All Packages  Class Hierarchy

M

m_ADNodes. Variable in class weka.classifiers.bayes.VaryNode

list of ADNode children

m_AttIndexes. Variable in class weka.classifiers.lazy.LBR.Indexes

the array attribute indexes

M_AVERAGE. Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

m_ClassIndex. Variable in class weka.classifiers.lazy.LBR.Indexes

the Class Index for the data set

m_col. Variable in class weka.gui.treevisualizer.NamedColor

The actual color object

m_cols. Variable in class weka.gui.treevisualizer.Colors

The array with all the colors input

m_CurrDebugFlag. Variable in class weka.clusterers.XMeans

m_customColour. Variable in class weka.gui.visualize.PlotData2D

M_DELETE. Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

Missing value handling mode

m_displayAllPoints. Variable in class weka.gui.visualize.PlotData2D

Display all points (ie.

m_experimentFinished. Variable in class weka.experiment.RemoteExperimentEvent

True if a remote experiment has finished

m_indexVal. Variable in class weka.gui.visualize.AttributePanelEvent

The index for the new attribute

m_iNode. Variable in class weka.classifiers.bayes.VaryNode

index of the node varied

m_Instances. Variable in class weka.classifiers.bayes.BayesNet

The dataset header for the purposes of printing out a semi-intelligible model

m_Instances. Variable in class weka.classifiers.bayes.ADNode

list of Instance children (either m_Instances or m_VaryNodes is instantiated)

m_InstIndexes. Variable in class weka.classifiers.lazy.LBR.Indexes

the array instance indexes

m_logMessage. Variable in class weka.experiment.RemoteExperimentEvent

A log type message

M_MAXDIFF. Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

m_messageString. Variable in class weka.experiment.RemoteExperimentEvent

The message

m_name. Variable in class weka.gui.treevisualizer.NamedColor

The name of the color

m_nCount. Variable in class weka.classifiers.bayes.ADNode

count

m_nMCV. Variable in class weka.classifiers.bayes.VaryNode

most common value

M_NORMAL. Static variable in interface weka.classifiers.lazy.kstar.KStarConstants

m_nStartNode. Variable in class weka.classifiers.bayes.ADNode

first node in VaryNode array

m_NumAttsSet. Variable in class weka.classifiers.lazy.LBR.Indexes

the number of attributes "in use" or set to a the original value (true or false)

m_NumInstsSet. Variable in class weka.classifiers.lazy.LBR.Indexes

the number of instances "in use" or set to a the original value (true or false)

m_numParameters. Variable in class weka.classifiers.trees.m5.RuleNode

the number of paramters in the chosen model for this node---either the subtree model or the linear model.

m_NumSeqAttsSet. Variable in class weka.classifiers.lazy.LBR.Indexes

the number of sequential attributes "in use" or set to a the original value (true or false)

m_NumSeqInstsSet. Variable in class weka.classifiers.lazy.LBR.Indexes

the number of sequential instances "in use" or set to a the original value (true or false)

m_Ranges. Variable in class weka.core.DistanceFunction

the range of the attributes

m_SequentialAttIndexes. Variable in class weka.classifiers.lazy.LBR.Indexes

an array of attribute indexes that are set to either true or false

m_SequentialInstIndexes. Variable in class weka.classifiers.lazy.LBR.Indexes

the array of instance indexes that are set to a either true or false

m_statusMessage. Variable in class weka.experiment.RemoteExperimentEvent

A status type message

m_useCustomColour. Variable in class weka.gui.visualize.PlotData2D

Custom colour for this plot

m_VaryNodes. Variable in class weka.classifiers.bayes.ADNode

list of VaryNode children

m_xChange. Variable in class weka.gui.visualize.AttributePanelEvent

True if the x selection changed

m_yChange. Variable in class weka.gui.visualize.AttributePanelEvent

True if the y selection changed

M5Base class weka.classifiers.trees.m5.M5Base.

M5Base.

M5Base(). Constructor for class weka.classifiers.trees.m5.M5Base

Constructor

M5P class weka.classifiers.trees.m5.M5P.

M5P.

M5P(). Constructor for class weka.classifiers.trees.m5.M5P

Creates a new M5P instance.

M5Rules class weka.classifiers.rules.M5Rules.

M5 Rules.

M5Rules(). Constructor for class weka.classifiers.rules.M5Rules

MahalanobisEstimator class weka.estimators.MahalanobisEstimator.

Simple probability estimator that places a single normal distribution over the observed values.

