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G

gainRatio(). Method in class weka.classifiers.j48.BinC45Split
Returns (C4.5-type) gain ratio for the generated split.
gainRatio(). Method in class weka.classifiers.j48.C45Split
Returns (C4.5-type) gain ratio for the generated split.
gainRatio(double[][]). Static method in class weka.core.ContingencyTables
Computes gain ratio for contingency table (split on rows).
GainRatioAttributeEval class weka.attributeSelection.GainRatioAttributeEval.
Class for Evaluating attributes individually by measuring gain ratio with respect to the class.
GainRatioAttributeEval(). Constructor for class weka.attributeSelection.GainRatioAttributeEval
Constructor
GainRatioSplitCrit class weka.classifiers.j48.GainRatioSplitCrit.
Class for computing the gain ratio for a given distribution.
GainRatioSplitCrit(). Constructor for class weka.classifiers.j48.GainRatioSplitCrit
generateRankingTipText(). Method in class weka.attributeSelection.RaceSearch
Returns the tip text for this property
generateRankingTipText(). Method in class weka.attributeSelection.ForwardSelection
Returns the tip text for this property
generateRankingTipText(). Method in class weka.attributeSelection.Ranker
Returns the tip text for this property
generateRules(double, FastVector, int). Method in class weka.associations.ItemSet
Generates all rules for an item set.
generateRulesBruteForce(double, int, FastVector, int, int, double). Method in class weka.associations.ItemSet
Generates all significant rules for an item set.
GeneratorPropertyIteratorPanel class weka.gui.experiment.GeneratorPropertyIteratorPanel.
This panel controls setting a list of values for an arbitrary resultgenerator property for an experiment to iterate over.
GeneratorPropertyIteratorPanel(). Constructor for class weka.gui.experiment.GeneratorPropertyIteratorPanel
Creates the property iterator panel initially disabled.
GeneratorPropertyIteratorPanel(Experiment). Constructor for class weka.gui.experiment.GeneratorPropertyIteratorPanel
Creates the property iterator panel and sets the experiment.
GenericArrayEditor class weka.gui.GenericArrayEditor.
A PropertyEditor for arrays of objects that themselves have property editors.
GenericArrayEditor(). Constructor for class weka.gui.GenericArrayEditor
Sets up the array editor.
GenericObjectEditor class weka.gui.GenericObjectEditor.
A PropertyEditor for objects that themselves have been defined as editable in the GenericObjectEditor configuration file, which lists possible values that can be selected from, and themselves configured.
GenericObjectEditor.GOEPanel class weka.gui.GenericObjectEditor.GOEPanel.
Handles the GUI side of editing values.
GenericObjectEditor.GOEPanel(GenericObjectEditor). Constructor for class weka.gui.GenericObjectEditor.GOEPanel
Creates the GUI editor component
GenericObjectEditor(). Constructor for class weka.gui.GenericObjectEditor
GeneticSearch class weka.attributeSelection.GeneticSearch.
Class for performing a genetic based search.
GeneticSearch(). Constructor for class weka.attributeSelection.GeneticSearch
Constructor.
getAcuity(). Method in class weka.clusterers.Cobweb
get the acuity value
getAdjustWeights(). Method in class weka.filters.SpreadSubsampleFilter
Returns true if instance weights will be adjusted to maintain total weight per class.
getAdvanceDataSetFirst(). Method in class weka.experiment.Experiment
Get the value of m_DataSetFirstFirst.
getArffFile(). Method in class weka.gui.streams.InstanceSavePanel
getArffFile(). Method in class weka.gui.streams.InstanceLoader
getAsText(). Method in class weka.gui.GenericArrayEditor
Returns null as we don't support getting/setting values as text.
getAsText(). Method in class weka.gui.SelectedTagEditor
Gets the current value as text.
getAsText(). Method in class weka.gui.GenericObjectEditor
Returns null as we don't support getting/setting values as text.
getAsText(). Method in class weka.gui.CostMatrixEditor
Returns null as we don't support getting/setting values as text.
getAttribute1(). Method in class weka.gui.visualize.VisualizePanelEvent
getAttribute2(). Method in class weka.gui.visualize.VisualizePanelEvent
getAttributeEvaluator(). Method in class weka.attributeSelection.RankSearch
Get the attribute evaluator used to generate the ranking.
getAttributeEvaluator(). Method in class weka.attributeSelection.RaceSearch
Get the attribute evaluator used to generate the ranking.
getAttributeIndex(). Method in class weka.filters.InstanceFilter
Get the attribute to be used for selection (-1 for last)
getAttributeIndex(). Method in class weka.filters.SwapAttributeValuesFilter
Get the index of the attribute used.
getAttributeIndex(). Method in class weka.filters.StringToNominalFilter
Get the index of the attribute used.
getAttributeIndex(). Method in class weka.filters.MergeTwoValuesFilter
Get the index of the attribute used.
getAttributeIndex(). Method in class weka.filters.AddFilter
Get the index where the attribute will be inserted
getAttributeIndex(). Method in class weka.filters.MakeIndicatorFilter
Get the index of the attribute used.
getAttributeIndices(). Method in class weka.filters.AbstractTimeSeriesFilter
Get the current range selection
getAttributeIndices(). Method in class weka.filters.CopyAttributesFilter
Get the current range selection
getAttributeIndices(). Method in class weka.filters.NumericTransformFilter
Get the current range selection
getAttributeIndices(). Method in class weka.filters.FirstOrderFilter
Get the current range selection
getAttributeIndices(). Method in class weka.filters.AttributeFilter
Get the current range selection.
getAttributeIndices(). Method in class weka.filters.DiscretizeFilter
Gets the current range selection
getAttributeMax(int). Method in class weka.classifiers.IBk
Get an attributes maximum observed value
getAttributeMin(int). Method in class weka.classifiers.IBk
Get an attributes minimum observed value
getAttributeName(). Method in class weka.filters.AddFilter
Get the name of the attribute to be created
getAttributeSelectionMethod(). Method in class weka.classifiers.LinearRegression
Gets the method used to select attributes for use in the linear regression.
getAttributeType(). Method in class weka.filters.AttributeTypeFilter
Gets the type of attribute that will be deleted.
getAutoBuild(). Method in class weka.classifiers.neural.NeuralNetwork
getBagSizePercent(). Method in class weka.classifiers.MetaCost
Gets the size of each bag, as a percentage of the training set size.
getBagSizePercent(). Method in class weka.classifiers.Bagging
Gets the size of each bag, as a percentage of the training set size.
getBaseClassifier(int). Method in class weka.classifiers.Stacking
Gets the specific classifier from the set of base classifiers.
getBaseClassifiers(). Method in class weka.classifiers.Stacking
Gets the list of possible classifers to choose from.
getBaseExperiment(). Method in class weka.experiment.RemoteExperiment
Get the base experiment used by this remote experiment
getBias(). Method in class weka.classifiers.BVDecompose
Get the calculated bias squared
getBias(). Method in class weka.classifiers.VFI
Get the value of the bias parameter
getBiasToUniformClass(). Method in class weka.filters.ResampleFilter
Gets the bias towards a uniform class.
getBinarizeNumericAttributes(). Method in class weka.attributeSelection.ChiSquaredAttributeEval
get whether numeric attributes are just being binarized.
getBinarizeNumericAttributes(). Method in class weka.attributeSelection.InfoGainAttributeEval
get whether numeric attributes are just being binarized.
getBinaryAttributesNominal(). Method in class weka.filters.NominalToBinaryFilter
Gets if binary attributes are to be treated as nominal ones.
getBinarySplits(). Method in class weka.classifiers.j48.J48
Get the value of binarySplits.
getBinarySplits(). Method in class weka.classifiers.j48.PART
Get the value of binarySplits.
getBins(). Method in class weka.filters.DiscretizeFilter
Gets the number of bins numeric attributes will be divided into
getC(). Method in class weka.classifiers.SMO
Get the value of C.
getCacheKeyName(). Method in class weka.experiment.DatabaseResultListener
Get the value of CacheKeyName.
getCacheSize(). Method in class weka.classifiers.SMO
Get the size of the kernel cache
getCacheValues(double). Method in class weka.classifiers.kstar.KStarCache
Returns the values in the cache mapped by the specified key
getCalculatedNumToSelect(). Method in class weka.attributeSelection.RaceSearch
Gets the calculated number of attributes to retain.
getCalculatedNumToSelect(). Method in interface weka.attributeSelection.RankedOutputSearch
Gets the calculated number of attributes to retain.
getCalculatedNumToSelect(). Method in class weka.attributeSelection.ForwardSelection
Gets the calculated number of attributes to retain.
getCalculatedNumToSelect(). Method in class weka.attributeSelection.Ranker
Gets the calculated number to select.
getCalculateStdDevs(). Method in class weka.experiment.AveragingResultProducer
Get the value of CalculateStdDevs.
getCenter(). Method in class weka.gui.treevisualizer.Node
Get the value of center.
getChangeInWeights(). Method in class weka.classifiers.neural.NeuralNode
call this function to get the chnage in weights array.
getChild(int). Method in class weka.gui.treevisualizer.Node
Get the Edge for the child number 'i'.
getChildForBranch(int). Method in class weka.classifiers.adtree.Splitter
Gets the child for a branch of the split.
getChildForBranch(int). Method in class weka.classifiers.adtree.TwoWayNominalSplit
Gets the child for a branch of the split.
getChildForBranch(int). Method in class weka.classifiers.adtree.TwoWayNumericSplit
Gets the child for a branch of the split.
getChildren(). Method in class weka.classifiers.adtree.PredictionNode
Gets the children of this node.
getCindex(). Method in class weka.gui.visualize.PlotData2D
Get the currently set colouring index of the data
getCIndex(). Method in class weka.gui.visualize.VisualizePanel
Get the index of the attribute selected for coloring
getClassesToClusters(). Method in class weka.clusterers.ClusterEvaluation
Return the array (ordered by cluster number) of minimum error class to cluster mappings
getClassForIRStatistics(). Method in class weka.experiment.ClassifierSplitEvaluator
Get the value of ClassForIRStatistics.
getClassifier(). Method in class weka.attributeSelection.ClassifierSubsetEval
Get the classifier used as the base learner.
getClassifier(). Method in class weka.attributeSelection.WrapperSubsetEval
Get the classifier used as the base learner.
getClassifier(). Method in class weka.classifiers.MetaCost
Gets the distribution classifier used.
