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

T

TAGS_ATTRIBUTETYPE - Static variable in class weka.filters.unsupervised.attribute.RemoveType
Tag allowing selection of attribute type to delete
TAGS_DSTRS_TYPE - Static variable in class weka.filters.unsupervised.attribute.RandomProjection
 
TAGS_ESTIMATOR - Static variable in class weka.classifiers.functions.PaceRegression
 
TAGS_EVAL - Static variable in class weka.classifiers.meta.ThresholdSelector
 
TAGS_FILTER - Static variable in class weka.classifiers.functions.SMO
 
TAGS_FILTER - Static variable in class weka.classifiers.functions.SMOreg
 
TAGS_MATRIX_SOURCE - Static variable in class weka.classifiers.meta.CostSensitiveClassifier
 
TAGS_MATRIX_SOURCE - Static variable in class weka.classifiers.meta.MetaCost
 
TAGS_METHOD - Static variable in class weka.classifiers.meta.MultiClassClassifier
 
TAGS_MISSING - Static variable in class weka.associations.Tertius
 
TAGS_MISSING - Static variable in class weka.classifiers.lazy.KStar
Define possible missing value handling methods
TAGS_NEGATION - Static variable in class weka.associations.Tertius
 
TAGS_OPTIMIZE - Static variable in class weka.classifiers.meta.ThresholdSelector
 
TAGS_PRUNETYPE - Static variable in class weka.classifiers.meta.RacedIncrementalLogitBoost
 
TAGS_RANGE - Static variable in class weka.classifiers.meta.ThresholdSelector
 
TAGS_SCORE_TYPE - Static variable in class weka.classifiers.bayes.BayesNet
 
TAGS_SEARCHPATH - Static variable in class weka.classifiers.trees.ADTree
 
TAGS_SELECTION - Static variable in class weka.associations.Apriori
 
TAGS_SELECTION - Static variable in class weka.attributeSelection.BestFirst
 
TAGS_SELECTION - Static variable in class weka.attributeSelection.RaceSearch
 
TAGS_SELECTION - Static variable in class weka.classifiers.functions.LinearRegression
 
TAGS_VALUES - Static variable in class weka.associations.Tertius
 
TAGS_WEIGHTING - Static variable in class weka.classifiers.lazy.IBk
 
TEN_FOLD - Static variable in class weka.attributeSelection.RaceSearch
xval types
TFTransformTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
Returns the tip text for this property
THRESHOLD_NAME - Static variable in class weka.classifiers.evaluation.CostCurve
 
THRESHOLD_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
 
TIMESTAMP_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer
 
TIMESTAMP_FIELD_NAME - Static variable in class weka.experiment.RandomSplitResultProducer
 
TINY - Variable in class weka.classifiers.misc.VFI
 
TOOLBARS - Static variable in class weka.gui.beans.KnowledgeFlow
Holds the details needed to construct button bars for various supported classes of weka algorithms/tools
TO_BE_RUN - Static variable in class weka.experiment.TaskStatusInfo
 
TP_RATE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
 
TREE - Static variable in interface weka.core.Drawable
 
TRIANGLEDOWN_SHAPE - Static variable in class weka.gui.visualize.Plot2D
 
TRIANGLEUP_SHAPE - Static variable in class weka.gui.visualize.Plot2D
 
TRUE_NEG_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
 
TRUE_POS_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve
 
TWO_PI - Static variable in class weka.estimators.MahalanobisEstimator
2 * PI
TWO_PI - Static variable in class weka.estimators.NNConditionalEstimator
2 * PI
TYPE_CROSSVALIDATION_TEXT - Static variable in class weka.gui.experiment.SimpleSetupPanel
 
TYPE_FIXEDSPLIT_TEXT - Static variable in class weka.gui.experiment.SimpleSetupPanel
 
TYPE_RANDOMSPLIT_TEXT - Static variable in class weka.gui.experiment.SimpleSetupPanel
 
Tag - class weka.core.Tag.
A Tag simply associates a numeric ID with a String description.
Tag(int, String) - Constructor for class weka.core.Tag
Creates a new Tag instance.
Task - interface weka.experiment.Task.
Interface to something that can be remotely executed as a task.
TaskLogger - interface weka.gui.TaskLogger.
Interface for objects that display log and display information on running tasks.
TaskStatusInfo - class weka.experiment.TaskStatusInfo.
A class holding information for tasks being executed on RemoteEngines.
TaskStatusInfo() - Constructor for class weka.experiment.TaskStatusInfo
 
Tertius - class weka.associations.Tertius.
Class implementing a Tertius-type algorithm.
Tertius() - Constructor for class weka.associations.Tertius
Constructor that sets the options to the default values.
Test - class weka.datagenerators.Test.
Class to represent a test.
Test(int, double, Instances) - Constructor for class weka.datagenerators.Test
Constructor
Test(int, double, Instances, boolean) - Constructor for class weka.datagenerators.Test
Constructor
TestSetEvent - class weka.gui.beans.TestSetEvent.
Event encapsulating a test set
TestSetEvent(Object, Instances) - Constructor for class weka.gui.beans.TestSetEvent
 
TestSetListener - interface weka.gui.beans.TestSetListener.
Interface to something that can accpet test set events
TestSetMaker - class weka.gui.beans.TestSetMaker.
Bean that accepts data sets and produces test sets
TestSetMaker() - Constructor for class weka.gui.beans.TestSetMaker
 
TestSetMakerBeanInfo - class weka.gui.beans.TestSetMakerBeanInfo.
Bean info class for the test set maker bean.
TestSetMakerBeanInfo() - Constructor for class weka.gui.beans.TestSetMakerBeanInfo
 
TestSetProducer - interface weka.gui.beans.TestSetProducer.
Interface to something that can produce test sets
TextEvent - class weka.gui.beans.TextEvent.
Event that encapsulates some textual information
TextEvent(Object, String, String) - Constructor for class weka.gui.beans.TextEvent
Creates a new TextEvent instance.
TextListener - interface weka.gui.beans.TextListener.
Interface to something that can process a TextEvent
TextViewer - class weka.gui.beans.TextViewer.
Bean that collects and displays pieces of text
TextViewer() - Constructor for class weka.gui.beans.TextViewer
 
