All Packages  Class Hierarchy

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

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

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

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

Backward ordering of columns in terms of response explanation.

Bagging class weka.classifiers.meta.Bagging.

Class for bagging a classifier.

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

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 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

batchFilterFile(Filter, String[]). Static method in class weka.filters.Filter

Method for testing filters ability to process multiple batches.

batchFinished(). Method in class weka.gui.streams.InstanceSavePanel

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.InstanceViewer

batchFinished(). Method in class weka.gui.streams.InstanceTable

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.ClassOrder

Signify 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.attribute.Discretize

Signifies 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.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.ReplaceMissingValues

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.Discretize

Signifies 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.Normalize

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.RemoveType

Signify 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.StringToWordVector

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.instance.RemoveFolds

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.RemoveMisclassified

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.RemovePercentage

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.

BatchLoader interface weka.core.converters.BatchLoader.

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

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

score types

BayesNet class weka.classifiers.bayes.BayesNet.

Base class for a Bayes Network classifier.

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

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.

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

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

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.Link2 class weka.attributeSelection.BestFirst.Link2.

Class for a node in a linked list.

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

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

Class for handling a linked list.

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

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

Constructor

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

Returns the bias of each binary SMO.

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

Returns the tip text for this property

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

BinarySparseInstance class weka.core.BinarySparseInstance.

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

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

Constructor that generates a sparse instance from the given instance.

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.

BinarySparseInstance(SparseInstance). Constructor for class weka.core.BinarySparseInstance

Constructor that copies the info from the given instance.

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

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 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.

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:

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

blocker(boolean). Method in class weka.classifiers.functions.neural.NeuralNetwork

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

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

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

BoundaryPanel class weka.gui.boundaryvisualizer.BoundaryPanel.

BoundaryPanel.

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

Creates a new BoundaryPanel instance.

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.

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.

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.Associator

Generates an associator.

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.

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

Generates a classifier.

buildClassifier(Instances). Method in class weka.classifiers.lazy.IBk

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.lazy.IB1

Generates the classifier.

buildClassifier(Instances). Method in class weka.classifiers.lazy.kstar.KStar

Generates the classifier.

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

Build the classifier on the supplied data

buildClassifier(Instances). Method in class weka.classifiers.meta.ClassificationViaRegression

Builds the classifiers.

buildClassifier(Instances). Method in class weka.classifiers.meta.DistributionMetaClassifier

Builds a classifier for a set of instances.

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.MultiBoostAB

Boosting method.

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.meta.Bagging

Bagging method.

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

Generates the 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.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.MultiClassClassifier

Builds the classifiers.

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

Boosting method.

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

Builds the classifiers.

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.CVParameterSelection

Generates the classifier.

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

Builds the boosted classifier

buildClassifier(Instances). Method in class weka.classifiers.meta.Grading

buildClassifier(Instances). Method in class weka.classifiers.meta.StackingC

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

buildClassifier(Instances). Method in class weka.classifiers.meta.CostSensitiveClassifier

Builds the model of the base learner.

buildClassifier(Instances). Method in class weka.classifiers.meta.RegressionByDiscretization

Generates the classifier.

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

Builds the classifier.

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

Build the classifier on the filtered data.

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.bayes.BayesNet

Generates the classifier.

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

Generates the classifier.

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

Generates the classifier.

buildClassifier(Instances). Method in class weka.classifiers.bayes.NaiveBayes

Generates the classifier.

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

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.JRip

Builds Ripper in the order of class frequencies.

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.Nnge

Generates a classifier.

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

Generates the classifier.

buildClassifier(Instances). Method in class weka.classifiers.rules.OneR

Generates the classifier.

buildClassifier(Instances). Method in class weka.classifiers.rules.Prism

Generates the classifier.

buildClassifier(Instances). Method in class weka.classifiers.rules.part.PART

Generates the classifier.

buildClassifier(Instances). Method in class weka.classifiers.rules.part.MakeDecList

Builds dec list.

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

Generates the 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.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.Id3

Builds Id3 decision tree classifier.

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

Builds classifier.

buildClassifier(Instances). Method in class weka.classifiers.trees.m5.M5Base

Generates the classifier.

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.m5.Rule

Generates a single rule or m5 model tree.

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.NoSplit

Creates a "no-split"-split for a 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.C45PruneableClassifierTree

Method for building a pruneable classifier tree.

buildClassifier(Instances). Method in class weka.classifiers.trees.j48.J48

Generates the classifier.

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.j48.C45Split

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

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.adtree.ADTree

Builds a classifier for a set of instances.

buildClassifier(Instances). Method in class weka.classifiers.functions.SimpleLinearRegression

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

Build lms regression

buildClassifier(Instances). Method in class weka.classifiers.functions.VotedPerceptron

Builds the ensemble of perceptrons.

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.Winnow

Builds the classifier

buildClassifier(Instances). Method in class weka.classifiers.functions.Logistic

Builds the classifier

buildClassifier(Instances). Method in class weka.classifiers.functions.pace.PaceRegression

Builds a pace regression model for the given data.

buildClassifier(Instances). Method in class weka.classifiers.functions.neural.NeuralNetwork

Call this function to build and train a neural network for the training data provided.

buildClassifier(Instances). Method in class weka.classifiers.functions.supportVector.SMO

Method for building the classifier.

buildClassifier(Instances). Method in class weka.classifiers.functions.supportVector.SMOreg

Method for building the classifier.

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

Generates a 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.SimpleKMeans

Generates a clusterer.

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

Generates the X-Means clusterer.

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

Builds the clusterer.

buildClusterer(Instances). Method in class weka.clusterers.DistributionMetaClusterer

Builds a clusterer for a set of instances.

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

Builds the partial tree without hold out set.

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

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.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.GainRatioAttributeEval

Initializes a gain ratio attribute evaluator.

buildEvaluator(Instances). Method in class weka.attributeSelection.CfsSubsetEval

Generates a attribute evaluator.

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

Initializes a ReliefF attribute evaluator.

buildEvaluator(Instances). Method in class weka.attributeSelection.ChiSquaredAttributeEval

Initializes a chi-squared attribute evaluator.

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

Initializes an information gain attribute evaluator.

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

Initializes an information gain attribute evaluator.

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

Generates a attribute evaluator.

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

Generates a attribute evaluator.

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

Initializes principal components and performs the analysis

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

Generates a attribute evaluator.

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

Initialize the generator using the supplied instances

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

Build the data generator

buildKDTree(Instances). Method in class weka.core.KDTree

Builds the KDTree.

buildKDTree(Instances, double[][]). Method in class weka.core.KDTree

Builds the KDTree.

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(). 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.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.

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.

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

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

All Packages  Class Hierarchy