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

B

BACKWARD_RACE - Static variable in class weka.attributeSelection.RaceSearch

BATCH - Static variable in class weka.core.converters.AbstractLoader

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

BAYES - Static variable in interface weka.classifiers.bayes.Scoreable

score types

BEAN_EXECUTING - Static variable in class weka.gui.beans.BeanInstance

BEAN_PROPERTIES - Static variable in class weka.gui.beans.KnowledgeFlow

Contains the editor properties

BIFFormatException - exception weka.gui.graphvisualizer.BIFFormatException.

This is the Exception thrown by BIFParser, if there was an error in parsing the XMLBIF string or input stream.

BIFFormatException(String) - Constructor for class weka.gui.graphvisualizer.BIFFormatException

BIFParser - class weka.gui.graphvisualizer.BIFParser.

This class parses an inputstream or a string in XMLBIF ver. 0.3 format, and builds the datastructures that are passed to it through the constructor.

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)

BIRCHCluster - class weka.datagenerators.BIRCHCluster.

Cluster data generator designed for the BIRCH System Dataset is generated with instances in K clusters.

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

BIRCHCluster.Cluster - class weka.datagenerators.BIRCHCluster.Cluster.

class to represent cluster

BIRCHCluster.Cluster(int, double, Random) - Constructor for class weka.datagenerators.BIRCHCluster.Cluster

BIRCHCluster.Cluster(int, double, int[], double) - Constructor for class weka.datagenerators.BIRCHCluster.Cluster

BIRCHCluster.GridVector - class weka.datagenerators.BIRCHCluster.GridVector.

class to represent Vector for placement of the center in space

BIRCHCluster.GridVector(int, int) - Constructor for class weka.datagenerators.BIRCHCluster.GridVector

BODY - Static variable in class weka.associations.Tertius

BOOL - Static variable in class weka.experiment.DatabaseUtils

BUILDING_MODEL - Static variable in class weka.gui.beans.Classifier

BVDecompose - class weka.classifiers.BVDecompose.

Class for performing a Bias-Variance decomposition on any classifier using the method specified in: R.

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

BVDecomposeSegCVSub - class weka.classifiers.BVDecomposeSegCVSub.

This class performs Bias-Variance decomposion on any classifier using the sub-sampled cross-validation procedure as specified in: Geoffrey I.

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

BYTE - Static variable in class weka.experiment.DatabaseUtils

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

Bagging - class weka.classifiers.meta.Bagging.

Class for bagging a classifier.

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

Constructor.

BatchClassifierEvent - class weka.gui.beans.BatchClassifierEvent.

Class encapsulating a built classifier and a batch of instances to test on.

BatchClassifierEvent(Object, Classifier, Instances, int, int) - Constructor for class weka.gui.beans.BatchClassifierEvent

Creates a new BatchClassifierEvent instance.

BatchClassifierListener - interface weka.gui.beans.BatchClassifierListener.

Interface to something that can process a BatchClassifierEvent

BatchLoader - interface weka.core.converters.BatchLoader.

Marker interface for a loader that can retrieve instances in batch mode

BayesNet - class weka.classifiers.bayes.BayesNet.

Base class for a Bayes Network classifier.

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

BayesNet - Static variable in interface weka.core.Drawable

BayesNetB - class weka.classifiers.bayes.BayesNetB.

Class for a Bayes Network classifier based on a hill climbing algorithm for learning structure as described in Buntine, W. (1991).

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

BayesNetB2 - class weka.classifiers.bayes.BayesNetB2.

Class for a Bayes Network classifier based on Buntines hill climbing algorithm for learning structure, but augmented to allow arc reversal as an operation.

BayesNetB2() - Constructor for class weka.classifiers.bayes.BayesNetB2

BayesNetK2 - class weka.classifiers.bayes.BayesNetK2.

Class for a Bayes Network classifier based on K2 for learning structure.

BayesNetK2() - Constructor for class weka.classifiers.bayes.BayesNetK2

BeanCommon - interface weka.gui.beans.BeanCommon.

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 excercise some control over connections.

BeanConnection - class weka.gui.beans.BeanConnection.

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 weka.gui.beans.BeanInstance.

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 weka.gui.beans.BeanVisual.

BeanVisual encapsulates icons and label for a given bean.

BeanVisual(String, String, String) - Constructor for class weka.gui.beans.BeanVisual

Constructor

BestFirst - class weka.attributeSelection.BestFirst.

Class for performing a best first search.

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

Constructor

BestFirst.Link2 - class weka.attributeSelection.BestFirst.Link2.

Class for a node in a linked list.