TextViewerBeanInfo - class weka.gui.beans.TextViewerBeanInfo.
Bean info class for the text viewer
TextViewerBeanInfo() - Constructor for class weka.gui.beans.TextViewerBeanInfo
 
ThresholdCurve - class weka.classifiers.evaluation.ThresholdCurve.
Generates points illustrating prediction tradeoffs that can be obtained by varying the threshold value between classes.
ThresholdCurve() - Constructor for class weka.classifiers.evaluation.ThresholdCurve
 
ThresholdSelector - class weka.classifiers.meta.ThresholdSelector.
Class for selecting a threshold on a probability output by a distribution classifier.
ThresholdSelector() - Constructor for class weka.classifiers.meta.ThresholdSelector
 
ThresholdVisualizePanel - class weka.gui.visualize.ThresholdVisualizePanel.
This panel is a VisualizePanel, with the added ablility to display the area under the ROC curve if an ROC curve is chosen.
ThresholdVisualizePanel() - Constructor for class weka.gui.visualize.ThresholdVisualizePanel
 
TimeSeriesDelta - class weka.filters.unsupervised.attribute.TimeSeriesDelta.
An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the difference between the current value and the equivalent attribute attribute value of some previous (or future) instance.
TimeSeriesDelta() - Constructor for class weka.filters.unsupervised.attribute.TimeSeriesDelta
 
TimeSeriesTranslate - class weka.filters.unsupervised.attribute.TimeSeriesTranslate.
An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the equivalent attribute attribute values of some previous (or future) instance.
TimeSeriesTranslate() - Constructor for class weka.filters.unsupervised.attribute.TimeSeriesTranslate
 
TrainTestSplitMaker - class weka.gui.beans.TrainTestSplitMaker.
Bean that accepts data sets, training sets, test sets and produces both a training and test set by randomly spliting the data
TrainTestSplitMaker() - Constructor for class weka.gui.beans.TrainTestSplitMaker
 
TrainTestSplitMakerBeanInfo - class weka.gui.beans.TrainTestSplitMakerBeanInfo.
Bean info class for the train test split maker bean
TrainTestSplitMakerBeanInfo() - Constructor for class weka.gui.beans.TrainTestSplitMakerBeanInfo
 
TrainTestSplitMakerCustomizer - class weka.gui.beans.TrainTestSplitMakerCustomizer.
GUI customizer for the train test split maker bean
TrainTestSplitMakerCustomizer() - Constructor for class weka.gui.beans.TrainTestSplitMakerCustomizer
 
TrainingSetEvent - class weka.gui.beans.TrainingSetEvent.
Event encapsulating a training set
TrainingSetEvent(Object, Instances) - Constructor for class weka.gui.beans.TrainingSetEvent
Creates a new TrainingSetEvent
TrainingSetListener - interface weka.gui.beans.TrainingSetListener.
Interface to something that can accept and process training set events
TrainingSetMaker - class weka.gui.beans.TrainingSetMaker.
Bean that accepts a data sets and produces a training set
TrainingSetMaker() - Constructor for class weka.gui.beans.TrainingSetMaker
 
TrainingSetMakerBeanInfo - class weka.gui.beans.TrainingSetMakerBeanInfo.
Bean info class for the training set maker bean
TrainingSetMakerBeanInfo() - Constructor for class weka.gui.beans.TrainingSetMakerBeanInfo
 
TrainingSetProducer - interface weka.gui.beans.TrainingSetProducer.
Interface to something that can produce a training set
TreeBasedMultiClassClassifier - class weka.classifiers.meta.TreeBasedMultiClassClassifier.
Class that represents and builds a classifier tree.
TreeBasedMultiClassClassifier() - Constructor for class weka.classifiers.meta.TreeBasedMultiClassClassifier
 
TreeBuild - class weka.gui.treevisualizer.TreeBuild.
This class will parse a dotty file and construct a tree structure from it with Edge's and Node's
TreeBuild() - Constructor for class weka.gui.treevisualizer.TreeBuild
Upon construction this will only setup the color table for quick reference of a color.
TreeBuild.InfoObject - class weka.gui.treevisualizer.TreeBuild.InfoObject.
This is an internal class used to keep track of the info for the objects before they are actually created.
TreeBuild.InfoObject(String) - Constructor for class weka.gui.treevisualizer.TreeBuild.InfoObject
This will construct a new InfoObject with the specified ID string.
TreeDisplayEvent - class weka.gui.treevisualizer.TreeDisplayEvent.
An event containing the user selection from the tree display
TreeDisplayEvent(int, String) - Constructor for class weka.gui.treevisualizer.TreeDisplayEvent
Constructs an event with the specified command and what the command is applied to.
TreeDisplayListener - interface weka.gui.treevisualizer.TreeDisplayListener.
Interface implemented by classes that wish to recieve user selection events from a tree displayer.
TreeLoader - class weka.core.converters.TreeLoader.
Abstract TreeLoader should be extended by Loaders for tree-formatted data.
TreeLoader() - Constructor for class weka.core.converters.TreeLoader
 
TreeVisualizer - class weka.gui.treevisualizer.TreeVisualizer.
Class for displaying a Node structure in Swing.
TreeVisualizer(TreeDisplayListener, String, NodePlace) - Constructor for class weka.gui.treevisualizer.TreeVisualizer
Constructs Displayer to display a tree provided in a dot format.
TreeVisualizer(TreeDisplayListener, Node, NodePlace) - Constructor for class weka.gui.treevisualizer.TreeVisualizer
Constructs Displayer with the specified Node as the top of the tree, and uses the NodePlacer to place the Nodes.
TreeVisualizer.EdgeInfo - class weka.gui.treevisualizer.TreeVisualizer.EdgeInfo.
Internal Class for containing display information about an Edge.
TreeVisualizer.EdgeInfo() - Constructor for class weka.gui.treevisualizer.TreeVisualizer.EdgeInfo
 
