholdDataEvent) - Method in interface weka.gui.beans.ThresholdDataListener
 
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TrainingSetMaker
Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker
Accept a data set
acceptDataSet(VisualizableErrorEvent) - Method in interface weka.gui.beans.VisualizableErrorListener
 
acceptGraph(GraphEvent) - Method in interface weka.gui.beans.GraphListener
Describe acceptGraph method here.
acceptGraph(GraphEvent) - Method in class weka.gui.beans.GraphViewer
Accept a graph
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.AbstractDataSink
Accept an instance
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.ClassAssigner
 
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Classifier
Accepts an instance for incremental processing.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Filter
Accept an instance for processing by StreamableFilters only
acceptInstance(InstanceEvent) - Method in interface weka.gui.beans.InstanceListener
Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
Accept an instance to add to the batch.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Saver
Methods reacts to instance events and saves instances incrementally.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.StripChart
 
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.AveragingResultProducer
Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.CSVResultListener
Just prints out each result as it is received.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseResultListener
Submit the result to the appropriate table of the database
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseResultProducer
Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.InstancesResultListener
Collects each instance and adjusts the header information.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.LearningRateResultProducer
Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in interface weka.experiment.ResultListener
Accepts results from a ResultProducer.
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.AbstractDataSink
Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.ClassAssigner
 
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Classifier
Accepts a test set for a batch trained classifier
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Clusterer
Accepts a test set for a batch trained clusterer
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker
Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.DataVisualizer
Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Filter
Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Saver
Method reacts to a test set event and starts the writing process in batch mode
acceptTestSet(TestSetEvent) - Method in interface weka.gui.beans.TestSetListener
Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TextViewer
Accept a test set for displaying as text
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker
Accept a test set
acceptText(TextEvent) - Method in interface weka.gui.beans.TextListener
Accept and process a text event
acceptText(TextEvent) - Method in class weka.gui.beans.TextViewer
Accept some text
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.AbstractDataSink
Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Associator
Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.ClassAssigner
 
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Classifier
Accepts a training set and builds batch classifier
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Clusterer
Accepts a training set and builds batch clusterer
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker
Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.DataVisualizer
Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Filter
Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Saver
Method reacts to a training set event and starts the writing process in batch mode
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TextViewer
Accept a training set for displaying as text
acceptTrainingSet(TrainingSetEvent) - Method in interface weka.gui.beans.TrainingSetListener
Accept and process a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker
Accept a training set
accuracy() - Method in class weka.associations.RuleItem
Gets the expected predictive accuracy of a rule
ACCURACY - Static variable in class weka.classifiers.meta.ThresholdSelector
accuracy
actEntropy - Variable in class weka.classifiers.lazy.kstar.KStarWrapper
used/reused to hold the actual entropy
action_table() - Method in class weka.core.mathematicalexpression.Parser
Access to parse-action table.
action_table() - Method in class weka.filters.unsupervised.instance.subsetbyexpression.Parser
Access to parse-action table.
actionPerformed(ActionEvent) - Method in class weka.gui.arffviewer.ArffPanel
invoked when an action occurs
actionPerformed(ActionEvent) - Method in class weka.gui.arffviewer.ArffViewerMainPanel
invoked when an action occurs
actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.AddModelsPanel
This will support the button triggered events for this panel.
actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.DefaultModelsPanel
Deals with user input to the various buttons in this GUI
actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.ListModelsPanel
This handles all of the button events.
actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.LoadModelsPanel
This will support the button triggered events for this panel.
actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.tree.GenericObjectNodeEditor
This implements the action listener for the buttons in this editor, If they hit the choose class button then the popup menu for choosing the generic object ype is created.
actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.tree.ModelTreeNodeEditor
The item Listener that gets registered with all node editors that have a widget that had actionPerformed events.
actionPerformed(ActionEvent) - Method in class weka.gui.ensembleLibraryEditor.tree.NumberNodeEditor
This is the actionListener that while handle events from the JButton that specifies the type of iterator.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.AlgorithmListPanel
Handle actions when buttons get pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.DatasetListPanel
Handle actions when buttons get pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel
Handles the various button clicking type activities.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.HostListPanel
Handle actions when text is entered into the host field or the delete button is pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.RunPanel
Controls starting and stopping the experiment.
actionPerformed(ActionEvent) - Method in class weka.gui.SimpleCLIPanel
Only gets called when return is pressed in the input area, which starts the command running.
actionPerformed(ActionEvent) - Method in class weka.gui.streams.InstanceLoader
 
actionPerformed(ActionEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer
Performs the action associated with the ActionEvent.
actual() - Method in class weka.classifiers.evaluation.NominalPrediction
Gets the actual class value.
actual() - Method in class weka.classifiers.evaluation.NumericPrediction
Gets the actual class value.
actual() - Method in interface weka.classifiers.evaluation.Prediction
Gets the actual class value.
actualNumBags() - Method in class weka.classifiers.trees.j48.Distribution
Returns number of non-empty bags of distribution.
actualNumClasses() - Method in class weka.classifiers.trees.j48.Distribution
Returns number of classes actually occuring in distribution.
actualNumClasses(int) - Method in class weka.classifiers.trees.j48.Distribution
Returns number of classes actually occuring in given bag.
acuityTipText() - Method in class weka.clusterers.Cobweb
Returns the tip text for this property
AdaBoostM1 - Class in weka.classifiers.meta
Class for boosting a nominal class classifier using the Adaboost M1 method.
AdaBoostM1() - Constructor for class weka.classifiers.meta.AdaBoostM1
Constructor.
add(Object) - Method in class weka.associations.tertius.SimpleLinkedList
 
add(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution
Adds given instance to given bag.
add(int, double[]) - Method in class weka.classifiers.trees.j48.Distribution
Adds counts to given bag.
add(double, Object) - Method in class weka.clusterers.forOPTICSAndDBScan.Utils.PriorityQueue
Adds a new Object to the queue
add(double, Object, String) - Method in class weka.clusterers.forOPTICSAndDBScan.Utils.UpdateQueue
Adds a new Object to the queue
add(AlgVector) - Method in class weka.core.AlgVector
Returns the sum of this vector with another.
add(Instance) - Method in class weka.core.Instances
Adds one instance to the end of the set.
add(Matrix) - Method in class weka.core.Matrix
Deprecated. Returns the sum of this matrix with another.
add(String) - Method in class weka.core.Stopwords
adds the given word to the stopword list (is automatically converted to lower case and trimmed)
add(TechnicalInformation) - Method in class weka.core.TechnicalInformation
adds the given information to the list of additional technical informations
add(TechnicalInformation.Type) - Method in class weka.core.TechnicalInformation
Adds an empty technical information with the given type to the list of additional informations and returns the instance.
add(PrintStream) - Method in class weka.core.Tee
adds the given PrintStream to the list of streams, with NO timestamp and NO prefix.
add(PrintStream, boolean) - Method in class weka.core.Tee
adds the given PrintStream to the list of streams, with NO prefix.
add(PrintStream, boolean, String) - Method in class weka.core.Tee
adds the given PrintStream to the list of streams.
add(String) - Method in class weka.core.Trie
Ensures that this collection contains the specified element.
add(String) - Method in class weka.core.Trie.TrieNode
adds the given string to its children (creates children if necessary)
add(String, Method) - Method in class weka.core.xml.MethodHandler
adds the specified method for the property with the given displayname to its internal list.
add(Class, Method) - Method in class weka.core.xml.MethodHandler
adds the specified method for the given class to its internal list.
add(double, double) - Method in class weka.experiment.PairedStats
Add an observed pair of values.
add(double[], double[]) - Method in class weka.experiment.PairedStats
Adds an array of observed pair of values.
add(double) - Method in class weka.experiment.Stats
Adds a value to the observed values
add(double, double) - Method in class weka.experiment.Stats
Adds a value that has been seen n times to the observed values
Add - Class in weka.filters.unsupervised.attribute
An instance filter that adds a new attribute to the dataset.
Add() - Constructor for class weka.filters.unsupervised.attribute.Add
 
add(int, Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel
Inserts the specified element at the specified position in this list.
add(Object) - Method in class weka.gui.ensembleLibraryEditor.ModelList.SortedListModel
 
add(String) - Method in class weka.gui.HierarchyPropertyParser
Add the given item of property to the tree
ADD_CHILDREN - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
 
addActionListener(ActionListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
Register a listener to be notified when plotting completes
addActionListener(ActionListener) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel
Add a listener interested in kowing about editor status changes
addActionListener(ActionListener) - Method in class weka.gui.visualize.ClassPanel
Add an action listener that will be notified if the user changes the colour of a label
addActionListener(ActionListener) - Method in class weka.gui.visualize.VisualizePanel
Add a listener for this visualize panel
addAll(SimpleLinkedList) - Method in class weka.associations.tertius.SimpleLinkedList
 
addAll(Collection) - Method in class weka.core.neighboursearch.covertrees.Stack
Adds all the given elements in the stack.
addAll(Collection<? extends String>) - Method in class weka.core.Trie
Adds all of the elements in the specified collection to this collection
addAll(Object[]) - Method in class weka.gui.ensembleLibraryEditor.ModelList.SortedListModel
 
addAllBeansToContainer(JComponent) - Static method in class weka.gui.beans.BeanInstance
Adds all beans to the supplied component
addAllowed(Class, String) - Method in class weka.core.xml.PropertyHandler
adds the given property (display name) to the list of allowed properties for the specified class.
addAndUpdate(Rule) - Method in class weka.classifiers.rules.RuleStats
Add a rule to the ruleset and update the stats
addArc(String, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
addArc(int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
addArc(String, FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Add arc between parent node and each of the nodes in a given list.
addAttributePanelListener(AttributePanelListener) - Method in class weka.gui.visualize.AttributePanel
Add a listener to the list of things listening to this panel
addBatchClassifierListener(BatchClassifierListener) - Method in class weka.gui.beans.Classifier
Add a batch classifier listener
addBatchClustererListener(BatchClustererListener) - Method in class weka.gui.beans.Clusterer
Add a batch clusterer listener
addBean(JComponent) - Method in class weka.gui.beans.BeanInstance
Adds this bean to the global list of beans and to the supplied container.
addBefore(Object) - Method in class weka.associations.tertius.SimpleLinkedList.LinkedListIterator
 
addCancelListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel
This is used to hook an action listener to the cancel button.
addCapabilitiesFilterListener(Explorer.CapabilitiesFilterChangeListener) - Method in class weka.gui.explorer.Explorer
adds the listener to the list of objects that listen for changes of the CapabilitiesFilter
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffPanel
Adds a ChangeListener to the panel
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffTable
Adds a ChangeListener to the panel
addChartListener(ChartListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator
Add a chart listener
addCheckBoxActionListener(ActionListener) - Method in class weka.gui.experiment.DistributeExperimentPanel
Enable objects to listen for changes to the check box
addChild(Splitter, ADTree) - Method in class weka.classifiers.trees.adtree.PredictionNode
Adds a child to this node.
addChild(Edge) - Method in class weka.gui.treevisualizer.Node
Set the value of children.
addChildClique(MarginCalculator.JunctionTreeNode) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
 
addChildFrame(Container) - Method in class weka.gui.GUIChooser
adds the given child frame to the list of frames.
addChildFrame(Container) - Method in class weka.gui.Main
adds the given child frame to the list of frames.
AddClassification - Class in weka.filters.supervised.attribute
A filter for adding the classification, the class distribution and an error flag to a dataset with a classifier.
AddClassification() - Constructor for class weka.filters.supervised.attribute.AddClassification
 
AddCluster - Class in weka.filters.unsupervised.attribute
A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm.
Either the clustering algorithm gets built with the first batch of data or one specifies are serialized clusterer model file to use instead.
AddCluster() - Constructor for class weka.filters.unsupervised.attribute.AddCluster
 
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Associator
We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Classifier
We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Clusterer
We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in interface weka.gui.beans.ConfigurationProducer
We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Filter
We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConnectionListener(ConnectionListener) - Method in class weka.gui.sql.ConnectionPanel
adds the given listener to the list of listeners.
addConnectionListener(ConnectionListener) - Method in class weka.gui.sql.SqlViewer
adds the given listener to the list of listeners.
addCons(int[]) - Method in class weka.associations.PriorEstimation
generates a class association rule out of a given premise.
addCVParameter(String) - Method in class weka.classifiers.meta.CVParameterSelection
Adds a scheme parameter to the list of parameters to be set by cross-validation
addDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassAssigner
 
addDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassValuePicker
 
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.AbstractDataSource
Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassAssigner
 
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassValuePicker
 
addDataSourceListener(DataSourceListener) - Method in interface weka.gui.beans.DataSource
Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.DataVisualizer
Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Filter
Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
 
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Loader
Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.PredictionAppender
Add a datasource listener
addEditorNodes(String, String) - Method in class weka.gui.ensembleLibraryEditor.tree.PropertyNode
This method figures out what kind of parameter type this node represents and then creates the appropriate set of child nodes for editing.
addElement(Literal) - Method in class weka.associations.tertius.LiteralSet
Add a Literal to this set.
addElement(Object) - Method in class weka.core.FastVector
Adds an element to this vector.
addElement(int, int, double) - Method in class weka.core.Matrix
Deprecated. Add a value to an element.
addElement(double) - Method in class weka.core.matrix.DoubleVector
Adds an element into the vector
addElement(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel
Adds the specified component to the end of this list.
addErrs(double, double, float) - Static method in class weka.classifiers.trees.j48.Stats
Computes estimated extra error for given total number of instances and error using normal approximation to binomial distribution (and continuity correction).
AddExpression - Class in weka.filters.unsupervised.attribute
An instance filter that creates a new attribute by applying a mathematical expression to existing attributes.
AddExpression() - Constructor for class weka.filters.unsupervised.attribute.AddExpression
 
addFile(String) - Static method in class weka.core.ClassloaderUtil
Add file to CLASSPATH
addFile(File) - Static method in class weka.core.ClassloaderUtil
Add file to CLASSPATH
addFirst(Object) - Method in class weka.associations.tertius.SimpleLinkedList
 
addGraphListener(GraphListener) - Method in class weka.gui.beans.Associator
Add a graph listener
addGraphListener(GraphListener) - Method in class weka.gui.beans.Classifier
Add a graph listener
addGraphListener(GraphListener) - Method in class weka.gui.beans.Clusterer
Add a graph listener
addHeader(String, String) - Method in class weka.experiment.ResultMatrix
adds the key-value pair to the header.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.ConnectionPanel
adds the given listener to the list of listeners.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.QueryPanel
adds the given listener to the list of listeners.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.SqlViewer
adds the given listener to the list of listeners.
AddID - Class in weka.filters.unsupervised.attribute
An instance filter that adds an ID attribute to the dataset.
AddID() - Constructor for class weka.filters.unsupervised.attribute.AddID
 
addIgnored(String) - Method in class weka.core.xml.PropertyHandler
adds the given display name of a property to the ignore list.
addIgnored(Class, String) - Method in class weka.core.xml.PropertyHandler
adds the given class with the display name of a property to the ignore list.
addIncrementalClassifierListener(IncrementalClassifierListener) - Method in class weka.gui.beans.Classifier
Add an incremental classifier listener
addInstance(Instance) - Method in class weka.clusterers.Cobweb
Deprecated. updateClusterer(Instance) should be used instead
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor
Adds an instance to the ball tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor
Adds an instance to the ball tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor
Adds an instance to the tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor
Adds an instance to the ball tree.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.BallTree
Adds the given instance's info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.CoverTree
Adds the given instance info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.KDTree
Adds one instance to KDTree loosly.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.LinearNNSearch
Adds the given instance info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.NearestNeighbourSearch
Adds information from the given instance without modifying the datastructure a lot.
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.AbstractDataSource
Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.ClassAssigner
 
addInstanceListener(InstanceListener) - Method in interface weka.gui.beans.DataSource
Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Filter
Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
 