getClassifier(). Method in class weka.classifiers.AdaBoostM1
Get the classifier used as the classifier
getClassifier(). Method in class weka.classifiers.ClassificationViaRegression
Get the base classifier (regression scheme) used as the classifier
getClassifier(). Method in class weka.classifiers.AttributeSelectedClassifier
Gets the classifier used.
getClassifier(). Method in class weka.classifiers.CheckClassifier
Get the classifier used as the classifier
getClassifier(). Method in class weka.classifiers.CVParameterSelection
Get the classifier used as the classifier
getClassifier(). Method in class weka.classifiers.Bagging
Get the classifier used as the classifier
getClassifier(). Method in class weka.classifiers.RegressionByDiscretization
Get the classifier used as the classifier
getClassifier(). Method in class weka.classifiers.LogitBoost
Get the classifier used as the classifier
getClassifier(). Method in class weka.classifiers.AdditiveRegression
Gets the classifier used.
getClassifier(). Method in class weka.classifiers.BVDecompose
Gets the name of the classifier being analysed
getClassifier(). Method in class weka.classifiers.CostSensitiveClassifier
Gets the classifier used.
getClassifier(). Method in class weka.classifiers.DistributionMetaClassifier
Get the classifier used as the classifier
getClassifier(). Method in class weka.classifiers.FilteredClassifier
Gets the classifier used.
getClassifier(). Method in class weka.experiment.ClassifierSplitEvaluator
Get the value of Classifier.
getClassifier(). Method in class weka.experiment.RegressionSplitEvaluator
Get the value of Classifier.
getClassifier(int). Method in class weka.classifiers.MultiScheme
Gets a single classifier from the set of available classifiers.
getClassifiers(). Method in class weka.classifiers.MultiScheme
Gets the list of possible classifers to choose from.
getClassIndex(). Method in class weka.classifiers.BVDecompose
Get the index (starting from 1) of the attribute used as the class.
getClassName(). Method in class weka.filters.NumericTransformFilter
Get the class containing the transformation method.
getClearEachDataset(). Method in class weka.gui.streams.InstanceViewer
getClusterAssignments(). Method in class weka.clusterers.ClusterEvaluation
Return an array of cluster assignments corresponding to the most recent set of instances clustered.
getClusterer(). Method in class weka.clusterers.DistributionMetaClusterer
Get the clusterer used as the clusterer
getColor(). Method in class weka.gui.treevisualizer.Node
Get the value of color.
getCommand(). Method in class weka.gui.treevisualizer.TreeDisplayEvent
getCompatibilityState(). Method in interface weka.experiment.ResultProducer
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState(). Method in class weka.experiment.LearningRateResultProducer
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState(). Method in class weka.experiment.CrossValidationResultProducer
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState(). Method in class weka.experiment.RandomSplitResultProducer
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState(). Method in class weka.experiment.AveragingResultProducer
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState(). Method in class weka.experiment.DatabaseResultProducer
Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getConfidenceFactor(). Method in class weka.classifiers.j48.J48
Get the value of CF.
getConfidenceFactor(). Method in class weka.classifiers.j48.PART
Get the value of CF.
getConfusionMatrix(). Method in class weka.classifiers.evaluation.TwoClassStats
Generates a ConfusionMatrix representing the current two-class statistics, using class names "negative" and "positive".
getCostMatrix(). Method in class weka.classifiers.MetaCost
Gets the misclassification cost matrix.
getCostMatrix(). Method in class weka.classifiers.CostSensitiveClassifier
Gets the misclassification cost matrix.
getCostMatrixSource(). Method in class weka.classifiers.MetaCost
Gets the source location method of the cost matrix.
getCostMatrixSource(). Method in class weka.classifiers.CostSensitiveClassifier
Gets the source location method of the cost matrix.
getCount(Node, int). Static method in class weka.gui.treevisualizer.Node
Recursively finds the number of visible nodes there are (this may accidentally count some of the invis nodes).
getCrossoverProb(). Method in class weka.attributeSelection.GeneticSearch
get the probability of crossover
getCrossVal(). Method in class weka.classifiers.DecisionTable
Gets the number of folds for cross validation
getCrossValidate(). Method in class weka.classifiers.IBk
Gets whether hold-one-out cross-validation will be used to select the best k value
getCurrentDatasetNumber(). Method in class weka.experiment.Experiment
When an experiment is running, this returns the current dataset number.
getCurrentPropertyNumber(). Method in class weka.experiment.Experiment
When an experiment is running, this returns the index of the current custom property value.
getCurrentRunNumber(). Method in class weka.experiment.Experiment
When an experiment is running, this returns the current run number.
getCurve(FastVector). Method in class weka.classifiers.evaluation.ThresholdCurve
Calculates the performance stats for the default class and return results as a set of Instances.
getCurve(FastVector). Method in class weka.classifiers.evaluation.CostCurve
Calculates the performance stats for the default class and return results as a set of Instances.
getCurve(FastVector). Method in class weka.classifiers.evaluation.MarginCurve
Calculates the cumulative margin distribution for the set of predictions, returning the result as a set of Instances.
getCurve(FastVector, int). Method in class weka.classifiers.evaluation.ThresholdCurve
Calculates the performance stats for the desired class and return results as a set of Instances.
getCurve(FastVector, int). Method in class weka.classifiers.evaluation.CostCurve
Calculates the performance stats for the desired class and return results as a set of Instances.
getCustomEditor(). Method in class weka.gui.GenericArrayEditor
Returns the array editing component.
getCustomEditor(). Method in class weka.gui.GenericObjectEditor
Returns the array editing component.
getCustomEditor(). Method in class weka.gui.FileEditor
Gets the custom editor component.
getCustomEditor(). Method in class weka.gui.CostMatrixEditor
Returns the array editing component.
getCutoff(). Method in class weka.clusterers.Cobweb
get the cutoff
getCutPoints(int). Method in class weka.filters.DiscretizeFilter
Gets the cut points for an attribute
getCVisible(). Method in class weka.gui.treevisualizer.Node
Get If this node's childs are visible.
getCVParameter(int). Method in class weka.classifiers.CVParameterSelection
Gets the scheme paramter with the given index.
getCVPredictions(DistributionClassifier, Instances, int). Method in class weka.classifiers.evaluation.EvaluationUtils
Generate a bunch of predictions ready for processing, by performing a cross-validation on the supplied dataset.
getDatabaseURL(). Method in class weka.experiment.DatabaseUtils
Get the value of DatabaseURL.
getDataFileName(). Method in class weka.classifiers.BVDecompose
Get the name of the data file used for the decomposition
getDataSet(). Method in class weka.core.converters.AbstractLoader
Must be overridden by subclasses.
getDataSet(). Method in class weka.core.converters.CSVLoader
Return the full data set.
getDataSet(). Method in class weka.core.converters.ArffLoader
Return the full data set.
getDataSet(). Method in interface weka.core.converters.Loader
Return the full data set.
getDataSet(). Method in class weka.core.converters.C45Loader
Return the full data set.
getDataSet(). Method in class weka.core.converters.SerializedInstancesLoader
Return the full data set.
getDatasetKeyColumns(). Method in class weka.experiment.PairedTTester
Get the value of DatasetKeyColumns.
getDatasets(). Method in class weka.experiment.Experiment
Gets the datasets in the experiment.
getDebug(). Method in class weka.attributeSelection.RaceSearch
Get whether output is to be verbose
getDebug(). Method in class weka.classifiers.AdaBoostM1
Get whether debugging is turned on
getDebug(). Method in class weka.classifiers.CheckClassifier
Get whether debugging is turned on
getDebug(). Method in class weka.classifiers.CVParameterSelection
Gets whether debugging is turned on
getDebug(). Method in class weka.classifiers.IBk
Get the value of Debug.
getDebug(). Method in class weka.classifiers.RegressionByDiscretization
Gets whether debugging output will be printed
getDebug(). Method in class weka.classifiers.LogitBoost
Get whether debugging is turned on
getDebug(). Method in class weka.classifiers.MultiScheme
Get whether debugging is turned on
getDebug(). Method in class weka.classifiers.AdditiveRegression
Gets whether debugging has been turned on
getDebug(). Method in class weka.classifiers.BVDecompose
Gets whether debugging is turned on
getDebug(). Method in class weka.classifiers.Logistic
Gets whether debugging output will be printed.
getDebug(). Method in class weka.classifiers.LWR
SGts whether debugging output should be produced
getDebug(). Method in class weka.classifiers.LinearRegression
Controls whether debugging output will be printed
getDebug(). Method in class weka.clusterers.EM
Get debug mode
getDebug(). Method in class weka.filters.AttributeExpressionFilter
Gets whether debug is set
getDebug(). Method in class weka.gui.streams.InstanceSavePanel
getDebug(). Method in class weka.gui.streams.InstanceLoader
getDebug(). Method in class weka.gui.streams.InstanceViewer
getDebug(). Method in class weka.gui.streams.InstanceJoiner
getDebug(). Method in class weka.gui.streams.InstanceCounter
getDebug(). Method in class weka.gui.streams.InstanceTable
getDecay(). Method in class weka.classifiers.neural.NeuralNetwork
getDelta(). Method in class weka.associations.Apriori
Get the value of delta.
getDescription(). Method in class weka.gui.ExtensionFileFilter
Gets the description of accepted files.
getDesignatedClass(). Method in class weka.classifiers.ThresholdSelector
Gets the method to determine which class value to optimize.
getDirection(). Method in class weka.attributeSelection.BestFirst
Get the search direction
getDisplayRules(). Method in class weka.classifiers.DecisionTable
Gets whether rules are being printed
getDistanceWeighting(). Method in class weka.classifiers.IBk
Gets the distance weighting method used.
getDistributionClassifier(). Method in class weka.classifiers.ThresholdSelector
Get the DistributionClassifier used as the classifier.
getDistributionClassifier(). Method in class weka.classifiers.MultiClassClassifier
Get the classifier used as the classifier
getDistributionSpread(). Method in class weka.filters.SpreadSubsampleFilter
Gets the value for the distribution spread
getDontStratifyData(). Method in class weka.filters.SplitDatasetFilter
Gets whether stratification is not performed.
getEditor(). Method in class weka.gui.PropertyDialog
Gets the current property editor.
getEditorActive(). Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel
Returns true if the editor is currently in an active status---that is the array is active and able to be edited.
getElement(int, int). Method in class weka.core.Matrix
Returns the value of a cell in the matrix.
getEntropicAutoBlend(). Method in class weka.classifiers.kstar.KStar
Get whether entropic blending being used
getEntry(double). Method in class weka.classifiers.kstar.KStarCache.CacheTable
Returns the table entry to which the specified key is mapped in this hashtable.