MahalanobisEstimator(Matrix, double, double). Constructor for class weka.estimators.MahalanobisEstimator

Constructor

main(String[]). Static method in class weka.gui.ResultHistoryPanel

Tests out the result history from the command line.

main(String[]). Static method in class weka.gui.GenericArrayEditor

Tests out the array editor from the command line.

main(String[]). Static method in class weka.gui.SelectedTagEditor

Tests out the selectedtag editor from the command line.

main(String[]). Static method in class weka.gui.AttributeVisualizationPanel

Main method to test this class from command line

main(String[]). Static method in class weka.gui.HierarchyPropertyParser

Tests out the parser.

main(String[]). Static method in class weka.gui.AttributeSelectionPanel

Tests the attribute selection panel from the command line.

main(String[]). Static method in class weka.gui.GenericObjectEditor

Tests out the Object editor from the command line.

main(String[]). Static method in class weka.gui.InstancesSummaryPanel

Tests out the instance summary panel from the command line.

main(String[]). Static method in class weka.gui.PropertySelectorDialog

Tests out the property selector from the command line.

main(String[]). Static method in class weka.gui.LogPanel

Tests out the log panel from the command line.

main(String[]). Static method in class weka.gui.GUIChooser

Tests out the GUIChooser environment.

main(String[]). Static method in class weka.gui.AttributeSummaryPanel

Tests out the attribute summary panel from the command line.

main(String[]). Static method in class weka.gui.ListSelectorDialog

Tests out the list selector from the command line.

main(String[]). Static method in class weka.gui.SaveBuffer

Main method for testing this class

main(String[]). Static method in class weka.gui.WekaTaskMonitor

Main method for testing this class

main(String[]). Static method in class weka.gui.AttributeListPanel

Tests the attribute list panel from the command line.

main(String[]). Static method in class weka.gui.SimpleCLI

Method to start up the simple cli

main(String[]). Static method in class weka.gui.explorer.PreprocessPanel

Tests out the instance-preprocessing panel from the command line.

main(String[]). Static method in class weka.gui.explorer.ClustererPanel

Tests out the clusterer panel from the command line.

main(String[]). Static method in class weka.gui.explorer.Explorer

Tests out the explorer environment.

main(String[]). Static method in class weka.gui.explorer.AttributeSelectionPanel

Tests out the attribute selection panel from the command line.

main(String[]). Static method in class weka.gui.explorer.ClassifierPanel

Tests out the classifier panel from the command line.

main(String[]). Static method in class weka.gui.explorer.AssociationsPanel

Tests out the Associator panel from the command line.

main(String[]). Static method in class weka.gui.treevisualizer.TreeVisualizer

Main method for testing this class.

main(String[]). Static method in class weka.gui.beans.DataVisualizer

main(String[]). Static method in class weka.gui.beans.ScatterPlotMatrix

main(String[]). Static method in class weka.gui.beans.StripChart

Tests out the StripChart from the command line

main(String[]). Static method in class weka.gui.beans.KnowledgeFlow

Main method.

main(String[]). Static method in class weka.gui.beans.AttributeSummarizer

main(String[]). Static method in class weka.gui.experiment.SetupPanel

Tests out the experiment setup from the command line.

main(String[]). Static method in class weka.gui.experiment.DistributeExperimentPanel

Tests out the panel from the command line.

main(String[]). Static method in class weka.gui.experiment.DatasetListPanel

Tests out the dataset list panel from the command line.

main(String[]). Static method in class weka.gui.experiment.RunPanel

Tests out the run panel from the command line.

main(String[]). Static method in class weka.gui.experiment.AlgorithmListPanel

Tests out the algorithm list panel from the command line.

main(String[]). Static method in class weka.gui.experiment.RunNumberPanel

Tests out the panel from the command line.

main(String[]). Static method in class weka.gui.experiment.Experimenter

Tests out the experiment environment.

main(String[]). Static method in class weka.gui.experiment.GeneratorPropertyIteratorPanel

Tests out the panel from the command line.

main(String[]). Static method in class weka.gui.experiment.HostListPanel

Tests out the host list panel from the command line.

main(String[]). Static method in class weka.gui.experiment.SimpleSetupPanel

Tests out the experiment setup from the command line.

main(String[]). Static method in class weka.gui.experiment.ResultsPanel

Tests out the results panel from the command line.

main(String[]). Static method in class weka.gui.visualize.Plot2D

Main method for testing this class

main(String[]). Static method in class weka.gui.visualize.ClassPanel

Main method for testing this class.

main(String[]). Static method in class weka.gui.visualize.AttributePanel

Main method for testing this class.

main(String[]). Static method in class weka.gui.visualize.LegendPanel

Main method for testing this class

main(String[]). Static method in class weka.gui.visualize.MatrixPanel

Main method for testing this class

main(String[]). Static method in class weka.gui.visualize.VisualizePanel

Main method for testing this class

main(String[]). Static method in class weka.gui.boundaryvisualizer.BoundaryPanel

Main method for testing this class

main(String[]). Static method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed

