All Packages  Class Hierarchy

R

R_HIGH. Static variable in class weka.clusterers.XMeans

R_LOW. Static variable in class weka.clusterers.XMeans

Index in ranges for LOW and HIGH and WIDTH

R_MAX. Static variable in class weka.core.Instances

R_MAX. Static variable in class weka.core.KDTree

R_MIN. Static variable in class weka.core.Instances

Index in ranges for MIN and MAX and WIDTH

R_MIN. Static variable in class weka.core.KDTree

Index in ranges for LOW and HIGH and WIDTH

R_WIDTH. Static variable in class weka.core.Instances

R_WIDTH. Static variable in class weka.core.KDTree

R_WIDTH. Static variable in class weka.clusterers.XMeans

RacedIncrementalLogitBoost class weka.classifiers.meta.RacedIncrementalLogitBoost.

Classifier for incremental learning of large datasets by way of racing logit-boosted committees.

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

RaceSearch class weka.attributeSelection.RaceSearch.

Class for performing a racing search.

RaceSearch(). Constructor for class weka.attributeSelection.RaceSearch

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

Returns the tip text for this property

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

used/reused to hold the random entropy

RANDOM. Static variable in class weka.filters.supervised.attribute.ClassOrder

The class values are sorted in random order

random(int). Static method in class weka.classifiers.functions.pace.DoubleVector

Returns a random vector of uniform distribution

random(int, int). Static method in class weka.classifiers.functions.pace.Matrix

Generate matrix with random elements

RandomForest class weka.classifiers.trees.RandomForest.

Class for constructing random forests.

RandomForest(). Constructor for class weka.classifiers.trees.RandomForest

Randomizable interface weka.core.Randomizable.

Interface to something that has random behaviour that is able to be seeded with an integer.

Randomize class weka.filters.unsupervised.instance.Randomize.

This filter randomly shuffles the order of instances passed through it.

Randomize(). Constructor for class weka.filters.unsupervised.instance.Randomize

randomize(Random). Method in class weka.core.Instances

Shuffles the instances in the set so that they are ordered randomly.

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

Returns the tip text for this property

randomNormal(int, int). Static method in class weka.classifiers.functions.pace.PaceMatrix

Generate matrix with standard-normally distributed random elements

randomOrderTipText(). Method in class weka.classifiers.bayes.BayesNetK2

RandomSearch class weka.attributeSelection.RandomSearch.

Class for performing a random search.

RandomSearch(). Constructor for class weka.attributeSelection.RandomSearch

Constructor

randomSeedTipText(). Method in class weka.filters.unsupervised.attribute.AddNoise

Returns the tip text for this property

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

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

RandomSplitResultProducer class weka.experiment.RandomSplitResultProducer.

Generates a single train/test split and calls the appropriate SplitEvaluator to generate some results.

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

RandomTree class weka.classifiers.trees.RandomTree.

Class for constructing a tree that considers K random features at each node.

RandomTree(). Constructor for class weka.classifiers.trees.RandomTree

RandomVariates class weka.core.RandomVariates.

Class implementing some simple random variates generator.

RandomVariates(). Constructor for class weka.core.RandomVariates

Simply the constructor of super class

RandomVariates(long). Constructor for class weka.core.RandomVariates

Simply the constructor of super class

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

Range class weka.core.Range.

Class representing a range of cardinal numbers.

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

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

Range(). Constructor for class weka.core.Range

Default constructor.

Range(String). Constructor for class weka.core.Range

Constructor to set initial range.

rangeCorrectionTipText(). Method in class weka.classifiers.meta.ThresholdSelector

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

Check if ranges are set.

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

rankedAttributes(). Method in interface weka.attributeSelection.RankedOutputSearch

Returns a X by 2 list of attribute indexes and corresponding evaluations from best (highest) to worst.

rankedAttributes(). Method in class weka.attributeSelection.ForwardSelection

Produces a ranked list of attributes.

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

get the final ranking of the attributes.