TreeVisualizer.NodeInfo - class weka.gui.treevisualizer.TreeVisualizer.NodeInfo.
Internal Class for containing display information about a Node.
TreeVisualizer.NodeInfo() - Constructor for class weka.gui.treevisualizer.TreeVisualizer.NodeInfo
 
TwoClassStats - class weka.classifiers.evaluation.TwoClassStats.
Encapsulates performance functions for two-class problems.
TwoClassStats(double, double, double, double) - Constructor for class weka.classifiers.evaluation.TwoClassStats
Creates the TwoClassStats with the given initial performance values.
TwoWayNominalSplit - class weka.classifiers.trees.adtree.TwoWayNominalSplit.
Class representing a two-way split on a nominal attribute, of the form: either 'is some_value' or 'is not some_value'.
TwoWayNominalSplit(int, int) - Constructor for class weka.classifiers.trees.adtree.TwoWayNominalSplit
Creates a new two-way nominal splitter.
TwoWayNumericSplit - class weka.classifiers.trees.adtree.TwoWayNumericSplit.
Class representing a two-way split on a numeric attribute, of the form: either 'is < some_value' or 'is >= some_value'.
TwoWayNumericSplit(int, double) - Constructor for class weka.classifiers.trees.adtree.TwoWayNumericSplit
Creates a new two-way numeric splitter.
tableChanged(TableModelEvent) - Method in class weka.gui.CostMatrixEditor.CustomEditor
Responds to a change in the cost matrix table.
tableExists(String) - Method in class weka.experiment.DatabaseUtils
Checks that a given table exists.
takeStep(int, int, double) - Method in class weka.classifiers.functions.SMO.BinarySMO
Method solving for the Lagrange multipliers for two instances.
takeStep(int, int) - Method in class weka.classifiers.functions.SMOreg
Method solving for the Lagrange multipliers for two instances.
taskFinished() - Method in class weka.gui.LogPanel
Record a task ending
taskFinished() - Method in interface weka.gui.TaskLogger
Tells the task logger that a task has completed
taskFinished() - Method in class weka.gui.WekaTaskMonitor
Tells the panel that a task has completed
taskStarted() - Method in class weka.gui.LogPanel
Record the starting of a new task
taskStarted() - Method in interface weka.gui.TaskLogger
Tells the task logger that a new task has been started
taskStarted() - Method in class weka.gui.WekaTaskMonitor
Tells the panel that a new task has been started
tauVal(double[][]) - Static method in class weka.core.ContingencyTables
Computes Goodman and Kruskal's tau-value for a contingency table.
tempCnt - Variable in class weka.classifiers.lazy.LBR
 
tempMethod(int[]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine
 
tempSubInstances - Variable in class weka.classifiers.lazy.LBR
 
templateString() - Method in class weka.experiment.PairedTTester.Resultset
Returns a string descriptive of the resultset key column values for this resultset
templateString(Instance) - Method in class weka.experiment.PairedTTester
Returns a string descriptive of the key column values for the "datasets
test(String[]) - Static method in class weka.core.Instances
Method for testing this class.
testCV(int, int) - Method in class weka.core.Instances
Creates the test set for one fold of a cross-validation on the dataset.
testComparisonString() - Method in class weka.datagenerators.Test
Gives a string representation of the test, starting from the comparison symbol.
testEigen(Matrix, double[], boolean) - Method in class weka.core.Matrix
Test eigenvectors and eigenvalues.
testPrologComparisonString() - Method in class weka.datagenerators.Test
Gives a string representation of the test in Prolog notation, starting from the comparison symbol.
testWRTZeroR(Classifier, Evaluation, Instances, Instances) - Method in class weka.classifiers.CheckClassifier
Determine whether the scheme performs worse than ZeroR during testing
testsPerClassType(boolean, boolean, boolean) - Method in class weka.classifiers.CheckClassifier
Run a battery of tests for a given class attribute type
theRules - Variable in class weka.classifiers.rules.part.MakeDecList
Vector storing the rules.
theoryDL(int) - Method in class weka.classifiers.rules.RuleStats
The description length of the theory for a given rule.
threadRun - Variable in class weka.gui.AttributeVisualizationPanel
 
thresholdTipText() - Method in class weka.attributeSelection.ForwardSelection
Returns the tip text for this property
thresholdTipText() - Method in class weka.attributeSelection.RaceSearch
Returns the tip text for this property
thresholdTipText() - Method in class weka.attributeSelection.Ranker
Returns the tip text for this property
thresholdTipText() - Method in class weka.attributeSelection.WrapperSubsetEval
Returns the tip text for this property
thresholdTipText() - Method in class weka.classifiers.functions.PaceRegression
Returns the tip text for this property
thresholdTipText() - Method in class weka.classifiers.functions.Winnow
Returns the tip text for this property
thresholdTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified
Returns the tip text for this property
times(double) - Method in class weka.classifiers.functions.pace.DoubleVector
Multiplies a scalar
times(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
Multiplies another DoubleVector element by element
times(double) - Method in class weka.classifiers.functions.pace.Matrix
Multiply a matrix by a scalar, C = s*A
times(Matrix) - Method in class weka.classifiers.functions.pace.Matrix
Linear algebraic matrix multiplication, A * B
times(int, int, int, PaceMatrix, int) - Method in class weka.classifiers.functions.pace.PaceMatrix
Multiplication between a row (or part of a row) of the first matrix and a column (or part or a column) of the second matrix.
timesEquals(double) - Method in class weka.classifiers.functions.pace.DiscreteFunction
All function values are multiplied by a double
timesEquals(double) - Method in class weka.classifiers.functions.pace.DoubleVector
Multiply a vector by a scalar in place, u = s * u
timesEquals(DoubleVector) - Method in class weka.classifiers.functions.pace.DoubleVector
Multiplies another DoubleVector element by element in place
timesEquals(double) - Method in class weka.classifiers.functions.pace.Matrix
Multiply a matrix by a scalar in place, A = s*A
toArray() - Method in class weka.core.FastVector
Returns all the elements of this vector as an array
toClassDetailsString() - Method in class weka.classifiers.Evaluation
 
