All Packages  Class Hierarchy

A

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

Set the abort flag

AbstractDataSource class weka.gui.beans.AbstractDataSource.

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 weka.gui.beans.AbstractDataSourceBeanInfo.

Bean info class for AbstractDataSource.

AbstractDataSourceBeanInfo(). Constructor for class weka.gui.beans.AbstractDataSourceBeanInfo

AbstractEvaluator class weka.gui.beans.AbstractEvaluator.

Abstract class for objects that can provide some kind of evaluation for classifier, clusterers etc.

AbstractEvaluator(). Constructor for class weka.gui.beans.AbstractEvaluator

Constructor

AbstractLoader class weka.core.converters.AbstractLoader.

Abstract class gives default implementation of setSource methods.

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

AbstractTestSetProducer class weka.gui.beans.AbstractTestSetProducer.

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 weka.gui.beans.AbstractTestSetProducerBeanInfo.

BeanInfo class for AbstractTestSetProducer

AbstractTestSetProducerBeanInfo(). Constructor for class weka.gui.beans.AbstractTestSetProducerBeanInfo

AbstractTimeSeries class weka.filters.unsupervised.attribute.AbstractTimeSeries.

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 weka.gui.beans.AbstractTrainAndTestSetProducer.

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 weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo.

Bean info class for AbstractTrainAndTestSetProducers

AbstractTrainAndTestSetProducerBeanInfo(). Constructor for class weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo

AbstractTrainingSetProducer class weka.gui.beans.AbstractTrainingSetProducer.

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 weka.gui.beans.AbstractTrainingSetProducerBeanInfo.

BeanInfo class for AbstractTrainingSetProducer

AbstractTrainingSetProducerBeanInfo(). Constructor for class weka.gui.beans.AbstractTrainingSetProducerBeanInfo

ACCEPT. Static variable in class weka.gui.treevisualizer.TreeDisplayEvent

States that the user has accepted the tree.

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.

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 interface weka.gui.beans.IncrementalClassifierListener

Accept the event

acceptClassifier(IncrementalClassifierEvent). Method in class weka.gui.beans.IncrementalClassifierEvaluator

Accepts and processes a classifier encapsulated in an incremental classifier event

acceptDataPoint(ChartEvent). Method in class weka.gui.beans.StripChart

Accept a data point (encapsulated in a chart event) to plot

acceptDataPoint(ChartEvent). Method in interface weka.gui.beans.ChartListener

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

Accept a data point to plot

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.TestSetMaker

Accepts and processes a data set event

acceptDataSet(DataSetEvent). Method in class weka.gui.beans.Filter

Accept a data set

acceptDataSet(DataSetEvent). Method in class weka.gui.beans.TrainingSetMaker

Accept a data set

acceptDataSet(DataSetEvent). Method in class weka.gui.beans.AbstractTrainAndTestSetProducer

Subclass must implement

acceptDataSet(DataSetEvent). Method in class weka.gui.beans.TrainTestSplitMaker

Accept a data set

acceptDataSet(DataSetEvent). Method in class weka.gui.beans.TextViewer

Accept a data set for displaying as text

acceptDataSet(DataSetEvent). Method in class weka.gui.beans.CrossValidationFoldMaker

Accept a data set

acceptDataSet(DataSetEvent). Method in class weka.gui.beans.ClassAssigner

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 interface weka.gui.beans.InstanceListener

Accept and process an instance event

acceptInstance(InstanceEvent). Method in class weka.gui.beans.Filter

Accept an instance for processing by StreamableFilters only

acceptInstance(InstanceEvent). Method in class weka.gui.beans.Classifier

Accepts an instance for incremental processing.

acceptInstance(InstanceEvent). Method in class weka.gui.beans.ClassAssigner

acceptResult(ResultProducer, Object[], Object[]). Method in class weka.experiment.LearningRateResultProducer

Accepts results from a ResultProducer.

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.CSVResultListener

Just prints out each result as it is received.

acceptResult(ResultProducer, Object[], Object[]). Method in class weka.experiment.InstancesResultListener

Collects each instance and adjusts the header information.

acceptResult(ResultProducer, Object[], Object[]). Method in interface weka.experiment.ResultListener

Accepts results from a ResultProducer.

acceptResult(ResultProducer, Object[], Object[]). Method in class weka.experiment.AveragingResultProducer

Accepts results from a ResultProducer.

acceptResult(ResultProducer, Object[], Object[]). Method in class weka.experiment.DatabaseResultProducer

Accepts results from a ResultProducer.