BestFirst.Link2(BitSet, double) - Constructor for class weka.attributeSelection.BestFirst.Link2

BestFirst.LinkedList2 - class weka.attributeSelection.BestFirst.LinkedList2.

Class for handling a linked list.

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

BinC45ModelSelection - class weka.classifiers.trees.j48.BinC45ModelSelection.

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

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

Initializes the split selection method with the given parameters.

BinC45Split - class weka.classifiers.trees.j48.BinC45Split.

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.

BinarySparseInstance - class weka.core.BinarySparseInstance.

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.

Body - class weka.associations.tertius.Body.

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.

BoundaryPanel - class weka.gui.boundaryvisualizer.BoundaryPanel.

BoundaryPanel.

BoundaryPanel(int, int) - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanel

Creates a new BoundaryPanel instance.

BoundaryPanel.PlotPanel - class weka.gui.boundaryvisualizer.BoundaryPanel.PlotPanel.

BoundaryPanel.PlotPanel() - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanel.PlotPanel

BoundaryPanel.PlotThread - class weka.gui.boundaryvisualizer.BoundaryPanel.PlotThread.

BoundaryPanel.PlotThread() - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanel.PlotThread

BoundaryPanelDistributed - class weka.gui.boundaryvisualizer.BoundaryPanelDistributed.

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 weka.gui.boundaryvisualizer.BoundaryVisualizer.

BoundaryVisualizer.

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

Creates a new BoundaryVisualizer instance.

BoundaryVisualizer.AxisPanel - class weka.gui.boundaryvisualizer.BoundaryVisualizer.AxisPanel.

Inner class to handle rendering the axis

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

b_Debug - Variable in class weka.classifiers.functions.LinearRegression

True if debug output will be printed

b_Debug - Variable in class weka.gui.streams.InstanceJoiner

Debugging mode

b_Debug - Variable in class weka.gui.streams.InstanceSavePanel

b_FirstInputFinished - Variable in class weka.gui.streams.InstanceJoiner

Whether the first input batch has finished

b_SecondInputFinished - Variable in class weka.gui.streams.InstanceJoiner

backQuoteChars(String) - Static method in class weka.core.Utils

Converts carriage returns and new lines in a string into \r and \n.

backfitHoldOutInstance(Instance, double, REPTree.Tree) - Method in class weka.classifiers.trees.REPTree.Tree

Inserts an instance from the hold-out set into the tree.

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

Inserts hold-out set into tree.

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

Backward ordering of columns in terms of response explanation.

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

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

Returns the tip text for this property

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.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.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.AddNoise

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.Normalize

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.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.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

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

Begin the search by starting a new thread.

bestCnt - Variable in class weka.classifiers.lazy.LBR

best_first() - Method in class weka.classifiers.rules.DecisionTable

Does a best first search

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

Returns the tip text for this property

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

Returns the bias of each binary SMO.

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

bicEstimator - Static variable in class weka.classifiers.functions.PaceRegression

big - Static variable in class weka.core.Statistics

biginv - Static variable in class weka.core.Statistics

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

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

binarySearch(int[], double[], double) - Static method in class weka.classifiers.evaluation.ThresholdCurve

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

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

Significance test binomp:

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

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

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

block(boolean) - Method in class weka.gui.beans.Classifier

Function used to stop code that calls acceptTrainingSet.

block(boolean) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Function used to stop code that calls acceptClassifier.

block(boolean) - Method in class weka.gui.beans.CrossValidationFoldMaker

Function used to stop code that calls acceptDataSet.

block(boolean) - Method in class weka.gui.beans.Filter

Function used to stop code that calls acceptTrainingSet, acceptTestSet, or acceptDataSet.

block(boolean) - Method in class weka.gui.beans.TrainTestSplitMaker

Function used to stop code that calls acceptDataSet.

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.

blocker(boolean) - Method in class weka.classifiers.trees.UserClassifier

A function used to stop the code that called buildclassifier from continuing on before the user has finished the decision tree.

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

Test if the body of the rule contains a literal.

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

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

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

bounds - Variable in class weka.classifiers.misc.FLR

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.

breakupLabel() - Method in class weka.gui.treevisualizer.Edge

This function is called to break the label of the edge up in to seperate lines

breakupLabel() - Method in class weka.gui.treevisualizer.Node

This Will break the node's text up into lines.

bufferInput(Instance) - Method in class weka.filters.Filter

Adds the supplied input instance to the inputformat dataset for later processing.

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 class weka.associations.Associator

Generates an associator.

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

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

buildAttributeConstructor(Instances) - Method in class weka.attributeSelection.PrincipalComponents

buildBranch(HierarchyPropertyParser.TreeNode, String[], int) - Method in class weka.gui.HierarchyPropertyParser

Private function to build one branch of the tree based on one property

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

Generates a classifier.