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

Sorts the evaluated attribute list

RankedOutputSearch interface weka.attributeSelection.RankedOutputSearch.

Interface for search methods capable of producing a ranked list of attributes.

Ranker class weka.attributeSelection.Ranker.

Class for ranking the attributes evaluated by a AttributeEvaluator Valid options are:

-P
Specify a starting set of attributes.

Ranker(). Constructor for class weka.attributeSelection.Ranker

Constructor

RankSearch class weka.attributeSelection.RankSearch.

Class for evaluating a attribute ranking (given by a specified evaluator) using a specified subset evaluator.

RankSearch(). Constructor for class weka.attributeSelection.RankSearch

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

Returns the tip text for this property

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

Returns the tip text for this property

RBFKernel class weka.classifiers.functions.supportVector.RBFKernel.

The RBF kernel.

RBFKernel(Instances, int, double). Constructor for class weka.classifiers.functions.supportVector.RBFKernel

Constructor.

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

Returns a new matrix which binds two matrices together with rows.

rchisq(int, double, Random). Static method in class weka.classifiers.functions.pace.Maths

Generates a sample of a Chi-square distribution.

read(BufferedReader). Static method in class weka.classifiers.functions.pace.Matrix

Read a matrix from a stream.

readInstance(Reader). Method in class weka.core.Instances

Reads a single instance from the reader and appends it to the dataset.

readOldFormat(Reader). Method in class weka.classifiers.CostMatrix

Loads a cost matrix in the old format from a reader.

readProperties(String). Static method in class weka.core.Utils

Reads properties that inherit from three locations.

realCount. Variable in class weka.core.AttributeStats

The number of real-like values (i.e.

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

recall(int). Method in class weka.classifiers.Evaluation

Calculate the recall with respect to a particular class.

RECTANGLE. Static variable in class weka.gui.visualize.VisualizePanelEvent

reduceDimensionality(Instance). Method in class weka.attributeSelection.AttributeSelection

reduce the dimensionality of a single instance to include only those attributes chosen by the last run of attribute selection.

reduceDimensionality(Instances). Method in class weka.attributeSelection.AttributeSelection

reduce the dimensionality of a set of instances to include only those attributes chosen by the last run of attribute selection.

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

Try to reduce the DL of the ruleset by testing removing the rules one by one in reverse order and update all the stats

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

Reduces a matrix by deleting all zero rows and columns.

ReferenceInstances class weka.classifiers.trees.adtree.ReferenceInstances.

Simple class that extends the Instances class making it possible to create subsets of instances that reference their source set.

ReferenceInstances(Instances, int). Constructor for class weka.classifiers.trees.adtree.ReferenceInstances

Creates an empty set of instances.

refreshFreqTipText(). Method in class weka.gui.beans.StripChart

GUI Tip text

regression(Matrix, double). Method in class weka.core.Matrix

Performs a (ridged) linear regression.

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

Performs a weighted (ridged) linear regression.

RegressionByDiscretization class weka.classifiers.meta.RegressionByDiscretization.

Class for a regression scheme that employs any distribution classifier on a copy of the data that has the class attribute discretized.

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

RegressionSplitEvaluator class weka.experiment.RegressionSplitEvaluator.

A SplitEvaluator that produces results for a classification scheme on a numeric class attribute.

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

No args constructor.

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

The name of the relation used in threshold curve datasets

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

The name of the relation used in cost curve datasets

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

Returns the relation's name.

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

Returns the relative absolute error.

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

The description length (DL) of the ruleset relative to if the rule in the given position is deleted, which is obtained by:
MDL if the rule exists - MDL if the rule does not exist
Note the minimal possible DL of the ruleset is calculated(i.e.

ReliefFAttributeEval class weka.attributeSelection.ReliefFAttributeEval.

Class for Evaluating attributes individually using ReliefF.

ReliefFAttributeEval(). Constructor for class weka.attributeSelection.ReliefFAttributeEval

Constructor

RemoteBoundaryVisualizerSubTask class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask.