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Loader
Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.PredictionAppender
Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceJoiner
 
addInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceLoader
 
addInstanceListener(InstanceListener) - Method in interface weka.gui.streams.InstanceProducer
 
addInstanceNumberAttribute() - Method in class weka.gui.visualize.PlotData2D
Adds an instance number attribute to the plottable instances,
AddInstanceToBestCluster(Instance) - Method in class weka.clusterers.CLOPE
Add instance to best cluster
addInstWithUnknown(Instances, int) - Method in class weka.classifiers.trees.j48.Distribution
Adds all instances with unknown values for given attribute, weighted according to frequency of instances in each bag.
additional() - Method in class weka.core.TechnicalInformation
returns an enumeration of all the additional technical informations (if there are any)
AdditionalMeasureProducer - Interface in weka.core
Interface to something that can produce measures other than those calculated by evaluation modules.
AdditiveRegression - Class in weka.classifiers.meta
Meta classifier that enhances the performance of a regression base classifier.
AdditiveRegression() - Constructor for class weka.classifiers.meta.AdditiveRegression
Default constructor specifying DecisionStump as the classifier
AdditiveRegression(Classifier) - Constructor for class weka.classifiers.meta.AdditiveRegression
Constructor which takes base classifier as argument.
addKeyword(String, MutableAttributeSet) - Method in class weka.gui.scripting.SyntaxDocument
Associates a keyword with a particular formatting style.
addKeywords(String[], MutableAttributeSet) - Method in class weka.gui.scripting.SyntaxDocument
Associates the keywords with a particular formatting style.
addLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
Method to add a LayoutCompleteEventListener
addLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in interface weka.gui.graphvisualizer.LayoutEngine
This method adds a LayoutCompleteEventListener to the LayoutEngine.
addLiteral(Literal) - Method in class weka.associations.tertius.Predicate
 
addModel(EnsembleLibraryModel) - Method in class weka.classifiers.EnsembleLibrary
adds a LibraryModel to the Library
addModel(String) - Method in class weka.classifiers.EnsembleLibrary
adds a LibraryModel to the Library
addModel(EnsembleLibraryModel) - Method in class weka.gui.ensembleLibraryEditor.ListModelsPanel
Adds a model to the current library
AddModelsPanel - Class in weka.gui.ensembleLibraryEditor
The purpose of this class is to create a user interface that will provide an intuitive method of building "playlists" of weka classifiers to be trained.
AddModelsPanel(ListModelsPanel) - Constructor for class weka.gui.ensembleLibraryEditor.AddModelsPanel
This constructor simply stores the reference to the ListModelsPanel and builf the user interface.
addMouseListener(MouseListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
Adds a mouse listener.
addMouseListenerToHeader(JTable) - Method in class weka.gui.SortedTableModel
adds a mouselistener to the header
addNode(String, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Add new node to the network, initializing instances, parentsets, distributions.
addNode(String, int, int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Add node to network at a given position, initializing instances, parentsets, distributions.
addNodeValue(int, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet
Add node value to a node.
AddNoise - Class in weka.filters.unsupervised.attribute
An instance filter that changes a percentage of a given attributes values.
AddNoise() - Constructor for class weka.filters.unsupervised.attribute.AddNoise
 
addNoise(Instances, int, int, int, boolean) - Method in class weka.filters.unsupervised.attribute.AddNoise
add noise to the dataset a given percentage of the instances are changed in the way, that a set of instances are randomly selected using seed.
addNumbers(Number, Number) - Method in class weka.gui.ensembleLibraryEditor.tree.NumberNode
adds two objects that are instances of one of the child classes of java.lang.Number
addObject(String, Object) - Method in class weka.gui.ResultHistoryPanel
Adds an object to the results list
addOkListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel
This is used to hook an action listener to the ok button.
addParent(int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet
Add parent to parent set and update internals (specifically the cardinality of the parent set)
addParent(int, int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet
Add parent to parent set at specific location and update internals (specifically the cardinality of the parent set)
addPlot(PlotData2D) - Method in class weka.gui.visualize.Plot2D
Add a plot to the list of plots to display
addPlot(PlotData2D) - Method in class weka.gui.visualize.VisualizePanel
Set a new plot to the visualize panel
addPrediction(NominalPrediction) - Method in class weka.classifiers.evaluation.ConfusionMatrix
Includes a prediction in the confusion matrix.
addPredictions(FastVector) - Method in class weka.classifiers.evaluation.ConfusionMatrix
Includes a whole bunch of predictions in the confusion matrix.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.classifiers.EnsembleLibrary
Adds an object to the list of those that wish to be informed when the library changes.
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.AbstractDataSource
Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.AssociatorCustomizer
Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.BeanVisual
Add a listener for property change events
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassAssignerCustomizer
Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierCustomizer
Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassValuePickerCustomizer
Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClustererCustomizer
Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer
Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.DataVisualizer
Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.FilterCustomizer
Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer
Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.LoaderCustomizer
Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart
Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.PredictionAppenderCustomizer
Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SaverCustomizer
Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SerializedModelSaverCustomizer
Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.StripChartCustomizer
Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.TextViewer
Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer
Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.CostMatrixEditor
Adds an object to the list of those that wish to be informed when the cost matrix changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.EnsembleLibraryEditor
Adds an object to the list of those that wish to be informed when the library changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupModePanel
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupPanel
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SimpleSetupPanel
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.PreprocessPanel
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericArrayEditor
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericObjectEditor
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.PropertySheetPanel
Adds a PropertyChangeListener.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SetInstancesPanel
Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SimpleDateFormatEditor
Adds an object to the list of those that wish to be informed when the date format changes.
addPropertyChangeListenersSubFlow(PropertyChangeListener) - Method in class weka.gui.beans.MetaBean
 
addPSFontReplacement(String, String) - Static method in class weka.gui.visualize.PostscriptGraphics
adds the PS font name to replace and its replacement in the replacement hashtable
addQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.QueryPanel
adds the given listener to the list of listeners.
addQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.SqlViewer
adds the given listener to the list of listeners.
addRange(int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution
Adds all instances in given range to given bag.
addReference(Instance) - Method in class weka.classifiers.trees.adtree.ReferenceInstances
Adds one instance reference to the end of the set.
addRelation(Instances) - Method in class weka.core.Attribute
Adds a relation to a relation-valued attribute.
addRemoteExperimentListener(RemoteExperimentListener) - Method in class weka.experiment.RemoteExperiment
Add an object to the list of those interested in recieving update information from the RemoteExperiment
addRemoteExperimentListener(RemoteExperimentListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed
Add an object to the list of those interested in recieving update information from the RemoteExperiment
addRemoteHost(String) - Method in class weka.experiment.RemoteExperiment
Add a host name to the list of remote hosts
addRenderingHints(Map) - Method in class weka.gui.visualize.PostscriptGraphics
 
addRepaintNotify(Component) - Method in class weka.gui.visualize.ClassPanel
Adds a component that will need to be repainted if the user changes the colour of a label.
addRepaintNotify(Component) - Method in class weka.gui.visualize.LegendPanel
Adds a component that will need to be repainted if the user changes the colour of a label.
addResult(String, StringBuffer) - Method in class weka.gui.ResultHistoryPanel
Adds a new result to the result list.
addResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.ResultPanel
adds the given listener to the list of listeners
addResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.SqlViewer
adds the given listener to the list of listeners.
addScriptFinishedListener(ScriptExecutionListener) - Method in class weka.gui.scripting.Script
Adds the given listener to its internal list.
addStartupListener(StartUpListener) - Static method in class weka.gui.beans.KnowledgeFlowApp
Add a listener to be notified when startup is complete
addStartupListener(StartUpListener) - Static method in class weka.gui.Main
Add a listener to be notified when startup is complete.
addStringValue(String) - Method in class weka.core.Attribute
Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addStringValue(Attribute, int) - Method in class weka.core.Attribute
Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffSortedTableModel
adds a listener to the list that is notified each time a change to data model occurs
addTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffTableModel
adds a listener to the list that is notified each time a change to data model occurs
addTableModelListener(TableModelListener) - Method in class weka.gui.sql.ResultSetTableModel
adds a listener to the list that is notified each time a change to data model occurs.
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTestSetProducer
Add a listener for test sets
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
Add a test set listener
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.ClassAssigner
 
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.Filter
Add a test set listener
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.PredictionAppender
Add a test set listener
addTestSetListener(TestSetListener) - Method in interface weka.gui.beans.TestSetProducer
Add a listener for test set events
addTextListener(TextListener) - Method in class weka.gui.beans.Associator
Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.Classifier
Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.Clusterer
Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.ClustererPerformanceEvaluator
Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator
Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.TextViewer
Add a text listener
addThresholdDataListener(ThresholdDataListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
Add a threshold data listener
addTitleUpdatedListener(TitleUpdatedListener) - Method in class weka.gui.scripting.ScriptingPanel
Adds the listener to the internal list.
addToList(Object[], double) - Method in class weka.attributeSelection.BestFirst.LinkedList2
adds an element (Link) to the list.
addToList(Object[], double) - Method in class weka.attributeSelection.LFSMethods.LinkedList2
adds an element (Link) to the list.
addTrainingInstance(Instance) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
Adds a training instance to the visualization dataset.
addTrainingInstanceFromMouseLocation(int, int, int, double) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel
Adds a training instance to our dataset, based on the coordinates of the mouse on the panel.
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer
Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainingSetProducer
Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.ClassAssigner
 
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.Filter
Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.PredictionAppender
Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in interface weka.gui.beans.TrainingSetProducer
Add a training set listener
addUndoPoint() - Method in interface weka.core.Undoable
adds an undo point to the undo history
addUndoPoint() - Method in class weka.gui.arffviewer.ArffPanel
adds the current state of the instances to the undolist
addUndoPoint() - Method in class weka.gui.arffviewer.ArffSortedTableModel
adds an undo point to the undo history
addUndoPoint() - Method in class weka.gui.arffviewer.ArffTableModel
adds an undo point to the undo history, if the undo support is enabled
addUndoPoint() - Method in class weka.gui.explorer.PreprocessPanel
Backs up the current state of the dataset, so the changes can be undone.
addURL(URL) - Static method in class weka.core.ClassloaderUtil
Add URL to CLASSPATH
addValue(double, double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes
Add a new data value to the current estimator.
addValue(double, double, double) - Method in interface weka.estimators.ConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DDConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.DiscreteEstimator
Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DKConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DNConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.Estimator
Add a new data value to the current estimator.
addValue(double, double) - Method in interface weka.estimators.IncrementalEstimator
Add one value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.KDConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.KernelEstimator
Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.KKConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.MahalanobisEstimator
Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.NDConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.NNConditionalEstimator
Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.NormalEstimator
Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.PoissonEstimator
Add a new data value to the current estimator.
addValues(Instances, int) - Method in class weka.estimators.Estimator
Initialize the estimator with a new dataset.
addValues(Instances, int, double, double, double) - Method in class weka.estimators.Estimator
Initialize the estimator with all values of one attribute of a dataset.
addValues(Instances, int, int, int) - Method in class weka.estimators.Estimator
Initialize the estimator using only the instance of one class.
addValues(Instances, int, int, int, double, double) - Method in class weka.estimators.Estimator
Initialize the estimator using only the instance of one class.
AddValues - Class in weka.filters.unsupervised.attribute
Adds the labels from the given list to an attribute if they are missing.
AddValues() - Constructor for class weka.filters.unsupervised.attribute.AddValues
 
addVariable(String, String) - Method in class weka.core.Environment
Add a variable to the internal map.
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.AbstractDataSource
Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.DataVisualizer
Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.GraphViewer
Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart
Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.TextViewer
Add a vetoable change listener to this bean
addVisualizableErrorListener(VisualizableErrorListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator
Add a visualizable error listener
addWeights(Instance, double[]) - Method in class weka.classifiers.trees.j48.Distribution
Adds given instance to all bags weighting it according to given weights.
addWorkingDirectoryListener(PropertyChangeListener) - Method in class weka.classifiers.meta.ensembleSelection.EnsembleSelectionLibrary
Adds an object to the list of those that wish to be informed when the eotking directory changes.
adjustCenter(double) - Method in class weka.gui.treevisualizer.Node
Will increase or decrease the postion of center.
adjustSize(SERObject) - Method in class weka.clusterers.forOPTICSAndDBScan.OPTICS_GUI.GraphPanel
Adjusts the size of this panel in respect of the shown content
adjustWeightsTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample
Returns the tip text for this property
ADNode - Class in weka.classifiers.bayes.net
The ADNode class implements the ADTree datastructure which increases the speed with which sub-contingency tables can be constructed from a data set in an Instances object.
ADNode() - Constructor for class weka.classifiers.bayes.net.ADNode
Creates new ADNode
ADTree - Class in weka.classifiers.trees
Class for generating an alternating decision tree.
ADTree() - Constructor for class weka.classifiers.trees.ADTree
 
advanceCounters() - Method in class weka.experiment.Experiment
Increments iteration counters appropriately.
advanceCounters() - Method in class weka.experiment.RemoteExperiment
overides the one in Experiment
Agrawal - Class in weka.datagenerators.classifiers.classification
Generates a people database and is based on the paper by Agrawal et al.:
R.
Agrawal() - Constructor for class weka.datagenerators.classifiers.classification.Agrawal
initializes the generator with default values
AIC - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
 
ALGORITHM_BACKWARD - Static variable in class weka.classifiers.meta.EnsembleSelection
 
ALGORITHM_BEST - Static variable in class weka.classifiers.meta.EnsembleSelection
 
ALGORITHM_BUILD_LIBRARY - Static variable in class weka.classifiers.meta.EnsembleSelection
 
ALGORITHM_FORWARD - Static variable in class weka.classifiers.meta.EnsembleSelection
The "enumeration" of the algorithms we can use.
ALGORITHM_FORWARD_BACKWARD - Static variable in class weka.classifiers.meta.EnsembleSelection
 
ALGORITHM_HAAR - Static variable in class weka.filters.unsupervised.attribute.Wavelet
the type of algorithm: Haar wavelet
ALGORITHM_PLS1 - Static variable in class weka.filters.supervised.attribute.PLSFilter
the type of algorithm: PLS1
ALGORITHM_SIMPLS - Static variable in class weka.filters.supervised.attribute.PLSFilter
the type of algorithm: SIMPLS
AlgorithmListPanel - Class in weka.gui.experiment
This panel controls setting a list of algorithms for an experiment to iterate over.
AlgorithmListPanel(Experiment) - Constructor for class weka.gui.experiment.AlgorithmListPanel
Creates the algorithm list panel with the given experiment.
AlgorithmListPanel() - Constructor for class weka.gui.experiment.AlgorithmListPanel
Create the algorithm list panel initially disabled.
AlgorithmListPanel.ObjectCellRenderer - Class in weka.gui.experiment
Class required to show the Classifiers nicely in the list
AlgorithmListPanel.ObjectCellRenderer() - Constructor for class weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer
 
algorithmTipText() - Method in class weka.classifiers.meta.EnsembleSelection
Returns the tip text for this property
algorithmTipText() - Method in class weka.filters.supervised.attribute.PLSFilter
Returns the tip text for this property
algorithmTipText() - Method in class weka.filters.unsupervised.attribute.Wavelet
Returns the tip text for this property
ALGORITHMTYPE_ARITHMETIC - Static variable in class weka.classifiers.mi.MILR
collective MI assumption, arithmetic mean for posteriors
ALGORITHMTYPE_DEFAULT - Static variable in class weka.classifiers.mi.MILR
standard MI assumption
ALGORITHMTYPE_GEOMETRIC - Static variable in class weka.classifiers.mi.MILR
collective MI assumption, geometric mean for posteriors
algorithmTypeTipText() - Method in class weka.classifiers.mi.MILR
Returns the tip text for this property
AlgVector - Class in weka.core
Class for performing operations on an algebraic vector of floating-point values.
AlgVector(int) - Constructor for class weka.core.AlgVector
Constructs a vector and initializes it with default values.
AlgVector(double[]) - Constructor for class weka.core.AlgVector
Constructs a vector using a given array.
AlgVector(Instances, Random) - Constructor for class weka.core.AlgVector
Constructs a vector using a given data format.
AlgVector(Instance) - Constructor for class weka.core.AlgVector
Constructs a vector using an instance.
alignBottom(FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet
align set of nodes with the bottom most node in the list
alignLeft(FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet
align set of nodes with the left most node in the list
alignRight(FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet
align set of nodes with the right most node in the list
alignTop(FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet
align set of nodes with the top most node in the list
ALL - Static variable in class weka.core.Debug
the log level All
AllFilter - Class in weka.filters
A simple instance filter that passes all instances directly through.
AllFilter() - Constructor for class weka.filters.AllFilter
 
AllJavadoc - Class in weka.core
Applies all known Javadoc-derived classes to a source file.
AllJavadoc() - Constructor for class weka.core.AllJavadoc
 
allowed() - Method in class weka.core.xml.PropertyHandler
returns an enumeration of the classnames for which only certain properties (display names) are allowed
allowUnclassifiedInstancesTipText() - Method in class weka.classifiers.trees.RandomTree
Returns the tip text for this property
AlphabeticTokenizer - Class in weka.core.tokenizers
Alphabetic string tokenizer, tokens are to be formed only from contiguous alphabetic sequences.
AlphabeticTokenizer() - Constructor for class weka.core.tokenizers.AlphabeticTokenizer
 
alphaTipText() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
 
alphaTipText() - Method in class weka.classifiers.functions.Winnow
Returns the tip text for this property
amplitudeTipText() - Method in class weka.datagenerators.classifiers.regression.Expression
Returns the tip text for this property
amplitudeTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat
Returns the tip text for this property
and(Capabilities) - Method in class weka.core.Capabilities
performs an AND conjunction with the capabilities of the given Capabilities object and updates itself
AND - Static variable in interface weka.core.mathematicalexpression.sym
 