toClassDetailsString(String) - Method in class weka.classifiers.Evaluation
Generates a breakdown of the accuracy for each class, incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toCumulativeMarginDistributionString() - Method in class weka.classifiers.Evaluation
Output the cumulative margin distribution as a string suitable for input for gnuplot or similar package.
toDotty(StringBuffer) - Method in class weka.classifiers.trees.UserClassifier.TreeClass
Converts The tree structure to a dotty string.
toDoubleArray() - Method in class weka.core.BinarySparseInstance
Returns the values of each attribute as an array of doubles.
toDoubleArray() - Method in class weka.core.Instance
Returns the values of each attribute as an array of doubles.
toDoubleArray() - Method in class weka.core.SparseInstance
Returns the values of each attribute as an array of doubles.
toGraph(StringBuffer, int, REPTree.Tree) - Method in class weka.classifiers.trees.REPTree.Tree
Outputs one node for graph.
toGraph() - Method in class weka.classifiers.trees.RandomTree
Outputs the decision tree as a graph
toGraph(StringBuffer, int) - Method in class weka.classifiers.trees.RandomTree
Outputs one node for graph.
toMatrixString() - Method in class weka.classifiers.Evaluation
Calls toMatrixString() with a default title.
toMatrixString(String) - Method in class weka.classifiers.Evaluation
Outputs the performance statistics as a classification confusion matrix.
toMatrixString(int[][], int[], Instances) - Method in class weka.clusterers.ClusterEvaluation
Returns a "confusion" style matrix of classes to clusters assignments
toPrologString() - Method in class weka.datagenerators.Test
Returns the test represented by a string in Prolog notation.
toResultsString() - Method in class weka.attributeSelection.AttributeSelection
get a description of the attribute selection
toRules() - Method in class weka.classifiers.rules.NNge.Exemplar
Returns a string of the rules induced by this examplar
toSelectModeL - Variable in class weka.classifiers.rules.part.MakeDecList
The model selection method.
toSource(String) - Method in interface weka.classifiers.Sourcable
Returns a string that describes the classifier as source.
toSource(String) - Method in class weka.classifiers.meta.AdaBoostM1
Returns the boosted model as Java source code.
toSource(String) - Method in class weka.classifiers.meta.LogitBoost
Returns the boosted model as Java source code.
toSource(String) - Method in class weka.classifiers.trees.DecisionStump
Returns the decision tree as Java source code.
toSource(String) - Method in class weka.classifiers.trees.J48
Returns tree as an if-then statement.
toSource(String, REPTree.Tree) - Method in class weka.classifiers.trees.REPTree.Tree
Returns source code for the tree as if-then statements.
toSource(String) - Method in class weka.classifiers.trees.REPTree
Returns the tree as if-then statements.
toSource(String) - Method in class weka.classifiers.trees.j48.ClassifierTree
Returns source code for the tree as an if-then statement.
toString() - Method in class weka.associations.Apriori
Outputs the size of all the generated sets of itemsets and the rules.
toString(Instances) - Method in class weka.associations.ItemSet
Returns the contents of an item set as a string.
toString() - Method in class weka.associations.Tertius
Outputs the best rules found with their confirmation value and number of counter-instances.
toString() - Method in class weka.associations.tertius.AttributeValueLiteral
 
toString() - Method in class weka.associations.tertius.Body
Gives a String representation of this set of literals as a conjunction.
toString() - Method in class weka.associations.tertius.Head
Gives a String representation of this set of literals as a disjunction.
toString() - Method in class weka.associations.tertius.Literal
 
toString() - Method in class weka.associations.tertius.LiteralSet
Gives a String representation for this set of literals.
toString() - Method in class weka.associations.tertius.Predicate
 
toString() - Method in class weka.associations.tertius.Rule
Retrun a String for this rule.
toString() - Method in class weka.associations.tertius.SimpleLinkedList
 
toString() - Method in class weka.attributeSelection.BestFirst.Link2
 
toString() - Method in class weka.attributeSelection.BestFirst
returns a description of the search as a String
toString() - Method in class weka.attributeSelection.CfsSubsetEval
returns a string describing CFS
toString() - Method in class weka.attributeSelection.ChiSquaredAttributeEval
Describe the attribute evaluator
toString() - Method in class weka.attributeSelection.ClassifierSubsetEval
Returns a string describing classifierSubsetEval
toString(Instances, int) - Method in class weka.attributeSelection.ConsistencySubsetEval.hashKey
Convert a hash entry to a string
toString() - Method in class weka.attributeSelection.ConsistencySubsetEval
returns a description of the evaluator
toString() - Method in class weka.attributeSelection.ExhaustiveSearch
prints a description of the search
toString() - Method in class weka.attributeSelection.ForwardSelection
returns a description of the search.
toString() - Method in class weka.attributeSelection.GainRatioAttributeEval
Return a description of the evaluator
toString() - Method in class weka.attributeSelection.GeneticSearch
returns a description of the search
toString() - Method in class weka.attributeSelection.InfoGainAttributeEval
Describe the attribute evaluator
toString() - Method in class weka.attributeSelection.OneRAttributeEval
Return a description of the evaluator
toString() - Method in class weka.attributeSelection.PrincipalComponents
Returns a description of this attribute transformer
toString() - Method in class weka.attributeSelection.RaceSearch
 