Class that encapsulates a sub task for distributed boundary visualization.

RemoteBoundaryVisualizerSubTask(). Constructor for class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask

RemoteEngine class weka.experiment.RemoteEngine.

A general purpose server for executing Task objects sent via RMI.

RemoteEngine(String). Constructor for class weka.experiment.RemoteEngine

Constructor

RemoteExperiment class weka.experiment.RemoteExperiment.

Holds all the necessary configuration information for a distributed experiment.

RemoteExperiment(Experiment). Constructor for class weka.experiment.RemoteExperiment

Construct a new RemoteExperiment using a base Experiment

RemoteExperimentEvent class weka.experiment.RemoteExperimentEvent.

Class encapsulating information on progress of a remote experiment

RemoteExperimentEvent(boolean, boolean, boolean, String). Constructor for class weka.experiment.RemoteExperimentEvent

Constructor

RemoteExperimentListener interface weka.experiment.RemoteExperimentListener.

Interface for classes that want to listen for updates on RemoteExperiment progress

remoteExperimentStatus(RemoteExperimentEvent). Method in interface weka.experiment.RemoteExperimentListener

Called when progress has been made in a remote experiment

RemoteExperimentSubTask class weka.experiment.RemoteExperimentSubTask.

Class to encapsulate an experiment as a task that can be executed on a remote host.

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

RemoteResult class weka.gui.boundaryvisualizer.RemoteResult.

Class that encapsulates a result (and progress info) for part of a distributed boundary visualization.

RemoteResult(int, int). Constructor for class weka.gui.boundaryvisualizer.RemoteResult

Creates a new RemoteResult instance.

Remove class weka.filters.unsupervised.attribute.Remove.

An instance filter that deletes a range of attributes from the dataset.

Valid filter-specific options are:

-R index1,index2-index4,...
Specify list of columns to delete.

REMOVE_CHILDREN. Static variable in class weka.gui.treevisualizer.TreeDisplayEvent

remove(). Method in class weka.gui.beans.BeanConnection

Remove this connection

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

remove(Object). Method in class weka.core.ProtectedProperties

Overrides a method to prevent the properties from being modified.

removeActionListener(ActionListener). Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Remove a listener

removeAllBeansFromContainer(JComponent). Static method in class weka.gui.beans.BeanInstance

Removes all beans from containing component

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

Removes all objects from the queue.

removeAllElements(). Method in class weka.core.FastVector

Removes all components from this vector and sets its size to zero.

removeAllInputs(). Method in class weka.classifiers.functions.neural.NeuralConnection

This function will remove all the inputs to this unit.

removeAllInputs(). Method in class weka.classifiers.functions.neural.NeuralNode

This function will remove all the inputs to this unit.

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

Returns the tip text for this property

removeAllOutputs(). Method in class weka.classifiers.functions.neural.NeuralConnection

This function will remove all outputs to this unit.

removeAllPlots(). Method in class weka.gui.visualize.Plot2D

Clears all plots

removeBatchClassifierListener(BatchClassifierListener). Method in class weka.gui.beans.Classifier

Remove a batch classifier listener

removeBean(JComponent). Method in class weka.gui.beans.BeanInstance

Remove this bean from the list of beans and from the containing component

removeCancelListener(ActionListener). Method in class weka.gui.GenericObjectEditor.GOEPanel

This is used to remove an action listener from the cancel button

removeChartListener(ChartListener). Method in class weka.gui.beans.IncrementalClassifierEvaluator

Remove a chart listener

ethod in class weka.gui.beans.AbstractDataSource

Remove a listener

removeDataSourceListener(DataSourceListener). Method in class weka.gui.beans.Loader

Remove a listener

removeDataSourceListener(DataSourceListener). Method in class weka.gui.beans.Filter

Remove a data source listener

removeDataSourceListener(DataSourceListener). Method in interface weka.gui.beans.DataSource

Remove a data source listener

removeDataSourceListener(DataSourceListener). Method in class weka.gui.beans.ClassAssigner

removeElementAt(int). Method in class weka.core.FastVector

Deletes an element from this vector.