AND - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
 
AODE - Class in weka.classifiers.bayes
AODE achieves highly accurate classification by averaging over all of a small space of alternative naive-Bayes-like models that have weaker (and hence less detrimental) independence assumptions than naive Bayes.
AODE() - Constructor for class weka.classifiers.bayes.AODE
 
AODEsr - Class in weka.classifiers.bayes
AODEsr augments AODE with Subsumption Resolution.AODEsr detects specializations between two attribute values at classification time and deletes the generalization attribute value.
For more information, see:
Fei Zheng, Geoffrey I.
AODEsr() - Constructor for class weka.classifiers.bayes.AODEsr
 
append(String, String) - Method in class weka.gui.sql.InfoPanel
adds the given message to the end of the list (with the associated icon at the beginning)
append(Object) - Method in class weka.gui.sql.InfoPanel
adds the given message to the end of the list
appendElements(FastVector) - Method in class weka.core.FastVector
Appends all elements of the supplied vector to this vector.
appendPredictedProbabilitiesTipText() - Method in class weka.gui.beans.PredictionAppender
Return a tip text suitable for displaying in a GUI
applyClassifier(PMMLModel, Instances) - Static method in class weka.core.pmml.PMMLFactory
 
applyCostMatrix(Instances, Random) - Method in class weka.classifiers.CostMatrix
Applies the cost matrix to a set of instances.
applyFileSizeFilters() - Method in class weka.gui.ensembleLibraryEditor.DefaultModelsPanel
Removes models from the list that fit the regular expressions defining models that have large file sizes
applyFilters(Pattern[]) - Method in class weka.gui.ensembleLibraryEditor.DefaultModelsPanel
This is the code common to the previous three methods.
applyMinMaxRescaleCast(double) - Method in class weka.core.pmml.TargetMetaInfo
Apply min and max, rescaleFactor, rescaleConstant and castInteger - in that order (where defined).
applyMissingAndOutlierTreatments(double[]) - Method in class weka.core.pmml.MiningSchema
Apply both missing and outlier treatments to an incoming instance.
applyMissingValuesTreatment(double[]) - Method in class weka.core.pmml.MiningSchema
Apply the missing value treatments (if any) to an incoming instance.
applyMissingValueTreatment(double) - Method in class weka.core.pmml.MiningFieldMetaInfo
Apply the missing value treatment method for this field.
applyOutlierTreatment(double) - Method in class weka.core.pmml.MiningFieldMetaInfo
Apply the outlier treatment method for this field.
applyOutlierTreatment(double[]) - Method in class weka.core.pmml.MiningSchema
Apply the outlier treatment methods (if any) to an incoming instance.
applyTestTimeFilters() - Method in class weka.gui.ensembleLibraryEditor.DefaultModelsPanel
Removes models from the list that fit the regular expressions defining models that have large test times
applyTrainTimeFilters() - Method in class weka.gui.ensembleLibraryEditor.DefaultModelsPanel
Removes models from the list that fit the regular expressions defining models that have large train times
APPROVE_OPTION - Static variable in class weka.gui.experiment.OutputFormatDialog
Signifies an OK property selection.
APPROVE_OPTION - Static variable in class weka.gui.ListSelectorDialog
Signifies an OK property selection
APPROVE_OPTION - Static variable in class weka.gui.PropertySelectorDialog
Signifies an OK property selection
APPROVE_OPTION - Static variable in class weka.gui.ViewerDialog
Signifies an OK property selection
Apriori - Class in weka.associations
Class implementing an Apriori-type algorithm.
Apriori() - Constructor for class weka.associations.Apriori
Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.
aprioriGen(FastVector) - Static method in class weka.associations.gsp.Sequence
Generates all possible candidate k-Sequences and prunes the ones that contain an infrequent (k-1)-Sequence.
AprioriItemSet - Class in weka.associations
Class for storing a set of items.
AprioriItemSet(int) - Constructor for class weka.associations.AprioriItemSet
Constructor
areaUnderROC(int) - Method in class weka.classifiers.Evaluation
Returns the area under ROC for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
ARFF_ATTRIBUTE - Static variable in class weka.core.Attribute
The keyword used to denote the start of an arff attribute declaration
ARFF_ATTRIBUTE_DATE - Static variable in class weka.core.Attribute
The keyword used to denote a date attribute
ARFF_ATTRIBUTE_INTEGER - Static variable in class weka.core.Attribute
A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_NUMERIC - Static variable in class weka.core.Attribute
A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_REAL - Static variable in class weka.core.Attribute
A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_RELATIONAL - Static variable in class weka.core.Attribute
The keyword used to denote a relation-valued attribute
ARFF_ATTRIBUTE_STRING - Static variable in class weka.core.Attribute
The keyword used to denote a string attribute
ARFF_DATA - Static variable in class weka.core.Instances
The keyword used to denote the start of the arff data section
ARFF_END_SUBRELATION - Static variable in class weka.core.Attribute
The keyword used to denote the end of the declaration of a subrelation
ARFF_RELATION - Static variable in class weka.core.Instances
The keyword used to denote the start of an arff header
ArffLoader - Class in weka.core.converters
Reads a source that is in arff (attribute relation file format) format.
ArffLoader() - Constructor for class weka.core.converters.ArffLoader
 
ArffLoader.ArffReader - Class in weka.core.converters
Reads data from an ARFF file, either in incremental or batch mode.
ArffLoader.ArffReader(Reader) - Constructor for class weka.core.converters.ArffLoader.ArffReader
Reads the data completely from the reader.
ArffLoader.ArffReader(Reader, int) - Constructor for class weka.core.converters.ArffLoader.ArffReader
Reads only the header and reserves the specified space for instances.
ArffLoader.ArffReader(Reader, Instances, int) - Constructor for class weka.core.converters.ArffLoader.ArffReader
Reads the data without header according to the specified template.
ArffLoader.ArffReader(Reader, Instances, int, int) - Constructor for class weka.core.converters.ArffLoader.ArffReader
Initializes the reader without reading the header according to the specified template.
ArffPanel - Class in weka.gui.arffviewer
A Panel representing an ARFF-Table and the associated filename.
ArffPanel() - Constructor for class weka.gui.arffviewer.ArffPanel
initializes the panel with no data
ArffPanel(String) - Constructor for class weka.gui.arffviewer.ArffPanel
initializes the panel and loads the specified file
ArffPanel(Instances) - Constructor for class weka.gui.arffviewer.ArffPanel
initializes the panel with the given data
ArffSaver - Class in weka.core.converters
Writes to a destination in arff text format.
ArffSaver() - Constructor for class weka.core.converters.ArffSaver
Constructor
ArffSortedTableModel - Class in weka.gui.arffviewer
A sorter for the ARFF-Viewer - necessary because of the custom CellRenderer.
ArffSortedTableModel(String) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel
initializes the sorter w/o a model, but loads the given file and creates from that a model
ArffSortedTableModel(Instances) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel
initializes the sorter w/o a model, but uses the given data to create a model from that
ArffSortedTableModel(TableModel) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel
initializes the sorter with the given model
ArffTable - Class in weka.gui.arffviewer
A specialized JTable for the Arff-Viewer.
ArffTable() - Constructor for class weka.gui.arffviewer.ArffTable
initializes with no model
ArffTable(TableModel) - Constructor for class weka.gui.arffviewer.ArffTable
initializes with the given model
ArffTableCellRenderer - Class in weka.gui.arffviewer
Handles the background colors for missing values differently than the DefaultTableCellRenderer.
ArffTableCellRenderer() - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer
initializes the Renderer with a standard color
ArffTableCellRenderer(Color, Color) - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer
initializes the Renderer with the given colors
ArffTableCellRenderer(Color, Color, Color, Color) - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer
initializes the Renderer with the given colors
ArffTableModel - Class in weka.gui.arffviewer
The model for the Arff-Viewer.
ArffTableModel(String) - Constructor for class weka.gui.arffviewer.ArffTableModel
initializes the object and loads the given file
ArffTableModel(Instances) - Constructor for class weka.gui.arffviewer.ArffTableModel
initializes the model with the given data
ArffViewer - Class in weka.gui.arffviewer
A little tool for viewing ARFF files.
ArffViewer() - Constructor for class weka.gui.arffviewer.ArffViewer
initializes the object
ArffViewerMainPanel - Class in weka.gui.arffviewer
The main panel of the ArffViewer.
ArffViewerMainPanel(Container) - Constructor for class weka.gui.arffviewer.ArffViewerMainPanel
initializes the object
Array - Class in weka.core.pmml
Class for encapsulating a PMML Array element.
Array.ArrayType - Enum in weka.core.pmml
 
arrayLeftDivide(Matrix) - Method in class weka.core.matrix.Matrix
Element-by-element left division, C = A.\B
arrayLeftDivideEquals(Matrix) - Method in class weka.core.matrix.Matrix
Element-by-element left division in place, A = A.\B
arrayRightDivide(Matrix) - Method in class weka.core.matrix.Matrix
Element-by-element right division, C = A./B
arrayRightDivideEquals(Matrix) - Method in class weka.core.matrix.Matrix
Element-by-element right division in place, A = A./B
arrayTimes(Matrix) - Method in class weka.core.matrix.Matrix
Element-by-element multiplication, C = A.*B
arrayTimesEquals(Matrix) - Method in class weka.core.matrix.Matrix
Element-by-element multiplication in place, A = A.*B
arrayToString(Object) - Static method in class weka.core.Utils
Returns the given Array in a string representation.
arrayToString(Object[]) - Static method in class weka.experiment.DatabaseUtils
Converts an array of objects to a string by inserting a space between each element.
artificialSizeTipText() - Method in class weka.classifiers.meta.Decorate
Returns the tip text for this property
ASEvaluation - Class in weka.attributeSelection
Abstract attribute selection evaluation class
ASEvaluation() - Constructor for class weka.attributeSelection.ASEvaluation
 
ASSearch - Class in weka.attributeSelection
Abstract attribute selection search class.
ASSearch() - Constructor for class weka.attributeSelection.ASSearch
 
assign(Capabilities) - Method in class weka.core.Capabilities
retrieves the data from the given Capabilities object
assign(TestInstances) - Method in class weka.core.TestInstances
updates itself with all the settings from the given TestInstances object
assign(Tester) - Method in class weka.experiment.PairedTTester
retrieves all the settings from the given Tester
assign(ResultMatrix) - Method in class weka.experiment.ResultMatrix
acquires the data from the given matrix.
assign(Tester) - Method in interface weka.experiment.Tester
retrieves all the settings from the given Tester
assignIDs(int) - Method in class weka.classifiers.trees.ft.FTtree
Assigns unique IDs to all nodes in the tree
assignIDs(int) - Method in class weka.classifiers.trees.j48.ClassifierTree
Assigns a uniqe id to every node in the tree.
assignIDs(int) - Method in class weka.classifiers.trees.lmt.LMTNode
Assigns unique IDs to all nodes in the tree
assignLeafModelNumbers(int) - Method in class weka.classifiers.trees.ft.FTtree
Assigns numbers to the logistic regression models at the leaves of the tree
assignLeafModelNumbers(int) - Method in class weka.classifiers.trees.lmt.LMTNode
Assigns numbers to the logistic regression models at the leaves of the tree
assignSubToCenters(KDTreeNode, Instances, int[], int[]) - Method in class weka.core.neighboursearch.KDTree
Assigns instances of this node to center.
associatedConnections(Vector) - Static method in class weka.gui.beans.BeanConnection
Returns a vector of BeanConnections associated with the supplied vector of BeanInstances, i.e.
associationAttributeClasses(double[][]) - Method in class weka.attributeSelection.SignificanceAttributeEval
evaluates an individual attribute by measuring the attribute-classes association
associationClassesAttribute(double[][]) - Method in class weka.attributeSelection.SignificanceAttributeEval
evaluates an individual attribute by measuring the classes-attribute association
AssociationsPanel - Class in weka.gui.explorer
This panel allows the user to select, configure, and run a scheme that learns associations.
AssociationsPanel() - Constructor for class weka.gui.explorer.AssociationsPanel
Creates the associator panel
Associator - Interface in weka.associations
 
Associator - Class in weka.gui.beans
Bean that wraps around weka.associations
Associator() - Constructor for class weka.gui.beans.Associator
Creates a new Associator instance.
AssociatorBeanInfo - Class in weka.gui.beans
BeanInfo class for the Associator wrapper bean
AssociatorBeanInfo() - Constructor for class weka.gui.beans.AssociatorBeanInfo
 
AssociatorCustomizer - Class in weka.gui.beans
GUI customizer for the associator wrapper bean
AssociatorCustomizer() - Constructor for class weka.gui.beans.AssociatorCustomizer
 
AssociatorEvaluation - Class in weka.associations
Class for evaluating Associaters.
AssociatorEvaluation() - Constructor for class weka.associations.AssociatorEvaluation
default constructor
associatorTipText() - Method in class weka.associations.SingleAssociatorEnhancer
Returns the tip text for this property
aSubsumesB(RuleItem, RuleItem) - Static method in class weka.associations.CaRuleGeneration
Methods that decides whether or not rule a subsumes rule b.
aSubsumesB(RuleItem, RuleItem) - Static method in class weka.associations.RuleGeneration
Methods that decides whether or not rule a subsumes rule b.
ATT_ARRAY - Static variable in class weka.core.xml.XMLSerialization
the tag whether array or not (yes/no)
ATT_ARRAY_DEFAULT - Static variable in class weka.core.xml.XMLSerialization
default value for attribute ATT_ARRAY
ATT_CLASS - Static variable in class weka.core.xml.XMLInstances
the class attribute
ATT_CLASS - Static variable in class weka.core.xml.XMLSerialization
the tag for the class
ATT_FORMAT - Static variable in class weka.core.xml.XMLInstances
the format attribute (for date attributes)
ATT_INDEX - Static variable in class weka.classifiers.evaluation.output.prediction.XML
the index attribute.
ATT_INDEX - Static variable in class weka.core.xml.XMLInstances
the index attribute
ATT_MISSING - Static variable in class weka.core.xml.XMLInstances
the missing attribute
ATT_NAME - Static variable in class weka.classifiers.evaluation.output.prediction.XML
the "name" attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLDocument
the "name" attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLOptions
the name attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLSerialization
the tag for the name
ATT_NULL - Static variable in class weka.core.xml.XMLSerialization
the tag whether null or not (yes/no)
ATT_NULL_DEFAULT - Static variable in class weka.core.xml.XMLSerialization
default value for attribute ATT_NULL
ATT_PREDICTED - Static variable in class weka.classifiers.evaluation.output.prediction.XML
the predicted attribute.
ATT_PRIMITIVE - Static variable in class weka.core.xml.XMLSerialization
the tag whether primitive or not (yes/no)
ATT_PRIMITIVE_DEFAULT - Static variable in class weka.core.xml.XMLSerialization
default value for attribute ATT_PRIMITIVE
ATT_TYPE - Static variable in class weka.classifiers.evaluation.output.prediction.XML
the "type" attribute.
ATT_TYPE - Static variable in class weka.core.xml.XMLInstances
the type attribute
ATT_TYPE - Static variable in class weka.core.xml.XMLOptions
the type attribute.
ATT_VALUE - Static variable in class weka.core.xml.XMLOptions
the value attribute.
ATT_VERSION - Static variable in class weka.classifiers.evaluation.output.prediction.XML
the "version" attribute.
ATT_VERSION - Static variable in class weka.core.xml.XMLDocument
the "version" attribute.
ATT_VERSION - Static variable in class weka.core.xml.XMLInstances
the version attribute
ATT_VERSION - Static variable in class weka.core.xml.XMLSerialization
the version attribute
ATT_WEIGHT - Static variable in class weka.core.xml.XMLInstances
the weight attribute
attIndex() - Method in class weka.classifiers.trees.j48.BinC45Split
Returns index of attribute for which split was generated.
attIndex() - Method in class weka.classifiers.trees.j48.C45Split
Returns index of attribute for which split was generated.
attIndex() - Method in class weka.classifiers.trees.j48.NBTreeSplit
Returns index of attribute for which split was generated.
attList_IrrTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1
Returns the tip text for this property
attribute() - Method in class weka.classifiers.trees.j48.GraftSplit
 
