All Packages Class Hierarchy
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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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