RemoveFolds class weka.filters.unsupervised.instance.RemoveFolds.

This filter takes a dataset and outputs a specified fold for cross validation.

RemoveFolds(). Constructor for class weka.filters.unsupervised.instance.RemoveFolds

removeGraphListener(GraphListener). Method in class weka.gui.beans.Classifier

Remove a graph listener

removeIncrementalClassifierListener(IncrementalClassifierListener). Method in class weka.gui.beans.Classifier

Remove an incremental classifier listener

removeInstanceListener(InstanceListener). Method in class weka.gui.beans.AbstractDataSource

Remove an instance listener

removeInstanceListener(InstanceListener). Method in class weka.gui.beans.Loader

Remove an instance listener

removeInstanceListener(InstanceListener). Method in class weka.gui.beans.Filter

Remove an instance listener

removeInstanceListener(InstanceListener). Method in interface weka.gui.beans.DataSource

Remove an instance listener

removeInstanceListener(InstanceListener). Method in class weka.gui.beans.ClassAssigner

removeInstanceListener(InstanceListener). Method in class weka.gui.streams.InstanceLoader

removeInstanceListener(InstanceListener). Method in class weka.gui.streams.InstanceJoiner

removeInstanceListener(InstanceListener). Method in interface weka.gui.streams.InstanceProducer

removeLast(). Method in class weka.classifiers.rules.RuleStats

Remove the last rule in the ruleset as well as it's stats.

removeLinkAt(int). Method in class weka.attributeSelection.BestFirst.LinkedList2

removes an element (Link) at a specific index from the list.

removeLinkAt(int). Method in class weka.classifiers.rules.DecisionTable.LinkedList

Removes an element (Link) at a specific index from the list.

RemoveMisclassified class weka.filters.unsupervised.instance.RemoveMisclassified.

A filter that removes instances which are incorrectly classified.

RemoveMisclassified(). Constructor for class weka.filters.unsupervised.instance.RemoveMisclassified

removeNotify(). Method in class weka.gui.PropertyPanel

Cleans up when the panel is destroyed.

removeOkListener(ActionListener). Method in class weka.gui.GenericObjectEditor.GOEPanel

This is used to remove an action listener from the ok button

RemovePercentage class weka.filters.unsupervised.instance.RemovePercentage.

This filter outputs a given percentage of a dataset.

RemovePercentage(). Constructor for class weka.filters.unsupervised.instance.RemovePercentage

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.GenericArrayEditor

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.GenericObjectEditor

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.SetInstancesPanel

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.CostMatrixEditor

Removes an object from the list of those that wish to be informed when the cost matrix changes.

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.PropertySheetPanel

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.explorer.PreprocessPanel

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.LoaderCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.ClassifierCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.StripChartCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.FilterCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.ClassAssignerCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.TrainTestSplitMakerCustomizer

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.beans.BeanVisual

Remove a property change listener

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.experiment.SetupPanel

Removes a PropertyChangeListener.

removePropertyChangeListener(PropertyChangeListener). Method in class weka.gui.experiment.SimpleSetupPanel

Removes a PropertyChangeListener.

removePropertyChangeListener(String, PropertyChangeListener). Method in class weka.gui.beans.DataVisualizer

Remove a property change listener from this bean

RemoveRange class weka.filters.unsupervised.instance.RemoveRange.

This filter takes a dataset and outputs a subset of it.