Attribute - Class in weka.core
Class for handling an attribute.
Attribute(String) - Constructor for class weka.core.Attribute
Constructor for a numeric attribute.
Attribute(String, ProtectedProperties) - Constructor for class weka.core.Attribute
Constructor for a numeric attribute, where metadata is supplied.
Attribute(String, String) - Constructor for class weka.core.Attribute
Constructor for a date attribute.
Attribute(String, String, ProtectedProperties) - Constructor for class weka.core.Attribute
Constructor for a date attribute, where metadata is supplied.
Attribute(String, FastVector) - Constructor for class weka.core.Attribute
Constructor for nominal attributes and string attributes.
Attribute(String, FastVector, ProtectedProperties) - Constructor for class weka.core.Attribute
Constructor for nominal attributes and string attributes, where metadata is supplied.
Attribute(String, Instances) - Constructor for class weka.core.Attribute
Constructor for relation-valued attributes.
Attribute(String, Instances, ProtectedProperties) - Constructor for class weka.core.Attribute
Constructor for relation-valued attributes.
Attribute(String, int) - Constructor for class weka.core.Attribute
Constructor for a numeric attribute with a particular index.
Attribute(String, String, int) - Constructor for class weka.core.Attribute
Constructor for date attributes with a particular index.
Attribute(String, FastVector, int) - Constructor for class weka.core.Attribute
Constructor for nominal attributes and string attributes with a particular index.
Attribute(String, Instances, int) - Constructor for class weka.core.Attribute
Constructor for a relation-valued attribute with a particular index.
attribute(int) - Method in class weka.core.Instance
Returns the attribute with the given index.
attribute(int) - Method in class weka.core.Instances
Returns an attribute.
attribute(String) - Method in class weka.core.Instances
Returns an attribute given its name.
ATTRIBUTE - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
 
attributeAsClass() - Method in class weka.gui.arffviewer.ArffPanel
sets the current attribute as class attribute, i.e.
attributeAsClass() - Method in class weka.gui.arffviewer.ArffViewerMainPanel
sets the current selected Attribute as class attribute, i.e.
attributeAsClassAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel
sets the attribute at the given col index as the new class attribute
attributeAsClassAt(int) - Method in class weka.gui.arffviewer.ArffTableModel
sets the attribute at the given col index as the new class attribute, i.e.
AttributeEvaluator - Interface in weka.attributeSelection
Interface for classes that evaluate attributes individually.
attributeEvaluatorTipText() - Method in class weka.attributeSelection.FilteredAttributeEval
Returns the tip text for this property
attributeEvaluatorTipText() - Method in class weka.attributeSelection.RaceSearch
Returns the tip text for this property
attributeEvaluatorTipText() - Method in class weka.attributeSelection.RankSearch
Returns the tip text for this property
AttributeExpression - Class in weka.core
A general purpose class for parsing mathematical expressions involving attribute values.
AttributeExpression() - Constructor for class weka.core.AttributeExpression
 
attributeIndexesTipText() - Method in class weka.filters.unsupervised.attribute.NominalToString
Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.Add
Returns the tip text for this property.
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise
Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.AddValues
Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
 
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
 
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
 
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.SwapValues
 
attributeIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues
Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.core.NormalizableDistance
Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.filters.supervised.attribute.Discretize
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Copy
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Discretize
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.FirstOrder
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericToNominal
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.RELAGGS
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Remove
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Reorder
Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.SortLabels
Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
Returns the tip text for this property.
attributeList(BitSet) - Method in class weka.attributeSelection.ScatterSearchV1
converts a BitSet into a list of attribute indexes
attributeList(BitSet) - Method in class weka.attributeSelection.TabuSearch
converts a BitSet into a list of attribute indexes
AttributeListPanel - Class in weka.gui
Creates a panel that displays the attributes contained in a set of instances, letting the user select a single attribute for inspection.
AttributeListPanel() - Constructor for class weka.gui.AttributeListPanel
Creates the attribute selection panel with no initial instances.
AttributeLocator - Class in weka.core
This class locates and records the indices of a certain type of attributes, recursively in case of Relational attributes.
AttributeLocator(Instances, int) - Constructor for class weka.core.AttributeLocator
Initializes the AttributeLocator with the given data for the specified type of attribute.
AttributeLocator(Instances, int, int, int) - Constructor for class weka.core.AttributeLocator
Initializes the AttributeLocator with the given data for the specified type of attribute.
AttributeLocator(Instances, int, int[]) - Constructor for class weka.core.AttributeLocator
initializes the AttributeLocator with the given data for the specified type of attribute.
attributeNamePrefixTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
Returns the tip text for this property.
attributeNames() - Method in class weka.classifiers.functions.SMO
Returns the attribute names.
attributeNames() - Method in class weka.classifiers.mi.MISMO
Returns the attribute names.
attributeNameTipText() - Method in class weka.filters.unsupervised.attribute.Add
Returns the tip text for this property.
attributeNameTipText() - Method in class weka.filters.unsupervised.attribute.AddID
Returns the tip text for this property
AttributePanel - Class in weka.gui.visualize
This panel displays one dimensional views of the attributes in a dataset.
AttributePanel() - Constructor for class weka.gui.visualize.AttributePanel
 
AttributePanel(Color) - Constructor for class weka.gui.visualize.AttributePanel
This constructs an attributePanel.
AttributePanelEvent - Class in weka.gui.visualize
Class encapsulating a change in the AttributePanel's selected x and y attributes.
AttributePanelEvent(boolean, boolean, int) - Constructor for class weka.gui.visualize.AttributePanelEvent
Constructor
AttributePanelListener - Interface in weka.gui.visualize
Interface for classes that want to listen for Attribute selection changes in the attribute panel
attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.StringToNominal
 
AttributeSelectedClassifier - Class in weka.classifiers.meta
Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.
AttributeSelectedClassifier() - Constructor for class weka.classifiers.meta.AttributeSelectedClassifier
Default constructor.
AttributeSelection - Class in weka.attributeSelection
Attribute selection class.
AttributeSelection() - Constructor for class weka.attributeSelection.AttributeSelection
constructor.
AttributeSelection - Class in weka.filters.supervised.attribute
A supervised attribute filter that can be used to select attributes.
AttributeSelection() - Constructor for class weka.filters.supervised.attribute.AttributeSelection
Constructor
attributeSelectionChange(AttributePanelEvent) - Method in interface weka.gui.visualize.AttributePanelListener
Called when the user clicks on an attribute bar
attributeSelectionMethodTipText() - Method in class weka.classifiers.functions.LinearRegression
Returns the tip text for this property
AttributeSelectionPanel - Class in weka.gui
Creates a panel that displays the attributes contained in a set of instances, letting the user toggle whether each attribute is selected or not (eg: so that unselected attributes can be removed before classification).
AttributeSelectionPanel() - Constructor for class weka.gui.AttributeSelectionPanel
Creates the attribute selection panel with no initial instances.
AttributeSelectionPanel - Class in weka.gui.explorer
This panel allows the user to select and configure an attribute evaluator and a search method, set the attribute of the current dataset to be used as the class, and perform attribute selection using one of two selection modes (select using all the training data or perform a n-fold cross validation---on each trial selecting features using n-1 folds of the data).
AttributeSelectionPanel() - Constructor for class weka.gui.explorer.AttributeSelectionPanel
Creates the classifier panel
AttributeSetEvaluator - Class in weka.attributeSelection
Abstract attribute set evaluator.
AttributeSetEvaluator() - Constructor for class weka.attributeSelection.AttributeSetEvaluator
 
attributeSparse(int) - Method in class weka.core.Instance
Returns the attribute with the given index.
attributeSparse(int) - Method in class weka.core.SparseInstance
Returns the attribute associated with the internal index.
AttributeStats - Class in weka.core
A Utility class that contains summary information on an the values that appear in a dataset for a particular attribute.
AttributeStats() - Constructor for class weka.core.AttributeStats
 
attributeStats(int) - Method in class weka.core.Instances
Calculates summary statistics on the values that appear in this set of instances for a specified attribute.
attributesTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput
Returns the tip text for this property.
attributesToString() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition
Make a string from the attribues list.
attributeString(Instances) - Method in class weka.classifiers.trees.adtree.Splitter
Gets the string describing the attributes the split depends on.
attributeString(Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Gets the string describing the attributes the split depends on.
attributeString(Instances) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Gets the string describing the attributes the split depends on.
AttributeSummarizer - Class in weka.gui.beans
Bean that encapsulates displays bar graph summaries for attributes in a data set.
AttributeSummarizer() - Constructor for class weka.gui.beans.AttributeSummarizer
Creates a new AttributeSummarizer instance.
AttributeSummarizerBeanInfo - Class in weka.gui.beans
Bean info class for the attribute summarizer bean
AttributeSummarizerBeanInfo() - Constructor for class weka.gui.beans.AttributeSummarizerBeanInfo
 
AttributeSummaryPanel - Class in weka.gui
This panel displays summary statistics about an attribute: name, type number/% of missing/unique values, number of distinct values.
AttributeSummaryPanel() - Constructor for class weka.gui.AttributeSummaryPanel
Creates the instances panel with no initial instances.
attributeToDoubleArray(int) - Method in class weka.core.Instances
Gets the value of all instances in this dataset for a particular attribute.
AttributeTransformer - Interface in weka.attributeSelection
Abstract attribute transformer.
attributeTypeTipText() - Method in class weka.filters.unsupervised.attribute.Add
Returns the tip text for this property
attributeTypeTipText() - Method in class weka.filters.unsupervised.attribute.RemoveType
Returns the tip text for this property
attributeTypeToString(int) - Static method in class weka.core.CheckScheme
returns a string representation of the attribute type
AttributeValueLiteral - Class in weka.associations.tertius
 
AttributeValueLiteral(Predicate, String, int, int, int) - Constructor for class weka.associations.tertius.AttributeValueLiteral
 
AttributeVisualizationPanel - Class in weka.gui
Creates a panel that shows a visualization of an attribute in a dataset.
AttributeVisualizationPanel() - Constructor for class weka.gui.AttributeVisualizationPanel
Constructor - If used then the class will not show the class selection combo box.
AttributeVisualizationPanel(boolean) - Constructor for class weka.gui.AttributeVisualizationPanel
Constructor.
attrIndexRangeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition
Returns the tip text for this property
attrSplit(int, Instances) - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo
Finds the best splitting point for an attribute in the instances
attrSplit(int, Instances) - Method in interface weka.classifiers.trees.m5.SplitEvaluate
Finds the best splitting point for an attribute in the instances
attrSplit(int, Instances) - Method in class weka.classifiers.trees.m5.YongSplitInfo
Finds the best splitting point for an attribute in the instances
attsToEliminatePerIterationTipText() - Method in class weka.attributeSelection.SVMAttributeEval
Returns a tip text for this property suitable for display in the GUI
autoBuildTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
 
autoKeyGenerationTipText() - Method in class weka.core.converters.DatabaseSaver
Returns the tip text for this property.
AVERAGE_RULE - Static variable in class weka.classifiers.meta.Vote
combination rule: Average of Probabilities
AveragingResultProducer - Class in weka.experiment
Takes the results from a ResultProducer and submits the average to the result listener.
AveragingResultProducer() - Constructor for class weka.experiment.AveragingResultProducer
 
avgCost() - Method in class weka.classifiers.Evaluation
Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.
avgProb - Variable in class weka.classifiers.lazy.kstar.KStarWrapper
used/reused to hold the average transformation probability

B

B_ENTROPY - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
 
B_SPHERE - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
Blend setting modes
backfitData(Instances) - Method in class weka.classifiers.trees.RandomTree
Backfits the given data into the tree.
backQuoteChars(String) - Static method in class weka.core.Utils
Converts carriage returns and new lines in a string into \r and \n.
BACKUP_EXTENSION - Static variable in class weka.gui.scripting.Script
the backup extension.
backward(PaceMatrix, IntVector, int, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Backward ordering of columns in terms of response explanation.
backwardEliminate(Instances, int) - Method in class weka.classifiers.meta.ensembleSelection.ModelBag
Find the model whose removal will help the ensemble's performance the most, and remove it.
Bagging - Class in weka.classifiers.meta
Class for bagging a classifier to reduce variance.
Bagging() - Constructor for class weka.classifiers.meta.Bagging
Constructor.
bagSizePercentTipText() - Method in class weka.classifiers.meta.Bagging
Returns the tip text for this property
bagSizePercentTipText() - Method in class weka.classifiers.meta.MetaCost
Returns the tip text for this property
balanceClassTipText() - Method in class weka.datagenerators.classifiers.classification.Agrawal
Returns the tip text for this property
balancedTipText() - Method in class weka.classifiers.functions.Winnow
Returns the tip text for this property
BallNode - Class in weka.core.neighboursearch.balltrees
Class representing a node of a BallTree.
BallNode(int) - Constructor for class weka.core.neighboursearch.balltrees.BallNode
Constructor.
BallNode(int, int, int) - Constructor for class weka.core.neighboursearch.balltrees.BallNode
Creates a new instance of BallNode.
BallNode(int, int, int, Instance, double) - Constructor for class weka.core.neighboursearch.balltrees.BallNode
Creates a new instance of BallNode.
BallSplitter - Class in weka.core.neighboursearch.balltrees
Abstract class for splitting a ball tree's BallNode.
BallSplitter() - Constructor for class weka.core.neighboursearch.balltrees.BallSplitter
default constructor.
BallSplitter(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.balltrees.BallSplitter
Creates a new instance of BallSplitter.
ballSplitterTipText() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor
Returns the tip text for this property.
BallTree - Class in weka.core.neighboursearch
Class implementing the BallTree/Metric Tree algorithm for nearest neighbour search.
The connection to dataset is only a reference.
BallTree() - Constructor for class weka.core.neighboursearch.BallTree
Creates a new instance of BallTree.
BallTree(Instances) - Constructor for class weka.core.neighboursearch.BallTree
Creates a new instance of BallTree.
BallTreeConstructor - Class in weka.core.neighboursearch.balltrees
Abstract class for constructing a BallTree .
BallTreeConstructor() - Constructor for class weka.core.neighboursearch.balltrees.BallTreeConstructor
Creates a new instance of BallTreeConstructor.
ballTreeConstructorTipText() - Method in class weka.core.neighboursearch.BallTree
Returns the tip text for this property.
baseTipText() - Method in class weka.core.neighboursearch.CoverTree
Returns the tip text for this property.
BATCH - Static variable in interface weka.core.converters.Saver
 
BATCH_FINISHED - Static variable in class weka.gui.beans.IncrementalClassifierEvent
 
BATCH_FINISHED - Static variable in class weka.gui.beans.InstanceEvent
 
BATCH_FINISHED - Static variable in class weka.gui.streams.InstanceEvent
Specifies that the batch of instances is finished
BatchClassifierEvent - Class in weka.gui.beans
Class encapsulating a built classifier and a batch of instances to test on.
BatchClassifierEvent(Object, Classifier, DataSetEvent, DataSetEvent, int, int) - Constructor for class weka.gui.beans.BatchClassifierEvent
Creates a new BatchClassifierEvent instance.
BatchClassifierEvent(Object, Classifier, DataSetEvent, DataSetEvent, int, int, int, int) - Constructor for class weka.gui.beans.BatchClassifierEvent
Creates a new BatchClassifierEvent instance.
BatchClassifierListener - Interface in weka.gui.beans
Interface to something that can process a BatchClassifierEvent
BatchClustererEvent - Class in weka.gui.beans
Class encapsulating a built clusterer and a batch of instances to test on.
BatchClustererEvent(Object, Clusterer, DataSetEvent, int, int, int) - Constructor for class weka.gui.beans.BatchClustererEvent
Creates a new BatchClustererEvent instance.
BatchClustererListener - Interface in weka.gui.beans
Interface to something that can process a BatchClustererEvent
BatchConverter - Interface in weka.core.converters
Marker interface for a loader/saver that can retrieve instances in batch mode
batchFilterFile(Filter, String[]) - Static method in class weka.filters.Filter
Method for testing filters ability to process multiple batches.
batchFinished() - Method in class weka.filters.Filter
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.SimpleBatchFilter
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.SimpleStreamFilter
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.AttributeSelection
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.ClassOrder
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.Discretize
Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.NominalToBinary
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.Resample
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.SMOTE
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.SpreadSubsample
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries
Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddCluster
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddID
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddNoise
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Center
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.ClusterMembership
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Discretize
Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.MathExpression
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.MultiInstanceToPropositional
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.NominalToString
Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Normalize
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.PropositionalToMultiInstance
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RandomProjection
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RemoveType
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RemoveUseless
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Standardize
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.StringToNominal
Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.Randomize
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveFolds
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues
Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemovePercentage
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveRange
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.Resample
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.ReservoirSample
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.gui.streams.InstanceJoiner
Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.gui.streams.InstanceSavePanel
 
batchFinished() - Method in class weka.gui.streams.InstanceTable
 
batchFinished() - Method in class weka.gui.streams.InstanceViewer
 
BAYES - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
score types
BayesianLogisticRegression - Class in weka.classifiers.bayes
Implements Bayesian Logistic Regression for both Gaussian and Laplace Priors.