Main method for testing this class

main(String[]). Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer

Main method for testing this class

main(String[]). Static method in class weka.core.RandomVariates

Main method for testing this class.

main(String[]). Static method in class weka.core.Queue

Main method for testing this class.

main(String[]). Static method in class weka.core.Instance

Main method for testing this class.

main(String[]). Static method in class weka.core.SparseInstance

Main method for testing this class.

main(String[]). Static method in class weka.core.BinarySparseInstance

Main method for testing this class.

main(String[]). Static method in class weka.core.Attribute

Simple main method for testing this class.

main(String[]). Static method in class weka.core.EuclideanDistance

Main method for testing this class.

main(String[]). Static method in class weka.core.Matrix

Main method for testing this class.

main(String[]). Static method in class weka.core.Range

Main method for testing this class.

main(String[]). Static method in class weka.core.SpecialFunctions

Main method for testing this class.

main(String[]). Static method in class weka.core.Instances

Main method for this class -- just prints a summary of a set of instances.

main(String[]). Static method in class weka.core.Statistics

Main method for testing this class.

main(String[]). Static method in class weka.core.AlgVector

Main method for testing this class.

main(String[]). Static method in class weka.core.CheckOptionHandler

Main method for using the CheckOptionHandler.

Valid options are:

-W classname
The name of the class implementing an OptionHandler.

main(String[]). Static method in class weka.core.ContingencyTables

Main method for testing this class.

main(String[]). Static method in class weka.core.KDTree

Main method for testing this class

main(String[]). Static method in class weka.core.Utils

Main method for testing this class.

main(String[]). Static method in class weka.core.converters.CSVLoader

Main method.

main(String[]). Static method in class weka.core.converters.C45Loader

Main method for testing this class.

main(String[]). Static method in class weka.core.converters.ArffLoader

Main method.

main(String[]). Static method in class weka.core.converters.SerializedInstancesLoader

Main method.

main(String[]). Static method in class weka.clusterers.EM

Main method for testing this class.

main(String[]). Static method in class weka.clusterers.ClusterEvaluation

Main method for testing this class.

main(String[]). Static method in class weka.clusterers.FarthestFirst

Main method for testing this class.

main(String[]). Static method in class weka.clusterers.SimpleKMeans

Main method for testing this class.

main(String[]). Static method in class weka.clusterers.AlgVector

Main method for testing this class.

main(String[]). Static method in class weka.clusterers.XMeans

Main method for testing this class.

main(String[]). Static method in class weka.clusterers.Cobweb

main(String[]). Static method in class weka.clusterers.DistributionMetaClusterer

Main method for testing this class.

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

Main method for testing this class.

main(String[]). Static method in class weka.filters.NullFilter

Main method for testing this class.

main(String[]). Static method in class weka.filters.AllFilter

Main method for testing this class.

main(String[]). Static method in class weka.filters.supervised.attribute.ClassOrder

Main method for testing this class.

main(String[]). Static method in class weka.filters.supervised.attribute.NominalToBinary

Main method for testing this class.

main(String[]). Static method in class weka.filters.supervised.attribute.Discretize

Main method for testing this class.

main(String[]). Static method in class weka.filters.supervised.attribute.AttributeSelection

Main method for testing this class.

main(String[]). Static method in class weka.filters.supervised.instance.Resample

Main method for testing this class.

instance.StratifiedRemoveFolds.html">StratifiedRemoveFolds

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.Remove

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.AddExpression

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.ReplaceMissingValues

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.Add

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.MergeTwoValues

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.Copy

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.AddNoise

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.SwapValues

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.NumericToBinary

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.Discretize

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.FirstOrder

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.RemoveUseless

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.Normalize

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.Standardize

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.RemoveType

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.Obfuscate

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.AddCluster

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.StringToWordVector

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.NominalToBinary

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.TimeSeriesDelta

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.StringToNominal

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.PKIDiscretize

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.MakeIndicator

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.attribute.NumericTransform

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.instance.NonSparseToSparse

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.instance.RemoveFolds

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.instance.RemoveRange

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.instance.RemoveMisclassified

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.instance.Randomize

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.instance.SparseToNonSparse

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.instance.RemovePercentage

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.instance.Resample

Main method for testing this class.

main(String[]). Static method in class weka.filters.unsupervised.instance.RemoveWithValues

Main method for testing this class.

main(String[]). Static method in class weka.experiment.PairedTTester

Test the class from the command line.

main(String[]). Static method in class weka.experiment.PairedCorrectedTTester

Test the class from the command line.