toString() - Method in class weka.attributeSelection.RandomSearch
prints a description of the search
toString() - Method in class weka.attributeSelection.RankSearch
returns a description of the search as a String
toString() - Method in class weka.attributeSelection.Ranker
returns a description of the search as a String
toString() - Method in class weka.attributeSelection.ReliefFAttributeEval
Return a description of the ReliefF attribute evaluator.
toString() - Method in class weka.attributeSelection.SVMAttributeEval
Return a description of the evaluator
toString() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
Return a description of the evaluator
toString() - Method in class weka.attributeSelection.WrapperSubsetEval
Returns a string describing the wrapper
toString() - Method in class weka.classifiers.BVDecompose
Returns description of the bias-variance decomposition results.
toString() - Method in class weka.classifiers.BVDecomposeSegCVSub
Returns description of the bias-variance decomposition results.
toString() - Method in class weka.classifiers.bayes.AODE
Returns a description of the classifier.
toString() - Method in class weka.classifiers.bayes.BayesNet
Returns a description of the classifier.
toString() - Method in class weka.classifiers.bayes.ComplementNaiveBayes
Prints out the internal model built by the classifier.
toString() - Method in class weka.classifiers.bayes.DiscreteEstimatorBayes
Display a representation of this estimator
toString() - Method in class weka.classifiers.bayes.NaiveBayes
Returns a description of the classifier.
toString() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial
 
toString() - Method in class weka.classifiers.bayes.NaiveBayesSimple
Returns a description of the classifier.
toString() - Method in class weka.classifiers.evaluation.ConfusionMatrix
Calls toString() with a default title.
toString(String) - Method in class weka.classifiers.evaluation.ConfusionMatrix
Outputs the performance statistics as a classification confusion matrix.
toString() - Method in class weka.classifiers.evaluation.NominalPrediction
Gets a human readable representation of this prediction.
toString() - Method in class weka.classifiers.evaluation.NumericPrediction
Gets a human readable representation of this prediction.
toString() - Method in class weka.classifiers.evaluation.TwoClassStats
Returns a string containing the various performance measures for the current object
toString() - Method in class weka.classifiers.functions.LeastMedSq
Returns a string representing the best LinearRegression classifier found.
toString() - Method in class weka.classifiers.functions.LinearRegression
Outputs the linear regression model as a string.
toString() - Method in class weka.classifiers.functions.Logistic
Gets a string describing the classifier.
toString() - Method in class weka.classifiers.functions.MultilayerPerceptron
 
toString() - Method in class weka.classifiers.functions.PaceRegression
Outputs the linear regression model as a string.
toString() - Method in class weka.classifiers.functions.RBFNetwork
Returns a description of this classifier as a String
toString() - Method in class weka.classifiers.functions.SMO.BinarySMO
Prints out the classifier.
toString() - Method in class weka.classifiers.functions.SMO
Prints out the classifier.
toString() - Method in class weka.classifiers.functions.SMOreg
Prints out the classifier.
toString() - Method in class weka.classifiers.functions.SimpleLinearRegression
Returns a description of this classifier as a string
toString() - Method in class weka.classifiers.functions.SimpleLogistic
Returns a description of the logistic model (attributes/coefficients).
toString() - Method in class weka.classifiers.functions.VotedPerceptron
Returns textual description of classifier.
toString() - Method in class weka.classifiers.functions.Winnow
Returns textual description of the classifier.
toString() - Method in class weka.classifiers.functions.pace.ChisqMixture
Converts to a string
toString() - Method in class weka.classifiers.functions.pace.DiscreteFunction
Converts the discrete function to string.
toString() - Method in class weka.classifiers.functions.pace.DoubleVector
Convert the DoubleVecor to a string
toString(int, boolean) - Method in class weka.classifiers.functions.pace.DoubleVector
Convert the DoubleVecor to a string
toString() - Method in class weka.classifiers.functions.pace.IntVector
Converts the IntVecor to a string
toString(int, boolean) - Method in class weka.classifiers.functions.pace.IntVector
Convert the IntVecor to a string
toString() - Method in class weka.classifiers.functions.pace.MixtureDistribution
Converts to a string
toString() - Method in class weka.classifiers.functions.pace.NormalMixture
Converts to a string
toString() - Method in class weka.classifiers.functions.pace.PaceMatrix
Converts matrix to string
toString(int, boolean) - Method in class weka.classifiers.functions.pace.PaceMatrix
Converts matrix to string
toString() - Method in class weka.classifiers.lazy.IB1
Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.IBk
Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.KStar
Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.LBR
Returns a description of the classifier.
toString() - Method in class weka.classifiers.lazy.LWL
Returns a description of this classifier.
toString() - Method in class weka.classifiers.meta.AdaBoostM1
Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.AdditiveRegression
Returns textual description of the classifier.
toString() - Method in class weka.classifiers.meta.AttributeSelectedClassifier
Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.Bagging
Returns description of the bagged classifier.
toString() - Method in class weka.classifiers.meta.CVParameterSelection.CVParameter
Returns a CVParameter as a string.
toString() - Method in class weka.classifiers.meta.CVParameterSelection
Returns description of the cross-validated classifier.
toString() - Method in class weka.classifiers.meta.ClassificationViaRegression
Prints the classifiers.
toString() - Method in class weka.classifiers.meta.CostSensitiveClassifier
Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.Decorate
Returns description of the Decorate classifier.
toString() - Method in class weka.classifiers.meta.END
Returns description of the committee.
toString() - Method in class weka.classifiers.meta.FilteredClassifier
Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.Grading
Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.HND
Returns a description of this classifier.
toString() - Method in class weka.classifiers.meta.LogitBoost
Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.MetaCost
Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.MultiBoostAB
Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.MultiClassClassifier.Code
Returns a human-readable representation of the codes.
toString() - Method in class weka.classifiers.meta.MultiClassClassifier
Prints the classifiers.
toString() - Method in class weka.classifiers.meta.MultiScheme
Output a representation of this classifier
toString(StringBuffer, int[], int) - Method in class weka.classifiers.meta.ND.NDTree
Returns a description of the tree rooted at this node.
toString() - Method in class weka.classifiers.meta.ND
Outputs the classifier as a string.
toString() - Method in class weka.classifiers.meta.OrdinalClassClassifier
Prints the classifiers.
toString() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost.Committee
 
