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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_ATTRIBUTES. Static variable in class weka.filters.AttributeTypeFilter
TAGS_ERROR. Static variable in class weka.classifiers.MultiClassClassifier
TAGS_EVAL. Static variable in class weka.classifiers.ThresholdSelector
TAGS_MATRIX_SOURCE. Static variable in class weka.classifiers.MetaCost
TAGS_MATRIX_SOURCE. Static variable in class weka.classifiers.CostSensitiveClassifier
TAGS_MISSING. Static variable in class weka.classifiers.kstar.KStar
Define possible missing value handling methods
TAGS_MODEL_TYPES. Static variable in class weka.classifiers.m5.M5Prime
TAGS_OPTIMIZE. Static variable in class weka.classifiers.ThresholdSelector
TAGS_RANGE. Static variable in class weka.classifiers.ThresholdSelector
TAGS_SEARCHPATH. Static variable in class weka.classifiers.adtree.ADTree
TAGS_SELECTION. Static variable in class weka.associations.Apriori
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.classifiers.LinearRegression
TAGS_WEIGHTING. Static variable in class weka.classifiers.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.
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.ThresholdSelector.
Class for selecting a threshold on a probability output by a distribution classifier.
ThresholdSelector(). Constructor for class weka.classifiers.ThresholdSelector
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
TimeSeriesDeltaFilter class weka.filters.TimeSeriesDeltaFilter.
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.
TimeSeriesDeltaFilter(). Constructor for class weka.filters.TimeSeriesDeltaFilter
TimeSeriesTranslateFilter class weka.filters.TimeSeriesTranslateFilter.
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.
TimeSeriesTranslateFilter(). Constructor for class weka.filters.TimeSeriesTranslateFilter
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.
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 class weka.classifiers.DecisionStump
Returns the decision tree as Java source code.
toSource(String). Method in class weka.classifiers.AdaBoostM1
Returns the boosted model as Java source code.
toSource(String). Method in interface weka.classifiers.Sourcable
Returns a string that describes the classifier as source.
toSource(String). Method in class weka.classifiers.LogitBoost
Returns the boosted model as Java source code.
toSource(String). Method in class weka.classifiers.j48.J48
Returns tree as an if-then statement.
toSource(String). Method in class weka.classifiers.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(). Method in class weka.attributeSelection.ExhaustiveSearch
prints a description of the search
toString(). Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
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.RandomSearch
prints a description of the search
toString(). Method in class weka.attributeSelection.GainRatioAttributeEval
Return a description of the evaluator
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.classifiers.MetaCost
Output a representation of this classifier
toString(). Method in class weka.classifiers.Prism
Prints a description of the classifier.
toString(). Method in class weka.classifiers.DecisionTable
Returns a description of the classifier.
toString(). Method in class weka.classifiers.DecisionTable.Link
Returns string representation.
toString(). Method in class weka.classifiers.DecisionStump
Returns a description of the classifier.
toString(). Method in class weka.classifiers.AdaBoostM1
Returns description of the boosted classifier.
toString(). Method in class weka.classifiers.ClassificationViaRegression
Prints the classifiers.
toString(). Method in class weka.classifiers.AttributeSelectedClassifier
Output a representation of this classifier
toString(). Method in class weka.classifiers.Stacking
Output a representation of this classifier
toString(). Method in class weka.classifiers.CVParameterSelection
Returns description of the cross-validated classifier.
toString(). Method in class weka.classifiers.OneR
Returns a description of the classifier
toString(). Method in class weka.classifiers.Bagging
Returns description of the bagged classifier.
toString(). Method in class weka.classifiers.ThresholdSelector
Returns description of the cross-validated classifier.
toString(). Method in class weka.classifiers.KernelDensity
Returns a description of the classifier.
toString(). Method in class weka.classifiers.IBk
Returns a description of this classifier.
toString(). Method in class weka.classifiers.ZeroR
Returns a description of the classifier.
toString(). Method in class weka.classifiers.RegressionByDiscretization
Returns a description of the classifier.
toString(). Method in class weka.classifiers.IB1
Returns a description of this classifier.
toString(). Method in class weka.classifiers.LogitBoost
Returns description of the boosted classifier.
toString(). Method in class weka.classifiers.HyperPipes
Returns a description of this classifier.
toString(). Method in class weka.classifiers.Id3
Prints the decision tree using the private toString method from below.
toString(). Method in class weka.classifiers.MultiClassClassifier
Prints the classifiers.
toString(). Method in class weka.classifiers.MultiScheme
Output a representation of this classifier
toString(). Method in class weka.classifiers.UserClassifier
toString(). Method in class weka.classifiers.AdditiveRegression
Returns textual description of the classifier.
toString(). Method in class weka.classifiers.BVDecompose
Returns description of the bias-variance decomposition results.