RemoveRange(). Constructor for class weka.filters.unsupervised.instance.RemoveRange

removeResult(String). Method in class weka.gui.ResultHistoryPanel

Removes one of the result buffers from the history.

removeSubstring(String, String). Static method in class weka.core.Utils

Removes all occurrences of a string from another string.

removeTestSetListener(TestSetListener). Method in class weka.gui.beans.AbstractTestSetProducer

Remove a listener for test sets

removeTestSetListener(TestSetListener). Method in class weka.gui.beans.Filter

Remove a test set listener

removeTestSetListener(TestSetListener). Method in class weka.gui.beans.AbstractTrainAndTestSetProducer

Remove a test set listener

removeTestSetListener(TestSetListener). Method in class weka.gui.beans.ClassAssigner

removeTestSetListener(TestSetListener). Method in interface weka.gui.beans.TestSetProducer

Remove a listener for test set events

removeTextListener(TextListener). Method in class weka.gui.beans.ClassifierPerformanceEvaluator

Remove a text listener

removeTextListener(TextListener). Method in class weka.gui.beans.Classifier

Remove a text listener

removeTextListener(TextListener). Method in class weka.gui.beans.IncrementalClassifierEvaluator

Remove a text listener

removeTrainingSetListener(TrainingSetListener). Method in class weka.gui.beans.Filter

Remove a training set listener

removeTrainingSetListener(TrainingSetListener). Method in class weka.gui.beans.AbstractTrainingSetProducer

Remove a training set listener

removeTrainingSetListener(TrainingSetListener). Method in class weka.gui.beans.AbstractTrainAndTestSetProducer

Remove a training set listener

removeTrainingSetListener(TrainingSetListener). Method in class weka.gui.beans.ClassAssigner

removeTrainingSetListener(TrainingSetListener). Method in interface weka.gui.beans.TrainingSetProducer

Remove a training set listener

RemoveType class weka.filters.unsupervised.attribute.RemoveType.

A filter that removes attributes of a given type.

Valid filter-specific options are:

-T type
Attribute type to delete.

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

RemoveUseless class weka.filters.unsupervised.attribute.RemoveUseless.

This filter removes attributes that do not vary at all or that vary too much.

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

removeVetoableChangeListener(String, VetoableChangeListener). Method in class weka.gui.beans.DataVisualizer

Remove a vetoable change listener from this bean

RemoveWithValues class weka.filters.unsupervised.instance.RemoveWithValues.

Filters instances according to the value of an attribute.

Valid filter-specific options are:

-C num
Choose attribute to be used for selection (default last).

-S num
Numeric value to be used for selection on numeric attribute.

RemoveWithValues(). Constructor for class weka.filters.unsupervised.instance.RemoveWithValues

Default constructor

renameAttribute(Attribute, String). Method in class weka.core.Instances

Renames an attribute.

renameAttribute(int, String). Method in class weka.core.Instances

Renames an attribute.

renameAttributeValue(Attribute, String, String). Method in class weka.core.Instances

Renames the value of a nominal (or string) attribute value.

renameAttributeValue(int, int, String). Method in class weka.core.Instances

Renames the value of a nominal (or string) attribute value.

ReplaceMissingValues class weka.filters.unsupervised.attribute.ReplaceMissingValues.

Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means from the training data.

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

replaceMissingValues(double[]). Method in class weka.core.Instance

Replaces all missing values in the instance with the values contained in the given array.

replaceMissingValues(double[]). Method in class weka.core.SparseInstance

Replaces all missing values in the instance with the values contained in the given array.

replaceMissingValues(double[]). Method in class weka.core.BinarySparseInstance

Does nothing, since we don't support missing values.

replaceSubstring(String, String, String). Static method in class weka.core.Utils

Replaces with a new string, all occurrences of a string from another string.

replot(). Method in class weka.gui.boundaryvisualizer.BoundaryPanel

Quickly replot the display using cached probability estimates

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

Returns the tip text for this property

REPTree class weka.classifiers.trees.REPTree.

Fast decision tree learner.

REPTree(). Constructor for class weka.classifiers.trees.REPTree

Resample class weka.filters.supervised.instance.Resample.

Produces a random subsample of a dataset.

Resample class weka.filters.unsupervised.instance.Resample.

Produces a random subsample of a dataset.