For more information, see

Alexander Genkin, David D.
BayesianLogisticRegression() - Constructor for class weka.classifiers.bayes.BayesianLogisticRegression
 
BayesNet - Class in weka.classifiers.bayes
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
BayesNet() - Constructor for class weka.classifiers.bayes.BayesNet
 
BayesNet - Static variable in interface weka.core.Drawable
 
BayesNet - Class in weka.datagenerators.classifiers.classification
Generates random instances based on a Bayes network.
BayesNet() - Constructor for class weka.datagenerators.classifiers.classification.BayesNet
initializes the generator
BayesNetEstimator - Class in weka.classifiers.bayes.net.estimate
BayesNetEstimator is the base class for estimating the conditional probability tables of a Bayes network once the structure has been learned.
BayesNetEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.BayesNetEstimator
 
BayesNetGenerator - Class in weka.classifiers.bayes.net
Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
BayesNetGenerator() - Constructor for class weka.classifiers.bayes.net.BayesNetGenerator
Constructor for BayesNetGenerator.
BDeu - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
 
BEAN_EXECUTING - Static variable in class weka.gui.beans.BeanInstance
 
BeanCommon - Interface in weka.gui.beans
Interface specifying routines that all weka beans should implement in order to allow the bean environment to exercise some control over the bean and also to allow the bean to exercise some control over connections.
BeanConnection - Class in weka.gui.beans
Class for encapsulating a connection between two beans.
BeanConnection(BeanInstance, BeanInstance, EventSetDescriptor) - Constructor for class weka.gui.beans.BeanConnection
Creates a new BeanConnection instance.
BeanInstance - Class in weka.gui.beans
Class that manages a set of beans.
BeanInstance(JComponent, Object, int, int) - Constructor for class weka.gui.beans.BeanInstance
Creates a new BeanInstance instance.
BeanInstance(JComponent, String, int, int) - Constructor for class weka.gui.beans.BeanInstance
Creates a new BeanInstance instance given the fully qualified name of the bean
BeanVisual - Class in weka.gui.beans
BeanVisual encapsulates icons and label for a given bean.
BeanVisual(String, String, String) - Constructor for class weka.gui.beans.BeanVisual
Constructor
BestFirst - Class in weka.attributeSelection
BestFirst:

Searches the space of attribute subsets by greedy hillclimbing augmented with a backtracking facility.
BestFirst() - Constructor for class weka.attributeSelection.BestFirst
Constructor
BestFirst.Link2 - Class in weka.attributeSelection
Class for a node in a linked list.
BestFirst.Link2(Object[], double) - Constructor for class weka.attributeSelection.BestFirst.Link2
Constructor
BestFirst.LinkedList2 - Class in weka.attributeSelection
Class for handling a linked list.
BestFirst.LinkedList2(int) - Constructor for class weka.attributeSelection.BestFirst.LinkedList2
 
betaTipText() - Method in class weka.classifiers.functions.Winnow
Returns the tip text for this property
BetaVector - Variable in class weka.classifiers.bayes.BayesianLogisticRegression
Array for storing coefficients of Bayesian regression model.
BFTree - Class in weka.classifiers.trees
Class for building a best-first decision tree classifier.
BFTree() - Constructor for class weka.classifiers.trees.BFTree
 
bias() - Method in class weka.classifiers.functions.SMO
Returns the bias of each binary SMO.
bias() - Method in class weka.classifiers.mi.MISMO
Returns the bias of each binary SMO.
biasTipText() - Method in class weka.classifiers.functions.LibLINEAR
Returns the tip text for this property
biasTipText() - Method in class weka.classifiers.misc.VFI
Returns the tip text for this property
biasToUniformClassTipText() - Method in class weka.filters.supervised.instance.Resample
Returns the tip text for this property.
BIBTEX_ENDTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc
the end comment tag for inserting the generated BibTex
BIBTEX_STARTTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc
the start comment tag for inserting the generated BibTex
BIFFileTipText() - Method in class weka.classifiers.bayes.BayesNet
 
BIFFormatException - Exception in weka.gui.graphvisualizer
This is the Exception thrown by BIFParser, if there was an error in parsing the XMLBIF string or input stream.
BIFFormatException(String) - Constructor for exception weka.gui.graphvisualizer.BIFFormatException
 
BIFParser - Class in weka.gui.graphvisualizer
This class parses an inputstream or a string in XMLBIF ver.
BIFParser(String, FastVector, FastVector) - Constructor for class weka.gui.graphvisualizer.BIFParser
Constructor (if our input is a String)
BIFParser(InputStream, FastVector, FastVector) - Constructor for class weka.gui.graphvisualizer.BIFParser
Constructor (if our input is an InputStream)
BIFReader - Class in weka.classifiers.bayes.net
Builds a description of a Bayes Net classifier stored in XML BIF 0.3 format.

For more details on XML BIF see:

Fabio Cozman, Marek Druzdzel, Daniel Garcia (1998).
BIFReader() - Constructor for class weka.classifiers.bayes.net.BIFReader
the default constructor
bigF(double, double) - Static method in class weka.classifiers.bayes.BayesianLogisticRegression
This is a convient function that defines and upper bound (Delta>0) for values of r(i) reachable by updates in the trust region.
binarizeNumericAttributesTipText() - Method in class weka.attributeSelection.ChiSquaredAttributeEval
Returns the tip text for this property
binarizeNumericAttributesTipText() - Method in class weka.attributeSelection.InfoGainAttributeEval
Returns the tip text for this property
BINARY - Static variable in class weka.gui.beans.SerializedModelSaver
 
binaryAttributesNominalTipText() - Method in class weka.filters.supervised.attribute.NominalToBinary
Returns the tip text for this property
binaryAttributesNominalTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary
Returns the tip text for this property
BinarySparseInstance - Class in weka.core
Class for storing a binary-data-only instance as a sparse vector.
BinarySparseInstance(Instance) - Constructor for class weka.core.BinarySparseInstance
Constructor that generates a sparse instance from the given instance.
BinarySparseInstance(SparseInstance) - Constructor for class weka.core.BinarySparseInstance
Constructor that copies the info from the given instance.
BinarySparseInstance(double, double[]) - Constructor for class weka.core.BinarySparseInstance
Constructor that generates a sparse instance from the given parameters.
BinarySparseInstance(double, int[], int) - Constructor for class weka.core.BinarySparseInstance
Constructor that inititalizes instance variable with given values.
BinarySparseInstance(int) - Constructor for class weka.core.BinarySparseInstance
Constructor of an instance that sets weight to one, all values to 1, and the reference to the dataset to null.
binarySplitsTipText() - Method in class weka.classifiers.rules.PART
Returns the tip text for this property
binarySplitsTipText() - Method in class weka.classifiers.trees.J48
Returns the tip text for this property
binarySplitsTipText() - Method in class weka.classifiers.trees.J48graft
Returns the tip text for this property
binaryToKOML(String, String) - Static method in class weka.core.xml.SerialUIDChanger
converts a binary file into a KOML XML file
binaryWordTipText() - Method in class weka.classifiers.bayes.DMNBtext
Returns the tip text for this property
BinC45ModelSelection - Class in weka.classifiers.trees.j48
Class for selecting a C4.5-like binary (!) split for a given dataset.
BinC45ModelSelection(int, Instances) - Constructor for class weka.classifiers.trees.j48.BinC45ModelSelection
Initializes the split selection method with the given parameters.
BinC45Split - Class in weka.classifiers.trees.j48
Class implementing a binary C4.5-like split on an attribute.
BinC45Split(int, int, double) - Constructor for class weka.classifiers.trees.j48.BinC45Split
Initializes the split model.
binomialDistribution(double, double, double) - Static method in class weka.associations.RuleGeneration
calculates the probability using a binomial distribution.
binomialStandardError(double, int) - Static method in class weka.core.Statistics
Computes standard error for observed values of a binomial random variable.
binomP(double, double, double) - Method in class weka.classifiers.lazy.LBR
Significance test binomp:
binSplitTipText() - Method in class weka.classifiers.trees.FT
Returns the tip text for this property
binsTipText() - Method in class weka.filters.unsupervised.attribute.Discretize
Returns the tip text for this property
binsTipText() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize
Returns the tip text for this property
binValueTipText() - Method in class weka.clusterers.XMeans
Returns the tip text for this property.
biprob(double, double, double) - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTreeG
Significance test
BIRCHCluster - Class in weka.datagenerators.clusterers
Cluster data generator designed for the BIRCH System

Dataset is generated with instances in K clusters.
Instances are 2-d data points.
Each cluster is characterized by the number of data points in itits radius and its center.
BIRCHCluster() - Constructor for class weka.datagenerators.clusterers.BIRCHCluster
initializes the generator with default values
blocker(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
A function used to stop the code that called buildclassifier from continuing on before the user has finished the decision tree.
BMAEstimator - Class in weka.classifiers.bayes.net.estimate
BMAEstimator estimates conditional probability tables of a Bayes network using Bayes Model Averaging (BMA).
BMAEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.BMAEstimator
 
BMPWriter - Class in weka.gui.visualize
This class takes any JComponent and outputs it to a BMP-file.
BMPWriter() - Constructor for class weka.gui.visualize.BMPWriter
initializes the object
BMPWriter(JComponent) - Constructor for class weka.gui.visualize.BMPWriter
initializes the object with the given Component
BMPWriter(JComponent, File) - Constructor for class weka.gui.visualize.BMPWriter
initializes the object with the given Component and filename
Body - Class in weka.associations.tertius
Class representing the body of a rule.
Body() - Constructor for class weka.associations.tertius.Body
Constructor without storing the counter-instances.
Body(Instances) - Constructor for class weka.associations.tertius.Body
Constructor storing the counter-instances.
bodyContains(Literal) - Method in class weka.associations.tertius.Rule
Test if the body of the rule contains a literal.
BOOL - Static variable in class weka.experiment.DatabaseUtils
Type mapping for BOOL used for reading experiment results.
BOOLEAN - Static variable in interface weka.core.mathematicalexpression.sym
 
BOOLEAN - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
 
booleanColsTipText() - Method in class weka.datagenerators.ClusterGenerator
Returns the tip text for this property
boost() - Method in class weka.classifiers.trees.ADTree
Performs a single boosting iteration, using two-class optimized method.
BottomUpConstructor - Class in weka.core.neighboursearch.balltrees
The class that constructs a ball tree bottom up.
BottomUpConstructor() - Constructor for class weka.core.neighboursearch.balltrees.BottomUpConstructor
Creates a new instance of BottomUpConstructor.
BoundaryPanel - Class in weka.gui.boundaryvisualizer
BoundaryPanel.
BoundaryPanel(int, int) - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanel
Creates a new BoundaryPanel instance.
BoundaryPanelDistributed - Class in weka.gui.boundaryvisualizer
This class extends BoundaryPanel with code for distributing the processing necessary to create a visualization among a list of remote machines.
BoundaryPanelDistributed(int, int) - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanelDistributed
Creates a new BoundaryPanelDistributed instance.
BoundaryVisualizer - Class in weka.gui.boundaryvisualizer
BoundaryVisualizer.
BoundaryVisualizer() - Constructor for class weka.gui.boundaryvisualizer.BoundaryVisualizer
Creates a new BoundaryVisualizer instance.
boundsFileTipText() - Method in class weka.classifiers.misc.FLR
Returns the tip text for this property
branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.Splitter
Gets the index of the branch that an instance applies to.
branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.TwoWayNominalSplit
Gets the index of the branch that an instance applies to.
branchInstanceGoesDown(Instance) - Method in class weka.classifiers.trees.adtree.TwoWayNumericSplit
Gets the index of the branch that an instance applies to.
BrowserHelper - Class in weka.gui
A little helper class for browser related stuff.
BrowserHelper() - Constructor for class weka.gui.BrowserHelper
 
bubbleSubsetSort(List<ScatterSearchV1.Subset>) - Method in class weka.attributeSelection.ScatterSearchV1
Sort a List of subsets according to their merits
bubbleSubsetSort(List<TabuSearch.Subset>) - Method in class weka.attributeSelection.TabuSearch
Sort a List of subsets according to their merits
build(String, String) - Method in class weka.gui.HierarchyPropertyParser
Build a tree from the given property with the given delimitor
buildAssociations(Instances) - Method in class weka.associations.Apriori
Method that generates all large itemsets with a minimum support, and from these all association rules with a minimum confidence.
buildAssociations(Instances) - Method in interface weka.associations.Associator
Generates an associator.
buildAssociations(Instances) - Method in class weka.associations.FilteredAssociator
Build the associator on the filtered data.
buildAssociations(Instances) - Method in class weka.associations.GeneralizedSequentialPatterns
Extracts all sequential patterns out of a given sequential data set and prints out the results.
buildAssociations(Instances) - Method in class weka.associations.HotSpot
Build the tree
buildAssociations(Instances) - Method in class weka.associations.PredictiveApriori
Method that generates all large itemsets with a minimum support, and from these all association rules.
buildAssociations(Instances) - Method in class weka.associations.Tertius
Method that launches the search to find the rules with the highest confirmation.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.AODE
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.AODEsr
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.BayesianLogisticRegression
(1) Set the data to the class attribute m_Instances. (2)Call the method initialize() to initialize the values.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.BayesNet
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.ComplementNaiveBayes
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.DMNBtext
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.HNB
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayes
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesSimple
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.WAODE
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.Classifier
Generates a classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.GaussianProcesses
Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.IsotonicRegression
Builds an isotonic regression model given the supplied training data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.LeastMedSq
Build lms regression
buildClassifier(Instances) - Method in class weka.classifiers.functions.LibLINEAR
builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.functions.LibSVM
builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.LinearRegression
Builds a regression model for the given data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.Logistic
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.functions.MultilayerPerceptron
Call this function to build and train a neural network for the training data provided.
buildClassifier(Instances) - Method in class weka.classifiers.functions.PaceRegression
Builds a pace regression model for the given data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.PLSClassifier
builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.functions.RBFNetwork
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.functions.SimpleLinearRegression
Builds a simple linear regression model given the supplied training data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SimpleLogistic
Builds the logistic regression using LogitBoost.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SMO
Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SMOreg
Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegOptimizer
learn SVM parameters from data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegSMO
learn SVM parameters from data using Smola's SMO algorithm.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegSMOImproved
learn SVM parameters from data using Keerthi's SMO algorithm.
buildClassifier(Instances) - Method in class weka.classifiers.functions.VotedPerceptron
Builds the ensemble of perceptrons.
buildClassifier(Instances) - Method in class weka.classifiers.functions.Winnow
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer
Stump method for building the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.IB1
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.IBk
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.KStar
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.LBR
For lazy learning, building classifier is only to prepare their inputs until classification time.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.LWL
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AdaBoostM1
Boosting method.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AdditiveRegression
Build the classifier on the supplied data
buildClassifier(Instances) - Method in class weka.classifiers.meta.AttributeSelectedClassifier
Build the classifier on the dimensionally reduced data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Bagging
Bagging method.
buildClassifier(Instances) - Method in class weka.classifiers.meta.ClassificationViaClustering
builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.meta.ClassificationViaRegression
Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.CostSensitiveClassifier
Builds the model of the base learner.
buildClassifier(Instances) - Method in class weka.classifiers.meta.CVParameterSelection
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Dagging
Bagging method.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Decorate
Build Decorate classifier
buildClassifier(Instances) - Method in class weka.classifiers.meta.END
Builds the committee of randomizable classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.EnsembleSelection
Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.FilteredClassifier
Build the classifier on the filtered data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.GridSearch
builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.meta.LogitBoost
Builds the boosted classifier
buildClassifier(Instances) - Method in class weka.classifiers.meta.MetaCost
Builds the model of the base learner.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiBoostAB
Method for building this classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiClassClassifier
Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiScheme
Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Builds tree recursively.
buildClassifier(Instances) - Method in class weka.classifiers.meta.nestedDichotomies.DataNearBalancedND
Builds tree recursively.
buildClassifier(Instances) - Method in class weka.classifiers.meta.nestedDichotomies.ND
Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.OrdinalClassClassifier
Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomCommittee
Builds the committee of randomizable classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomSubSpace
builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RegressionByDiscretization
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RotationForest
builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Stacking
Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.ThresholdSelector
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Vote
Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.mi.CitationKNN
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.mi.MDD
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.mi.MIBoost
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.mi.MIDD
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.mi.MIEMDD
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.mi.MILR
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.mi.MINND
As normal Nearest Neighbour algorithm does, it's lazy and simply records the exemplar information (i.e.
buildClassifier(Instances) - Method in class weka.classifiers.mi.MIOptimalBall
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.mi.MISMO
Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.mi.MISVM
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.mi.MIWrapper
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.mi.SimpleMI
Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.mi.TLD
 