toString() - Method in class weka.classifiers.meta.RacedIncrementalLogitBoost
Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.RandomCommittee
Returns description of the committee.
toString() - Method in class weka.classifiers.meta.RegressionByDiscretization
Returns a description of the classifier.
toString() - Method in class weka.classifiers.meta.Stacking
Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.StackingC
Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.ThresholdSelector
Returns description of the cross-validated classifier.
toString() - Method in class weka.classifiers.meta.TreeBasedMultiClassClassifier
Outputs the classifier as a string.
toString() - Method in class weka.classifiers.meta.Vote
Output a representation of this classifier
toString() - Method in class weka.classifiers.misc.FLR.FuzzyLattice
Returns a description of the Fuzzy Lattice
toString() - Method in class weka.classifiers.misc.FLR
Returns a description of the classifier.
toString() - Method in class weka.classifiers.misc.HyperPipes
Returns a description of this classifier.
toString() - Method in class weka.classifiers.misc.VFI
Returns a description of this classifier.
toString() - Method in class weka.classifiers.rules.ConjunctiveRule.Antd
 
toString() - Method in class weka.classifiers.rules.ConjunctiveRule.NominalAntd
Prints this antecedent
toString() - Method in class weka.classifiers.rules.ConjunctiveRule.NumericAntd
Prints this antecedent
toString(String, String) - Method in class weka.classifiers.rules.ConjunctiveRule
Prints this rule with the specified class label
toString() - Method in class weka.classifiers.rules.ConjunctiveRule
Prints this rule
toString() - Method in class weka.classifiers.rules.DecisionTable.Link
Returns string representation.
toString(Instances, int) - Method in class weka.classifiers.rules.DecisionTable.hashKey
Convert a hash entry to a string
toString() - Method in class weka.classifiers.rules.DecisionTable
Returns a description of the classifier.
toString() - Method in class weka.classifiers.rules.JRip.Antd
 
toString() - Method in class weka.classifiers.rules.JRip.NominalAntd
Prints this antecedent
toString() - Method in class weka.classifiers.rules.JRip.NumericAntd
Prints this antecedent
toString(Attribute) - Method in class weka.classifiers.rules.JRip.RipperRule
Prints this rule
toString() - Method in class weka.classifiers.rules.JRip
Prints the all the rules of the rule learner.
toString() - Method in class weka.classifiers.rules.NNge
Returns a description of this classifier.
toString() - Method in class weka.classifiers.rules.OneR.OneRRule
Returns a description of the rule.
toString() - Method in class weka.classifiers.rules.OneR
Returns a description of the classifier
toString() - Method in class weka.classifiers.rules.PART
Returns a description of the classifier
toString() - Method in class weka.classifiers.rules.Prism.PrismRule
Prints the set of rules.
toString() - Method in class weka.classifiers.rules.Prism
Prints a description of the classifier.
toString() - Method in class weka.classifiers.rules.Ridor.Antd
 
toString() - Method in class weka.classifiers.rules.Ridor.NominalAntd
Prints this antecedent
toString() - Method in class weka.classifiers.rules.Ridor.NumericAntd
Prints this antecedent
toString(String, String) - Method in class weka.classifiers.rules.Ridor.RidorRule
Prints this rule with the specified class label
toString() - Method in class weka.classifiers.rules.Ridor.RidorRule
Prints this rule
toString() - Method in class weka.classifiers.rules.Ridor.Ridor_node
Prints the all the rules of one node of Ridor.
toString() - Method in class weka.classifiers.rules.Ridor
Prints the all the rules of the rule learner.
toString() - Method in class weka.classifiers.rules.ZeroR
Returns a description of the classifier.
toString() - Method in class weka.classifiers.rules.part.ClassifierDecList
Prints rules.
toString() - Method in class weka.classifiers.rules.part.MakeDecList
Outputs the classifier into a string.
toString() - Method in class weka.classifiers.trees.ADTree
Returns a description of the classifier.
toString(PredictionNode, int) - Method in class weka.classifiers.trees.ADTree
Traverses the tree, forming a string that describes it.
toString() - Method in class weka.classifiers.trees.DecisionStump
Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.Id3
Prints the decision tree using the private toString method from below.
toString(int) - Method in class weka.classifiers.trees.Id3
Outputs a tree at a certain level.
toString() - Method in class weka.classifiers.trees.J48
Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.LMT
Returns a description of the classifier.
toString(int, REPTree.Tree) - Method in class weka.classifiers.trees.REPTree.Tree
Recursively outputs the tree.
toString() - Method in class weka.classifiers.trees.REPTree
Outputs the decision tree.
toString() - Method in class weka.classifiers.trees.RandomForest
Outputs a description of this classifier.
toString() - Method in class weka.classifiers.trees.RandomTree
Outputs the decision tree.
toString(int) - Method in class weka.classifiers.trees.RandomTree
Recursively outputs the tree.
toString(int, StringBuffer) - Method in class weka.classifiers.trees.UserClassifier.TreeClass
Converts the tree structure to a string. for people to read.
toString() - Method in class weka.classifiers.trees.UserClassifier
 
