All Packages  Class Hierarchy

T

tableExists(String). Method in class weka.experiment.DatabaseUtils

Checks that a given table exists.

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.

TAGS_ATTRIBUTETYPE. Static variable in class weka.filters.unsupervised.attribute.RemoveType

Tag allowing selection of attribute type to delete

TAGS_ESTIMATOR. Static variable in class weka.classifiers.functions.pace.PaceRegression

TAGS_EVAL. Static variable in class weka.classifiers.meta.ThresholdSelector

TAGS_FILTER. Static variable in class weka.classifiers.functions.supportVector.SMO

TAGS_FILTER. Static variable in class weka.classifiers.functions.supportVector.SMOreg

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

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

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

TAGS_MISSING. Static variable in class weka.classifiers.lazy.kstar.KStar

Define possible missing value handling methods

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.ADTree

TAGS_SELECTION. Static variable in class weka.attributeSelection.RaceSearch

TAGS_SELECTION. Static variable in class weka.attributeSelection.BestFirst

TAGS_SELECTION. Static variable in class weka.associations.Apriori

TAGS_SELECTION. Static variable in class weka.classifiers.functions.LinearRegression

TAGS_WEIGHTING. Static variable in class weka.classifiers.lazy.IBk

Task interface weka.experiment.Task.

Interface to something that can be remotely executed as a task.

taskFinished(). Method in interface weka.gui.TaskLogger

Tells the task logger that a task has completed

taskFinished(). Method in class weka.gui.LogPanel

Record a task ending

taskFinished(). Method in class weka.gui.WekaTaskMonitor

Tells the panel that a task has completed

TaskLogger interface weka.gui.TaskLogger.

Interface for objects that display log and display information on running tasks.

taskStarted(). Method in interface weka.gui.TaskLogger

Tells the task logger that a new task has been started

taskStarted(). Method in class weka.gui.LogPanel

Record the starting of a new task

taskStarted(). Method in class weka.gui.WekaTaskMonitor

Tells the panel that a new task has been started

TaskStatusInfo class weka.experiment.TaskStatusInfo.

A class holding information for tasks being executed on RemoteEngines.

TaskStatusInfo(). Constructor for class weka.experiment.TaskStatusInfo

tauVal(double[][]). Static method in class weka.core.ContingencyTables

Computes Goodman and Kruskal's tau-value for a contingency table.

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.

testEigen(Matrix, double[], boolean). Method in class weka.core.Matrix

Test eigenvectors and eigenvalues.

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

theoryDL(int). Method in class weka.classifiers.rules.RuleStats

The description length of the theory for a given rule.

THRESHOLD_NAME. Static variable in class weka.classifiers.evaluation.ThresholdCurve

THRESHOLD_NAME. Static variable in class weka.classifiers.evaluation.CostCurve

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

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

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.ForwardSelection

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

times(double). Method in class weka.classifiers.functions.pace.Matrix

Multiply a matrix by a scalar, C = s*A

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(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.

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

Linear algebraic matrix multiplication, A * B

timesEquals(double). Method in class weka.classifiers.functions.pace.Matrix

Multiply a matrix by a scalar in place, A = s*A

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

Multiply a vector by a scalar in place, u = s * u

timesEquals(double). Method in class weka.classifiers.functions.pace.DiscreteFunction

All function values are multiplied by a double

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

Multiplies another DoubleVector element by element in place

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

TIMESTAMP_FIELD_NAME. Static variable in class weka.experiment.CrossValidationResultProducer

TIMESTAMP_FIELD_NAME. Static variable in class weka.experiment.RandomSplitResultProducer

TO_BE_RUN. Static variable in class weka.experiment.TaskStatusInfo

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.

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.

toDoubleArray(). Method in class weka.core.BinarySparseInstance

Returns the values of each attribute as an array of doubles.

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.

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

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.

toResultsString(). Method in class weka.attributeSelection.AttributeSelection

get a description of the attribute selection

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.MultiBoostAB

Returns the boosted model as Java source code.

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.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.

toSource(String). Method in class weka.classifiers.trees.j48.J48

Returns tree as an if-then statement.

toString(). Method in class weka.core.Queue

Produces textual description of queue.