getEntry(double). Method in class weka.classifiers.kstar.LightHashTable
Returns the table entry to which the specified key is mapped in this hashtable.
getEpsilon(). Method in class weka.classifiers.SMO
Get the value of epsilon.
getError(). Method in class weka.classifiers.BVDecompose
Get the calculated error rate
getErrorCorrectionMode(). Method in class weka.classifiers.MultiClassClassifier
Gets the error correction mode used.
getEstimatedErrorsForLeaf(). Method in class weka.classifiers.j48.C45PruneableDecList
Computes estimated errors for leaf.
getEstimator(double). Method in interface weka.estimators.ConditionalEstimator
Get a probability estimator for a value
getEstimator(double). Method in class weka.estimators.DDConditionalEstimator
Get a probability estimator for a value
getEstimator(double). Method in class weka.estimators.NDConditionalEstimator
Get a probability estimator for a value
getEstimator(double). Method in class weka.estimators.KDConditionalEstimator
Get a probability estimator for a value
getEstimator(double). Method in class weka.estimators.DKConditionalEstimator
Get a probability estimator for a value
getEstimator(double). Method in class weka.estimators.KKConditionalEstimator
Get a probability estimator for a value
getEstimator(double). Method in class weka.estimators.DNConditionalEstimator
Get a probability estimator for a value
getEstimator(double). Method in class weka.estimators.NNConditionalEstimator
Get a probability estimator for a value
getEvaluationMode(). Method in class weka.classifiers.ThresholdSelector
Gets the evaluation mode used.
getEvaluator(). Method in class weka.classifiers.AttributeSelectedClassifier
Gets the attribute evaluator used
getEvaluator(). Method in class weka.filters.AttributeSelectionFilter
Get the name of the attribute/subset evaluator
getExecutionStatus(). Method in class weka.experiment.TaskStatusInfo
Get the execution status of this Task.
getExpectedResultsPerAverage(). Method in class weka.experiment.AveragingResultProducer
Get the value of ExpectedResultsPerAverage.
getExperiment(). Method in class weka.experiment.RemoteExperimentSubTask
Get the experiment for this sub task
getExperiment(). Method in class weka.gui.experiment.SetupPanel
Gets the currently configured experiment.
getExponent(). Method in class weka.classifiers.SMO
Get the value of exponent.
getExponent(). Method in class weka.classifiers.VotedPerceptron
Get the value of exponent.
getExpression(). Method in class weka.filters.AttributeExpressionFilter
Get the expression
getFallout(). Method in class weka.classifiers.evaluation.TwoClassStats
Calculate the fallout.
getFalseNegative(). Method in class weka.classifiers.evaluation.TwoClassStats
Gets the number of positive instances predicted as negative
getFalsePositive(). Method in class weka.classifiers.evaluation.TwoClassStats
Gets the number of negative instances predicted as positive
getFalsePositiveRate(). Method in class weka.classifiers.evaluation.TwoClassStats
Calculate the false positive rate.
getFillWithMissing(). Method in class weka.filters.AbstractTimeSeriesFilter
Gets whether missing values should be used rather than removing instances where the translated value is not known (due to border effects).
getFilter(). Method in class weka.classifiers.FilteredClassifier
Gets the filter used.
getFindNumBins(). Method in class weka.filters.DiscretizeFilter
Get the value of FindNumBins.
getFirstToken(StreamTokenizer). Static method in class weka.core.converters.ConverterUtils
Gets token, skipping empty lines.
getFirstValueIndex(). Method in class weka.filters.SwapAttributeValuesFilter
Get the index of the first value used.
getFirstValueIndex(). Method in class weka.filters.MergeTwoValuesFilter
Get the index of the first value used.
getFlag(char, String[]). Static method in class weka.core.Utils
Checks if the given array contains the flag "-Char".
getFMeasure(). Method in class weka.classifiers.evaluation.TwoClassStats
Calculate the F-Measure.
getFold(). Method in class weka.filters.SplitDatasetFilter
Gets the fold which is selected.
getFolds(). Method in class weka.attributeSelection.WrapperSubsetEval
Get the number of folds used for accuracy estimation
getFoldsType(). Method in class weka.attributeSelection.RaceSearch
Get the xfold type
getGCount(Node, int). Static method in class weka.gui.treevisualizer.Node
Recursively finds the number of visible groups of siblings there are.
getGenerateRanking(). Method in class weka.attributeSelection.RaceSearch
Gets whether ranking has been requested.
getGenerateRanking(). Method in interface weka.attributeSelection.RankedOutputSearch
Gets whether the user has opted to see a ranked list of attributes rather than the normal result of the search
getGenerateRanking(). Method in class weka.attributeSelection.ForwardSelection
Gets whether ranking has been requested.
getGenerateRanking(). Method in class weka.attributeSelection.Ranker
This is a dummy method.
getGlobalBlend(). Method in class weka.classifiers.kstar.KStar
Get the value of the global blend parameter
getGroup(). Method in class weka.attributeSelection.BestFirst.Link2
Get a group
getGroup(). Method in class weka.classifiers.DecisionTable.Link
Gets the group.
getGUI(). Method in class weka.classifiers.neural.NeuralNetwork
getHashtable(FastVector, int). Static method in class weka.associations.ItemSet
Return a hashtable filled with the given item sets.
getHeight(Node, int). Static method in class weka.gui.treevisualizer.Node
Recursively finds the number of visible levels there are.
getHiddenLayers(). Method in class weka.classifiers.neural.NeuralNetwork
getHoldOutFile(). Method in class weka.attributeSelection.ClassifierSubsetEval
Gets the file that holds hold out/test instances.
getId(). Method in class weka.classifiers.neural.NeuralConnection
getID(). Method in class weka.core.Tag
Gets the numeric ID of the Tag.
getID(). Method in class weka.gui.streams.InstanceEvent
Get the event type
getID(). Method in class weka.gui.treevisualizer.TreeDisplayEvent
getInputNums(). Method in class weka.classifiers.neural.NeuralConnection
Use this to get easy access to the input numbers.
getInputs(). Method in class weka.classifiers.neural.NeuralConnection
Use this to get easy access to the inputs.
getInstanceRange(). Method in class weka.filters.AbstractTimeSeriesFilter
Gets the number of instances forward to translate values between.
getInstances(). Method in class weka.experiment.PairedTTester
Get the value of Instances.
getInstances(). Method in class weka.gui.SetInstancesPanel
Gets the set of instances currently held by the panel
getInstances(). Method in class weka.gui.treevisualizer.Node
This will return the Instances object related to this node.
getInstances(). Method in class weka.gui.visualize.VisualizePanel
Get the master plot's instances
getInstances1(). Method in class weka.gui.visualize.VisualizePanelEvent
getInstances2(). Method in class weka.gui.visualize.VisualizePanelEvent
getInstancesIndices(). Method in class weka.filters.SplitDatasetFilter
Gets ranges of instances selected.
getInvert(). Method in class weka.core.Range
Gets whether the range sense is inverted, i.e.
getInvertSelection(). Method in class weka.filters.InstanceFilter
Get whether the supplied columns are to be removed or kept
getInvertSelection(). Method in class weka.filters.AbstractTimeSeriesFilter
Get whether the supplied columns are to be removed or kept
getInvertSelection(). Method in class weka.filters.SplitDatasetFilter
Gets if selection is to be inverted.
getInvertSelection(). Method in class weka.filters.CopyAttributesFilter
Get whether the supplied columns are to be removed or kept
getInvertSelection(). Method in class weka.filters.NumericTransformFilter
Get whether the supplied columns are to be transformed or not
getInvertSelection(). Method in class weka.filters.AttributeFilter
Get whether the supplied columns are to be removed or kept
getInvertSelection(). Method in class weka.filters.DiscretizeFilter
Gets whether the supplied columns are to be removed or kept
getJavaInitializationString(). Method in class weka.gui.GenericArrayEditor
Supposedly returns an initialization string to create a classifier identical to the current one, including it's state, but this doesn't appear possible given that the initialization string isn't supposed to contain multiple statements.
getJavaInitializationString(). Method in class weka.gui.SelectedTagEditor
Returns a description of the property value as java source.
getJavaInitializationString(). Method in class weka.gui.GenericObjectEditor
Supposedly returns an initialization string to create a Object identical to the current one, including it's state, but this doesn't appear possible given that the initialization string isn't supposed to contain multiple statements.
getJavaInitializationString(). Method in class weka.gui.FileEditor
Returns a representation of the current property value as java source.
getJavaInitializationString(). Method in class weka.gui.CostMatrixEditor
Supposedly returns an initialization string to create a classifier identical to the current one, including it's state, but this doesn't appear possible given that the initialization string isn't supposed to contain multiple statements.
getKey(). Method in class weka.experiment.ClassifierSplitEvaluator
Gets the key describing the current SplitEvaluator.
getKey(). Method in class weka.experiment.RegressionSplitEvaluator
Gets the key describing the current SplitEvaluator.
getKey(). Method in interface weka.experiment.SplitEvaluator
Gets the key describing the current SplitEvaluator.
getKeyFieldName(). Method in class weka.experiment.AveragingResultProducer
Get the value of KeyFieldName.
getKeyNames(). Method in interface weka.experiment.ResultProducer
Gets the names of each of the key columns produced for a single run.
getKeyNames(). Method in class weka.experiment.ClassifierSplitEvaluator
Gets the names of each of the key columns produced for a single run.
getKeyNames(). Method in class weka.experiment.LearningRateResultProducer
Gets the names of each of the columns produced for a single run.
getKeyNames(). Method in class weka.experiment.CrossValidationResultProducer
Gets the names of each of the columns produced for a single run.
getKeyNames(). Method in class weka.experiment.RegressionSplitEvaluator
Gets the names of each of the key columns produced for a single run.
getKeyNames(). Method in class weka.experiment.RandomSplitResultProducer
Gets the names of each of the columns produced for a single run.
getKeyNames(). Method in class weka.experiment.AveragingResultProducer
Gets the names of each of the columns produced for a single run.
getKeyNames(). Method in class weka.experiment.DatabaseResultProducer
Gets the names of each of the columns produced for a single run.
getKeyNames(). Method in interface weka.experiment.SplitEvaluator
Gets the names of each of the key columns produced for a single run.
getKeyTypes(). Method in interface weka.experiment.ResultProducer
Gets the data types of each of the key columns produced for a single run.
getKeyTypes(). Method in class weka.experiment.ClassifierSplitEvaluator
Gets the data types of each of the key columns produced for a single run.
getKeyTypes(). Method in class weka.experiment.LearningRateResultProducer
Gets the data types of each of the columns produced for a single run.