Resample(). Constructor for class weka.filters.supervised.instance.Resample

Resample(). Constructor for class weka.filters.unsupervised.instance.Resample

resample(Random). Method in class weka.core.Instances

Creates a new dataset of the same size using random sampling with replacement.

resampleWithWeights(Random). Method in class weka.core.Instances

Creates a new dataset of the same size using random sampling with replacement according to the current instance weights.

resampleWithWeights(Random, double[]). Method in class weka.core.Instances

Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.

reset(). Static method in class weka.gui.beans.BeanConnection

Reset the list of connections

reset(). Method in class weka.core.converters.CSVLoader

Resets the loader ready to read a new data set

reset(). Method in class weka.core.converters.C45Loader

Resets the Loader ready to read a new data set

reset(). Method in class weka.core.converters.ArffLoader

Resets the Loader ready to read a new data set

reset(). Method in class weka.core.converters.SerializedInstancesLoader

Resets the Loader ready to read a new data set

reset(). Method in class weka.classifiers.functions.neural.NeuralConnection

Call this to reset the unit for another run.

reset(). Method in class weka.classifiers.functions.neural.NeuralNode

Call this to reset the value and error for this unit, ready for the next run.

reset(JComponent). Static method in class weka.gui.beans.BeanInstance

Reset the list of beans

resetAttIndex(boolean). Method in class weka.classifiers.lazy.LBR.Indexes

Resets the boolean value in AttIndexes array

resetAttIndexTo(LBR.Indexes). Method in class weka.classifiers.lazy.LBR.Indexes

Resets the boolean value in AttIndexes array based on another set of Indexes

resetDatasetBasedOn(LBR.Indexes). Method in class weka.classifiers.lazy.LBR.Indexes

Resets the boolean values in Attribute and Instance array to reflect an empty dataset withthe same attributes set as in the incoming Indexes Object

resetDistribution(Instances). Method in class weka.classifiers.trees.j48.ClassifierSplitModel

Sets distribution associated with model.

resetDistribution(Instances). Method in class weka.classifiers.trees.j48.C45Split

Sets distribution associated with model.

resetDistribution(Instances). Method in class weka.classifiers.trees.j48.BinC45Split

Sets distribution associated with model.

resetInstanceIndex(boolean). Method in class weka.classifiers.lazy.LBR.Indexes

Resets the boolean value in the Instance Indexes array to a specified value

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

Resets the options to the default values.

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

ResultHistoryPanel class weka.gui.ResultHistoryPanel.

A component that accepts named stringbuffers and displays the name in a list box.

ResultHistoryPanel.RKeyAdapter class weka.gui.ResultHistoryPanel.RKeyAdapter.

Extension of KeyAdapter that implements Serializable.

ResultHistoryPanel.RKeyAdapter(). Constructor for class weka.gui.ResultHistoryPanel.RKeyAdapter

ResultHistoryPanel.RMouseAdapter class weka.gui.ResultHistoryPanel.RMouseAdapter.

Extension of MouseAdapter that implements Serializable.

ResultHistoryPanel.RMouseAdapter(). Constructor for class weka.gui.ResultHistoryPanel.RMouseAdapter

ResultHistoryPanel(JTextComponent). Constructor for class weka.gui.ResultHistoryPanel

Create the result history object

ResultListener interface weka.experiment.ResultListener.

Interface for objects able to listen for results obtained by a ResultProducer

ResultProducer interface weka.experiment.ResultProducer.

This interface defines the methods required for an object that produces results for different randomizations of a dataset.

resultProducerTipText(). Method in class weka.experiment.LearningRateResultProducer

Returns the tip text for this property

resultProducerTipText(). Method in class weka.experiment.AveragingResultProducer

Returns the tip text for this property

resultProducerTipText(). Method in class weka.experiment.DatabaseResultProduriment.ResultsPanel.html">ResultsPanel class weka.gui.experiment.ResultsPanel.

This panel controls simple analysis of experimental results.