buildClassifier(Instances) - Method in class weka.classifiers.mi.TLDSimple
 
buildClassifier(Instances) - Method in class weka.classifiers.misc.FLR
Builds the FLR Classifier
buildClassifier(Instances) - Method in class weka.classifiers.misc.HyperPipes
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.misc.SerializedClassifier
loads only the serialized classifier
buildClassifier(Instances) - Method in class weka.classifiers.misc.VFI
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier
Throw an exception - PMML models are pre-built.
buildClassifier(Instances) - Method in class weka.classifiers.rules.ConjunctiveRule
Builds a single rule learner with REP dealing with nominal classes or numeric classes.
buildClassifier(Instances) - Method in class weka.classifiers.rules.DecisionTable
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.DTNB
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.JRip
Builds Ripper in the order of class frequencies.
buildClassifier(Instances) - Method in class weka.classifiers.rules.NNge
Generates a classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.OneR
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.PART
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.part.MakeDecList
Builds dec list.
buildClassifier(Instances) - Method in class weka.classifiers.rules.Prism
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.Ridor
Builds a ripple-down manner rule learner.
buildClassifier(Instances) - Method in class weka.classifiers.rules.ZeroR
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.scripting.GroovyClassifier
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.scripting.JythonClassifier
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.ADTree
Builds a classifier for a set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.BFTree
Method for building a BestFirst decision tree classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.DecisionStump
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.FT
Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.ft.FTInnerNode
Method for building a Functional Inner tree (only called for the root node).
buildClassifier(Instances) - Method in class weka.classifiers.trees.ft.FTLeavesNode
Method for building a Functional Leaves tree (only called for the root node).
buildClassifier(Instances) - Method in class weka.classifiers.trees.ft.FTNode
Method for building a Functional tree (only called for the root node).
buildClassifier(Instances) - Method in class weka.classifiers.trees.ft.FTtree
Method for building a Functional Tree (only called for the root node).
buildClassifier(Instances) - Method in class weka.classifiers.trees.Id3
Builds Id3 decision tree classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split
Creates a C4.5-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.J48
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree
Method for building a pruneable classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTreeG
Method for building a pruneable classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45Split
Creates a C4.5-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
Builds the classifier split model for the given set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.ClassifierTree
Method for building a classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.GraftSplit
builds m_graftdistro using the passed data
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree
Method for building a naive bayes classifier tree
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
Build the no-split node
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit
Creates a NBTree-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NoSplit
Creates a "no-split"-split for a given set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.PruneableClassifierTree
Method for building a pruneable classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.J48graft
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.LADTree
Builds a classifier for a set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.LMT
Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.LMTNode
Method for building a logistic model tree (only called for the root node).
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.LogisticBase
Builds the logistic regression model usiing LogitBoost.
buildClassifier(Instances, double[][], double[][]) - Method in class weka.classifiers.trees.lmt.ResidualSplit
Builds the split.
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit
Method not in use
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.M5Base
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel
Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.Rule
Generates a single rule or m5 model tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.RuleNode
Build this node (find an attribute and split point)
buildClassifier(Instances) - Method in class weka.classifiers.trees.NBTree
Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomForest
Builds a classifier for a set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomTree
Builds classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.REPTree
Builds classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.SimpleCart
Build the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.UserClassifier
Call this function to build a decision tree for the training data provided.
buildClassifierForNode(ND.NDTree, Instances) - Method in class weka.classifiers.meta.nestedDichotomies.ND
Builds the classifier for one node.
buildClassifierTree(Classifier) - Method in class weka.gui.ensembleLibraryEditor.AddModelsPanel
This method necessarily seperates the process of building the tree object from the rest of the GUI construction.
buildClusterer(Instances) - Method in class weka.clusterers.AbstractClusterer
Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.CLOPE
Generate Clustering via CLOPE
buildClusterer(Instances) - Method in interface weka.clusterers.Clusterer
Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.Cobweb
Builds the clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.DBScan
Generate Clustering via DBScan
buildClusterer(Instances) - Method in class weka.clusterers.EM
Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.FarthestFirst
Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.FilteredClusterer
Build the clusterer on the filtered data.
buildClusterer(Instances) - Method in class weka.clusterers.MakeDensityBasedClusterer
Builds a clusterer for a set of instances.
buildClusterer(Instances) - Method in class weka.clusterers.OPTICS
Generate Clustering via OPTICS
buildClusterer(Instances) - Method in class weka.clusterers.sIB
Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.SimpleKMeans
Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.XMeans
Generates the X-Means clusterer.
buildCNN() - Method in class weka.classifiers.mi.CitationKNN
generates all the variables associated to the citation classifier
buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.C45PruneableDecList
Builds the partial tree without hold out set.
buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.ClassifierDecList
Builds the partial tree without hold out set.
buildDecList(Instances, Instances, boolean) - Method in class weka.classifiers.rules.part.PruneableDecList
Builds the partial tree with hold out set
buildDistribution(double, double) - Method in class weka.associations.PriorEstimation
updates the distribution of the confidence values.
buildEstimator(Estimator, String[], boolean) - Static method in class weka.estimators.Estimator
Build an estimator using the options.
buildEstimator(Estimator, Instances, int, int, int, boolean) - Static method in class weka.estimators.Estimator
 
buildEvaluator(Instances) - Method in class weka.attributeSelection.ASEvaluation
Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.CfsSubsetEval
Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.ChiSquaredAttributeEval
Initializes a chi-squared attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.ClassifierSubsetEval
Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.ConsistencySubsetEval
Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.CostSensitiveASEvaluation
Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.FilteredAttributeEval
Initializes a filtered attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.FilteredSubsetEval
Initializes a filtered attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.GainRatioAttributeEval
Initializes a gain ratio attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.InfoGainAttributeEval
Initializes an information gain attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.LatentSemanticAnalysis
Initializes the singular values/vectors and performs the analysis
buildEvaluator(Instances) - Method in class weka.attributeSelection.OneRAttributeEval
Initializes a OneRAttribute attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.PrincipalComponents
Initializes principal components and performs the analysis
buildEvaluator(Instances) - Method in class weka.attributeSelection.ReliefFAttributeEval
Initializes a ReliefF attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.SignificanceAttributeEval
Initializes the Significance attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.SVMAttributeEval
Initializes the evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
Initializes a symmetrical uncertainty attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.SymmetricalUncertAttributeSetEval
Initializes a symmetrical uncertainty attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.WrapperSubsetEval
Generates a attribute evaluator.
buildGenerator(Instances) - Method in interface weka.gui.boundaryvisualizer.DataGenerator
Build the data generator
buildGenerator(Instances) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator
Initialize the generator using the supplied instances
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.CachedKernel
builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.Kernel
builds the kernel with the given data
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.Puk
builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.RBFKernel
builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.StringKernel
builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.mi.supportVector.MIRBFKernel
builds the kernel with the given data.
buildLogisticModelsTipText() - Method in class weka.classifiers.functions.SMO
Returns the tip text for this property
buildLogisticModelsTipText() - Method in class weka.classifiers.mi.MISMO
Returns the tip text for this property
buildRegressionTreeTipText() - Method in class weka.classifiers.trees.m5.M5Base
Returns the tip text for this property
buildRule(Instances) - Method in class weka.classifiers.rules.part.ClassifierDecList
Method for building a pruned partial tree.
buildRule(Instances, Instances) - Method in class weka.classifiers.rules.part.PruneableDecList
Method for building a pruned partial tree.
buildStructure() - Method in class weka.classifiers.bayes.BayesNet
buildStructure determines the network structure/graph of the network.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.fixed.FromFile
 
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.fixed.NaiveBayes
 
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.global.TAN
buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
buildStructure determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.TAN
buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm
buildStructure determines the network structure/graph of the network.
buildTree(Instances, SimpleLinearRegression[][], double, double) - Method in class weka.classifiers.trees.ft.FTInnerNode
Method for building the tree structure.
buildTree(Instances, SimpleLinearRegression[][], double, double) - Method in class weka.classifiers.trees.ft.FTLeavesNode
Method for building the tree structure.
buildTree(Instances, SimpleLinearRegression[][], double, double) - Method in class weka.classifiers.trees.ft.FTNode
Method for building the tree structure.
buildTree(Instances, SimpleLinearRegression[][], double, double) - Method in class weka.classifiers.trees.ft.FTtree
Abstract method for building the tree structure.
buildTree(Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree
Builds the tree structure.
buildTree(Instances, Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree
Builds the tree structure with hold out set
buildTree(Instances, SimpleLinearRegression[][], double, double) - Method in class weka.classifiers.trees.lmt.LMTNode
Method for building the tree structure.
buildTree() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor
Builds the ball tree.
buildTree() - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor
Builds the ball tree bottom up.
buildTree() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor
Builds a ball tree middle out.
buildTree() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor
Builds the ball tree top down.
BuiltInArithmetic - Class in weka.core.pmml
Built-in function for +, -, *, /.
BuiltInArithmetic(BuiltInArithmetic.Operator) - Constructor for class weka.core.pmml.BuiltInArithmetic
Construct a new Arithmetic built-in pmml function.
BuiltInMath - Class in weka.core.pmml
Built-in function for min, max, sum, avg, log10, ln, sqrt, abs, exp, pow, threshold, floor, ceil and round.
BuiltInMath(BuiltInMath.MathFunc) - Constructor for class weka.core.pmml.BuiltInMath
Construct a new built-in pmml Math function.
BuiltInString - Class in weka.core.pmml
Built-in function for uppercase, substring and trimblanks.
BVDecompose - Class in weka.classifiers
Class for performing a Bias-Variance decomposition on any classifier using the method specified in:

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

Geoffrey I.
BVDecomposeSegCVSub() - Constructor for class weka.classifiers.BVDecomposeSegCVSub
 
BYTE - Static variable in class weka.experiment.DatabaseUtils
Type mapping for BYTE used for reading experiment results.

C

C45Loader - Class in weka.core.converters
Reads a file that is C45 format.
C45Loader() - Constructor for class weka.core.converters.C45Loader
 
C45ModelSelection - Class in weka.classifiers.trees.j48
Class for selecting a C4.5-type split for a given dataset.
C45ModelSelection(int, Instances) - Constructor for class weka.classifiers.trees.j48.C45ModelSelection
Initializes the split selection method with the given parameters.
C45PruneableClassifierTree - Class in weka.classifiers.trees.j48
Class for handling a tree structure that can be pruned using C4.5 procedures.
C45PruneableClassifierTree(ModelSelection, boolean, float, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45PruneableClassifierTree
Constructor for pruneable tree structure.
C45PruneableClassifierTreeG - Class in weka.classifiers.trees.j48
Class for handling a tree structure that can be pruned using C4.5 procedures and have nodes grafted on.
C45PruneableClassifierTreeG(ModelSelection, boolean, float, boolean, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45PruneableClassifierTreeG
Constructor for pruneable tree structure.
C45PruneableClassifierTreeG(ModelSelection, Instances, ClassifierSplitModel, boolean, float, boolean, boolean, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45PruneableClassifierTreeG
Constructor for pruneable tree structure.
C45PruneableDecList - Class in weka.classifiers.rules.part
Class for handling a partial tree structure pruned using C4.5's pruning heuristic.
C45PruneableDecList(ModelSelection, double, int) - Constructor for class weka.classifiers.rules.part.C45PruneableDecList
Constructor for pruneable tree structure.
C45Saver - Class in weka.core.converters
Writes to a destination that is in the format used by the C4.5 algorithm.
Therefore it outputs a names and a data file.
C45Saver() - Constructor for class weka.core.converters.C45Saver
Constructor
C45Split - Class in weka.classifiers.trees.j48
Class implementing a C4.5-type split on an attribute.
C45Split(int, int, double) - Constructor for class weka.classifiers.trees.j48.C45Split
Initializes the split model.
CachedKernel - Class in weka.classifiers.functions.supportVector
Base class for RBFKernel and PolyKernel that implements a simple LRU.
CachedKernel() - Constructor for class weka.classifiers.functions.supportVector.CachedKernel
default constructor - does nothing.
cacheKeyNameTipText() - Method in class weka.experiment.DatabaseResultListener
Returns the tip text for this property
cacheSizeTipText() - Method in class weka.classifiers.functions.LibSVM
Returns the tip text for this property.
cacheSizeTipText() - Method in class weka.classifiers.functions.supportVector.CachedKernel
Returns the tip text for this property
cacheSizeTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel
Returns the tip text for this property
calcCentroidPivot(int[], Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode
Calculates the centroid pivot of a node.
calcCentroidPivot(int, int, int[], Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode
Calculates the centroid pivot of a node.
calcColumnWidth(int) - Method in class weka.gui.JTableHelper
calcs the optimal column width of the given column
calcColumnWidth(JTable, int) - Static method in class weka.gui.JTableHelper
Calculates the optimal width for the column of the given table.
calcFullMargins(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator
 