getKeyTypes(). Method in class weka.experiment.CrossValidationResultProducer
Gets the data types of each of the columns produced for a single run.
getKeyTypes(). Method in class weka.experiment.RegressionSplitEvaluator
Gets the data types of each of the key columns produced for a single run.
getKeyTypes(). Method in class weka.experiment.RandomSplitResultProducer
Gets the data types of each of the columns produced for a single run.
getKeyTypes(). Method in class weka.experiment.AveragingResultProducer
Gets the data types of each of the columns produced for a single run.
getKeyTypes(). Method in class weka.experiment.DatabaseResultProducer
Gets the data types of each of the columns produced for a single run.
getKeyTypes(). Method in interface weka.experiment.SplitEvaluator
Gets the data types of each of the key columns produced for a single run.
getKNN(). Method in class weka.classifiers.IBk
Gets the number of neighbours the learner will use.
getKNN(). Method in class weka.classifiers.LWR
Gets the number of neighbours used for kernel bandwidth setting.
getLabel(). Method in class weka.gui.treevisualizer.Edge
Get the value of label.
getLabel(). Method in class weka.gui.treevisualizer.Node
Get the value of label.
getLearningRate(). Method in class weka.classifiers.neural.NeuralNetwork
getLine(int). Method in class weka.gui.treevisualizer.Edge
Returns line number n
getLine(int). Method in class weka.gui.treevisualizer.Node
Returns the text String for the specfied line.
getLinkAt(int). Method in class weka.attributeSelection.BestFirst.LinkedList2
returns the element (Link) at a specific index from the list.
getLinkAt(int). Method in class weka.classifiers.DecisionTable.LinkedList
Returns the element (Link) at a specific index from the list.
getList(). Method in class weka.gui.ResultHistoryPanel
Gets the JList used by the results list
getLocallyPredictive(). Method in class weka.attributeSelection.CfsSubsetEval
Return true if including locally predictive attributes
getLower(). Method in class weka.gui.experiment.RunNumberPanel
Gets the current lower run number.
getLowerBoundMinSupport(). Method in class weka.associations.Apriori
Get the value of lowerBoundMinSupport.
getLowerOrderTerms(). Method in class weka.classifiers.SMO
Check whether lower-order terms are being used.
getLowerSize(). Method in class weka.experiment.LearningRateResultProducer
Get the value of LowerSize.
getMakeBinary(). Method in class weka.filters.DiscretizeFilter
Gets whether binary attributes should be made for discretized ones.
getMasterPlot(). Method in class weka.gui.visualize.Plot2D
Get the master plot
getMatchMissingValues(). Method in class weka.filters.InstanceFilter
Gets whether missing values are counted as a match.
getMaxC(). Method in class weka.gui.visualize.Plot2D
Return the current max value of the colouring attribute
getMaxCost(int). Method in class weka.classifiers.CostMatrix
Gets the maximum misclassification cost possible for a given actual class value
getMaxCount(). Method in class weka.filters.SpreadSubsampleFilter
Gets the value for the max count
getMaxGenerations(). Method in class weka.attributeSelection.GeneticSearch
get the number of generations
getMaxIterations(). Method in class weka.classifiers.AdaBoostM1
Get the maximum number of boost iterations
getMaxIterations(). Method in class weka.classifiers.LogitBoost
Get the maximum number of boost iterations
getMaxIterations(). Method in class weka.clusterers.EM
Get the maximum number of iterations
getMaxK(). Method in class weka.classifiers.VotedPerceptron
Get the value of maxK.
getMaxModels(). Method in class weka.classifiers.AdditiveRegression
Get the max number of models to generate
getMaxStale(). Method in class weka.classifiers.DecisionTable
Gets the number of non improving decision tables
getMaxX(). Method in class weka.gui.visualize.Plot2D
Return the current max value of the attribute plotted on the x axis
getMaxY(). Method in class weka.gui.visualize.Plot2D
Return the current max value of the attribute plotted on the y axis
getMeanSquared(). Method in class weka.classifiers.IBk
Gets whether the mean squared error is used rather than mean absolute error when doing cross-validation.
getMeasure(String). Method in class weka.classifiers.DecisionTable
Returns the value of the named measure
getMeasure(String). Method in class weka.classifiers.AttributeSelectedClassifier
Returns the value of the named measure
getMeasure(String). Method in class weka.classifiers.AdditiveRegression
Returns the value of the named measure
getMeasure(String). Method in class weka.classifiers.adtree.ADTree
Returns the value of the named measure.
getMeasure(String). Method in class weka.classifiers.j48.J48
Returns the value of the named measure
getMeasure(String). Method in class weka.classifiers.j48.PART
Returns the value of the named measure
getMeasure(String). Method in class weka.classifiers.m5.M5Prime
Returns the value of the named measure
getMeasure(String). Method in interface weka.core.AdditionalMeasureProducer
Returns the value of the named measure
getMeasure(String). Method in class weka.experiment.ClassifierSplitEvaluator
Returns the value of the named measure
getMeasure(String). Method in class weka.experiment.LearningRateResultProducer
Returns the value of the named measure
getMeasure(String). Method in class weka.experiment.CrossValidationResultProducer
Returns the value of the named measure
getMeasure(String). Method in class weka.experiment.RegressionSplitEvaluator
Returns the value of the named measure
getMeasure(String). Method in class weka.experiment.RandomSplitResultProducer
Returns the value of the named measure
getMeasure(String). Method in class weka.experiment.AveragingResultProducer
Returns the value of the named measure
getMeasure(String). Method in class weka.experiment.DatabaseResultProducer
Returns the value of the named measure
getMerit(). Method in class weka.classifiers.DecisionTable.Link
Gets the merit.
getMetaClassifier(). Method in class weka.classifiers.Stacking
Gets the meta classifier.
getMethod(). Method in class weka.classifiers.neural.NeuralNode
getMethodName(). Method in class weka.filters.NumericTransformFilter
Get the transformation method.
getMetricType(). Method in class weka.associations.Apriori
Get the metric type
getMinBucketSize(). Method in class weka.classifiers.OneR
Get the value of minBucketSize.
getMinC(). Method in class weka.gui.visualize.Plot2D
Return the current min value of the colouring attribute
getMinimizeExpectedCost(). Method in class weka.classifiers.CostSensitiveClassifier
Gets the value of MinimizeExpectedCost.
getMinMetric(). Method in class weka.associations.Apriori
Get the value of minConfidence.
getMinNumObj(). Method in class weka.classifiers.j48.J48
Get the value of minNumObj.
getMinNumObj(). Method in class weka.classifiers.j48.PART
Get the value of minNumObj.
getMinStdDev(). Method in class weka.clusterers.EM
Get the minimum allowable standard deviation.
getMinX(). Method in class weka.gui.visualize.Plot2D
Return the current min value of the attribute plotted on the x axis
getMinY(). Method in class weka.gui.visualize.Plot2D
Return the current min value of the attribute plotted on the y axis
getMissingMerge(). Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
get whether missing values are being distributed or not
getMissingMerge(). Method in class weka.attributeSelection.GainRatioAttributeEval
get whether missing values are being distributed or not
getMissingMerge(). Method in class weka.attributeSelection.ChiSquaredAttributeEval
get whether missing values are being distributed or not
getMissingMerge(). Method in class weka.attributeSelection.InfoGainAttributeEval
get whether missing values are being distributed or not
getMissingMode(). Method in class weka.classifiers.kstar.KStar
Gets the method to use for handling missing values.
getMissingSeperate(). Method in class weka.attributeSelection.CfsSubsetEval
Return true is missing is treated as a seperate value
getModelType(). Method in class weka.classifiers.m5.M5Prime
Get the value of Model.
getModifyHeader(). Method in class weka.filters.InstanceFilter
Gets whether the header will be modified when selecting on nominal attributes.
getMomentum(). Method in class weka.classifiers.neural.NeuralNetwork
getMutationProb(). Method in class weka.attributeSelection.GeneticSearch
get the probability of mutation
getName(). Method in class weka.filters.AttributeExpressionFilter
Returns the name of the new attribute
getName(). Method in class weka.gui.visualize.VisualizePanel
Returns the name associated with this plot.
getNameAtIndex(int). Method in class weka.gui.ResultHistoryPanel
Gets the name of theitem in the list at the specified index
getNamedBuffer(String). Method in class weka.gui.ResultHistoryPanel
Gets the named buffer
getNamedObject(String). Method in class weka.gui.ResultHistoryPanel
Get the named object from the list
getNextInstance(). Method in class weka.core.converters.AbstractLoader
Must be overridden by subclasses.
getNextInstance(). Method in class weka.core.converters.CSVLoader
CSVLoader is unable to process a data set incrementally.
getNextInstance(). Method in class weka.core.converters.ArffLoader
Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(). Method in interface weka.core.converters.Loader
Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(). Method in class weka.core.converters.C45Loader
Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(). Method in class weka.core.converters.SerializedInstancesLoader
Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNominalIndices(). Method in class weka.filters.InstanceFilter
Get the set of nominal value indices that will be used for selection
getNominalLabels(). Method in class weka.filters.AddFilter
Get the list of labels for nominal attribute creation
getNominalToBinaryFilter(). Method in class weka.classifiers.neural.NeuralNetwork
getNoNormalization(). Method in class weka.classifiers.IBk
Gets whether normalization is turned off.
getNormalize(). Method in class weka.attributeSelection.PrincipalComponents
Gets whether or not input data is to be normalized
getNormalizeAttributes(). Method in class weka.classifiers.neural.NeuralNetwork
getNormalizeData(). Method in class weka.classifiers.SMO
Check whether data is to be normalized.
getNormalizeNumericClass(). Method in class weka.classifiers.neural.NeuralNetwork
getNotes(). Method in class weka.experiment.Experiment
Get the user notes.
getNPointPrecision(Instances, int). Static method in class weka.classifiers.evaluation.ThresholdCurve
Calculates the n point precision result, which is the precision averaged over n evenly spaced (w.r.t recall) samples of the curve.
getNumBins(). Method in class weka.classifiers.RegressionByDiscretization
Gets the number of bins the class attribute will be discretized into.
getNumClusters(). Method in class weka.clusterers.SimpleKMeans
gets the number of clusters to generate
getNumClusters(). Method in class weka.clusterers.EM
Get the number of clusters
getNumClusters(). Method in class weka.clusterers.ClusterEvaluation
Return the number of clusters found for the most recent call to evaluateClusterer
getNumDatasets(). Method in class weka.experiment.PairedTTester
Gets the number of datasets in the resultsets
getNumeric(). Method in class weka.filters.MakeIndicatorFilter
Check if new attribute is to be numeric.