toString() - Method in class weka.classifiers.trees.j48.ClassifierTree
Prints tree structure.
toString() - Method in class weka.classifiers.trees.lmt.LMTNode
Returns a description of the logistic model tree (tree structure and logistic models)
toString() - Method in class weka.classifiers.trees.lmt.LogisticBase
Returns a description of the logistic model (i.e., attributes and coefficients).
toString() - Method in class weka.classifiers.trees.m5.Impurity
Converts an Impurity object to a string
toString() - Method in class weka.classifiers.trees.m5.M5Base
Returns a description of the classifier
toString() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel
Returns a textual description of this linear model
toString() - Method in class weka.classifiers.trees.m5.Rule
Return a description of the m5 tree or rule
toString() - Method in class weka.classifiers.trees.m5.RuleNode
print the linear model at this node
toString() - Method in class weka.classifiers.trees.m5.Values
Converts the stats to a string
toString(Instances) - Method in class weka.classifiers.trees.m5.YongSplitInfo
Converts the spliting information to string
toString() - Method in class weka.clusterers.Cobweb
Returns a description of the clusterer as a string.
toString() - Method in class weka.clusterers.EM
Outputs the generated clusters into a string.
toString() - Method in class weka.clusterers.FarthestFirst
return a string describing this clusterer
toString() - Method in class weka.clusterers.MakeDensityBasedClusterer
Returns a description of the clusterer.
toString() - Method in class weka.clusterers.SimpleKMeans
return a string describing this clusterer
toString() - Method in class weka.core.Attribute
Returns a description of this attribute in ARFF format.
toString() - Method in class weka.core.AttributeStats
Returns a human readable representation of this AttributeStats instance.
toString() - Method in class weka.core.BinarySparseInstance
Returns the description of one instance in sparse format.
toString() - Method in interface weka.core.ClassHierarchy
Returns a String-representation of this Hierarchy.
toString() - Method in class weka.core.ClassTree
Returns a String-representation of this ClassTree readable by a ClassTreeParser.
toString() - Method in class weka.core.Instance
Returns the description of one instance.
toString(int) - Method in class weka.core.Instance
Returns the description of one value of the instance as a string.
toString(Attribute) - Method in class weka.core.Instance
Returns the description of one value of the instance as a string.
toString() - Method in class weka.core.Instances
Returns the dataset as a string in ARFF format.
toString() - Method in class weka.core.Matrix
Converts a matrix to a string
toString() - Method in class weka.core.Queue
Produces textual description of queue.
toString() - Method in class weka.core.Range
Constructs a representation of the current range.
toString() - Method in class weka.core.SingleIndex
Constructs a representation of the current range.
toString() - Method in class weka.core.SparseInstance
Returns the description of one instance in sparse format.
toString() - Method in class weka.core.converters.HierarchicalCostMatrix
Returns a String representation of the cost matrix suitable for usage mit cost dependend classifiers.
toString() - Method in class weka.datagenerators.RDG1.RuleList
 
toString() - Method in class weka.datagenerators.Test
Returns the test represented by a string.
toString() - Method in class weka.estimators.DDConditionalEstimator
Display a representation of this estimator
toString() - Method in class weka.estimators.DKConditionalEstimator
Display a representation of this estimator
toString() - Method in class weka.estimators.DNConditionalEstimator
Display a representation of this estimator
toString() - Method in class weka.estimators.DiscreteEstimator
Display a representation of this estimator
toString() - Method in class weka.estimators.KDConditionalEstimator
Display a representation of this estimator
toString() - Method in class weka.estimators.KKConditionalEstimator
Display a representation of this estimator
toString() - Method in class weka.estimators.KernelEstimator
Display a representation of this estimator
toString() - Method in class weka.estimators.MahalanobisEstimator
Display a representation of this estimator
toString() - Method in class weka.estimators.NDConditionalEstimator
Display a representation of this estimator
toString() - Method in class weka.estimators.NNConditionalEstimator
Display a representation of this estimator
toString() - Method in class weka.estimators.NormalEstimator
Display a representation of this estimator
toString() - Method in class weka.estimators.PoissonEstimator
Display a representation of this estimator
toString() - Method in class weka.experiment.AveragingResultProducer
Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.ClassifierSplitEvaluator
Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.CrossValidationResultProducer
Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.DatabaseResultProducer
Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.Experiment
Gets a string representation of the experiment configuration.
toString() - Method in class weka.experiment.LearningRateResultProducer
Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.PairedStats
Returns statistics on the paired comparison.
toString() - Method in class weka.experiment.PropertyNode
Returns a string description of this property.
toString() - Method in class weka.experiment.RandomSplitResultProducer
Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.RegressionSplitEvaluator
Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.RemoteExperiment
Overides toString in Experiment
toString() - Method in class weka.experiment.Stats
Returns a string summarising the stats so far.
toString() - Method in class weka.filters.unsupervised.attribute.AddExpression.AttributeOperand
Return a string describing this object
toString() - Method in class weka.filters.unsupervised.attribute.AddExpression.NumericOperand
Return a string describing this object
toString() - Method in class weka.filters.unsupervised.attribute.AddExpression.Operator
Return a string describing this object
toString() - Method in class weka.gui.graphvisualizer.GraphEdge
 
toString2() - Method in class weka.classifiers.rules.NNge.Exemplar
Returns a description of this Exemplar
toStringFormat() - Method in class weka.datagenerators.ClusterGenerator
Returns a string representing the dataset in the instance queue.
toStringFormat() - Method in class weka.datagenerators.Generator
Returns a string representing the dataset in the instance queue.
toSummaryString() - Method in class weka.classifiers.Evaluation
Calls toSummaryString() with no title and no complexity stats
toSummaryString(boolean) - Method in class weka.classifiers.Evaluation
Calls toSummaryString() with a default title.
toSummaryString(String, boolean) - Method in class weka.classifiers.Evaluation
Outputs the performance statistics in summary form.
toSummaryString() - Method in class weka.classifiers.meta.CVParameterSelection
 