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

Returns the description of one instance.

toString(). Method in class weka.core.SparseInstance

Returns the description of one instance in sparse format.

toString(). Method in class weka.core.BinarySparseInstance

Returns the description of one instance in sparse format.

toString(). Method in class weka.core.Attribute

Returns a description of this attribute in ARFF format.

toString(). Method in class weka.core.DistanceFunction

Converts a DistanceFunction object to a string

toString(). Method in class weka.core.EuclideanDistance

Documents the content of an EuclideanDistance object in a string.

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

Converts a matrix to a string

toString(). Method in class weka.core.AttributeStats

Returns a human readable representation of this AttributeStats instance.

toString(). Method in class weka.core.Range

Constructs a representation of the current range.

toString(). Method in class weka.core.Instances

Returns the dataset as a string in ARFF format.

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

Converts a vector to a string

toString(). Method in class weka.core.DynamicArrayOfPosInt

Build a string representing this array.

toString(). Method in class weka.core.KDTree

toString

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.SimpleKMeans

return a string describing this clusterer

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

Converts a vector to a string

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

Return a string describing this clusterer.

toString(). Method in class weka.clusterers.Cobweb

Returns a description of the clusterer as a string.

toString(). Method in class weka.clusterers.DistributionMetaClusterer

Returns a description of the clusterer.

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.LearningRateResultProducer

Gets a text descrption of the result producer.

toString(). Method in class weka.experiment.CrossValidationResultProducer

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.RandomSplitResultProducer

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.AveragingResultProducer

Gets a text descrption of the result producer.

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

Overides toString in Experiment

toString(). Method in class weka.experiment.PairedStats

Returns statistics on the paired comparison.

toString(). Method in class weka.experiment.Stats

Returns a string summarising the stats so far.

toString(). Method in class weka.experiment.DatabaseResultProducer

Gets a text descrption of the result producer.

toString(). Method in class weka.experiment.PropertyNode

Returns a string description of this property.

toString(). Method in class weka.estimators.NormalEstimator

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.DDConditionalEstimator

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.DKConditionalEstimator

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.KKConditionalEstimator

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.MahalanobisEstimator

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.NNConditionalEstimator

Display a representation of this estimator

toString(). Method in class weka.estimators.PoissonEstimator

Display a representation of this estimator

toString(). Method in class weka.attributeSelection.ExhaustiveSearch

prints a description of the search

toString(). Method in class weka.attributeSelection.SVMAttributeEval

Return a description of the evaluator

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

returns a description of the search as a String

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

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

Return a description of the evaluator

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

Return a description of the evaluator

toString(). Method in class weka.attributeSelection.RandomSearch

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.GeneticSearch

returns a description of the search

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

returns a string describing CFS

toString(). Method in class weka.attributeSelection.BestFirst

returns a description of the search as a String

toString(). Method in class weka.attributeSelection.BestFirst.Link2

toString(). Method in class weka.attributeSelection.ReliefFAttributeEval

Return a description of the ReliefF attribute evaluator.

toString(). Method in class weka.attributeSelection.Ranker

returns a description of the search as a String

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

Describe the attribute evaluator

toString(). Method in class weka.attributeSelection.OneRAttributeEval

Return a description of the evaluator

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

Describe the attribute evaluator

toString(). Method in class weka.attributeSelection.ConsistencySubsetEval

returns a description of the evaluator

toString(). Method in class weka.attributeSelection.ClassifierSubsetEval

Returns a string describing classifierSubsetEval

toString(). Method in class weka.attributeSelection.PrincipalComponents

Returns a description of this attribute transformer

toString(). Method in class weka.attributeSelection.WrapperSubsetEval

Returns a string describing the wrapper

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

Outputs the size of all the generated sets of itemsets and the rules.

toString(). Method in class weka.classifiers.BVDecompose

Returns description of the bias-variance decomposition results.

toString(). Method in class weka.classifiers.lazy.IBk

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.lazy.IB1

Returns a description of this classifier.

toString(). Method in class weka.classifiers.lazy.kstar.KStar

Returns a description of this classifier.