main(String[]). Static method in class weka.experiment.CrossValidationResultProducer

main(String[]). Static method in class weka.experiment.Experiment

Configures/Runs the Experiment from the command line.

main(String[]). Static method in class weka.experiment.RemoteExperiment

Configures/Runs the Experiment from the command line.

main(String[]). Static method in class weka.experiment.PairedStats

Tests the paired stats object from the command line.

main(String[]). Static method in class weka.experiment.Stats

Tests the paired stats object from the command line.

main(String[]). Static method in class weka.experiment.RemoteEngine

Main method.

main(String[]). Static method in class weka.experiment.InstanceQuery

Test the class from the command line.

main(String[]). Static method in class weka.experiment.OutputZipper

Main method for testing this class

main(String[]). Static method in class weka.estimators.NormalEstimator

Main method for testing this class.

main(String[]). Static method in class weka.estimators.DiscreteEstimator

Main method for testing this class.

main(String[]). Static method in class weka.estimators.DDConditionalEstimator

Main method for testing this class.

main(String[]). Static method in class weka.estimators.KDConditionalEstimator

Main method for testing this class.

main(String[]). Static method in class weka.estimators.DKConditionalEstimator

Main method for testing this class.

main(String[]). Static method in class weka.estimators.NDConditionalEstimator

Main method for testing this class.

main(String[]). Static method in class weka.estimators.KKConditionalEstimator

Main method for testing this class.

main(String[]). Static method in class weka.estimators.DNConditionalEstimator

Main method for testing this class.

main(String[]). Static method in class weka.estimators.MahalanobisEstimator

Main method for testing this class.

main(String[]). Static method in class weka.estimators.KernelEstimator

Main method for testing this class.

main(String[]). Static method in class weka.estimators.NNConditionalEstimator

Main method for testing this class.

main(String[]). Static method in class weka.estimators.PoissonEstimator

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.SVMAttributeEval

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.GainRatioAttributeEval

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.CfsSubsetEval

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.ReliefFAttributeEval

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.AttributeSelection

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.ChiSquaredAttributeEval

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.OneRAttributeEval

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.InfoGainAttributeEval

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.ConsistencySubsetEval

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.ClassifierSubsetEval

Main method for testing this class.

main(String[]). Static method in class weka.attributeSelection.PrincipalComponents

Main method for testing this class

main(String[]). Static method in class weka.attributeSelection.WrapperSubsetEval

Main method for testing this class.

main(String[]). Static method in class weka.associations.Apriori

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.BVDecompose

Test method for this class

main(String[]). Static method in class weka.classifiers.Evaluation

A test method for this class.

main(String[]). Static method in class weka.classifiers.CheckClassifier

Test method for this class

main(String[]). Static method in class weka.classifiers.lazy.IBk

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.lazy.LBR

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.lazy.LWL

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.lazy.IB1

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.lazy.kstar.KStar

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.AdditiveRegression

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.ClassificationViaRegression

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.DistributionMetaClassifier

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.Stacking

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.MultiBoostAB

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.Vote

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.Bagging

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.ThresholdSelector

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.MetaCost

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.MultiScheme

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.MultiClassClassifier

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.AdaBoostM1

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.OrdinalClassClassifier

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.AttributeSelectedClassifier

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.CVParameterSelection

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.LogitBoost

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.Grading

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.StackingC

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.CostSensitiveClassifier

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.RegressionByDiscretization

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.meta.RacedIncrementalLogitBoost

Main method for this class.

main(String[]). Static method in class weka.classifiers.meta.FilteredClassifier

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.misc.HyperPipes

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.misc.VFI

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.bayes.DiscreteEstimatorBayes

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.bayes.BayesNet

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.bayes.AODE

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.bayes.NaiveBayesSimple

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.bayes.BayesNetB

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.bayes.BayesNetK2

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.bayes.BayesNetB2

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.bayes.NaiveBayes

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.bayes.NaiveBayesUpdateable

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.rules.DecisionTable

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.rules.Ridor

Main method.

main(String[]). Static method in class weka.classifiers.rules.JRip

Main method.

main(String[]). Static method in class weka.classifiers.rules.ConjunctiveRule

Main method.

main(String[]). Static method in class weka.classifiers.rules.Nnge

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.rules.ZeroR

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.rules.M5Rules

Main method by which this class can be tested

main(String[]). Static method in class weka.classifiers.rules.OneR

Main method for testing this class

main(String[]). Static method in class weka.classifiers.rules.Prism

Main method for testing this class

main(String[]). Static method in class weka.classifiers.rules.part.PART

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.trees.DecisionStump

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.trees.UserClassifier

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.trees.REPTree

Main method for this class.

main(String[]). Static method in class weka.classifiers.trees.RandomForest

Main method for this class.