calcGraph() - Method in class weka.gui.AttributeVisualizationPanel
Recalculates the barplot or histogram to display, required usually when the attribute is changed or the component is resized.
calcHeaderWidth(int) - Method in class weka.gui.JTableHelper
calcs the optimal header width of the given column
calcHeaderWidth(JTable, int) - Static method in class weka.gui.JTableHelper
Calculates the optimal width for the header of the given table.
calcMargins(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator
Calc marginal distributions of nodes in Bayesian network Note that a connected network is assumed.
calcNodeScore(int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
Calc Node Score for given parent set
calcOutOfBagTipText() - Method in class weka.classifiers.meta.Bagging
Returns the tip text for this property
calcPivot(BallNode, BallNode, Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode
Calculates the centroid pivot of a node based on its two child nodes (if merging two nodes).
calcPivot(BottomUpConstructor.TempNode, BottomUpConstructor.TempNode, Instances) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor
Calculates the centroid pivot of a node based on its two child nodes.
calcPivot(MiddleOutConstructor.TempNode, MiddleOutConstructor.TempNode, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor
/** Calculates the centroid pivot of a node based on its two child nodes (if merging two nodes).
calcPivot(MiddleOutConstructor.MyIdxList, MiddleOutConstructor.MyIdxList, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor
Calculates the centroid pivot of a node based on the list of points that it contains (tbe two lists of its children are provided).
calcRadius(int[], Instances, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode
Calculates the radius of node.
calcRadius(int, int, int[], Instances, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode
Calculates the radius of a node.
calcRadius(BallNode, BallNode, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode
Calculates the radius of a node based on its two child nodes (if merging two nodes).
calcRadius(BottomUpConstructor.TempNode, BottomUpConstructor.TempNode) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor
Calculates the radius of a node based on its two child nodes.
calcRadius(MiddleOutConstructor.TempNode, MiddleOutConstructor.TempNode) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor
Calculates the radius of a node based on its two child nodes (if merging two nodes).
calcRadius(MiddleOutConstructor.MyIdxList, MiddleOutConstructor.MyIdxList, Instance, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor
Calculates the radius of a node based on the list of points that it contains (the two lists of its children are provided).
calcScore(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
performCV returns the accuracy calculated using cross validation.
calcScoreWithExtraParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
Calc Node Score With Added Parent
calcScoreWithExtraParent(int, int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
Calc Node Score With AddedParent
calcScoreWithMissingParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
Calc Node Score With Parent Deleted
calcScoreWithMissingParent(int, int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
Calc Node Score With Parent Deleted
calcScoreWithReversedParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
Calc Node Score With Arrow reversed
calculateAlphas() - Method in class weka.classifiers.trees.lmt.LMTNode
Updates the alpha field for all nodes.
calculateAlphas() - Method in class weka.classifiers.trees.SimpleCart
Updates the alpha field for all nodes.
calculateConfirmation() - Method in class weka.associations.tertius.Rule
Calculate the confirmation of this rule.
calculateDerived() - Method in class weka.experiment.PairedStats
Calculates the derived statistics (significance etc).
calculateDerived() - Method in class weka.experiment.PairedStatsCorrected
Calculates the derived statistics (significance etc).
calculateDerived() - Method in class weka.experiment.Stats
Tells the object to calculate any statistics that don't have their values automatically updated during add.
calculateDistance(Instances) - Method in class weka.classifiers.mi.MIOptimalBall
calculate the distances from each instance in a positive bag to each bag.
calculateOptimistic() - Method in class weka.associations.tertius.Rule
Calculate the optimistic estimate of this rule.
calculatePriorSum(boolean, double) - Method in class weka.associations.PriorEstimation
calculates the numerator and the denominator of the prior equation
calculateStatistics(Instance, int, int, int) - Method in class weka.experiment.PairedCorrectedTTester
Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStatistics(Instance, int, int, int) - Method in class weka.experiment.PairedTTester
Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStatistics(Instance, int, int, int) - Method in interface weka.experiment.Tester
Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStdDevsTipText() - Method in class weka.experiment.AveragingResultProducer
Returns the tip text for this property
calculateTreshhold() - Method in class weka.attributeSelection.ScatterSearchV1
Calculate the treshold of a dataSet given an evaluator
canAcceptConnection(Class) - Method in class weka.gui.beans.MetaBean
Checks to see if any of the inputs to this group implements the supplied listener class
cancel() - Method in class weka.core.converters.AbstractFileSaver
Cancels the incremental saving process.
cancel() - Method in class weka.core.converters.AbstractSaver
Cancels the incremental saving process if the write mode is CANCEL.
cancel() - Method in class weka.core.converters.DatabaseSaver
Cancels the incremental saving process and tries to drop the table if the write mode is CANCEL.
CANCEL_OPTION - Static variable in class weka.gui.experiment.OutputFormatDialog
Signifies a cancelled property selection.
CANCEL_OPTION - Static variable in class weka.gui.ListSelectorDialog
Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class weka.gui.PropertySelectorDialog
Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class weka.gui.ViewerDialog
Signifies a cancelled property selection
canDeselect(DefaultMutableTreeNode) - Method in class weka.gui.ensembleLibraryEditor.tree.PropertyNode
informs a requesting child node whether or not it has permission to be deselected.
canKeep(Instance, Literal) - Method in class weka.associations.tertius.Body
Test if an instance can be kept as a counter-instance, if a new literal is added to this body.
canKeep(Instance, Literal) - Method in class weka.associations.tertius.Head
Test if an instance can be kept as a counter-instance, if a new literal is added to this head.
canKeep(Instance, Literal) - Method in class weka.associations.tertius.LiteralSet
Test if an instance can be kept as a counter-instance, given a new literal.
canMoveDown(JList) - Static method in class weka.gui.JListHelper
checks whether the selected items can be moved down
canMoveUp(JList) - Static method in class weka.gui.JListHelper
checks whether the selected items can be moved up
canRedo() - Method in class weka.classifiers.bayes.net.EditableBayesNet
return whether there is something on the undo stack that can be performed
canSelect(NumberNode) - Method in class weka.gui.ensembleLibraryEditor.tree.PropertyNode
This method informs a child number node whether or not it is allowed to be selected.
canUndo() - Method in class weka.classifiers.bayes.net.EditableBayesNet
return whether there is something on the undo stack that can be performed
canUndo() - Method in interface weka.core.Undoable
returns whether an undo is possible, i.e.
canUndo() - Method in class weka.gui.arffviewer.ArffPanel
returns whether an undo is possible
canUndo() - Method in class weka.gui.arffviewer.ArffSortedTableModel
returns whether an undo is possible, i.e.
canUndo() - Method in class weka.gui.arffviewer.ArffTableModel
returns whether an undo is possible, i.e.
Capabilities - Class in weka.core
A class that describes the capabilites (e.g., handling certain types of attributes, missing values, types of classes, etc.) of a specific classifier.
Capabilities(CapabilitiesHandler) - Constructor for class weka.core.Capabilities
initializes the capabilities for the given owner
capabilities() - Method in class weka.core.Capabilities
Returns an Iterator over the stored capabilities
Capabilities.Capability - Enum in weka.core
enumeration of all capabilities
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.AssociationsPanel
method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.AttributeSelectionPanel
method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.ClassifierPanel
method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.ClustererPanel
method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in interface weka.gui.explorer.Explorer.CapabilitiesFilterChangeListener
method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.PreprocessPanel
method gets called in case of a change event
CapabilitiesHandler - Interface in weka.core
Classes implementing this interface return their capabilities in regards to datasets.
capacity() - Method in class weka.core.FastVector
Returns the capacity of the vector.
capacity() - Method in class weka.core.matrix.DoubleVector
Gets the capacity of the vector.
capacity() - Method in class weka.core.matrix.IntVector
Returns the capacity of the vector
cardinality() - Method in class weka.attributeSelection.TabuSearch.Subset
 
cardinalityTipText() - Method in class weka.datagenerators.classifiers.classification.BayesNet
Returns the tip text for this property
caretUpdate(CaretEvent) - Method in class weka.gui.LogWindow
Called when the caret position is updated.
caretUpdate(CaretEvent) - Method in class weka.gui.sql.ConnectionPanel
Called when the caret position is updated.
caretUpdate(CaretEvent) - Method in class weka.gui.sql.QueryPanel
Called when the caret position is updated.
carTipText() - Method in class weka.associations.Apriori
Returns the tip text for this property
carTipText() - Method in class weka.associations.PredictiveApriori
Returns the tip text for this property
CaRuleGeneration - Class in weka.associations
Class implementing the rule generation procedure of the predictive apriori algorithm for class association rules.
CaRuleGeneration(ItemSet) - Constructor for class weka.associations.CaRuleGeneration
Constructor
CARuleMiner - Interface in weka.associations
Interface for learning class association rules.
cat(DoubleVector) - Method in class weka.core.matrix.DoubleVector
Combine two vectors together
cbind(PaceMatrix) - Method in class weka.classifiers.functions.pace.PaceMatrix
Returns a new matrix which binds two matrices with columns.
CEIL - Static variable in interface weka.core.mathematicalexpression.sym
 
CEIL - Static variable in interface weka.filters.unsupervised.instance.subsetbyexpression.sym
 
Center - Class in weka.filters.unsupervised.attribute
Centers all numeric attributes in the given dataset to have zero mean (apart from the class attribute, if set).
Center() - Constructor for class weka.filters.unsupervised.attribute.Center
 
centerHorizontal(FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet
center set of nodes half way between left and right most node in the list
centerInstances(Instances, int[], double) - Method in class weka.core.neighboursearch.KDTree
Assigns instances to centers using KDTree.
centerVertical(FastVector) - Method in class weka.classifiers.bayes.net.EditableBayesNet
center set of nodes half way between top and bottom most node in the list
CfsSubsetEval - Class in weka.attributeSelection
CfsSubsetEval :

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

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

For more information see:

M.
CfsSubsetEval() - Constructor for class weka.attributeSelection.CfsSubsetEval
Constructor
change() - Method in class weka.associations.RuleGeneration
Gets if the list fo the best rules has been changed
Change - Variable in class weka.classifiers.bayes.BayesianLogisticRegression
This variable is used to keep track of change in the value of delta summation of r(i).
ChangeDateFormat - Class in weka.filters.unsupervised.attribute
Changes the date format used by a date attribute.
ChangeDateFormat() - Constructor for class weka.filters.unsupervised.attribute.ChangeDateFormat
 
changeLength(double) - Method in class weka.core.AlgVector
Changes the length of a vector.
changeUID(long, long, String, String) - Static method in class weka.core.xml.SerialUIDChanger
changes the oldUID into newUID from the given file (binary/KOML) into the other one (binary/KOML).
CharacterDelimitedTokenizer - Class in weka.core.tokenizers
Abstract superclass for tokenizers that take characters as delimiters.
CharacterDelimitedTokenizer() - Constructor for class weka.core.tokenizers.CharacterDelimitedTokenizer
 
ChartEvent - Class in weka.gui.beans
Event encapsulating info for plotting a data point on the StripChart
ChartEvent(Object, Vector, double, double, double[], boolean) - Constructor for class weka.gui.beans.ChartEvent
Creates a new ChartEvent instance.
ChartEvent(Object) - Constructor for class weka.gui.beans.ChartEvent
Creates a new ChartEvent instance.
ChartListener - Interface in weka.gui.beans
Interface to something that can process a ChartEvent
ChebyshevDistance - Class in weka.core
Implements the Chebyshev distance.
ChebyshevDistance() - Constructor for class weka.core.ChebyshevDistance
Constructs an Chebyshev Distance object, Instances must be still set.
ChebyshevDistance(Instances) - Constructor for class weka.core.ChebyshevDistance
Constructs an Chebyshev Distance object and automatically initializes the ranges.
check(double) - Method in class weka.classifiers.trees.j48.Distribution
Checks if at least two bags contain a minimum number of instances.
Check - Class in weka.core
Abstract general class for testing in Weka.
Check() - Constructor for class weka.core.Check
 
CheckAssociator - Class in weka.associations
Class for examining the capabilities and finding problems with associators.
CheckAssociator() - Constructor for class weka.associations.CheckAssociator
 
CheckAttributeSelection - Class in weka.attributeSelection
Class for examining the capabilities and finding problems with attribute selection schemes.
CheckAttributeSelection() - Constructor for class weka.attributeSelection.CheckAttributeSelection
 
checkBounds() - Method in class weka.classifiers.misc.FLR
Checks the metric space
CheckBoxList - Class in weka.gui
An extended JList that contains CheckBoxes.
CheckBoxList() - Constructor for class weka.gui.CheckBoxList
initializes the list with an empty CheckBoxListModel
CheckBoxList(CheckBoxList.CheckBoxListModel) - Constructor for class weka.gui.CheckBoxList
initializes the list with the given CheckBoxListModel
CheckBoxList.CheckBoxListModel - Class in weka.gui
A specialized model.
CheckBoxList.CheckBoxListModel() - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel
initializes the model with no data.
CheckBoxList.CheckBoxListModel(Object[]) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel
Constructs a CheckBoxListModel from an array of objects and then applies setModel to it.
CheckBoxList.CheckBoxListModel(Vector) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel
Constructs a CheckBoxListModel from a Vector and then applies setModel to it.
CheckBoxList.CheckBoxListRenderer - Class in weka.gui
A specialized CellRenderer for the CheckBoxList
CheckBoxList.CheckBoxListRenderer() - Constructor for class weka.gui.CheckBoxList.CheckBoxListRenderer
 
CheckBoxNode - Class in weka.gui.ensembleLibraryEditor.tree
This class is responsible for implementing the underlying logic of tree nodes representing a single nominal value.
CheckBoxNode(String, boolean, String) - Constructor for class weka.gui.ensembleLibraryEditor.tree.CheckBoxNode
The constructor initializes the members of this node.
CheckBoxNodeEditor - Class in weka.gui.ensembleLibraryEditor.tree
This class is responsible for creating a simple checkBox editor for the CheckBoxNode class.
CheckBoxNodeEditor(CheckBoxNode) - Constructor for class weka.gui.ensembleLibraryEditor.tree.CheckBoxNodeEditor
The constructor builds the simple CheckBox GUI based on the information in the node that is passed to it.
checkCanonicalUserOptions() - Method in class weka.core.CheckOptionHandler
checks whether the user-supplied options stay the same after settting, getting and re-setting again
CheckClassifier - Class in weka.classifiers
Class for examining the capabilities and finding problems with classifiers.
CheckClassifier() - Constructor for class weka.classifiers.CheckClassifier
 
CheckClusterer - Class in weka.clusterers
Class for examining the capabilities and finding problems with clusterers.
CheckClusterer() - Constructor for class weka.clusterers.CheckClusterer
default constructor
checkDefaultOptions() - Method in class weka.core.CheckOptionHandler
checks whether the default options can be processed completely or some invalid options are returned by the getOptions() method.
checkErrorRateTipText() - Method in class weka.classifiers.rules.JRip
Returns the tip text for this property
CheckEstimator - Class in weka.estimators
Class for examining the capabilities and finding problems with estimators.
CheckEstimator() - Constructor for class weka.estimators.CheckEstimator
 
CheckEstimator.AttrTypes - Class in weka.estimators
class that contains info about the attribute types the estimator can estimate estimator work on one attribute only
CheckEstimator.EstTypes - Class in weka.estimators
public class that contains info about the chosen attribute type estimator work on one attribute only
CheckEstimator.EstTypes() - Constructor for class weka.estimators.CheckEstimator.EstTypes
Constructor
CheckEstimator.EstTypes(boolean, boolean, boolean) - Constructor for class weka.estimators.CheckEstimator.EstTypes
Constructor
CheckEstimator.PostProcessor - Class in weka.estimators
a class for postprocessing the test-data
CheckEstimator.PostProcessor() - Constructor for class weka.estimators.CheckEstimator.PostProcessor
 
checkForAttributeType(int) - Method in class weka.core.Instances
Checks for attributes of the given type in the dataset
checkForMissing(Instance, Instances) - Method in class weka.classifiers.functions.PaceRegression
Checks if an instance has a missing value.
checkForNominalAttributes(Instances) - Method in class weka.clusterers.XMeans
Checks for nominal attributes in the dataset.
checkForRemainingOptions(String[]) - Static method in class weka.core.Utils
Checks if the given array contains any non-empty options.
checkForStringAttributes() - Method in class weka.core.Instances
Checks for string attributes in the dataset
checkGlobalInfo() - Method in class weka.core.CheckGOE
checks whether the object declares a globalInfo method.
CheckGOE - Class in weka.core
Simple command line checking of classes that are editable in the GOE.

Usage:

CheckGOE -W classname -- test options

Valid options are:

CheckGOE() - Constructor for class weka.core.CheckGOE
default constructor
checkIndicesList(MiddleOutConstructor.MyIdxList, int, int) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor
Checks whether if the points in an index list are in some specified of the master index array.
checkInstance(Instance) - Method in class weka.core.Instances
Checks if the given instance is compatible with this dataset.
CheckKernel - Class in weka.classifiers.functions.supportVector
Class for examining the capabilities and finding problems with kernels.
CheckKernel() - Constructor for class weka.classifiers.functions.supportVector.CheckKernel
 
checkListOptions() - Method in class weka.core.CheckOptionHandler
checks whether the listOptions method works
checkModel() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
Checks if generated model is valid.
checkModel(int) - Method in class weka.classifiers.trees.lmt.ResidualSplit
Checks if there are at least 2 subsets that contain >= minNumInstances.
CheckOptionHandler - Class in weka.core
Simple command line checking of classes that implement OptionHandler.