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.Classifier

Accepts a test set for a batch trained classifier

acceptTestSet(TestSetEvent). Method in class weka.gui.beans.TrainTestSplitMaker

Accept a test set

acceptTestSet(TestSetEvent). Method in class weka.gui.beans.TextViewer

Accept a test set for displaying as text

acceptTestSet(TestSetEvent). Method in interface weka.gui.beans.TestSetListener

Accept and process a test set event

acceptTestSet(TestSetEvent). Method in class weka.gui.beans.CrossValidationFoldMaker

Accept a test set

acceptTestSet(TestSetEvent). Method in class weka.gui.beans.ClassAssigner

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.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.Classifier

Accepts a training set and builds batch classifier

acceptTrainingSet(TrainingSetEvent). Method in class weka.gui.beans.TrainTestSplitMaker

Accept a training set

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.CrossValidationFoldMaker

Accept a training set

acceptTrainingSet(TrainingSetEvent). Method in class weka.gui.beans.ClassAssigner

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

used/reused to hold the actual entropy

actionPerformed(ActionEvent). Method in class weka.gui.SimpleCLI

Only gets called when return is pressed in the input area, which starts the command running.

actionPerformed(ActionEvent). Method in class weka.gui.treevisualizer.TreeVisualizer

Performs the action associated with the ActionEvent.

actionPerformed(ActionEvent). Method in class weka.gui.experiment.DatasetListPanel

Handle actions when buttons get pressed.

actionPerformed(ActionEvent). Method in class weka.gui.experiment.RunPanel

Controls starting and stopping the experiment.

actionPerformed(ActionEvent). Method in class weka.gui.experiment.AlgorithmListPanel

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.streams.InstanceLoader

actual(). Method in class weka.classifiers.evaluation.NumericPrediction

Gets the actual class value.

actual(). Method in class weka.classifiers.evaluation.NominalPrediction

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 weka.classifiers.meta.AdaBoostM1.

Class for boosting a classifier using Freund & Schapire's Adaboost M1 method.

AdaBoostM1(). Constructor for class weka.classifiers.meta.AdaBoostM1

Add class weka.filters.unsupervised.attribute.Add.

An instance filter that adds a new attribute to the dataset.

ADD_CHILDREN. Static variable in class weka.gui.treevisualizer.TreeDisplayEvent

Add(). Constructor for class weka.filters.unsupervised.attribute.Add

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

Returns the sum of this vector with another.

add(AlgVector). Method in class weka.clusterers.AlgVector

Returns the sum of this vector with another.

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

Adds a value to the observed values

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

Add an observed pair of values.

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

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

add(Instance). Method in class weka.core.Instances

Adds one instance to the end of the set.

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

Adds counts to given bag.

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

Adds given instance to given bag.

add(Matrix). Method in class weka.core.Matrix

Returns the sum of this matrix with another.

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

Add the given item of property to the tree

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

addActionListener(ActionListener). Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Register a listener to be notified when plotting completes

addAllBeansToContainer(JComponent). Static method in class weka.gui.beans.BeanInstance

Adds all beans to the supplied component

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

Add a rule to the ruleset and update the stats

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

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

This is used to hook an action listener to the cancel button tributeExperimentPanel.html#addCheckBoxActionListener(java.awt.event.ActionListener)">addCheckBoxActionListener(ActionListener). Method in class weka.gui.experiment.DistributeExperimentPanel

Enable objects to listen for changes to the check box

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

Set the value of children.

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

Adds a child to this node.

AddCluster class weka.filters.unsupervised.attribute.AddCluster.

A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm.

Valid filter-specific options are:

-W clusterer string
Full class name of clusterer to use, followed by scheme options.

AddCluster(). Constructor for class weka.filters.unsupervised.attribute.AddCluster

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

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

addDataSourceListener(DataSourceListener). Method in class weka.gui.beans.AbstractDataSource

Add a listener

addDataSourceListener(DataSourceListener). Method in class weka.gui.beans.Loader

Add a listener

addDataSourceListener(DataSourceListener). Method in class weka.gui.beans.Filter

Add a data source listener

addDataSourceListener(DataSourceListener). Method in interface weka.gui.beans.DataSource

Add a data source listener

addDataSourceListener(DataSourceListener). Method in class weka.gui.beans.ClassAssigner

addElement(double). Method in class weka.classifiers.functions.pace.DoubleVector

Adds an element into the vector

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

Add a value to an element.

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

Adds an element to this vector.

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 weka.filters.unsupervised.attribute.AddExpression.

Applys a mathematical expression involving attributes and numeric constants to a dataset.