main(String[]). Static method in class weka.classifiers.trees.Id3

Main method.

main(String[]). Static method in class weka.classifiers.trees.RandomTree

Main method for this class.

main(String[]). Static method in class weka.classifiers.trees.m5.M5P

Main method by which this class can be tested

main(String[]). Static method in class weka.classifiers.trees.j48.J48

Main method for testing this class

main(String[]). Static method in class weka.classifiers.trees.adtree.ADTree

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.evaluation.ThresholdCurve

Tests the ThresholdCurve generation from the command line.

main(String[]). Static method in class weka.classifiers.evaluation.CostCurve

Tests the CostCurve generation from the command line.

main(String[]). Static method in class weka.classifiers.evaluation.MarginCurve

Tests the MarginCurve generation from the command line.

main(String[]). Static method in class weka.classifiers.functions.SimpleLinearRegression

Main method for testing this class

main(String[]). Static method in class weka.classifiers.functions.LeastMedSq

generate a Linear regression predictor for testing

main(String[]). Static method in class weka.classifiers.functions.VotedPerceptron

Main method.

main(String[]). Static method in class weka.classifiers.functions.LinearRegression

Generates a linear regression function predictor.

main(String[]). Static method in class weka.classifiers.functions.Winnow

Main method.

main(String[]). Static method in class weka.classifiers.functions.Logistic

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.functions.pace.PaceMatrix

main(String[]). Static method in class weka.classifiers.functions.pace.ChisqMixture

Method to test this class

main(String[]). Static method in class weka.classifiers.functions.pace.DoubleVector

main(String[]). Static method in class weka.classifiers.functions.pace.IntVector

Tests the IntVector class

main(String[]). Static method in class weka.classifiers.functions.pace.NormalMixture

Method to test this class

main(String[]). Static method in class weka.classifiers.functions.pace.DiscreteFunction

main(String[]). Static method in class weka.classifiers.functions.pace.PaceRegression

Generates a linear regression function predictor.

main(String[]). Static method in class weka.classifiers.functions.neural.NeuralNetwork

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.functions.supportVector.SMO

Main method for testing this class.

main(String[]). Static method in class weka.classifiers.functions.supportVector.SMOreg

Main method for testing this class.

MakeADTree(Instances). Static method in class weka.classifiers.bayes.ADNode

create AD tree from set of instances

MakeADTree(int, FastVector, Instances). Static method in class weka.classifiers.bayes.ADNode

create sub tree

makeBinaryTipText(). Method in class weka.filters.supervised.attribute.Discretize

Returns the tip text for this property

makeBinaryTipText(). Method in class weka.filters.unsupervised.attribute.Discretize

Returns the tip text for this property

makeCopies(ASEvaluation, int). Static method in class weka.attributeSelection.ASEvaluation

Creates copies of the current evaluator.

makeCopies(Associator, int). Static method in class weka.associations.Associator

Creates copies of the current associator.

makeCopies(Classifier, int). Static method in class weka.classifiers.Classifier

Creates copies of the current classifier, which can then be used for boosting etc.

makeCopies(Clusterer, int). Static method in class weka.clusterers.Clusterer

Creates copies of the current clusterer.

MakeDecList class weka.classifiers.rules.part.MakeDecList.

Class for handling a decision list.

MakeDecList(ModelSelection, double, int). Constructor for class weka.classifiers.rules.part.MakeDecList

Constructor for dec list pruned using C4.5 pruning.

MakeDecList(ModelSelection, int). Constructor for class weka.classifiers.rules.part.MakeDecList

Constructor for unpruned dec list.

MakeDecList(ModelSelection, int, int). Constructor for class weka.classifiers.rules.part.MakeDecList

Constructor for dec list pruned using hold-out pruning.

makeDistribution(double, int). Static method in class weka.classifiers.evaluation.NominalPrediction

Convert a single prediction into a probability distribution with all zero probabilities except the predicted value which has probability 1.0.

MakeIndicator class weka.filters.unsupervised.attribute.MakeIndicator.

Creates a new dataset with a boolean attribute replacing a nominal attribute.

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

makeUniformDistribution(int). Static method in class weka.classifiers.evaluation.NominalPrediction

Creates a uniform probability distribution -- where each of the possible classes is assigned equal probability.

MakeVaryNode(int, FastVector, Instances). Static method in class weka.classifiers.bayes.ADNode

create sub tree

makeWeighted(CostMatrix). Method in class weka.classifiers.evaluation.ConfusionMatrix

Makes a copy of this ConfusionMatrix after applying the supplied CostMatrix to the cells.

map(String, String). Method in class weka.classifiers.functions.pace.DoubleVector

Applies a method to the vector

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

Calculates the prediction margin.