toString(). Method in class weka.classifiers.CostSensitiveClassifier
Output a representation of this classifier
toString(). Method in class weka.classifiers.NaiveBayes
Returns a description of the classifier.
toString(). Method in class weka.classifiers.SMO
Prints out the classifier.
toString(). Method in class weka.classifiers.Logistic
Gets a string describing the classifier.
toString(). Method in class weka.classifiers.LWR
Returns a description of this classifier.
toString(). Method in class weka.classifiers.VotedPerceptron
Returns textual description of classifier.
toString(). Method in class weka.classifiers.NaiveBayesSimple
Returns a description of the classifier.
toString(). Method in class weka.classifiers.DistributionMetaClassifier
Prints the classifiers.
toString(). Method in class weka.classifiers.VFI
Returns a description of this classifier.
toString(). Method in class weka.classifiers.LinearRegression
Outputs the linear regression model as a string.
toString(). Method in class weka.classifiers.FilteredClassifier
Output a representation of this classifier
toString(). Method in class weka.classifiers.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.j48.J48
Returns a description of the classifier.
toString(). Method in class weka.classifiers.j48.ClassifierTree
Prints tree structure.
toString(). Method in class weka.classifiers.j48.MakeDecList
Outputs the classifier into a string.
toString(). Method in class weka.classifiers.j48.ClassifierDecList
Prints rules.
toString(). Method in class weka.classifiers.j48.PART
Returns a description of the classifier
toString(). Method in class weka.classifiers.kstar.KStar
Returns a description of this classifier.
toString(). Method in class weka.classifiers.m5.Values
Converts the stats to a string
toString(). Method in class weka.classifiers.m5.Errors
Converts the evaluation results of a model to a string
toString(). Method in class weka.classifiers.m5.Impurity
Converts an Impurity object to a string
toString(). Method in class weka.classifiers.m5.M5Prime
Converts the output of the training process into a string
toString(). Method in class weka.classifiers.neural.NeuralNetwork
toString(). Method in class weka.clusterers.Cobweb
Returns a description of the clusterer as a string.
toString(). Method in class weka.clusterers.SimpleKMeans
return a string describing this clusterer
toString(). Method in class weka.clusterers.EM
Outputs the generated clusters into a string.
toString(). Method in class weka.clusterers.DistributionMetaClusterer
Prints the clusterers.
toString(). Method in class weka.core.Matrix
Converts a matrix to a string
toString(). Method in class weka.core.Instances
Returns the dataset as a string in ARFF format.
toString(). Method in class weka.core.Attribute
Returns a description of this attribute in ARFF format.
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.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.SerializedObject
Returns a text representation of the state of this object.
toString(). Method in class weka.core.Queue
Produces textual description of queue.
toString(). Method in class weka.estimators.NormalEstimator
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.DiscreteEstimator
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.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.KKConditionalEstimator
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.DNConditionalEstimator
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.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(Attribute). Method in class weka.core.Instance
Returns the description of one value of the instance as a string.
toString(double, double, String, String). Method in class weka.classifiers.m5.Measures
Converts the performance measures to 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.m5.Options
Prints information stored in an 'Options' object, basically containing command line options
toString(Instances). Method in class weka.classifiers.m5.SplitInfo
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.DecisionTable.hashKey
Convert a hash entry to a string
toString(Instances, int). Method in class weka.classifiers.m5.Function
Converts a function 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[], int, int). Static method in class weka.classifiers.m5.Ivector
Converts a string
toString(int, int, int, int). Method in class weka.classifiers.m5.Matrix
Converts a matrix to a string
toString(String). Method in class weka.classifiers.evaluation.ConfusionMatrix
Outputs the performance statistics as a classification confusion matrix.
toSummaryString(). Method in class weka.classifiers.Evaluation
Calls toSummaryString() with no title and no complexity stats
toSummaryString(). Method in class weka.classifiers.CVParameterSelection
toSummaryString(). Method in class weka.classifiers.j48.J48
Returns a superconcise version of the model
toSummaryString(). Method in class weka.classifiers.j48.PART
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.
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.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.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.
TP_RATE_NAME. Static variable in class weka.classifiers.evaluation.ThresholdCurve
trainCV(int, int). Method in class weka.core.Instances
Creates the training set for one fold of a cross-validation on the dataset.
trainingTimeTipText(). Method in class weka.classifiers.neural.NeuralNetwork
trainPercentTipText(). Method in class weka.experiment.RandomSplitResultProducer
Returns the tip text for this property
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(int, int). Method in class weka.classifiers.m5.Matrix
Returns the transpose of a matrix [0:n-1][0:m-1]
transProb(). Method in class weka.classifiers.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.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, double). Method in class weka.classifiers.m5.Node
Converts the tree under this node to a string
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
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.
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.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.adtree.TwoWayNominalSplit
Creates a new two-way nominal splitter.
TwoWayNumericSplit class weka.classifiers.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.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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