AddExpression(). Constructor for class weka.filters.unsupervised.attribute.AddExpression

addGraphListener(GraphListener). Method in class weka.gui.beans.Classifier

Add a graph listener

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

Add an incremental classifier listener

addInstance(Instance). Method in class weka.clusterers.Cobweb

Adds an instance to the Cobweb tree.

addInstanceListener(InstanceListener). Method in class weka.gui.beans.AbstractDataSource

Add an instance listener

addInstanceListener(InstanceListener). Method in class weka.gui.beans.Loader

Add an instance listener

addInstanceListener(InstanceListener). Method in class weka.gui.beans.Filter

Add an instance listener

addInstanceListener(InstanceListener). Method in interface weka.gui.beans.DataSource

Add an instance listener

addInstanceListener(InstanceListener). Method in class weka.gui.beans.ClassAssigner

addInstanceListener(InstanceListener). Method in class weka.gui.streams.InstanceLoader

addInstanceListener(InstanceListener). Method in class weka.gui.streams.InstanceJoiner

addInstanceListener(InstanceListener). Method in interface weka.gui.streams.InstanceProducer

addInstanceNumberAttribute(). Method in class weka.gui.visualize.PlotData2D

Adds an instance number attribute to the plottable instances,

addInstWithUnknown(Instances, int). Method in class weka.classifiers.trees.j48.Distribution

Adds all instances with unknown values for given attribute, weighted according to frequency of instances in each bag.

AdditionalMeasureProducer interface weka.core.AdditionalMeasureProducer.

Interface to something that can produce measures other than those calculated by evaluation modules.

AdditiveRegression class weka.classifiers.meta.AdditiveRegression.

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.

addLooslyInstance(Instance). Method in class weka.core.KDTree

Adds one instance to KDTree loosly.

AddNoise class weka.filters.unsupervised.attribute.AddNoise.

Introduces noise data a random subsample of the dataset by changing a given attribute (attribute must be nominal) Valid options are:

-C col
Index of the attribute to be changed.

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

addNoise(Instances, int, int, int, boolean). Method in class weka.filters.unsupervised.attribute.AddNoise

add noise to the dataset a given percentage of the instances are changed in the way, that a set of instances are randomly selected using seed.

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

Adds an object to the results list

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

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

AddParent(int, Instances). Method in class weka.classifiers.bayes.ParentSet

Add parent to parent set 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.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.SetInstancesPanel

Adds a PropertyChangeListener who will be notified of value changes.

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.PropertySheetPanel

Adds a PropertyChangeListener.

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.beans.LoaderCustomizer

Add a property change listener

addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer

Add a property change listener

addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.ClassifierCustomizer

Add a property change listener

addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.StripChartCustomizer

Add a property change listener

addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.FilterCustomizer

Add a property change listener

addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.ClassAssignerCustomizer

Add a property change listener

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

Add a property change listener

addPropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.BeanVisual

Add a listener for property change events

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.SetupModePanel

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

Add a property change listener to this bean

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.

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

addRemoteExperimentListener(RemoteExperimentListener). Method in class weka.experiment.RemoteExperiment

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

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.

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.

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.

addTestSetListener(TestSetListener). Method in class weka.gui.beans.AbstractTestSetProducer

Add a listener for test sets

addTestSetListener(TestSetListener). Method in class weka.gui.beans.Filter

Add a test set listener

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 interface weka.gui.beans.TestSetProducer

Add a listener for test set events

addTextListener(TextListener). Method in class weka.gui.beans.ClassifierPerformanceEvaluator

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.IncrementalClassifierEvaluator

Add a text listener

addToList(BitSet, double). Method in class weka.attributeSelection.BestFirst.LinkedList2

adds an element (Link) to the list.

addToList(BitSet, double). Method in class weka.classifiers.rules.DecisionTable.LinkedList

Aadds an element (Link) to the list.

addTrainingSetListener(TrainingSetListener). Method in class weka.gui.beans.Filter

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.AbstractTrainAndTestSetProducer

Add a training set listener

addTrainingSetListener(TrainingSetListener). Method in class weka.gui.beans.ClassAssigner

addTrainingSetListener(TrainingSetListener). Method in interface weka.gui.beans.TrainingSetProducer

Add a training set listener

addUndoPoint(). Method in class weka.gui.explorer.PreprocessPanel

Backs up the current state of the dataset, so the changes can be undone.