getNumFolds(). Method in class weka.classifiers.Stacking
Gets the number of folds for the cross-validation.
getNumFolds(). Method in class weka.classifiers.CVParameterSelection
Get the number of folds used for cross-validation.
getNumFolds(). Method in class weka.classifiers.MultiScheme
Gets the number of folds for cross-validation.
getNumFolds(). Method in class weka.classifiers.j48.J48
Get the value of numFolds.
getNumFolds(). Method in class weka.classifiers.j48.PART
Get the value of numFolds.
getNumFolds(). Method in class weka.experiment.CrossValidationResultProducer
Get the value of NumFolds.
getNumFolds(). Method in class weka.filters.SplitDatasetFilter
Gets the number of folds in which dataset is to be split into.
getNumInputs(). Method in class weka.classifiers.neural.NeuralConnection
getNumIterations(). Method in class weka.classifiers.MetaCost
Gets the number of bagging iterations
getNumIterations(). Method in class weka.classifiers.Bagging
Gets the number of bagging iterations
getNumIterations(). Method in class weka.classifiers.VotedPerceptron
Get the value of NumIterations.
getNumNeighbours(). Method in class weka.attributeSelection.ReliefFAttributeEval
Get the number of nearest neighbours
getNumOfBoostingIterations(). Method in class weka.classifiers.adtree.ADTree
Gets the number of boosting iterations.
getNumOfBranches(). Method in class weka.classifiers.adtree.Splitter
Gets the number of branches of the split.
getNumOfBranches(). Method in class weka.classifiers.adtree.TwoWayNominalSplit
Gets the number of branches of the split.
getNumOfBranches(). Method in class weka.classifiers.adtree.TwoWayNumericSplit
Gets the number of branches of the split.
getNumOutputs(). Method in class weka.classifiers.neural.NeuralConnection
getNumResultsets(). Method in class weka.experiment.PairedTTester
Gets the number of resultsets in the data.
getNumRules(). Method in class weka.associations.Apriori
Get the value of numRules.
getNumSymbols(). Method in class weka.estimators.DiscreteEstimator
Gets the number of symbols this estimator operates with
getNumToSelect(). Method in class weka.attributeSelection.RaceSearch
Gets the number of attributes to be retained.
getNumToSelect(). Method in interface weka.attributeSelection.RankedOutputSearch
Gets the user specified number of attributes to be retained.
getNumToSelect(). Method in class weka.attributeSelection.ForwardSelection
Gets the number of attributes to be retained.
getNumToSelect(). Method in class weka.attributeSelection.Ranker
Gets the number of attributes to be retained.
getNumTraining(). Method in class weka.classifiers.IBk
Get the number of training instances the classifier is currently using
getNumXValFolds(). Method in class weka.classifiers.ThresholdSelector
Get the number of folds used for cross-validation.
getObject(). Method in class weka.core.SerializedObject
Gets the object stored in this SerializedObject.
getOnDemandDirectory(). Method in class weka.classifiers.MetaCost
Returns the directory that will be searched for cost files when loading on demand.
getOnDemandDirectory(). Method in class weka.classifiers.CostSensitiveClassifier
Returns the directory that will be searched for cost files when loading on demand.
getOnDemandDirectory(). Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
Returns the directory that will be searched for cost files when loading on demand.
getOptimizeBins(). Method in class weka.classifiers.RegressionByDiscretization
Gets whether the discretizer optimizes the number of bins
getOption(char, String[]). Static method in class weka.core.Utils
Gets an option indicated by a flag "-Char" from the given array of strings.
getOptions(). Method in class weka.associations.Apriori
Gets the current settings of the Apriori object.
getOptions(). Method in class weka.attributeSelection.ExhaustiveSearch
Gets the current settings of RandomSearch.
getOptions(). Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
Gets the current settings of WrapperSubsetEval.
getOptions(). Method in class weka.attributeSelection.RankSearch
Gets the current settings of WrapperSubsetEval.
getOptions(). Method in class weka.attributeSelection.RaceSearch
Gets the current settings of BestFirst.
getOptions(). Method in class weka.attributeSelection.RandomSearch
Gets the current settings of RandomSearch.
getOptions(). Method in class weka.attributeSelection.GainRatioAttributeEval
Gets the current settings of WrapperSubsetEval.
getOptions(). Method in class weka.attributeSelection.ForwardSelection
Gets the current settings of ReliefFAttributeEval.
getOptions(). Method in class weka.attributeSelection.GeneticSearch
Gets the current settings of ReliefFAttributeEval.
getOptions(). Method in class weka.attributeSelection.CfsSubsetEval
Gets the current settings of CfsSubsetEval
getOptions(). Method in class weka.attributeSelection.BestFirst
Gets the current settings of BestFirst.
getOptions(). Method in class weka.attributeSelection.ReliefFAttributeEval
Gets the current settings of ReliefFAttributeEval.
getOptions(). Method in class weka.attributeSelection.Ranker
Gets the current settings of ReliefFAttributeEval.
getOptions(). Method in class weka.attributeSelection.ChiSquaredAttributeEval
Gets the current settings of WrapperSubsetEval.
getOptions(). Method in class weka.attributeSelection.InfoGainAttributeEval
Gets the current settings of WrapperSubsetEval.
getOptions(). Method in class weka.attributeSelection.ClassifierSubsetEval
Gets the current settings of ClassifierSubsetEval
getOptions(). Method in class weka.attributeSelection.PrincipalComponents
Gets the current settings of PrincipalComponents
getOptions(). Method in class weka.attributeSelection.WrapperSubsetEval
Gets the current settings of WrapperSubsetEval.
getOptions(). Method in class weka.classifiers.MetaCost
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.DecisionTable
Gets the current settings of the classifier.
getOptions(). Method in class weka.classifiers.AdaBoostM1
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.ClassificationViaRegression
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.AttributeSelectedClassifier
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.Stacking
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.CheckClassifier
Gets the current settings of the CheckClassifier.
getOptions(). Method in class weka.classifiers.CVParameterSelection
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.OneR
Gets the current settings of the OneR classifier.
getOptions(). Method in class weka.classifiers.Bagging
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.ThresholdSelector
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.IBk
Gets the current settings of IBk.
getOptions(). Method in class weka.classifiers.RegressionByDiscretization
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.LogitBoost
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.MultiClassClassifier
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.MultiScheme
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.AdditiveRegression
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.BVDecompose
Gets the current settings of the CheckClassifier.
getOptions(). Method in class weka.classifiers.CostSensitiveClassifier
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.NaiveBayes
Gets the current settings of the classifier.
getOptions(). Method in class weka.classifiers.SMO
Gets the current settings of the classifier.
getOptions(). Method in class weka.classifiers.Logistic
Gets the current settings of the classifier.
getOptions(). Method in class weka.classifiers.LWR
Gets the current settings of the classifier.
getOptions(). Method in class weka.classifiers.VotedPerceptron
Gets the current settings of the classifier.
getOptions(). Method in class weka.classifiers.DistributionMetaClassifier
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.VFI
Gets the current settings of VFI
getOptions(). Method in class weka.classifiers.LinearRegression
Gets the current settings of the classifier.
getOptions(). Method in class weka.classifiers.FilteredClassifier
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.adtree.ADTree
Gets the current settings of ADTree.
getOptions(). Method in class weka.classifiers.j48.J48
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.j48.PART
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.kstar.KStar
Gets the current settings of K*.
getOptions(). Method in class weka.classifiers.m5.M5Prime
Gets the current settings of the Classifier.
getOptions(). Method in class weka.classifiers.neural.NeuralNetwork
Gets the current settings of NeuralNet.
getOptions(). Method in class weka.clusterers.Cobweb
Gets the current settings of Cobweb.
getOptions(). Method in class weka.clusterers.SimpleKMeans
Gets the current settings of SimpleKMeans
getOptions(). Method in class weka.clusterers.EM
Gets the current settings of EM.
getOptions(). Method in class weka.clusterers.DistributionMetaClusterer
Gets the current settings of the Clusterer.
getOptions(). Method in interface weka.core.OptionHandler
Gets the current option settings for the OptionHandler.
getOptions(). Method in class weka.experiment.ClassifierSplitEvaluator
Gets the current settings of the Classifier.
getOptions(). Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
Gets the current settings of the Classifier.
getOptions(). Method in class weka.experiment.LearningRateResultProducer
Gets the current settings of the result producer.
getOptions(). Method in class weka.experiment.CSVResultListener
Gets the current settings of the Classifier.
getOptions(). Method in class weka.experiment.CrossValidationResultProducer
Gets the current settings of the result producer.
getOptions(). Method in class weka.experiment.RegressionSplitEvaluator
Gets the current settings of the Classifier.
getOptions(). Method in class weka.experiment.RandomSplitResultProducer
Gets the current settings of the result producer.
getOptions(). Method in class weka.experiment.Experiment
Gets the current settings of the experiment iterator.
getOptions(). Method in class weka.experiment.AveragingResultProducer
Gets the current settings of the result producer.
getOptions(). Method in class weka.experiment.PairedTTester
Gets current settings of the PairedTTester.
getOptions(). Method in class weka.experiment.DatabaseResultProducer
Gets the current settings of the result producer.
getOptions(). Method in class weka.experiment.InstanceQuery
Gets the current settings of InstanceQuery
getOptions(). Method in class weka.filters.SpreadSubsampleFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.InstanceFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.AbstractTimeSeriesFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.SwapAttributeValuesFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.StringToNominalFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.MergeTwoValuesFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.SplitDatasetFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.CopyAttributesFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.ResampleFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.NumericTransformFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.AttributeTypeFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.NominalToBinaryFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.AddFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.AttributeSelectionFilter
Gets the current settings for the attribute selection (search, evaluator) etc.
getOptions(). Method in class weka.filters.FirstOrderFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.RandomizeFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.MakeIndicatorFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.AttributeExpressionFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.AttributeFilter
Gets the current settings of the filter.
getOptions(). Method in class weka.filters.DiscretizeFilter
Gets the current settings of the filter.
getOutputFile(). Method in class weka.experiment.CSVResultListener
Get the value of OutputFile.
getOutputFile(). Method in class weka.experiment.CrossValidationResultProducer
Get the value of OutputFile.
getOutputFile(). Method in class weka.experiment.RandomSplitResultProducer
Get the value of OutputFile.
getOutputFormat(). Method in class weka.filters.Filter
Gets the format of the output instances.