toSummaryString() - Method in class weka.classifiers.misc.FLR
Returns a superconcise version of the model
toSummaryString() - Method in class weka.classifiers.rules.PART
Returns a superconcise version of the model
toSummaryString() - Method in class weka.classifiers.trees.J48
Returns a superconcise version of the model
toSummaryString() - Method in class weka.core.Instances
Generates a string summarizing the set of instances.
toSummaryString() - Method in interface weka.core.Summarizable
Returns a string that summarizes the object.
toXMLBIF03() - Method in class weka.classifiers.bayes.BayesNet
Returns a description of the classifier in XML BIF 0.3 format.
tokenize(String) - Method in class weka.gui.HierarchyPropertyParser
Tokenize the given string based on the seperator and put the tokens into an array of strings
toleranceParameterTipText() - Method in class weka.attributeSelection.SVMAttributeEval
Returns a tip text for this property suitable for display in the GUI
toleranceParameterTipText() - Method in class weka.classifiers.functions.SMO
Returns the tip text for this property
toleranceParameterTipText() - Method in class weka.classifiers.functions.SMOreg
Returns the tip text for this property
topOfTree() - Method in class weka.classifiers.trees.m5.Rule
Returns the top of the tree.
totaL - Variable in class weka.classifiers.trees.j48.Distribution
Total weight of instances.
total() - Method in class weka.classifiers.evaluation.ConfusionMatrix
Gets the number of predictions that were made (actually the sum of the weights of predictions where the class value was known).
total() - Method in class weka.classifiers.trees.j48.Distribution
Returns total number of (possibly fractional) instances.
totalCost() - Method in class weka.classifiers.Evaluation
Gets the total cost, that is, the cost of each prediction times the weight of the instance, summed over all instances.
totalCount - Variable in class weka.core.AttributeStats
The total number of values (i.e. number of instances)
tql2(double[][], double[], double[], int) - Method in class weka.core.Matrix
Symmetric tridiagonal QL algorithm.
trace() - Method in class weka.classifiers.functions.pace.Matrix
Matrix trace.
trailing - Variable in class weka.classifiers.functions.pace.ExponentialFormat
 
trailing - Variable in class weka.classifiers.functions.pace.FlexibleDecimalFormat
 
trailing - Variable in class weka.classifiers.functions.pace.FloatingPointFormat
 
trainCV(int, int) - Method in class weka.core.Instances
Creates the training set for one fold of a cross-validation on the dataset.
trainCV(int, int, Random) - Method in class weka.core.Instances
Creates the training set for one fold of a cross-validation on the dataset.
trainPercentTipText() - Method in class weka.experiment.RandomSplitResultProducer
Returns the tip text for this property
trainPercentTipText() - Method in class weka.gui.beans.TrainTestSplitMaker
Tip text info for this property
trainingTimeTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
 
transProb() - Method in class weka.classifiers.lazy.kstar.KStarNominalAttribute
Calculates the probability of the indexed nominal attribute of the test instance transforming into the indexed nominal attribute of the training instance.
transProb() - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute
Calculates the transformation probability of the attribute indexed "m_AttrIndex" in test instance "m_Test" to the same attribute in the train instance "m_Train".
transformBackToOriginalTipText() - Method in class weka.attributeSelection.PrincipalComponents
Returns the tip text for this property
transformedData() - Method in interface weka.attributeSelection.AttributeTransformer
Returns the transformed data
transformedData() - Method in class weka.attributeSelection.PrincipalComponents
Gets the transformed training data.
transformedHeader() - Method in interface weka.attributeSelection.AttributeTransformer
Returns just the header for the transformed data (ie. an empty set of instances.
transformedHeader() - Method in class weka.attributeSelection.PrincipalComponents
Returns just the header for the transformed data (ie. an empty set of instances.
translateDBColumnType(String) - Method in class weka.experiment.DatabaseUtils
translates the column data type string to an integer value that indicates which data type / get()-Method to use in order to retrieve values from the database (see DatabaseUtils.Properties, InstanceQuery())
transpose() - Method in class weka.classifiers.functions.pace.Matrix
Matrix transpose.
transpose() - Method in class weka.core.Matrix
Returns the transpose of a matrix.
tred2(double[][], double[], double[], int) - Method in class weka.core.Matrix
Symmetric Householder reduction to tridiagonal form.
treeErrors() - Method in class weka.classifiers.trees.lmt.LMTNode
Updates the numIncorrectTree field for all nodes.
treeToString(StringBuffer, int) - Method in class weka.classifiers.meta.TreeBasedMultiClassClassifier
Returns string description of the tree.
treeToString() - Method in class weka.classifiers.trees.m5.Rule
Return a description of the m5 tree
treeToString(int) - Method in class weka.classifiers.trees.m5.RuleNode
Recursively builds a textual description of the tree
trim(DoubleVector) - Method in class weka.classifiers.functions.pace.ChisqMixture
Trims the small values of the estaimte
trim(DoubleVector) - Method in class weka.classifiers.functions.pace.NormalMixture
Trims the small values of the estaimte
trimToSize() - Method in class weka.core.FastVector
Sets the vector's capacity to its size.
trimingThreshold - Variable in class weka.classifiers.functions.pace.ChisqMixture
 
trimingThreshold - Variable in class weka.classifiers.functions.pace.NormalMixture
 
trueNegativeRate(int) - Method in class weka.classifiers.Evaluation
Calculate the true negative rate with respect to a particular class.
truePositiveRate(int) - Method in class weka.classifiers.Evaluation
Calculate the true positive rate with respect to a particular class.
trueSplitValue - Variable in class weka.classifiers.trees.adtree.TwoWayNominalSplit
The attribute value that is compared against
tryConverter(Loader, File) - Method in class weka.gui.explorer.PreprocessPanel
Applies the selected converter
tryLogistic(Instances) - Method in class weka.classifiers.trees.lmt.LMTNode
Determines the optimum number of LogitBoost iterations to perform by building a standalone logistic regression function on the training data.
ttest(Stats, Stats) - Method in class weka.attributeSelection.RaceSearch
 
turnChecksOff() - Method in class weka.classifiers.functions.LinearRegression
Turns off checks for missing values, etc.
turnChecksOff() - Method in class weka.classifiers.functions.SMO
Turns off checks for missing values, etc.
turnChecksOff() - Method in class weka.classifiers.functions.SMOreg
Turns off checks for missing values, etc.
turnChecksOn() - Method in class weka.classifiers.functions.LinearRegression
Turns on checks for missing values, etc.
turnChecksOn() - Method in class weka.classifiers.functions.SMO
Turns on checks for missing values, etc.
turnChecksOn() - Method in class weka.classifiers.functions.SMOreg
Turns on checks for missing values, etc.
type() - Method in class weka.core.Attribute
Returns the attribute's type as an integer.
type - Variable in class weka.gui.graphvisualizer.GraphEdge
The type of Edge
typeName(int) - Static method in class weka.experiment.DatabaseUtils
Returns the name associated with a SQL type.

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