MarginCurve class weka.classifiers.evaluation.MarginCurve.

Generates points illustrating the prediction margin.

MarginCurve(). Constructor for class weka.classifiers.evaluation.MarginCurve

Matchable interface weka.core.Matchable.

Interface to something that can be matched with tree matching algorithms.

Maths class weka.classifiers.functions.pace.Maths.

Class for some utility mathematical or statistical functions.

Maths(). Constructor for class weka.classifiers.functions.pace.Maths

Matrix class weka.core.Matrix.

Class for performing operations on a matrix of floating-point values.

Matrix class weka.classifiers.functions.pace.Matrix.

Jama = Java Matrix class.

MATRIX_ON_DEMAND. Static variable in class weka.classifiers.meta.MetaCost

MATRIX_ON_DEMAND. Static variable in class weka.classifiers.meta.CostSensitiveClassifier

MATRIX_SUPPLIED. Static variable in class weka.classifiers.meta.MetaCost

MATRIX_SUPPLIED. Static variable in class weka.classifiers.meta.CostSensitiveClassifier

matrix(). Method in class weka.classifiers.trees.j48.Distribution

Returns matrix with distribution of class values.

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

Constructs a matrix using a given array.

Matrix(double[][]). Constructor for class weka.classifiers.functions.pace.Matrix

Construct a matrix from a 2-D array.

Matrix(double[][], int, int). Constructor for class weka.classifiers.functions.pace.Matrix

Construct a matrix quickly without checking arguments.

Matrix(double[], int). Constructor for class weka.classifiers.functions.pace.Matrix

Construct a matrix from a one-dimensional packed array

Matrix(int, int). Constructor for class weka.core.Matrix

Constructs a matrix and initializes it with default values.

Matrix(int, int). Constructor for class weka.classifiers.functions.pace.Matrix

Construct an m-by-n matrix of zeros.

Matrix(int, int, double). Constructor for class weka.classifiers.functions.pace.Matrix

Construct an m-by-n constant matrix.

Matrix(Reader). Constructor for class weka.core.Matrix

Reads a matrix from a reader.

MatrixPanel class weka.gui.visualize.MatrixPanel.

This panel displays a plot matrix of the user selected attributes of a given data set.

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

Constructor

max. Variable in class weka.experiment.Stats

The maximum value seen, or Double.NaN if no values seen

MAX_SHAPES. Static variable in class weka.gui.visualize.Plot2D

max(). Method in class weka.classifiers.functions.pace.DoubleVector

Returns the maximum value of all elements

maxAbs(). Method in class weka.classifiers.functions.pace.PaceMatrix

Returns the maximum absolute value of all elements

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

Returns the maximum absolute value of some elements of a column, that is, the elements of A[i0:i1][j].

maxBag(). Method in class weka.classifiers.trees.j48.Distribution

Returns index of bag containing maximum number of instances.

maxChunkSizeTipText(). Method in class weka.classifiers.meta.RacedIncrementalLogitBoost

maxClass(). Method in class weka.classifiers.trees.j48.Distribution

Returns class with highest frequency over all bags.

maxClass(int). Method in class weka.classifiers.trees.j48.Distribution

Returns class with highest frequency for given bag.

maxGenerationsTipText(). Method in class weka.attributeSelection.GeneticSearch

Returns the tip text for this property

maxImpurity(). Method in interface weka.classifiers.trees.m5.SplitEvaluate

Returns the impurity of this split

maxImpurity(). Method in class weka.classifiers.trees.m5.YongSplitInfo

Returns the impurity of this split

maxImpurity(). Method in class weka.classifiers.trees.m5.CorrelationSplitInfo

Returns the impurity of this split

maximumVariancePercentageAllowedTipText(). Method in class weka.filters.unsupervised.attribute.RemoveUseless

Returns the tip text for this property

maxIndex(double[]). Static method in class weka.core.Utils

Returns index of maximum element in a given array of doubles.

maxIndex(int[]). Static method in class weka.core.Utils

Returns index of maximum element in a given array of integers.

maxIterationsTipText(). Method in class weka.clusterers.EM

Returns the tip text for this property

maxIterationsTipText(). Method in class weka.filters.unsupervised.instance.RemoveMisclassified

Returns the tip text for this property

maxModelsTipText(). Method in class weka.classifiers.meta.AdditiveRegression

Returns the tip text for this property

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

maxNumClustersTipText(). Method in class weka.clusterers.XMeans

Returns the tip text for this property

MaxParentSetSize(int). Method in class weka.classifiers.bayes.ParentSet

reserve memory for parent set

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

mean. Variable in class weka.experiment.Stats

The mean of values at the last calculateDerived() call

mean(double[]). Static method in class weka.core.Utils

Computes the mean for an array of doubles.

meanAbsoluteError(). Method in class weka.classifiers.Evaluation

Returns the mean absolute error.

meanOrMode(Attribute). Method in class weka.core.Instances

Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.

meanOrMode(int). Method in class weka.core.Instances

Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.

meanPriorAbsoluteError(). Method in class weka.classifiers.Evaluation

Returns the mean absolute error of the prior.