getOutputNums(). Method in class weka.classifiers.neural.NeuralConnection
Use this to get easy access to the output numbers.
getOutputs(). Method in class weka.classifiers.neural.NeuralConnection
Use this to get easy access to the outputs.
getParent(int). Method in class weka.gui.treevisualizer.Node
Get the parent edge.
getPath(). Method in class weka.gui.PropertySelectorDialog
Gets the path of property nodes to the selected property.
getPlotInstances(). Method in class weka.gui.visualize.PlotData2D
Returns the instances for this plot
getPlotName(). Method in class weka.gui.visualize.PlotData2D
Get the name of this plot
getPlots(). Method in class weka.gui.visualize.Plot2D
Return the list of plots
getPopulationSize(). Method in class weka.attributeSelection.GeneticSearch
get the size of the population
getPrecision(). Method in class weka.classifiers.evaluation.TwoClassStats
Calculate the precision.
getPrediction(DistributionClassifier, Instance). Method in class weka.classifiers.evaluation.EvaluationUtils
Generate a single prediction for a test instance given the pre-trained classifier.
getProbability(double). Method in class weka.estimators.NormalEstimator
Get a probability estimate for a value
getProbability(double). Method in class weka.estimators.DiscreteEstimator
Get a probability estimate for a value
getProbability(double). Method in class weka.estimators.MahalanobisEstimator
Get a probability estimate for a value
getProbability(double). Method in class weka.estimators.KernelEstimator
Get a probability estimate for a value.
getProbability(double). Method in interface weka.estimators.Estimator
Get a probability estimate for a value.
getProbability(double). Method in class weka.estimators.PoissonEstimator
Get a probability estimate for a value
getProbability(double, double). Method in interface weka.estimators.ConditionalEstimator
Get a probability for a value conditional on another value
getProbability(double, double). Method in class weka.estimators.DDConditionalEstimator
Get a probability estimate for a value
getProbability(double, double). Method in class weka.estimators.NDConditionalEstimator
Get a probability estimate for a value
getProbability(double, double). Method in class weka.estimators.KDConditionalEstimator
Get a probability estimate for a value
getProbability(double, double). Method in class weka.estimators.DKConditionalEstimator
Get a probability estimate for a value
getProbability(double, double). Method in class weka.estimators.KKConditionalEstimator
Get a probability estimate for a value
getProbability(double, double). Method in class weka.estimators.DNConditionalEstimator
Get a probability estimate for a value
getProbability(double, double). Method in class weka.estimators.NNConditionalEstimator
Get a probability estimate for a value
getProduceLatex(). Method in class weka.experiment.PairedTTester
Get whether latex is output
getPropertyArray(). Method in class weka.experiment.Experiment
Gets the array of values to set the custom property to.
getPropertyArrayLength(). Method in class weka.experiment.Experiment
Gets the number of custom iterator values that have been defined for the experiment.
getPropertyArrayValue(int). Method in class weka.experiment.Experiment
Gets a specified value from the custom property iterator array.
getPropertyPath(). Method in class weka.experiment.Experiment
Gets the path of properties taken to get to the custom property to iterate over.
getPruningFactor(). Method in class weka.classifiers.m5.M5Prime
Get the value of PruningFactor.
getQuery(). Method in class weka.experiment.InstanceQuery
Get the query to execute against the database
getRaceType(). Method in class weka.attributeSelection.RaceSearch
Get the race type
getRandomizeData(). Method in class weka.experiment.RandomSplitResultProducer
Get if dataset is to be randomized
getRandomSeed(). Method in class weka.classifiers.adtree.ADTree
Gets random seed for a random walk.
getRandomSeed(). Method in class weka.classifiers.neural.NeuralNetwork
getRandomSeed(). Method in class weka.filters.SpreadSubsampleFilter
Gets the random number seed.
getRandomSeed(). Method in class weka.filters.ResampleFilter
Gets the random number seed.
getRandomSeed(). Method in class weka.filters.RandomizeFilter
Get the random number generator seed value.
getRandomWidthFactor(). Method in class weka.classifiers.MultiClassClassifier
Gets the multiplier when generating random codes.
getRangeCorrection(). Method in class weka.classifiers.ThresholdSelector
Gets the confidence range correction mode used.
getRanges(). Method in class weka.core.Range
Gets the string representing the selected range of values
getRawOutput(). Method in class weka.experiment.CrossValidationResultProducer
Get if raw split evaluator output is to be saved
getRawOutput(). Method in class weka.experiment.RandomSplitResultProducer
Get if raw split evaluator output is to be saved
getRawResultOutput(). Method in class weka.experiment.ClassifierSplitEvaluator
Gets the raw output from the classifier
getRawResultOutput(). Method in class weka.experiment.RegressionSplitEvaluator
Gets the raw output from the classifier
getRawResultOutput(). Method in interface weka.experiment.SplitEvaluator
Returns the raw output for the most recent call to getResult.
getReadable(). Method in class weka.core.Tag
Gets the string description of the Tag.
getRecall(). Method in class weka.classifiers.evaluation.TwoClassStats
Calculate the recall.
getReducedErrorPruning(). Method in class weka.classifiers.j48.J48
Get the value of reducedErrorPruning.
getReducedErrorPruning(). Method in class weka.classifiers.j48.PART
Get the value of reducedErrorPruning.
getRefer(). Method in class weka.gui.treevisualizer.Node
Get the value of refer.
getRemoteHosts(). Method in class weka.experiment.RemoteExperiment
Get the list of remote host names
getRemoveAllMissingCols(). Method in class weka.associations.Apriori
Returns whether columns containing all missing values are to be removed
getReportFrequency(). Method in class weka.attributeSelection.GeneticSearch
get how often repports are generated
getRescaleKernel(). Method in class weka.classifiers.SMO
Check whether kernel is being rescaled.
getReset(). Method in class weka.classifiers.neural.NeuralNetwork
getResult(Instances, Instances). Method in class weka.experiment.ClassifierSplitEvaluator
Gets the results for the supplied train and test datasets.
getResult(Instances, Instances). Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
Gets the results for the supplied train and test datasets.
getResult(Instances, Instances). Method in class weka.experiment.RegressionSplitEvaluator
Gets the results for the supplied train and test datasets.
getResult(Instances, Instances). Method in interface weka.experiment.SplitEvaluator
Gets the results for the supplied train and test datasets.
getResultFromTable(String, ResultProducer, Object[]). Method in class weka.experiment.DatabaseUtils
Executes a database query to extract a result for the supplied key from the database.
getResultListener(). Method in class weka.experiment.Experiment
Gets the result listener where results will be sent.
getResultNames(). Method in interface weka.experiment.ResultProducer
Gets the names of each of the result columns produced for a single run.
getResultNames(). Method in class weka.experiment.ClassifierSplitEvaluator
Gets the names of each of the result columns produced for a single run.
getResultNames(). Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
Gets the names of each of the result columns produced for a single run.
getResultNames(). Method in class weka.experiment.LearningRateResultProducer
Gets the names of each of the columns produced for a single run.
getResultNames(). Method in class weka.experiment.CrossValidationResultProducer
Gets the names of each of the columns produced for a single run.
getResultNames(). Method in class weka.experiment.RegressionSplitEvaluator
Gets the names of each of the result columns produced for a single run.
getResultNames(). Method in class weka.experiment.RandomSplitResultProducer
Gets the names of each of the columns produced for a single run.
getResultNames(). Method in class weka.experiment.AveragingResultProducer
Gets the names of each of the columns produced for a single run.
getResultNames(). Method in class weka.experiment.DatabaseResultProducer
Gets the names of each of the columns produced for a single run.
getResultNames(). Method in interface weka.experiment.SplitEvaluator
Gets the names of each of the result columns produced for a single run.
getResultProducer(). Method in class weka.experiment.LearningRateResultProducer
Get the ResultProducer.
getResultProducer(). Method in class weka.experiment.Experiment
Get the result producer used for the current experiment.
getResultProducer(). Method in class weka.experiment.AveragingResultProducer
Get the ResultProducer.
getResultProducer(). Method in class weka.experiment.DatabaseResultProducer
Get the ResultProducer.
getResultSet(). Method in class weka.experiment.DatabaseUtils
Gets the results generated by a previous query.
getResultsetKeyColumns(). Method in class weka.experiment.PairedTTester
Get the value of ResultsetKeyColumns.
getResultsetName(int). Method in class weka.experiment.PairedTTester
Gets a string descriptive of the specified resultset.
getResultsTableName(ResultProducer). Method in class weka.experiment.DatabaseUtils
Gets the name of the experiment table that stores results from a particular ResultProducer.
getResultTypes(). Method in interface weka.experiment.ResultProducer
Gets the data types of each of the result columns produced for a single run.
getResultTypes(). Method in class weka.experiment.ClassifierSplitEvaluator
Gets the data types of each of the result columns produced for a single run.
getResultTypes(). Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
Gets the data types of each of the result columns produced for a single run.
getResultTypes(). Method in class weka.experiment.LearningRateResultProducer
Gets the data types of each of the columns produced for a single run.
getResultTypes(). Method in class weka.experiment.CrossValidationResultProducer
Gets the data types of each of the columns produced for a single run.
getResultTypes(). Method in class weka.experiment.RegressionSplitEvaluator
Gets the data types of each of the result columns produced for a single run.
getResultTypes(). Method in class weka.experiment.RandomSplitResultProducer
Gets the data types of each of the columns produced for a single run.
getResultTypes(). Method in class weka.experiment.AveragingResultProducer
Gets the data types of each of the columns produced for a single run.
getResultTypes(). Method in class weka.experiment.DatabaseResultProducer
Gets the data types of each of the columns produced for a single run.
getResultTypes(). Method in interface weka.experiment.SplitEvaluator
Gets the data types of each of the result columns produced for a single run.
getROCArea(Instances). Static method in class weka.classifiers.evaluation.ThresholdCurve
Calculates the area under the ROC curve.
getRoot(). Method in class weka.gui.treevisualizer.Node
Get the value of root.
getRsource(). Method in class weka.gui.treevisualizer.Edge
Get the value of rsource.
getRtarget(). Method in class weka.gui.treevisualizer.Edge
Get the value of rtarget.
getRunColumn(). Method in class weka.experiment.PairedTTester
Get the value of RunColumn.
getRunLower(). Method in class weka.experiment.Experiment
Get the lower run number for the experiment.
getRunUpper(). Method in class weka.experiment.Experiment
Get the upper run number for the experiment.
getSampleSize(). Method in class weka.attributeSelection.ReliefFAttributeEval
Get the number of instances used for estimating attributes
getSampleSizePercent(). Method in class weka.filters.ResampleFilter
Gets the subsample size as a percentage of the original set.