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.DiscreteEstimator

Add a new data value to the current estimator.

addValue(double, double). Method in class weka.estimators.MahalanobisEstimator

Add a new data value to the current estimator.

addValue(double, double). Method in class weka.estimators.KernelEstimator

Add a new data value to the current estimator.

addValue(double, double). Method in interface weka.estimators.Estimator

Add a new data value to the current estimator.

addValue(double, double). Method in class weka.estimators.PoissonEstimator

Add a new data value to the current estimator.

addValue(double, double). Method in class weka.classifiers.bayes.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, double). Method in class weka.estimators.KDConditionalEstimator

Add a new data value to the current estimator.

addValue(double, double, double). Method in class weka.estimators.DKConditionalEstimator

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.KKConditionalEstimator

Add a new data value to the current estimator.

addValue(double, double, double). Method in class weka.estimators.DNConditionalEstimator

Add a new data value to the current estimator.

addValue(double, double, double). Method in class weka.estimators.NNConditionalEstimator

Add a new data value to the current estimator.

addVetoableChangeListener(String, VetoableChangeListener). Method in class weka.gui.beans.DataVisualizer

Add a vetoable change listener to this bean

addWeights(Instance, double[]). Method in class weka.classifiers.trees.j48.Distribution

Adds given instance to all bags weighting it according to given weights.

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

Will increase or decrease the postion of center.

ADNode class weka.classifiers.bayes.ADNode.

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.ADNode

Creates new ADNode

ADTree class weka.classifiers.trees.adtree.ADTree.

Class for generating an alternating decision tree.

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

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

Increments iteration counters appropriately.

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

overides the one in Experiment

AIC. Static variable in interface weka.classifiers.bayes.Scoreable

AlgorithmListPanel class weka.gui.experiment.AlgorithmListPanel.

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

AlgorithmListPanel.ObjectCellRenderer class weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer.

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

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

Create the algorithm list panel initially disabled.

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

Creates the algorithm list panel with the given experiment.

AlgVector class weka.core.AlgVector.

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

AlgVector class weka.clusterers.AlgVector.

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

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

Constructs a vector using a given array.

AlgVector(double[]). Constructor for class weka.clusterers.AlgVector

Constructs a vector using a given array.

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

Constructs a vector using an instance.

AlgVector(Instance). Constructor for class weka.clusterers.AlgVector

Constructs a vector using an instance.

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

Constructs a vector using a given data format.

AlgVector(Instances, Random). Constructor for class weka.clusterers.AlgVector

Constructs a vector using a given data format.

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

Constructs a vector and initializes it with default values.

AlgVector(int). Constructor for class weka.clusterers.AlgVector

Constructs a vector and initializes it with default values.

AllFilter class weka.filters.AllFilter.

A simple instance filter that passes all instances directly through.

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

alphaTipText(). Method in class weka.classifiers.bayes.BayesNet

AODE class weka.classifiers.bayes.AODE.

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.  The resulting algorithm is computationally efficient while delivering highly accurate classification on many learning tasks.
For more information, see

G.

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

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

Appends all elements of the supplied vector to this vector.

applyCostMatrix(Instances, Random). Method in class weka.classifiers.CostMatrix

Applies the cost matrix to a set of instances.

APPROVE_OPTION. Static variable in class weka.gui.PropertySelectorDialog

Signifies an OK property selection

APPROVE_OPTION. Static variable in class weka.gui.ListSelectorDialog

Signifies an OK property selection

Apriori class weka.associations.Apriori.

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.

ArffLoader class weka.core.converters.ArffLoader.

Reads a source that is in arff text format.

ArffLoader(). Constructor for class weka.core.converters.ArffLoader

arrayLeftDivide(Matrix). Method in class weka.classifiers.functions.pace.Matrix

Element-by-element left division, C = A.\B

arrayLeftDivideEquals(Matrix). Method in class weka.classifiers.functions.pace.Matrix

Element-by-element left division in place, A = A.\B

arrayRightDivide(Matrix). Method in class weka.classifiers.functions.pace.Matrix

Element-by-element right division, C = A./B

arrayRightDivideEquals(Matrix). Method in class weka.classifiers.functions.pace.Matrix

Element-by-element right division in place, A = A./B

arrayTimes(Matrix). Method in class weka.classifiers.functions.pace.Matrix

Element-by-element multiplication, C = A.*B

arrayTimesEquals(Matrix). Method in class weka.classifiers.functions.pace.Matrix

Element-by-element multiplication in place, A = A.*B

arrayToString(Object[]). Static method in class weka.experiment.DatabaseUtils

Converts an array of objects to a string by inserting a space between each element.

ASEvaluation class weka.attributeSelection.ASEvaluation.

Abstract attribute selection evaluation class

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

ASSearch class weka.attributeSelection.ASSearch.

Abstract attribute selection search class.

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

assignIDs(int). Method in class weka.classifiers.trees.j48.ClassifierTree

Assigns a uniqe id to every node in the tree.

