All Packages Class Hierarchy
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
- 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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