getSaveInstanceData(). Method in class weka.classifiers.adtree.ADTree
Gets whether the tree is to save instance data.
getSaveInstanceData(). Method in class weka.classifiers.j48.J48
Check whether instance data is to be saved.
getSaveInstanceData(). Method in class weka.clusterers.Cobweb
Get the value of saveInstances.
getSearch(). Method in class weka.classifiers.AttributeSelectedClassifier
Gets the search method used
getSearch(). Method in class weka.filters.AttributeSelectionFilter
Get the name of the search method
getSearchPath(). Method in class weka.classifiers.adtree.ADTree
Gets the method of searching the tree for a new insertion.
getSearchPercent(). Method in class weka.attributeSelection.RandomSearch
get the percentage of the search space to consider
getSearchTermination(). Method in class weka.attributeSelection.BestFirst
Get the termination criterion (number of non-improving nodes).
getSecondValueIndex(). Method in class weka.filters.SwapAttributeValuesFilter
Get the index of the second value used.
getSecondValueIndex(). Method in class weka.filters.MergeTwoValuesFilter
Get the index of the second value used.
getSeed(). Method in class weka.attributeSelection.GeneticSearch
get the value of the random number generator's seed
getSeed(). Method in class weka.attributeSelection.ReliefFAttributeEval
Get the seed used for randomly sampling instances.
getSeed(). Method in class weka.attributeSelection.WrapperSubsetEval
Get the random number seed used for cross validation
getSeed(). Method in class weka.classifiers.MetaCost
Get seed for resampling.
getSeed(). Method in class weka.classifiers.AdaBoostM1
Get seed for resampling.
getSeed(). Method in class weka.classifiers.Stacking
Gets the random number seed.
getSeed(). Method in class weka.classifiers.CVParameterSelection
Gets the random number seed.
getSeed(). Method in class weka.classifiers.Bagging
Gets the seed for the random number generations
getSeed(). Method in class weka.classifiers.ThresholdSelector
Gets the random number seed.
getSeed(). Method in class weka.classifiers.LogitBoost
Get seed for resampling.
getSeed(). Method in class weka.classifiers.MultiScheme
Gets the random number seed.
getSeed(). Method in class weka.classifiers.BVDecompose
Gets the random number seed
getSeed(). Method in class weka.classifiers.CostSensitiveClassifier
Get seed for resampling.
getSeed(). Method in class weka.classifiers.VotedPerceptron
Get the value of Seed.
getSeed(). Method in class weka.classifiers.evaluation.EvaluationUtils
Gets the seed for randomization during cross-validation
getSeed(). Method in class weka.clusterers.SimpleKMeans
Get the random number seed
getSeed(). Method in class weka.clusterers.EM
Get the random number seed
getSeed(). Method in class weka.filters.SplitDatasetFilter
Gets the random number seed used for shuffling the dataset.
getSelectedAttributes(). Method in class weka.gui.AttributeSelectionPanel
Gets an array containing the indices of all selected attributes.
getSelectedBuffer(). Method in class weka.gui.ResultHistoryPanel
Gets the buffer associated with the currently selected item in the list.
getSelectedName(). Method in class weka.gui.ResultHistoryPanel
Get the name of the currently selected item in the list
getSelectedObject(). Method in class weka.gui.ResultHistoryPanel
Gets the object associated with the currently selected item in the list.
getSelectedTag(). Method in class weka.core.SelectedTag
Gets the selected Tag.
getSelection(). Method in class weka.core.Range
Gets an array containing all the selected values, in the order that they were selected (or ascending order if range inversion is on)
getSelectionModel(). Method in class weka.gui.ResultHistoryPanel
Gets the selection model used by the results list.
getSelectionModel(). Method in class weka.gui.AttributeSelectionPanel
Gets the selection model used by the table.
getSelectionThreshold(). Method in class weka.attributeSelection.RaceSearch
Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
getShape(). Method in class weka.gui.treevisualizer.Node
Get the value of shape.
getShowStdDevs(). Method in class weka.experiment.PairedTTester
Returns true if standard deviations have been requested.
getShrinkage(). Method in class weka.classifiers.AdditiveRegression
Get the shrinkage rate.
getSigma(). Method in class weka.attributeSelection.ReliefFAttributeEval
Get the value of sigma.
getSigma(). Method in class weka.classifiers.BVDecompose
Get the calculated sigma squared
getSignificanceLevel(). Method in class weka.associations.Apriori
Get the value of significanceLevel.
getSignificanceLevel(). Method in class weka.attributeSelection.RaceSearch
Get the significance level
getSignificanceLevel(). Method in class weka.experiment.PairedTTester
Get the value of SignificanceLevel.
getSIndex(). Method in class weka.gui.visualize.VisualizePanel
Get the index of the shape selected for creating splits.
getSource(). Method in class weka.gui.treevisualizer.Edge
Get the value of source.
getSparseData(). Method in class weka.experiment.InstanceQuery
Gets whether data is to be returned as a set of sparse instances
getSplitByDataSet(). Method in class weka.experiment.RemoteExperiment
Returns true if sub experiments are to be created on the basis of data set..
getSplitEvaluator(). Method in class weka.experiment.CrossValidationResultProducer
Get the SplitEvaluator.
getSplitEvaluator(). Method in class weka.experiment.RandomSplitResultProducer
Get the SplitEvaluator.
getSplitPoint(). Method in class weka.filters.InstanceFilter
Get the split point used for numeric selection
getStartSet(). Method in class weka.attributeSelection.ExhaustiveSearch
Returns a list of attributes (and or attribute ranges) as a String
getStartSet(). Method in class weka.attributeSelection.RandomSearch
Returns a list of attributes (and or attribute ranges) as a String
getStartSet(). Method in class weka.attributeSelection.ForwardSelection
Returns a list of attributes (and or attribute ranges) as a String
getStartSet(). Method in class weka.attributeSelection.GeneticSearch
Returns a list of attributes (and or attribute ranges) as a String
getStartSet(). Method in class weka.attributeSelection.BestFirst
Returns a list of attributes (and or attribute ranges) as a String
getStartSet(). Method in class weka.attributeSelection.Ranker
Returns a list of attributes (and or attribute ranges) as a String
getStartSet(). Method in interface weka.attributeSelection.StartSetHandler
Returns a list of attributes (and or attribute ranges) as a String
getStatusMessage(). Method in class weka.experiment.TaskStatusInfo
Get the status message.
getStepSize(). Method in class weka.experiment.LearningRateResultProducer
Get the value of StepSize.
getStructure(). Method in class weka.core.converters.AbstractLoader
Must be overridden by subclasses.
getStructure(). Method in class weka.core.converters.CSVLoader
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure(). Method in class weka.core.converters.ArffLoader
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure(). Method in interface weka.core.converters.Loader
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure(). Method in class weka.core.converters.C45Loader
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure(). Method in class weka.core.converters.SerializedInstancesLoader
Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getSubtreeRaising(). Method in class weka.classifiers.j48.J48
Get the value of subtreeRaising.
getSummary(). Method in class weka.gui.SetInstancesPanel
Gets the instances summary panel associated with this panel
getTags(). Method in class weka.core.SelectedTag
Gets the set of all valid Tags.
getTags(). Method in class weka.gui.GenericArrayEditor
Returns null as we don't support getting values as tags.
getTags(). Method in class weka.gui.SelectedTagEditor
Gets the list of tags that can be selected from.
getTags(). Method in class weka.gui.GenericObjectEditor
Returns null as we don't support getting values as tags.
getTags(). Method in class weka.gui.CostMatrixEditor
Returns null as we don't support getting values as tags.
getTarget(). Method in class weka.gui.treevisualizer.Edge
Get the value of target.
getTaskResult(). Method in class weka.experiment.TaskStatusInfo
Get the returnable result of this task.
getTestPredictions(DistributionClassifier, Instances). Method in class weka.classifiers.evaluation.EvaluationUtils
Generate a bunch of predictions ready for processing, by performing a evaluation on a test set assuming the classifier is already trained.
getThreshold(). Method in class weka.attributeSelection.RaceSearch
Get the threshold
getThreshold(). Method in interface weka.attributeSelection.RankedOutputSearch
Gets the threshold by which attributes can be discarded.
getThreshold(). Method in class weka.attributeSelection.ForwardSelection
Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
getThreshold(). Method in class weka.attributeSelection.Ranker
Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
getThreshold(). Method in class weka.attributeSelection.WrapperSubsetEval
Get the value of the threshold
getThresholdInstance(Instances, double). Static method in class weka.classifiers.evaluation.ThresholdCurve
Gets the index of the instance with the closest threshold value to the desired target
getTimestamp(). Static method in class weka.experiment.CrossValidationResultProducer
Gets a Double representing the current date and time.
getTimestamp(). Static method in class weka.experiment.RandomSplitResultProducer
Gets a Double representing the current date and time.
getToken(StreamTokenizer). Static method in class weka.core.converters.ConverterUtils
Gets token.
getToleranceParameter(). Method in class weka.classifiers.SMO
Get the value of tolerance parameter.
getTop(). Method in class weka.gui.treevisualizer.Node
Get the value of top.
getTotalCount(Node, int). Static method in class weka.gui.treevisualizer.Node
Recursively finds the total number of nodes there are.
getTotalGCount(Node, int). Static method in class weka.gui.treevisualizer.Node
Recursively finds the total number of groups of siblings there are.
getTotalHeight(Node, int). Static method in class weka.gui.treevisualizer.Node
Recursively finds the total number of levels there are.
getTrainingTime(). Method in class weka.classifiers.neural.NeuralNetwork
getTrainIterations(). Method in class weka.classifiers.BVDecompose
Gets the maximum number of boost iterations
getTrainPercent(). Method in class weka.experiment.RandomSplitResultProducer
Get the value of TrainPercent.
getTrainPoolSize(). Method in class weka.classifiers.BVDecompose
Get the number of instances in the training pool.
getTrainTestPredictions(DistributionClassifier, Instances, Instances). Method in class weka.classifiers.evaluation.EvaluationUtils
Generate a bunch of predictions ready for processing, by performing a evaluation on a test set after training on the given training set.
getTransformBackToOriginal(). Method in class weka.attributeSelection.PrincipalComponents
Gets whether the data is to be transformed back to the original space.
getTrueNegative(). Method in class weka.classifiers.evaluation.TwoClassStats
Gets the number of negative instances predicted as negative
getTruePositive(). Method in class weka.classifiers.evaluation.TwoClassStats
Gets the number of positive instances predicted as positive
getTruePositiveRate(). Method in class weka.classifiers.evaluation.TwoClassStats
Calculate the true positive rate.