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

Stump method for building the classifiers.

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

Generates the classifier.

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.NaiveBayes

Generates the classifier.

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

Generates the classifier.

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

Generates the classifier.

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

Build lms regression

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.RBFNetwork

Builds the classifier

buildClassifier(Instances, int, int, boolean, int, int) - Method in class weka.classifiers.functions.SMO.BinarySMO

Method for building the binary classifier.

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.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.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.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.CVParameterSelection

Generates 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.Decorate

Build Decorate classifier

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

Builds the committee of randomizable classifiers.

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

Build the classifier on the filtered data.

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

Builds the classifier for the given training data.

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.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.RegressionByDiscretization

Generates 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.TreeBasedMultiClassClassifier

Builds tree recursively

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.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.VFI

Generates the classifier.

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.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.Prism

Generates the classifier.

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

Builds a single rule learner with REP dealing with 2 classes.

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.rules.part.MakeDecList

Builds dec list.

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.DecisionStump

Generates the classifier.

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

Builds Id3 decision tree classifier.

buildClassifier(Instances) - Method in class weka.classifiers.trees.J48

Generates the classifier.

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

Builds the classifier.

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

Builds 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.UserClassifier

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

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.C45PruneableClassifierTree

Method for building a pruneable classifier tree.

buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45Split

Creates a C4.5-type split on the given data.

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

Builds the classifier split model for the given set of instances.

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

Method for building a classifier tree.

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

Creates a "no-split"-split for a given set of instances.

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

Method for building a pruneable classifier tree.

buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.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() - Method in class weka.gui.beans.Classifier

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

Builds the classifier for one node.

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

Boosting method.

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

Boosting method.

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

Generates a clusterer.

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

Builds the clusterer.

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

Generates a clusterer.

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

Generates a clusterer.

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

Builds a clusterer for a set of instances.

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

Generates a clusterer.

buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.C45PruneableDecList

Builds the partial tree without hold out set.

buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.ClassifierDecList

Builds the partial tree without hold out set.

buildDecList(Instances, Instances, boolean) - Method in class weka.classifiers.rules.part.PruneableDecList

Builds the partial tree with hold out set

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.GainRatioAttributeEval

Initializes a gain ratio attribute evaluator.

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

Initializes an information gain attribute evaluator.

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

Initializes a OneRAttribute attribute evaluator.

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

Initializes principal components and performs the analysis

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

Initializes a ReliefF attribute evaluator.

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

Initializes the evaluator.

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

Initializes a symmetrical uncertainty attribute evaluator.

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

Generates a attribute evaluator.

buildGenerator(Instances) - Method in interface weka.gui.boundaryvisualizer.DataGenerator

Build the data generator

buildGenerator(Instances) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator

Initialize the generator using the supplied instances

buildLevelwiseClassifier(Instances) - Method in class weka.classifiers.meta.HND

Build levelwise NDs with respect to the specified hierarchy of classes.

buildLinearModel(int[]) - Method in class weka.classifiers.trees.m5.RuleNode

Build a linear model for this node using those attributes specified in indices.

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

Returns the tip text for this property

buildPredicate(Instances, Attribute, boolean) - Method in class weka.associations.Tertius

Build the predicate corresponding to an attribute.

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

buildRLSRegression() - Method in class weka.classifiers.functions.LeastMedSq

Builds a new LinearRegression without the 'bad' data found by buildWeight

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.

buildRuleset(Instances, double, Vector) - Method in class weka.classifiers.rules.Ridor.Ridor_node

Private function to build a rule set and return the weighted avg of accuracy rate of rules in the set.

buildStructure() - Method in class weka.classifiers.bayes.BayesNet

buildStructure determines the network structure/graph of the network.

buildStructure() - Method in class weka.classifiers.bayes.BayesNetB

buildStructure determines the network structure/graph of the network with Buntines greedy hill climbing algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.

buildStructure() - Method in class weka.classifiers.bayes.BayesNetB2

buildStructure determines the network structure/graph of the network with Buntines greedy hill climbing algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.

buildStructure() - Method in class weka.classifiers.bayes.BayesNetK2

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.

buildTree(int[][], double[][], Instances, double, double[], Instances, double, double, int, int) - Method in class weka.classifiers.trees.REPTree.Tree

Recursively generates a tree.

buildTree(int[][], double[][], Instances, double[], Instances, double, boolean, int[], Random) - Method in class weka.classifiers.trees.RandomTree

Recursively generates a tree.

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

Method for building the tree structure.

buildWeight() - Method in class weka.classifiers.functions.LeastMedSq

Builds a weight function removing instances with an abnormally high scaled residual