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

Returns textual description of the classifier.

toString(). Method in class weka.classifiers.meta.ClassificationViaRegression

Prints the classifiers.

toString(). Method in class weka.classifiers.meta.DistributionMetaClassifier

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.MultiBoostAB

Returns description of the boosted classifier.

toString(). Method in class weka.classifiers.meta.Vote

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.ThresholdSelector

Returns description of the cross-validated classifier.

toString(). Method in class weka.classifiers.meta.MetaCost

Output a representation of this classifier

toString(). Method in class weka.classifiers.meta.MultiScheme

Output a representation of this classifier

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

Prints the classifiers.

toString(). Method in class weka.classifiers.meta.AdaBoostM1

Returns description of the boosted classifier.

toString(). Method in class weka.classifiers.meta.OrdinalClassClassifier

Prints the classifiers.

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

Output a representation of this classifier

toString(). Method in class weka.classifiers.meta.CVParameterSelection

Returns description of the cross-validated classifier.

toString(). Method in class weka.classifiers.meta.LogitBoost

Returns description of the boosted classifier.

toString(). Method in class weka.classifiers.meta.Grading

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.CostSensitiveClassifier

Output a representation of this classifier

toString(). Method in class weka.classifiers.meta.RegressionByDiscretization

Returns a description of the classifier.

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

Returns description of the boosted classifier.

toString(). Method in class weka.classifiers.meta.FilteredClassifier

Output a representation of this 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.bayes.DiscreteEstimatorBayes

Display a representation of this estimator

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

Returns a description of the classifier.

toString(). Method in class weka.classifiers.bayes.AODE

Returns a description of the classifier.

toString(). Method in class weka.classifiers.bayes.NaiveBayesSimple

Returns a description of the classifier.

toString(). Method in class weka.classifiers.bayes.NaiveBayes

Returns a description of the classifier.

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

Returns a description of the classifier.

toString(). Method in class weka.classifiers.rules.DecisionTable.Link

Returns string representation.

toString(). Method in class weka.classifiers.rules.Ridor

Prints the all the rules of the rule learner.

toString(). Method in class weka.classifiers.rules.JRip

Prints the all the rules of the rule learner.

toString(). Method in class weka.classifiers.rules.ConjunctiveRule

Prints this rule

toString(). Method in class weka.classifiers.rules.Nnge

Returns a description of this classifier.

toString(). Method in class weka.classifiers.rules.ZeroR

Returns a description of the classifier.

toString(). Method in class weka.classifiers.rules.OneR

Returns a description of the classifier

toString(). Method in class weka.classifiers.rules.Prism

Prints a description of the classifier.

toString(). Method in class weka.classifiers.rules.part.ClassifierDecList

Prints rules.

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

Returns a description of the classifier

toString(). Method in class weka.classifiers.rules.part.MakeDecList

Outputs the classifier into a string.

toString(). Method in class weka.classifiers.trees.DecisionStump

Returns a description of the classifier.

toString(). Method in class weka.classifiers.trees.UserClassifier

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.Id3

Prints the decision tree using the private toString method from below.

toString(). Method in class weka.classifiers.trees.RandomTree

Outputs the decision tree.

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

Returns a description of the classifier

toString(). Method in class weka.classifiers.trees.m5.RuleNode

print the linear model at this node

toString(). Method in class weka.classifiers.trees.m5.Impurity

Converts an Impurity object to a string

toString(). Method in class weka.classifiers.trees.m5.Values

Converts the stats to a string

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.j48.ClassifierTree

Prints tree structure.

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

Returns a description of the classifier.

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

Returns a description of the classifier.

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

Gets a human readable representation of this prediction.

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

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.evaluation.ConfusionMatrix

Calls toString() with a default title.

toString(). Method in class weka.classifiers.functions.SimpleLinearRegression

toString(). Method in class weka.classifiers.functions.LeastMedSq

Returns a string representing the best LinearRegression classifier found.

toString(). Method in class weka.classifiers.functions.VotedPerceptron

Returns textual description of classifier.

toString(). Method in class weka.classifiers.functions.LinearRegression

Outputs the linear regression model as a string.

toString(). Method in class weka.classifiers.functions.Winnow

Returns textual description of the classifier.

toString(). Method in class weka.classifiers.functions.Logistic

Gets a string describing the classifier.