getTwoClassStats(int). Method in class weka.classifiers.evaluation.ConfusionMatrix
Gets the performance with respect to one of the classes as a TwoClassStats object.
getType(). Method in class weka.classifiers.neural.NeuralConnection
getUnpruned(). Method in class weka.classifiers.j48.J48
Get the value of unpruned.
getUpper(). Method in class weka.gui.experiment.RunNumberPanel
Gets the current upper run number.
getUpperBoundMinSupport(). Method in class weka.associations.Apriori
Get the value of upperBoundMinSupport.
getUpperSize(). Method in class weka.experiment.LearningRateResultProducer
Get the value of UpperSize.
getUseBetterEncoding(). Method in class weka.filters.DiscretizeFilter
Gets whether better encoding is to be used for MDL.
getUseIBk(). Method in class weka.classifiers.DecisionTable
Gets whether IBk is being used instead of the majority class
getUseKernelEstimator(). Method in class weka.classifiers.NaiveBayes
Gets if kernel estimator is being used.
getUseKononenko(). Method in class weka.filters.DiscretizeFilter
Gets whether Kononenko's MDL criterion is to be used.
getUseLaplace(). Method in class weka.classifiers.j48.J48
Get the value of useLaplace.
getUseMDL(). Method in class weka.filters.DiscretizeFilter
Gets whether MDL will be used as the discretisation method.
getUsePropertyIterator(). Method in class weka.experiment.Experiment
Gets whether the custom property iterator should be used.
getUseResampling(). Method in class weka.classifiers.AdaBoostM1
Get whether resampling is turned on
getUseResampling(). Method in class weka.classifiers.LogitBoost
Get whether resampling is turned on
getUseTraining(). Method in class weka.attributeSelection.ClassifierSubsetEval
Get if training data is to be used instead of hold out/test data
getUseUnsmoothed(). Method in class weka.classifiers.m5.M5Prime
Get the value of UseUnsmoothed.
getValidationSetSize(). Method in class weka.classifiers.neural.NeuralNetwork
getValidationThreshold(). Method in class weka.classifiers.neural.NeuralNetwork
getValue(). Method in class weka.classifiers.adtree.PredictionNode
Gets the prediction value of the node.
getValue(). Method in class weka.gui.GenericArrayEditor
Gets the current object array.
getValue(). Method in class weka.gui.GenericObjectEditor
Gets the current Object.
getValue(). Method in class weka.gui.CostMatrixEditor
Gets the current object array.
getValueIndices(). Method in class weka.filters.MakeIndicatorFilter
Get the indices of the indicator values.
getValueRange(). Method in class weka.filters.MakeIndicatorFilter
Get the range containing the indicator values.
getValues(). Method in class weka.gui.visualize.VisualizePanelEvent
getVariance(). Method in class weka.classifiers.BVDecompose
Get the calculated variance
getVarianceCovered(). Method in class weka.attributeSelection.PrincipalComponents
Gets the proportion of total variance to account for when retaining principal components
getVerbose(). Method in class weka.attributeSelection.ExhaustiveSearch
get whether or not output is verbose
getVerbose(). Method in class weka.attributeSelection.RandomSearch
get whether or not output is verbose
getVerbosity(). Method in class weka.classifiers.m5.M5Prime
Get the value of Verbosity.
getVisible(). Method in class weka.gui.treevisualizer.Node
Get the value of visible.
getWeightByConfidence(). Method in class weka.classifiers.VFI
Get whether feature intervals are being weighted by confidence
getWeightByDistance(). Method in class weka.attributeSelection.ReliefFAttributeEval
Get whether nearest neighbours are being weighted by distance
getWeightingKernel(). Method in class weka.classifiers.LWR
Gets the kernel weighting method to use.
getWeights(). Method in class weka.classifiers.neural.NeuralNode
call this function to get the weights array.
getWeightThreshold(). Method in class weka.classifiers.AdaBoostM1
Get the degree of weight thresholding
getWeightThreshold(). Method in class weka.classifiers.LogitBoost
Get the degree of weight thresholding
getWindowSize(). Method in class weka.classifiers.IBk
Gets the maximum number of instances allowed in the training pool.
getWorkingInstances(). Method in class weka.gui.explorer.PreprocessPanel
Gets the working set of instances.
getX(). Method in class weka.classifiers.neural.NeuralConnection
getXindex(). Method in class weka.gui.visualize.PlotData2D
Get the currently set x index of the data
getXIndex(). Method in class weka.gui.visualize.VisualizePanel
Get the index of the attribute on the x axis
getY(). Method in class weka.classifiers.neural.NeuralConnection
getYindex(). Method in class weka.gui.visualize.PlotData2D
Get the currently set y index of the data
getYIndex(). Method in class weka.gui.visualize.VisualizePanel
Get the index of the attribute on the y axis
globalInfo(). Method in class weka.associations.Apriori
Returns a string describing this associator
globalInfo(). Method in class weka.attributeSelection.ExhaustiveSearch
Returns a string describing this search method
globalInfo(). Method in class weka.attributeSelection.SymmetricalUncertAttributeEval
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.attributeSelection.RankSearch
Returns a string describing this search method
globalInfo(). Method in class weka.attributeSelection.RaceSearch
Returns a string describing this search method
globalInfo(). Method in class weka.attributeSelection.RandomSearch
Returns a string describing this search method
globalInfo(). Method in class weka.attributeSelection.GainRatioAttributeEval
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.attributeSelection.ForwardSelection
Returns a string describing this search method
globalInfo(). Method in class weka.attributeSelection.GeneticSearch
Returns a string describing this search method
globalInfo(). Method in class weka.attributeSelection.CfsSubsetEval
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.attributeSelection.BestFirst
Returns a string describing this search method
globalInfo(). Method in class weka.attributeSelection.ReliefFAttributeEval
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.attributeSelection.Ranker
Returns a string describing this search method
globalInfo(). Method in class weka.attributeSelection.ChiSquaredAttributeEval
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.attributeSelection.OneRAttributeEval
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.attributeSelection.InfoGainAttributeEval
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.attributeSelection.ConsistencySubsetEval
Returns a string describing this search method
globalInfo(). Method in class weka.attributeSelection.ClassifierSubsetEval
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.attributeSelection.PrincipalComponents
Returns a string describing this attribute transformer
globalInfo(). Method in class weka.attributeSelection.WrapperSubsetEval
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.classifiers.AttributeSelectedClassifier
Returns a string describing this search method
globalInfo(). Method in class weka.classifiers.ThresholdSelector
globalInfo(). Method in class weka.classifiers.MultiClassClassifier
globalInfo(). Method in class weka.classifiers.UserClassifier
This will return a string describing the classifier.
globalInfo(). Method in class weka.classifiers.AdditiveRegression
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.classifiers.CostSensitiveClassifier
globalInfo(). Method in class weka.classifiers.VFI
Returns a string describing this search method
globalInfo(). Method in class weka.classifiers.adtree.ADTree
globalInfo(). Method in class weka.classifiers.neural.NeuralNetwork
This will return a string describing the classifier.
globalInfo(). Method in class weka.clusterers.SimpleKMeans
Returns a string describing this clusterer
globalInfo(). Method in class weka.clusterers.EM
Returns a string describing this clusterer
globalInfo(). Method in class weka.core.converters.CSVLoader
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.core.converters.C45Loader
Returns a string describing this attribute evaluator
globalInfo(). Method in class weka.experiment.ClassifierSplitEvaluator
Returns a string describing this split evaluator
globalInfo(). Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator
Returns a string describing this split evaluator
globalInfo(). Method in class weka.experiment.LearningRateResultProducer
Returns a string describing this result producer
globalInfo(). Method in class weka.experiment.DatabaseResultListener
Returns a string describing this result listener
globalInfo(). Method in class weka.experiment.CSVResultListener
Returns a string describing this result listener
globalInfo(). Method in class weka.experiment.InstancesResultListener
Returns a string describing this result listener
globalInfo(). Method in class weka.experiment.CrossValidationResultProducer
Returns a string describing this result producer
globalInfo(). Method in class weka.experiment.RegressionSplitEvaluator
Returns a string describing this split evaluator
globalInfo(). Method in class weka.experiment.RandomSplitResultProducer
Returns a string describing this result producer
globalInfo(). Method in class weka.experiment.AveragingResultProducer
Returns a string describing this result producer
globalInfo(). Method in class weka.experiment.DatabaseResultProducer
Returns a string describing this result producer
globalInfo(). Method in class weka.filters.SparseToNonSparseFilter
Returns a string describing this filter
globalInfo(). Method in class weka.filters.AllFilter
Returns a string describing this filter
globalInfo(). Method in class weka.filters.CopyAttributesFilter
Returns a string describing this filter
globalInfo(). Method in class weka.filters.NonSparseToSparseFilter
Returns a string describing this filter
globalInfo(). Method in class weka.filters.ObfuscateFilter
Returns a string describing this filter
globalInfo(). Method in class weka.filters.AddFilter
Returns a string describing this filter
globalInfo(). Method in class weka.filters.MakeIndicatorFilter
globalInfo(). Method in class weka.filters.AttributeExpressionFilter
Returns a string describing this filter
globalInfo(). Method in class weka.filters.AttributeFilter
Returns a string describing this filter
globalInfo(). Method in class weka.filters.DiscretizeFilter
Returns a string describing this filter
gr(double, double). Static method in class weka.core.Utils
Tests if a is smaller than b.
graph(). Method in class weka.classifiers.UserClassifier
graph(). Method in class weka.classifiers.CostSensitiveClassifier
Returns graph describing the classifier (if possible).
graph(). Method in class weka.classifiers.adtree.ADTree
Returns graph describing the tree.
graph(). Method in class weka.classifiers.j48.J48
Returns graph describing the tree.
graph(). Method in class weka.classifiers.j48.ClassifierTree
Returns graph describing the tree.
graph(). Method in class weka.clusterers.Cobweb
Generates the graph string of the Cobweb tree
graph(). Method in interface weka.core.Drawable
Returns a string that describes a graph representing the object.
grOrEq(double, double). Static method in class weka.core.Utils
Tests if a is greater or equal to b.
GUIChooser class weka.gui.GUIChooser.
The main class for the Weka GUIChooser.
GUIChooser(). Constructor for class weka.gui.GUIChooser
Creates the experiment environment gui with no initial experiment
GUITipText(). Method in class weka.classifiers.neural.NeuralNetwork

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