AssociationsPanel class weka.gui.explorer.AssociationsPanel.

This panel allows the user to select, configure, and run a scheme that learns associations.

AssociationsPanel(). Constructor for class weka.gui.explorer.AssociationsPanel

Creates the associator panel

Associator class weka.associations.Associator.

Abstract scheme for learning associations.

Associator(). Constructor for class weka.associations.Associator

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.BinC45Split

Returns index of attribute for which split was generated.

attIndexSetTipText(). Method in class weka.filters.unsupervised.attribute.AddNoise

Returns the tip text for this property

Attribute class weka.core.Attribute.

Class for handling an attribute.

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

Constructor for a numeric attribute.

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, 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.

AttributeEvaluator class weka.attributeSelection.AttributeEvaluator.

Abstract attribute evaluator.

AttributeEvaluator(). Constructor for class weka.attributeSelection.AttributeEvaluator

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

Returns the tip text for this property

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

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.MakeIndicator

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.Remove

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.NumericTransform

Returns the tip text for this property

AttributeListPanel class weka.gui.AttributeListPanel.

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.

attributeNames(). Method in class weka.classifiers.functions.supportVector.SMO

Returns the attribute names.

attributeNameTipText(). Method in class weka.filters.unsupervised.attribute.Add

Returns the tip text for this property

AttributePanel class weka.gui.visualize.AttributePanel.

This panel displays one dimensional views of the attributes in a dataset.

AttributePanel(). Constructor for class weka.gui.visualize.AttributePanel

This constructs an attributePanel.

AttributePanelEvent class weka.gui.visualize.AttributePanelEvent.

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 weka.gui.visualize.AttributePanelListener.

Interface for classes that want to listen for Attribute selection changes in the attribute panel

AttributeSelectedClassifier class weka.classifiers.meta.AttributeSelectedClassifier.

Class for running an arbitrary classifier on data that has been reduced through attribute selection.

AttributeSelectedClassifier(). Constructor for class weka.classifiers.meta.AttributeSelectedClassifier

AttributeSelection class weka.filters.supervised.attribute.AttributeSelection.

Filter for doing attribute selection.

Valid options are:

-S <"Name of search class [search options]">
Set search method for subset evaluators.

AttributeSelection class weka.attributeSelection.AttributeSelection.

Attribute selection class.

AttributeSelection(). Constructor for class weka.filters.supervised.attribute.AttributeSelection

Constructor

AttributeSelection(). Constructor for class weka.attributeSelection.AttributeSelection

constructor.

attributeSelectionChange(AttributePanelEvent). Method in interface weka.gui.visualize.AttributePanelListener

Called when the user clicks on an attribute bar

AttributeSelectionPanel class weka.gui.AttributeSelectionPanel.

Creates a panel that displays the attributes contained in a set of instances, letting the user toggle whether each attribute is selected or not (eg: so that unselected attributes can be removed before classification).

AttributeSelectionPanel class weka.gui.explorer.AttributeSelectionPanel.

This panel allows the user to select and configure an attribute evaluator and a search method, set the attribute of the current dataset to be used as the class, and perform attribute selection using one of two selection modes (select using all the training data or perform a n-fold cross validation---on each trial selecting features using n-1 folds of the data).

AttributeSelectionPanel(). Constructor for class weka.gui.AttributeSelectionPanel

Creates the attribute selection panel with no initial instances.

AttributeSelectionPanel(). Constructor for class weka.gui.explorer.AttributeSelectionPanel

Creates the classifier panel

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 weka.core.AttributeStats.

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.

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 weka.gui.beans.AttributeSummarizer.

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 weka.gui.beans.AttributeSummarizerBeanInfo.

Bean info class for the attribute summarizer bean

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

AttributeSummaryPanel class weka.gui.AttributeSummaryPanel.

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 weka.attributeSelection.AttributeTransformer.

Abstract attribute transformer.

attributeTypeTipText(). Method in class weka.filters.unsupervised.attribute.RemoveType

Returns the tip text for this property

AttributeVisualizationPanel class weka.gui.AttributeVisualizationPanel.

Creates a panel that shows a visualization of an attribute in a dataset.

AttributeVisualizationPanel(). Constructor for class weka.gui.AttributeVisualizationPanel

AttributeVisualizationPanel(boolean). Constructor for class weka.gui.AttributeVisualizationPanel

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

attrSplit(int, Instances). Method in class weka.classifiers.trees.m5.CorrelationSplitInfo

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.neural.NeuralNetwork

AveragingResultProducer class weka.experiment.AveragingResultProducer.

AveragingResultProducer 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

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