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

Returns the number of examples "counted".

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

Returns the number of nodes expanded.

measureNumAttributesSelected(). Method in class weka.classifiers.meta.AttributeSelectedClassifier

Additional measure --- number of attributes selected

measureNumIterations(). Method in class weka.classifiers.meta.AdditiveRegression

return the number of iterations (base classifiers) completed

measureNumLeaves(). Method in class weka.classifiers.trees.j48.J48

Returns the number of leaves

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

Calls measure function for leaf size - the number of prediction nodes.

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

Calls measure function for prediction leaf size - the number of prediction nodes without children.

measureNumRules(). Method in class weka.classifiers.rules.DecisionTable

Returns the number of rules

measureNumRules(). Method in class weka.classifiers.rules.part.PART

Return the number of rules.

measureNumRules(). Method in class weka.classifiers.trees.m5.M5Base

return the number of rules

measureNumRules(). Method in class weka.classifiers.trees.j48.J48

Returns the number of rules (same as number of leaves)

measureOutOfBagError(). Method in class weka.classifiers.meta.Bagging

Gets the out of bag error that was calculated as the classifier was built.

measureOutOfBagError(). Method in class weka.classifiers.trees.RandomForest

Gets the out of bag error that was calculated as the classifier was built.

measureSelectionTime(). Method in class weka.classifiers.meta.AttributeSelectedClassifier

Additional measure --- time taken (milliseconds) to select the attributes

measureTime(). Method in class weka.classifiers.meta.AttributeSelectedClassifier

Additional measure --- time taken (milliseconds) to select attributes and build the classifier

measureTreeSize(). Method in class weka.classifiers.trees.j48.J48

Returns the size of the tree

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

Calls measure function for tree size - the total number of nodes.

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

Merges two trees together.

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

Merges this node with another.

mergeAllItemSets(FastVector, int, int). Static method in class weka.associations.ItemSet

Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.

mergeInstance(Instance). Method in class weka.core.Instance

Merges this instance with the given instance and returns the result.

mergeInstance(Instance). Method in class weka.core.SparseInstance

Merges this instance with the given instance and returns the result.

mergeInstance(Instance). Method in class weka.core.BinarySparseInstance

Merges this instance with the given instance and returns the result.

mergeInstances(Instances, Instances). Static method in class weka.core.Instances

Merges two sets of Instances together.

MergeTwoValues class weka.filters.unsupervised.attribute.MergeTwoValues.

Merges two values of a nominal attribute.

Valid filter-specific options are:

-C col
The column containing the values to be merged.

MergeTwoValues(). Constructor for class weka.filters.unsupervised.attribute.METHOD_1_AGAINST_ALL. Static variable in class weka.classifiers.meta.MultiClassClassifier

The error correction modes

METHOD_ERROR_EXHAUSTIVE. Static variable in class weka.classifiers.meta.MultiClassClassifier

METHOD_ERROR_RANDOM. Static variable in class weka.classifiers.meta.MultiClassClassifier

methodTipText(). Method in class weka.classifiers.meta.MultiClassClassifier

metricTypeTipText(). Method in class weka.associations.Apriori

Returns the tip text for this property

min. Variable in class weka.experiment.Stats

The minimum value seen, or Double.NaN if no values seen

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

Returns the minimum absolute value of some elements of a column, that is, the elements of A[i0:i1][j].

minChunkSizeTipText(). Method in class weka.classifiers.meta.RacedIncrementalLogitBoost

minDataDLIfDeleted(int, double, boolean). Method in class weka.classifiers.rules.RuleStats

Compute the minimal data description length of the ruleset if the rule in the given position is deleted.
The min_data_DL_if_deleted = data_DL_if_deleted - potential

minDataDLIfExists(int, double, boolean). Method in class weka.classifiers.rules.RuleStats

Compute the minimal data description length of the ruleset if the rule in the given position is NOT deleted.
The min_data_DL_if_n_deleted = data_DL_if_n_deleted - potential

minimizeExpectedCostTipText(). Method in class weka.classifiers.meta.CostSensitiveClassifier

minIndex(double[]). Static method in class weka.core.Utils

Returns index of minimum element in a given array of doubles.

minIndex(int[]). Static method in class weka.core.Utils

Returns index of minimum element in a given array of integers.