Usage:

CheckOptionHandler -W optionHandlerClassName -- test options

Valid options are:

CheckOptionHandler() - Constructor for class weka.core.CheckOptionHandler
 
checkRemainingOptions() - Method in class weka.core.CheckOptionHandler
checks whether the user-supplied options can be processed completely or some "left-over" options remain
checkResettingOptions() - Method in class weka.core.CheckOptionHandler
checks whether the optionhandler can be re-setted again to default options after the user-supplied options have been set.
CheckScheme - Class in weka.core
Abstract general class for testing schemes in Weka.
CheckScheme() - Constructor for class weka.core.CheckScheme
 
CheckScheme.PostProcessor - Class in weka.core
a class for postprocessing the test-data
CheckScheme.PostProcessor() - Constructor for class weka.core.CheckScheme.PostProcessor
 
checkSetOptions() - Method in class weka.core.CheckOptionHandler
checks whether the user-supplied options can be processed at all
CheckSource - Class in weka.classifiers
A simple class for checking the source generated from Classifiers implementing the weka.classifiers.Sourcable interface.
CheckSource() - Constructor for class weka.classifiers.CheckSource
 
CheckSource - Class in weka.filters
A simple class for checking the source generated from Filters implementing the weka.filters.Sourcable interface.
CheckSource() - Constructor for class weka.filters.CheckSource
 
checkStatus(Object) - Method in interface weka.experiment.Compute
Check on the status of a Task
checkStatus(Object) - Method in class weka.experiment.RemoteEngine
Returns status information on a particular task
checksTurnedOffTipText() - Method in class weka.classifiers.functions.SMO
Returns the tip text for this property
checksTurnedOffTipText() - Method in class weka.classifiers.functions.supportVector.Kernel
Returns the tip text for this property
checksTurnedOffTipText() - Method in class weka.classifiers.mi.MISMO
Returns the tip text for this property
checksTurnedOffTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter
Returns the tip text for this property
checkToolTips() - Method in class weka.core.CheckGOE
checks whether the object declares tip text method for all its properties.
children() - Method in class weka.classifiers.trees.adtree.PredictionNode
Enumerates the children of this node.
childrenValues() - Method in class weka.gui.HierarchyPropertyParser
The value in the children nodes.
chisqDistribution - Static variable in class weka.core.matrix.Maths
Distribution type: chi-squared
ChisqMixture - Class in weka.classifiers.functions.pace
Class for manipulating chi-square mixture distributions.
ChisqMixture() - Constructor for class weka.classifiers.functions.pace.ChisqMixture
Contructs an empty ChisqMixture
chiSquared(double[][], boolean) - Static method in class weka.core.ContingencyTables
Returns chi-squared probability for a given matrix.
ChiSquaredAttributeEval - Class in weka.attributeSelection
ChiSquaredAttributeEval :

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

Valid options are:

ChiSquaredAttributeEval() - Constructor for class weka.attributeSelection.ChiSquaredAttributeEval
Constructor
chiSquaredProbability(double, double) - Static method in class weka.core.Statistics
Returns chi-squared probability for given value and degrees of freedom.
chiVal(double[][], boolean) - Static method in class weka.core.ContingencyTables
Computes chi-squared statistic for a contingency table.
chol() - Method in class weka.core.matrix.Matrix
Cholesky Decomposition
CholeskyDecomposition - Class in weka.core.matrix
Cholesky Decomposition.
CholeskyDecomposition(Matrix) - Constructor for class weka.core.matrix.CholeskyDecomposition
Cholesky algorithm for symmetric and positive definite matrix.
chooseIndex() - Method in class weka.classifiers.rules.part.ClassifierDecList
Method for choosing a subset to expand.
chooseLastIndex() - Method in class weka.classifiers.rules.part.ClassifierDecList
Choose last index (ie.
CISearchAlgorithm - Class in weka.classifiers.bayes.net.search.ci
The CISearchAlgorithm class supports Bayes net structure search algorithms that are based on conditional independence test (as opposed to for example score based of cross validation based search algorithms).
CISearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.ci.CISearchAlgorithm
 
CitationKNN - Class in weka.classifiers.mi
Modified version of the Citation kNN multi instance classifier.

For more information see:

Jun Wang, Zucker, Jean-Daniel: Solving Multiple-Instance Problem: A Lazy Learning Approach.
CitationKNN() - Constructor for class weka.classifiers.mi.CitationKNN
 
CLASS_GROOVYCLASSLOADER - Static variable in class weka.core.scripting.Groovy
the classname of the Groovy classloader.
CLASS_IS_LAST - Static variable in class weka.core.TestInstances
can be used for settting the class attribute index to last
CLASS_PYTHONINERPRETER - Static variable in class weka.core.scripting.Jython
the classname of the Python interpreter
CLASS_PYTHONOBJECTINPUTSTREAM - Static variable in class weka.core.scripting.Jython
the classname of the Python ObjectInputStream
ClassAssigner - Class in weka.filters.unsupervised.attribute
Filter that can set and unset the class index.
ClassAssigner() - Constructor for class weka.filters.unsupervised.attribute.ClassAssigner
 
ClassAssigner - Class in weka.gui.beans
Bean that assigns a class attribute to a data set.
ClassAssigner() - Constructor for class weka.gui.beans.ClassAssigner
 
ClassAssignerBeanInfo - Class in weka.gui.beans
BeanInfo class for the class assigner bean
ClassAssignerBeanInfo() - Constructor for class weka.gui.beans.ClassAssignerBeanInfo
 
ClassAssignerCustomizer - Class in weka.gui.beans
GUI customizer for the class assigner bean
ClassAssignerCustomizer() - Constructor for class weka.gui.beans.ClassAssignerCustomizer
 
classAttribute() - Method in class weka.core.Instance
Returns class attribute.
classAttribute() - Method in class weka.core.Instances
Returns the class attribute.
classAttributeNames() - Method in class weka.classifiers.functions.SMO
 
classAttributeNames() - Method in class weka.classifiers.mi.MISMO
Returns the names of the class attributes.
ClassBalancedND - Class in weka.classifiers.meta.nestedDichotomies
A meta classifier for handling multi-class datasets with 2-class classifiers by building a random class-balanced tree structure.

For more info, check

Lin Dong, Eibe Frank, Stefan Kramer: Ensembles of Balanced Nested Dichotomies for Multi-class Problems.
ClassBalancedND() - Constructor for class weka.classifiers.meta.nestedDichotomies.ClassBalancedND
Constructor.
classColumnTipText() - Method in class weka.gui.beans.ClassAssigner
Tool tip text for this property
ClassDiscovery - Class in weka.core
This class is used for discovering classes that implement a certain interface or a derived from a certain class.
ClassDiscovery() - Constructor for class weka.core.ClassDiscovery
 
ClassDiscovery.StringCompare - Class in weka.core
compares two strings.
ClassDiscovery.StringCompare() - Constructor for class weka.core.ClassDiscovery.StringCompare
 
classFirst(boolean) - Method in class weka.experiment.Experiment
Sets whether the first attribute is treated as the class for all datasets involved in the experiment.
classFlagTipText() - Method in class weka.datagenerators.ClusterGenerator
Returns the tip text for this property
ClassificationGenerator - Class in weka.datagenerators
Abstract class for data generators for classifiers.
ClassificationGenerator() - Constructor for class weka.datagenerators.ClassificationGenerator
initializes with default values
classificationTipText() - Method in class weka.associations.Tertius
Returns the tip text for this property.
ClassificationViaClustering - Class in weka.classifiers.meta
A simple meta-classifier that uses a clusterer for classification.
ClassificationViaClustering() - Constructor for class weka.classifiers.meta.ClassificationViaClustering
default constructor
ClassificationViaRegression - Class in weka.classifiers.meta
Class for doing classification using regression methods.
ClassificationViaRegression() - Constructor for class weka.classifiers.meta.ClassificationViaRegression
Default constructor.
Classifier - Class in weka.classifiers
Abstract classifier.
Classifier() - Constructor for class weka.classifiers.Classifier
 
Classifier - Class in weka.gui.beans
Bean that wraps around weka.classifiers
Classifier() - Constructor for class weka.gui.beans.Classifier
Creates a new Classifier instance.
ClassifierBeanInfo - Class in weka.gui.beans
BeanInfo class for the Classifier wrapper bean
ClassifierBeanInfo() - Constructor for class weka.gui.beans.ClassifierBeanInfo
 
ClassifierCustomizer - Class in weka.gui.beans
GUI customizer for the classifier wrapper bean
ClassifierCustomizer() - Constructor for class weka.gui.beans.ClassifierCustomizer
 
ClassifierDecList - Class in weka.classifiers.rules.part
Class for handling a rule (partial tree) for a decision list.
ClassifierDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.ClassifierDecList
Constructor - just calls constructor of class DecList.
ClassifierPanel - Class in weka.gui.explorer
This panel allows the user to select and configure a classifier, set the attribute of the current dataset to be used as the class, and evaluate the classifier using a number of testing modes (test on the training data, train/test on a percentage split, n-fold cross-validation, test on a separate split).
ClassifierPanel() - Constructor for class weka.gui.explorer.ClassifierPanel
Creates the classifier panel
ClassifierPerformanceEvaluator - Class in weka.gui.beans
A bean that evaluates the performance of batch trained classifiers
ClassifierPerformanceEvaluator() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluator
 
ClassifierPerformanceEvaluatorBeanInfo - Class in weka.gui.beans
Bean info class for the classifier performance evaluator
ClassifierPerformanceEvaluatorBeanInfo() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo
 
classifiers() - Method in class weka.classifiers.meta.LogitBoost
Returns the array of classifiers that have been built.
ClassifierSplitEvaluator - Class in weka.experiment
A SplitEvaluator that produces results for a classification scheme on a nominal class attribute.
ClassifierSplitEvaluator() - Constructor for class weka.experiment.ClassifierSplitEvaluator
No args constructor.
ClassifierSplitModel - Class in weka.classifiers.trees.j48
Abstract class for classification models that can be used recursively to split the data.
ClassifierSplitModel() - Constructor for class weka.classifiers.trees.j48.ClassifierSplitModel
 
classifiersTipText() - Method in class weka.classifiers.meta.MultiScheme
Returns the tip text for this property
classifiersTipText() - Method in class weka.classifiers.MultipleClassifiersCombiner
Returns the tip text for this property
ClassifierSubsetEval - Class in weka.attributeSelection
Classifier subset evaluator:

Evaluates attribute subsets on training data or a seperate hold out testing set.
ClassifierSubsetEval() - Constructor for class weka.attributeSelection.ClassifierSubsetEval
 
classifierTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval
Returns the tip text for this property
classifierTipText() - Method in class weka.attributeSelection.WrapperSubsetEval
Returns the tip text for this property
classifierTipText() - Method in class weka.classifiers.SingleClassifierEnhancer
Returns the tip text for this property
classifierTipText() - Method in class weka.experiment.ClassifierSplitEvaluator
Returns the tip text for this property
classifierTipText() - Method in class weka.experiment.RegressionSplitEvaluator
Returns the tip text for this property
classifierTipText() - Method in class weka.filters.supervised.attribute.AddClassification
Returns the tip text for this property
classifierTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
Returns the tip text for this property
ClassifierTree - Class in weka.classifiers.trees.j48
Class for handling a tree structure used for classification.
ClassifierTree(ModelSelection) - Constructor for class weka.classifiers.trees.j48.ClassifierTree
Constructor.
CLASSIFY_CHILD - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
Asks for another learning scheme to classify this node.
classifyInstance(Instance) - Method in class weka.classifiers.bayes.BayesianLogisticRegression
Classifies the given instance using the Bayesian Logistic Regression function.
classifyInstance(Instance) - Method in class weka.classifiers.bayes.ComplementNaiveBayes
Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.Classifier
Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcesses
Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.IsotonicRegression
Generate a prediction for the supplied instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.LeastMedSq
Classify a given instance using the best generated LinearRegression Classifier.
classifyInstance(Instance) - Method in class weka.classifiers.functions.LinearRegression
Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.functions.PaceRegression
Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.functions.PLSClassifier
Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.SimpleLinearRegression
Generate a prediction for the supplied instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.SMOreg
Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.functions.Winnow
Outputs the prediction for the given instance.
classifyInstance(Instance) - Method in class weka.classifiers.lazy.IB1
Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AdditiveRegression
Classify an instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.ClassificationViaClustering
Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.GridSearch
Classifies the given instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.RegressionByDiscretization
Returns a predicted class for the test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.Vote
Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.mi.MINND
Use Kullback Leibler distance to find the nearest neighbours of the given exemplar.
classifyInstance(Instance) - Method in class weka.classifiers.mi.TLD
 
classifyInstance(Instance) - Method in class weka.classifiers.mi.TLDSimple
 
classifyInstance(Instance) - Method in class weka.classifiers.misc.FLR
Classifies a given instance using the FLR Classifier model
classifyInstance(Instance) - Method in class weka.classifiers.rules.NNge
Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.OneR
Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList
Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.PART
Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.part.MakeDecList
Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.Prism
Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.Ridor
Classify the test instance with the rule learner
classifyInstance(Instance) - Method in class weka.classifiers.rules.ZeroR
Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.scripting.GroovyClassifier
Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.scripting.JythonClassifier
Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.FT
Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.Id3
Classifies a given test instance using the decision tree.
classifyInstance(Instance) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.j48.ClassifierTree
Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.J48
Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.J48graft
Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.LMT
Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.M5Base
Calculates a prediction for an instance using a set of rules or an M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel
Predicts the class of the supplied instance using the linear model.
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.Rule
Calculates a prediction for an instance using this rule or M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.RuleNode
Classify an instance using this node.
classifyInstance(Instance) - Method in class weka.classifiers.trees.NBTree
Classifies an instance.
ClassIndex - Variable in class weka.classifiers.bayes.BayesianLogisticRegression
The class index from the training data
classIndex() - Method in class weka.core.Instance
Returns the class attribute's index.
classIndex() - Method in class weka.core.Instances
Returns the class attribute's index.
classIndexTipText() - Method in class weka.associations.Apriori
Returns the tip text for this property
classIndexTipText() - Method in class weka.associations.FilteredAssociator
Returns the tip text for this property
classIndexTipText() - Method in class weka.associations.PredictiveApriori
Returns the tip text for this property
classIndexTipText() - Method in class weka.associations.Tertius
Returns the tip text for this property.
classIndexTipText() - Method in class weka.core.converters.LibSVMSaver
Returns the tip text for this property
classIndexTipText() - Method in class weka.core.converters.SVMLightSaver
Returns the tip text for this property.
classIndexTipText() - Method in class weka.core.converters.XRFFSaver
Returns the tip text for this property
classIndexTipText() - Method in class weka.filters.unsupervised.attribute.ClassAssigner
Returns the tip text for this property.
classIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
Returns the tip text for this property
classIsMissing() - Method in class weka.core.Instance
Tests if an instance's class is missing.
ClassloaderUtil - Class in weka.core
Utility class that can add jar files to the classpath dynamically.
ClassloaderUtil() - Constructor for class weka.core.ClassloaderUtil
 
className(int) - Method in class weka.classifiers.evaluation.ConfusionMatrix
Gets the name of one of the classes.
classNameTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform
Returns the tip text for this property
ClassOrder - Class in weka.filters.supervised.attribute
Changes the order of the classes so that the class values are no longer of in the order specified in the header.
ClassOrder() - Constructor for class weka.filters.supervised.attribute.ClassOrder
 
classOrderTipText() - Method in class weka.filters.supervised.attribute.ClassOrder
Returns the tip text for this property
ClassPanel - Class in weka.gui.visualize
This panel displays coloured labels for nominal attributes and a spectrum for numeric attributes.
ClassPanel() - Constructor for class weka.gui.visualize.ClassPanel
 
ClassPanel(Color) - Constructor for class weka.gui.visualize.ClassPanel
 
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.BinC45Split
Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.C45Split
Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.GraftSplit
returns the probability for instance for the specified class
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit
Return the probability for a class value
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.NBTreeSplit
Return the probability for a class value
classProbLaplace(int, Instance, int) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
Gets class probability for instance.
classSgn(double) - Static method in class weka.classifiers.bayes.BayesianLogisticRegression
This class is used to mask the internal class labels.
classValue() - Method in class weka.core.Instance
Returns an instance's class value in internal format.
ClassValuePicker - Class in weka.gui.beans
 
ClassValuePicker() - Constructor for class weka.gui.beans.ClassValuePicker
 
ClassValuePickerBeanInfo - Class in weka.gui.beans
BeanInfo class for the class value picker bean
ClassValuePickerBeanInfo() - Constructor for class weka.gui.beans.ClassValuePickerBeanInfo
 
ClassValuePickerCustomizer - Class in weka.gui.beans
 
ClassValuePickerCustomizer() - Constructor for class weka.gui.beans.ClassValuePickerCustomizer
 
classValueTipText() - Method in class weka.filters.supervised.instance.SMOTE
Returns the tip text for this property.
clean() - Method in class weka.classifiers.functions.supportVector.CachedKernel
Frees the cache used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.Kernel
Frees the memory used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.PolyKernel
Frees the cache used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
Frees the memory used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.StringKernel
Frees the memory used by the kernel.
clean() - Method in class weka.classifiers.mi.supportVector.MIPolyKernel
Frees the cache used by the kernel.
cleanse(Instance) - Method in class weka.classifiers.mi.MINND
Cleanse the given exemplar according to the valid and noise data statistics
cleanup(Instances) - Method in class weka.classifiers.rules.part.ClassifierDecList
Cleanup in order to save memory.
cleanUp() - Method in class weka.classifiers.rules.RuleStats
Frees up memory after classifier has been built.
cleanup() - Method in class weka.classifiers.trees.ft.FTtree
Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.j48.BinC45ModelSelection
Sets reference to training data to null.
cleanup() - Method in class weka.classifiers.trees.j48.C45ModelSelection
Sets reference to training data to null.
cleanup(Instances) - Method in class weka.classifiers.trees.j48.ClassifierTree
Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.j48.NBTreeModelSelection
Sets reference to training data to null.
cleanup() - Method in class weka.classifiers.trees.lmt.LMTNode
Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.lmt.LogisticBase
Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.lmt.ResidualModelSelection
Method not in use
clear() - Method in class weka.associations.tertius.SimpleLinkedList
 
clear() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable
Clears this hashtable so that it contains no keys.
clear() - Method in class weka.classifiers.xml.XMLClassifier
generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.neighboursearch.covertrees.Stack
Removes all the elements from the stack.
clear() - M