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

Converts matrix to string

toString(). Method in class weka.classifiers.functions.pace.MixtureDistribution

Converts to a string

toString(). Method in class weka.classifiers.functions.pace.ChisqMixture

Converts to a string

toString(). 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(). Method in class weka.classifiers.functions.pace.NormalMixture

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.PaceRegression

Outputs the linear regression model as a string.

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

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

Prints out the classifier.

toString(). Method in class weka.classifiers.functions.supportVector.SMOreg

Prints out the classifier.

toString(Attribute). Method in class weka.core.Instance

Returns the description of one value of the instance as a string.

toString(Instances). Method in class weka.associations.ItemSet

Returns the contents of an item set as a string.

toString(Instances). Method in class weka.classifiers.trees.m5.YongSplitInfo

Converts the spliting information to string

toString(Instances, int). Method in class weka.attributeSelection.ConsistencySubsetEval.hashKey

Convert a hash entry to a string

toString(Instances, int). Method in class weka.classifiers.rules.DecisionTable.hashKey

Convert a hash entry to a string

toString(int). Method in class weka.core.Instance

Returns the description of one value of the instance as a string.

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

Converts matrix to string

toString(int, boolean). Method in class weka.classifiers.functions.pace.DoubleVector

Convert the DoubleVecor to a string

toString(int, boolean). Method in class weka.classifiers.functions.pace.IntVector

Convert the IntVecor to a string

toString(String). Method in class weka.classifiers.evaluation.ConfusionMatrix

Outputs the performance statistics as a classification confusion matrix.

toString(String, String). Method in class weka.classifiers.rules.ConjunctiveRule

Prints this rule with the specified class label

toSummaryString(). Method in interface weka.core.Summarizable

Returns a string that summarizes the object.

toSummaryString(). Method in class weka.core.Instances

Generates a string summarizing the set of instances.

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

Calls toSummaryString() with no title and no complexity stats

toSummaryString(). Method in class weka.classifiers.meta.CVParameterSelection

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

Returns a superconcise version of the model

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

Returns a superconcise version of the model

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.

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

Returns total number of (possibly fractional) 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).

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.

TP_RATE_NAME. Static variable in class weka.classifiers.evaluation.ThresholdCurve

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

Matrix trace.

trainCV(int, int). Method in class weka.core.Instances

Creates the training set for one fold of a cross-validation on the dataset.

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

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

trainPercentTipText(). Method in class weka.gui.beans.TrainTestSplitMaker

Tip text info for this property

trainPercentTipText(). Method in class weka.experiment.RandomSplitResultProducer

Returns the tip text for this property

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

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.

transformedHeader(). Method in class weka.attributeSelection.PrincipalComponents

Returns just the header for the transformed data (ie.

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

Returns the transpose of a matrix.

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

Matrix transpose.

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".

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.

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.

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.

treeToString(int). Method in class weka.classifiers.trees.m5.RuleNode

Recursively builds a textual description of the tree

TreeVisualizer class weka.gui.treevisualizer.TreeVisualizer.

Class for displaying a Node structure in Swing.

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(TreeDisplayListener, String, NodePlace). Constructor for class weka.gui.treevisualizer.TreeVisualizer

Constructs Displayer to display a tree provided in a dot format.

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

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

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.

TRUE_NEG_NAME. Static variable in class weka.classifiers.evaluation.ThresholdCurve

TRUE_POS_NAME. Static variable in class weka.classifiers.evaluation.ThresholdCurve

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.

turnChecksOff(). Method in class weka.classifiers.functions.LinearRegression

Turns off checks for missing values, etc.

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

Turns off checks for missing values, etc.

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

Turns on checks for missing values, etc.

turnChecksOn(). Method in class weka.classifiers.functions.supportVector.SMOreg

Turns on checks for missing values, etc.

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.

type(). Method in class weka.core.Attribute

Returns the attribute's type as an integer.

typeName(int). Static method in class weka.experiment.DatabaseUtils

Returns the name associated with a SQL type.

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