minMetricTipText(). Method in class weka.associations.Apriori

Returns the tip text for this property

minNumClustersTipText(). Method in class weka.clusterers.XMeans

Returns the tip text for this property

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

used/reused to hold the smallest transformation probability

minsAndMaxs(Instances, double[][], int). Method in class weka.classifiers.trees.j48.C45Split

Returns the minsAndMaxs of the index.th subset.

minStdDevTipText(). Method in class weka.clusterers.EM

Returns the tip text for this property

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

Subtracts a value

minus(DoubleVector). Method in class weka.classifiers.functions.pace.DoubleVector

Subtracts another DoubleVector element by element

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

C = A - B

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

Subtracts a value in place

minusEquals(DoubleVector). Method in class weka.classifiers.functions.pace.DoubleVector

Subtracts another DoubleVector element by element in place

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

A = A - B

MISSING_SHAPE. Static variable in class weka.gui.visualize.Plot2D

MISSING_VALUE. Static variable in interface weka.classifiers.evaluation.Prediction

Constant representing a missing value.

missingCount. Variable in class weka.core.AttributeStats

The number of missing values

missingMergeTipText(). Method in class weka.attributeSelection.SymmetricalUncertAttributeEval

Returns the tip text for this property

missingMergeTipText(). Method in class weka.attributeSelection.GainRatioAttributeEval

Returns the tip text for this property

missingMergeTipText(). Method in class weka.attributeSelection.ChiSquaredAttributeEval

Returns the tip text for this property

missingMergeTipText(). Method in class weka.attributeSelection.InfoGainAttributeEval

Returns the tip text for this property

missingSeperateTipText(). Method in class weka.attributeSelection.CfsSubsetEval

Returns the tip text for this property

missingValue(). Static method in class weka.core.Instance

Returns the double that codes "missing".

MixtureDistribution class weka.classifiers.functions.pace.MixtureDistribution.

Abtract class for manipulating mixture distributions.

MixtureDistribution(). Constructor for class weka.classifiers.functions.pace.MixtureDistribution

ModelSelection class weka.classifiers.trees.j48.ModelSelection.

Abstract class for model selection criteria.

ModelSelection(). Constructor for class weka.classifiers.trees.j48.ModelSelection

momentumTipText(). Method in class weka.classifiers.functions.neural.NeuralNetwork

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

Returns the index of the column that has the largest (squared) response, when each of columns pvt[ks:] is moved to become the ks-th column.

mouseClicked(MouseEvent). Method in class weka.gui.treevisualizer.TreeVisualizer

Does nothing.

mouseDragged(MouseEvent). Method in class weka.gui.treevisualizer.TreeVisualizer

Performs intermediate updates to what the user wishes to do.

mouseEntered(MouseEvent). Method in class weka.gui.treevisualizer.TreeVisualizer

Does nothing.

mouseExited(MouseEvent). Method in class weka.gui.treevisualizer.TreeVisualizer

Does nothing.

mouseMoved(MouseEvent). Method in class weka.gui.treevisualizer.TreeVisualizer

Does nothing.

mousePressed(MouseEvent). Method in class weka.gui.treevisualizer.TreeVisualizer

Determines what action the user wants to perform.

mouseReleased(MouseEvent). Method in class weka.gui.treevisualizer.TreeVisualizer

Performs the final stages of what the user wants to perform.

MultiBoostAB class weka.classifiers.meta.MultiBoostAB.

Class for boosting a classifier using the MultiBoosting method.
MultiBoosting is an extension to the highly successful AdaBoost technique for forming decision committees.

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

MultiClassClassifier class weka.classifiers.meta.MultiClassClassifier.

Class for handling multi-class datasets with 2-class distribution classifiers.

Valid options are:

-M num
Sets the method to use.

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

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

Returns the multiplication of two matrices

multiResultsetFull(int, int). Method in class weka.experiment.PairedTTester

Creates a comparison table where a base resultset is compared to the other resultsets.

multiResultsetRanking(int). Method in class weka.experiment.PairedTTester

multiResultsetSummary(int). Method in class weka.experiment.PairedTTester

Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.

multiResultsetWins(int). Method in class weka.experiment.PairedTTester

Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.

MultiScheme class weka.classifiers.meta.MultiScheme.

Class for selecting a classifier from among several using cross validation on the training data.

Valid options from the command line are:

-D
Turn on debugging output.

-S seed
Random number seed (default 1).

-B classifierstring
Classifierstring should contain the full class name of a scheme included for selection followed by options to the classifier (required, option should be used once for each classifier).

-X num_folds
Use cross validation error as the basis for classifier selection.

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

mutationProbTipText(). Method in class weka.attributeSelection.GeneticSearch

Returns the tip text for this property

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