ResultsPanel(). Constructor for class weka.gui.experiment.ResultsPanel

Creates the results panel with no initial experiment.

retrieveInstances(). Method in class weka.experiment.InstanceQuery

Makes a database query using the query set through the -Q option to convert a table into a set of instances

retrieveInstances(String). Method in class weka.experiment.InstanceQuery

Makes a database query to convert a table into a set of instances

returnLeaves(FastVector[]). Method in class weka.classifiers.trees.m5.RuleNode

Return a list containing all the leaves in the tree

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

Returns the reverse vector

Ridor class weka.classifiers.rules.Ridor.

The implementation of a RIpple-DOwn Rule learner.

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

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

Get the right child of this node

rightSide(int, Instances). Method in class weka.classifiers.trees.j48.ClassifierSplitModel

Prints left side of condition satisfied by instances in subset index.

rightSide(int, Instances). Method in class weka.classifiers.trees.j48.NoSplit

Does nothing because no condition has to be satisfied.

rightSide(int, Instances). Method in class weka.classifiers.trees.j48.C45Split

Prints the condition satisfied by instances in a subset.

rightSide(int, Instances). Method in class weka.classifiers.trees.j48.BinC45Split

Prints the condition satisfied by instances in a subset.

rmCoveredBySuccessives(Instances, FastVector, int). Static method in class weka.classifiers.rules.RuleStats

Static utility function to count the data covered by the rules after the given index in the given rules, and then remove them.

rnorm(int, double, double, Random). Static method in class weka.classifiers.functions.pace.Maths

Generates a sample of a normal distribution.

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

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

How close the root finder for numeric and nominal have to get

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

Returns the root mean prior squared error.

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

Returns the root mean squared error.

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

Returns the root relative squared error if the class is numeric.

round(double). Static method in class weka.core.Utils

Rounds a double to the next nearest integer value.

roundDouble(double, int). Static method in class weka.core.Utils

Rounds a double to the given number of decimal places.

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

Solves upper-triangular equation R x = b

Rule class weka.classifiers.rules.Rule.

Abstract class of generic rule

Rule class weka.classifiers.trees.m5.Rule.

Generates a single m5 tree or rule

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

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

Constructor declaration

RuleNode class weka.classifiers.trees.m5.RuleNode.

Constructs a node for use in an m5 tree or rule

RuleNode(double, double, RuleNode). Constructor for class weka.classifiers.trees.m5.RuleNode

Creates a new RuleNode instance.

RuleStats class weka.classifiers.rules.RuleStats.

This class implements the statistics functions used in the propositional rule learner, from the simpler ones like count of true/false positive/negatives, filter data based on the ruleset, etc.

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

Default constructor

RuleStats(Instances, FastVector). Constructor for class weka.classifiers.rules.RuleStats

Constructor that provides ruleset and data

RUN_FIELD_NAME. Static variable in class weka.experiment.CrossValidationResultProducer

RUN_FIELD_NAME. Static variable in class weka.experiment.RandomSplitResultProducer

runCommand(String). Method in class weka.gui.SimpleCLI

Executes a simple cli command.

runExperiment(). Method in class weka.experiment.Experiment

Runs all iterations of the experiment, continuing past errors.

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

Overides runExperiment in Experiment

RunNumberPanel class weka.gui.experiment.RunNumberPanel.

This panel controls configuration of lower and upper run numbers in an experiment.

RunNumberPanel(). Constructor for class weka.gui.experiment.RunNumberPanel

Creates the panel with no initial experiment.

RunNumberPanel(Experiment). Constructor for class weka.gui.experiment.RunNumberPanel

Creates the panel with the supplied initial experiment.

RunPanel class weka.gui.experiment.RunPanel.

This panel controls the running of an experiment.

RunPanel(). Constructor for class weka.gui.experiment.RunPanel

Creates the run panel with no initial experiment.

RunPanel(Experiment). Constructor for class weka.gui.experiment.RunPanel

Creates the panel with the supplied initial experiment.

All Packages  Class Hierarchy